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As a plant production or operations manager, productivity and efficiency are your top priorities. Precision maintenance combined with data analysis makes these responsibilities more manageable, and enables you and your organisation to make more informed maintenance decisions.

What do we mean by precision maintenance? This concept comes from the idea of accurately pinpointing potential issues that signal the beginnings of anything from unexpected repair needs and downtime to catastrophic machine failure. Precision maintenance gives plant managers the information required to plan the best method of action, and helps them take that action at the optimal time.

In this blog post, we’ll cover:
●          How precision maintenance can help you solve common maintenance challenges
●          The benefits of leaving manual methods behind
●          The importance of leveraging data to make better decisions for your company

The traditional approach to industrial maintenance

Many companies in the energy, pulp and paper, steel and mining sectors still rely on manual maintenance and inspections. Although this is a longstanding practice, on average, only 8% of machinery is frequently inspected. This approach leaves a lot to chance in terms of unexpected downtime and faster machine deterioration.

With these risks in mind, it would be wise for plant managers to take a more proactive approach to industrial maintenance. However, with seemingly no systematic, data-backed way of determining when to inspect machinery or make repairs, these managers are left with a serious challenge.

Barriers to change

A reluctance toward investing in resources and technology, as well as a lack of awareness around precision maintenance methods can both be barriers to updating your maintenance approach. When asked about the main obstacles hindering their plant from improving maintenance methods, 48% of plant employees cited lack of resources or staff, while 38% cited a lack of understanding of new maintenance options and technologies.

However, relying heavily on mere routine check-ups often has costly consequences. It is well known by every operations and production manager that maintenance is crucial to machine health and the overall success of an industrial facility. In fact, maintenance costs account for 15 to 40% of total production costs according to Hans Löfsten, professor of Technology Management and Economics at Chalmers University of Technology.

With such a significant portion of a plant’s budget dedicated to maintenance, it’s imperative to take a cost-effective approach. A maintenance approach that lacks precision, or that relies on reacting to issues as they arise instead of trying to predict them, can result in prematurely ageing equipment and unplanned, costly downtime.

This reactive traditional maintenance method can often lead to repairing machinery once it has already failed or is beginning to fail, leaving little to no room for unexpected failures or monitoring machine wear and tear in between scheduled maintenance. Imagine the amount of energy and time that might be wasted when critical machinery requires extra downtime because you had no way of knowing the machine needed attention weeks or months before the usual scheduled time.

In fact, ageing machinery is the most significant pain point for operations and maintenance, followed closely by equipment failure. Fortunately, this is one of the major areas that precision maintenance is designed to address. Data-backed decision making for precision maintenance is essential for industrial sites because it allows plant managers to predict serious issues before they actually arise. Let’s explore how it works.

Addressing common challenges with precision maintenance

How does precision maintenance help production managers combat ageing machinery, equipment failure and the like? The foundation of precision maintenance is built around monitoring asset conditions and balancing your options.

This proactive approach to maintenance is essential to avoiding emergency shutdowns and ensuring that any shutdowns you do schedule are absolutely necessary. However, keep in mind that downtime needs to be planned well in advance and aligned with your production schedules to minimise production and revenue loss.

Overcoming common maintenance challenges is where precision maintenance and data come into play. By using data collection and analysis to monitor machine conditions in real-time, and predict downtime and repair needs, managers can use plant resources more wisely and delegate responsibilities to staff more effectively.

With precision maintenance software and hardware that automatically and consistently collects and analyses useful data, production managers can go far beyond the limitations of a computerized maintenance management system that only offers a small portion of the required data often collected manually, and stored in an unsystematic way that makes data insights challenging to gather.

Instead, data-backed precision maintenance operates on a system that can be monitored remotely; and plant managers already possess the skills and knowledge needed to adjust notifications and schedule maintenance and repairs in an optimal way.

Hardware and software for easy precision maintenance

Industrial machine maintenance often requires specialised skills and knowledge. If there aren’t enough people on your team with these skills, it creates a significant obstacle as you work to improve your maintenance strategy.

Below are three examples of how using data to collect real-time information about your machinery can alleviate the need for these specialised skills. Leveraging data makes precision maintenance easier and allows you to monitor the condition of individual parts closely.

1. Software

Precision maintenance software solutions collect and analyse data. Using the cloud and embedded edge-analytics, production and operations managers have access to data visualisation tools and various widgets, allowing them to monitor and customise how their data is delivered in an accessible way.

The software is always listening, safely and securely collecting relevant data even outside of regular work hours. It is also highly customisable, allowing managers to set specific notifications for the condition thresholds that best suit their team and their facility.

2. Application: Gearbox condition monitoring

A common, complex and essential component for many industrial facilities, gearboxes are manually inspected manually and quite often. But the way they are monitored is not ideal because facilities typically only collect the data they gather during each manual inspection. This limited view can lead to huge oversights. Instead, gearboxes should be monitored constantly to avoid unexpected downtime or failure.

Through continuous monitoring of several methods including oil condition, in-depth vibration analysis and temperature, managers can gain insights into early signs of wear, changes in oil quality and whether the gearbox is being used efficiently in terms of running hours.

3. Application: Compressor condition monitoring

There are many different types of compressors, so your solution needs to have multiple options for sensors and vibration analysis as well as customisable terminals to ensure that each manager can find a condition monitoring set up that suits their specific needs.

Compressor condition monitoring delivers metrics to help detect signs of wear, user errors, temperature changes and more to help you combat machine ageing and, of course, avoid unscheduled downtime.

Your partner in machine health

How exactly does precision maintenance impact an industrial facility? In terms of cost, the average direct savings cover four months of running a solution like Condence.io.

Monitoring conditions in real-time through precision maintenance instead of relying on traditional methods can reduce repair time significantly, decrease overall equipment effectiveness losses by nearly half, and save around €99,625 per failure, according to McKinsey.

At Condence, we can confidently say that we haven’t missed a single machine failure in 12 months. Through cloud and edge computing, our solution listens, collects and analyses data for plant managers to easily apply to their machinery and facilities.

Book a demo to discover how Condence can revamp the way your organisation approaches maintenance.

The new product from KraftPowercon is part of delivering their customer promise, “we ensure that you can focus on optimizing your core business”. It uses Condence.io technology from Distence.

The new solution unveils hidden and potential issues in rectifiers, saves money by optimizing service visits and maintenance costs as well as offers quick response by on-line support and remote services.

The goal is to increase the reliability and the lifespan of rectifiers. Without proper continuous service and monitoring, productivity and the effectiveness of maintenance and operations is drastically decreased. The new sensing capabilities and analytical tools coupled with a modern cloud-based monitoring architecture makes it a powerful scalable solution.

“Thanks to the interactive interface with logs and diagrams, we can easily keep track via PC, mobile or tablet remotely. The ability to select time intervals, either real-time or anything over the past two years, gives us a good overview for example of long-term changes in production. By proactively monitoring our different processes, we can prevent any malfunctions and increase the product lifetime and prioritize maintenance of the rectifiers. Our professional service engineers can simultaneously provide tips and service advice and keep a watchful eye on the rectifiers.” Niklas Tillbrandt, Global product Manager, commenting on the Condence capabilities.

“Distence and KraftPowercon have worked together for some time to deliver this new product. The Distence team has been more than a technology vendor on this project. We are happy with the partnership they have shown to deliver this to the market”, Niklas Tillbrant comments on the collaboration.

KraftPowercon is a global company with production facilities in Sweden, China and India. They offer innovative solutions, products and services within industrial power supply that make their customers’ processes secure, more reliable, as efficient as possible and improves their availability. In short – by guaranteeing your power supply, KraftPowercon ensures that you can focus on optimizing your core business.

For more information on KraftPowercon and their solutions for rectifiers, please visit https://kraftpowercon.com/

Considering the importance to any production process, the complexity of almost any industrial operation and the effectiveness of proactive maintenance is hard make short and simple if you can exclude full production stoppage from your calculations. It is obvious that significant impact comes from avoidance of downtime, yet this is only part of the total value.

Understanding the relevance and impact to perform right operations at optimal time on a larger fleet of different industrial machinery requires a thorough look into both direct and indirect costs, the IT-infrastructure, the maintenance processes and above all the strategy that guides all the above. It is for this reason that senior management should take a careful look into the preventive maintenance effectiveness and value they deliver “when nothing happens”.

Some principle questions to prepare:

  • What is the impact effectiveness of the preventive team – how do we argue the value that was delivered by actions done at the optimal point?
  • Are we ahead of events or scrambling when the alert comes?
  • How do we make preventive maintenance decisions? How to make sure it’s not too early “just in case” repair?
  • Is my required service and maintenance planning horizon hours, days or months?
  • Where does my maintenance operation stand on utilising digital tools to automatise repetitive tasks like inspection routines?

After considering the answers to the above questions, the next question is: What costs do the decisions or operating models carry. What indirect costs are hidden in the way we operate?

Are we following up and arguing how good work our preventive teams and technologies are delivering? – Do we have a standard practise to do aftermath after a repair to evaluate:

Sum of actual repair cost VS potential repair cost

  • Production time/device stoppage
  • Spare parts + repair services
  • Maintenance work + overtime

On top of the delta between actual and potential repair cost, there is the efficiency of daily operations. When focusing on rotating machinery, we claim that many preventive maintenance teams consume a lot of resources on manually inspecting healthy machines (wasted resources) and in parallel find themselves on the situation of colliding priorities due to repairs, measurements and/or other scheduled tasks. This is mainly due we only observe the tip of the iceberg as the preventive process was designed.

The Iceberg model is a great starting point to introduce the depth of the topic. Depending on the size of the operation, the costs get multiplied as the complexity and the sheer volume of transactions increases. Let’s use a concrete example. In the life cycle cost of a pump, the initial cost of the pump represents some 10%-15% of the LCC. The rest include spare parts, maintenance costs and energy – if, we look at the direct costs only. But what lies below the surface? That depends on the maintenance strategy. In a simple exercise, anyone can run through their own operations, ice chunk by ice chunk, cost driver by cost driver. The results of this exercise will reveal very different results, depending on whether your strategy is reactive or proactive.

The Iceberg Model, Michael Wienker, Ken Henderson, Jacques Volkerts

Modern SaaS-based tools have several benefits for them. We can pick out a few that walk hand in hand with the Ice Berg Model. One, they run in the cloud + edge of the cloud, significantly lowering the need and the cost of IT infrastructure. They are available everywhere anytime, globally – fast to roll out. And so is the data and respective information – centralised by default – available to all interested stakeholders.

Sophisticated tools like Condence.io that have a wide range of methods to detect early symptoms of potential failures, e.g. frequency range in vibration analysis and a large toolkit of analysis tools and algorithms. These will move the detection of potentially failing components earlier, from days to months, and allow for forecasting and tracking, thus enabling a proactive strategy – again globally from one User Interface, moving the detection point earlier and automatic. The ability to track specific parameters translates to time – time for planning. This will help preventive teams to focus on machines and conditions that require attention and plan when to take actions.

Planning results in better resource allocation and cost management as well as budgeting and transparency for the future. Transparency to budding issues, the early symptoms of potential problems results in both less downtime, surprises and increases safety. Failing assets also consume more energy as the performance is not optimal. On top of this, it’s also possible that the root cause of failure creates collateral failures leading to reduced asset life or a replacement. It is generally noted that even only an 8% to 10% increase in temperature over normal working conditions reduces the useful life of an electric motor by half.

Depending on the asset and the nature of the operation, various components of the model apply or carry more weight. An unmanned asset, say a pumping station, is very different from a fully staffed manufacturing facility. They both carry the same issues, just weighted differently. Modern SaaS-based tools work, thanks to their extreme flexibility, in both.

Are you interested to hear more? – Follow up on Linkedin or get in touch with the @distence team. I’d also like to hear your comment and opinion.

 

References & further readings:

The Computerized Maintenance Management System, An Essential Tool for World Class Maintenance – Michael Wienker, Ken Henderson, Jacques Volkerts

It is the deep understanding of both the technology and life cycle of industrial gears and drive trains, that led DB Santasalo to choose their approach to condition monitoring for their GearWatch solution. Lubrication oil is the lifeline, the blood, that keeps the gears running. Just like with us humans, this fluid tells stories, gives signals and helps us trace origins to symptoms and faults. In their highly successful GearWatch solution, lubrication oil plays a key role in helping understand the health of an industrial gear. By measuring both oil particles and oil quality, using proprietary technology, GearWatch not only monitors and analyses industrial gears but warns and assists customers when a situation arises.

It is such a warning that helped save a Pulp Mill the cost of a new €100k gear box in addition to the €2,6 million potential production losses. GearWatch had been installed in this 15-year-old gear only some months earlier. The cloud-based service gave access 24/7 to the critical data from the gear and by using the solution together with the expertise of the ISO certified lubrication and vibration analysts from DBS, the customer was able to run the gear safely until the next scheduled shutdown.

The key value driver in this case is time. GearWatch gave an automatic early warning to the customer so they had time to react and plan and maximize the availability of the asset and thus avoid a costly interruption to production. Time is the key difference between predictive and reactive, run to failure, methods. The further the issue brews, the less time there is to plan and react and the higher the cost is. With GearWatch, DBS customers know the health of their assets and have a professional and controlled way to solve emerging issues. Another benefit is the ability to assign resources with surgical accuracy. “Maintain only when needed” saves costs, as does reduced need for redundancy.

You can learn more about the GearWatch solution at https://dbsantasalo.com/products/gearwatch-condition-monitoring/ or watch their great video at https://vimeo.com/400601132

Flowplus Oy specializes in the maintenance and operation of flow technology. The customer base consists mainly of operators in the industrial, energy and infrastructure sectors. The offering includes versatile service & maintenance services for valves, pumps, electric motors and other rotating machines. Flowplus, operating out of nine locations throughout Finland, has a proactive maintenance concept driving their customers’ maintenance costs down and reliability up.

“The Flowplus philosophy and way of working aligns perfectly with what condence.io has been built for, condition monitoring of multiple critical varying assets in multiple locations. Their focus in industries using rotating machines and the understanding of the benefits of managing and understanding machine health over the life cycle of the machine is an ideal environment for condence.io technology,” comments Janne-Pekka Karttunen, CEO at Distence.

Condence.io technology identifies growing problems early on due to its advanced features, including a wide range of vibration frequencies and long sample lengths. Using condence.io technology, Flowplus professionals get a tool that, with the help of its analysis and clear graphics, gives not only a comprehensive look into the health of the machines but also more time to plan and react accordingly thus increasing their operational excellence and contributing to higher value-add to their customers.

“Condence complement s our offering and will be integrated into our Flowdicator monitoring offering. We have several cases in the sales pipeline, and the first deliveries are already made. We are excited this to initiate this collaboration”

Jarmo Piippo, Founder & CEO, Flowplus Oy
Read more about Flowplus Oy and Condence at:

Flowplus Oy: https://www.flowplus.fi

Condence solution page: https://condence.io

Distence Oy: https://www.distence.fi/en/

Condence team is continually working on making updates and improvements to the sampling and visualisations of the asset health. Condence monitoring technology is built on taking samples of the assets health parameters and doing analysis and visualisations of it, continuously.

Example of how minimum, maximum and average values are visualized in the user interface.
On our latest release, we have improved both, the actual measurement and how the metric is visualised in the cloud UI. In other words, the user can get more out of each measurement. Users are now able to see the full range of values, meaning maximum, minimum and average value of the metric from the period between the current and previous sample.

The new feature enables fast analogue channel monitoring. For instance, we are now able to detect quick changes in important asset health parameters like torque or current draw of electric motors. The update allows for practically constant measurement of analogue channels lifting the resolution to millisecond level. Users are of course able to set notifications and alarms to any of the newly added values.

The driver for the feature was to enable torque measurement and other rapid phenomena measured with sensors in analogue channels. But the visual component is without a doubt useful in monitoring other health metrics and parameters such as vibration analysis as well. The feature is automatically in use on Condence T200 & T210 terminals with software version 2.3.0 and higher. Users can toggle the min/max/avg feature on in the metrics trend component, or it can set as the default selection in the view templates.

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Single line blockquote:

Stay hungry. Stay foolish.

Multi line blockquote with a cite reference:

People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I’m actually as proud of the things we haven’t done as the things I have done. Innovation is saying no to 1,000 things. Steve Jobs – Apple Worldwide Developers’ Conference, 1997

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These supported tags come from the WordPress.com code FAQ.

Address Tag

1 Infinite Loop
Cupertino, CA 95014
United States

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This is an example of a link.

Abbreviation Tag

The abbreviation srsly stands for “seriously”.

Acronym Tag (deprecated in HTML5)

The acronym ftw stands for “for the win”.

Big Tag (deprecated in HTML5)

These tests are a big deal, but this tag is no longer supported in HTML5.

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“Code is poetry.” —Automattic

Code Tag

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This scarsly known tag emulates keyboard text, which is usually styled like the <code> tag.

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This tag styles large blocks of code.

.post-title {
	margin: 0 0 5px;
	font-weight: bold;
	font-size: 38px;
	line-height: 1.2;
	and here's a line of some really, really, really, really long text, just to see how the PRE tag handles it and to find out how it overflows;
}

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Developers, developers, developers… –Steve Ballmer

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Getting our science styling on with H2O, which should push the “2” down.

Superscript Tag

Still sticking with science and Isaac Newton’s E = MC2, which should lift the 2 up.

As a plant production or operations manager, productivity and efficiency are your top priorities. Precision maintenance combined with data analysis makes these responsibilities more manageable, and enables you and your organisation to make more informed maintenance decisions.

What do we mean by precision maintenance? This concept comes from the idea of accurately pinpointing potential issues that signal the beginnings of anything from unexpected repair needs and downtime to catastrophic machine failure. Precision maintenance gives plant managers the information required to plan the best method of action, and helps them take that action at the optimal time.

In this blog post, we’ll cover:
●          How precision maintenance can help you solve common maintenance challenges
●          The benefits of leaving manual methods behind
●          The importance of leveraging data to make better decisions for your company

The traditional approach to industrial maintenance

Many companies in the energy, pulp and paper, steel and mining sectors still rely on manual maintenance and inspections. Although this is a longstanding practice, on average, only 8% of machinery is frequently inspected. This approach leaves a lot to chance in terms of unexpected downtime and faster machine deterioration.

With these risks in mind, it would be wise for plant managers to take a more proactive approach to industrial maintenance. However, with seemingly no systematic, data-backed way of determining when to inspect machinery or make repairs, these managers are left with a serious challenge.

Barriers to change

A reluctance toward investing in resources and technology, as well as a lack of awareness around precision maintenance methods can both be barriers to updating your maintenance approach. When asked about the main obstacles hindering their plant from improving maintenance methods, 48% of plant employees cited lack of resources or staff, while 38% cited a lack of understanding of new maintenance options and technologies.

However, relying heavily on mere routine check-ups often has costly consequences. It is well known by every operations and production manager that maintenance is crucial to machine health and the overall success of an industrial facility. In fact, maintenance costs account for 15 to 40% of total production costs according to Hans Löfsten, professor of Technology Management and Economics at Chalmers University of Technology.

With such a significant portion of a plant’s budget dedicated to maintenance, it’s imperative to take a cost-effective approach. A maintenance approach that lacks precision, or that relies on reacting to issues as they arise instead of trying to predict them, can result in prematurely ageing equipment and unplanned, costly downtime.

This reactive traditional maintenance method can often lead to repairing machinery once it has already failed or is beginning to fail, leaving little to no room for unexpected failures or monitoring machine wear and tear in between scheduled maintenance. Imagine the amount of energy and time that might be wasted when critical machinery requires extra downtime because you had no way of knowing the machine needed attention weeks or months before the usual scheduled time.

In fact, ageing machinery is the most significant pain point for operations and maintenance, followed closely by equipment failure. Fortunately, this is one of the major areas that precision maintenance is designed to address. Data-backed decision making for precision maintenance is essential for industrial sites because it allows plant managers to predict serious issues before they actually arise. Let’s explore how it works.

Addressing common challenges with precision maintenance

How does precision maintenance help production managers combat ageing machinery, equipment failure and the like? The foundation of precision maintenance is built around monitoring asset conditions and balancing your options.

This proactive approach to maintenance is essential to avoiding emergency shutdowns and ensuring that any shutdowns you do schedule are absolutely necessary. However, keep in mind that downtime needs to be planned well in advance and aligned with your production schedules to minimise production and revenue loss.

Overcoming common maintenance challenges is where precision maintenance and data come into play. By using data collection and analysis to monitor machine conditions in real-time, and predict downtime and repair needs, managers can use plant resources more wisely and delegate responsibilities to staff more effectively.

With precision maintenance software and hardware that automatically and consistently collects and analyses useful data, production managers can go far beyond the limitations of a computerized maintenance management system that only offers a small portion of the required data often collected manually, and stored in an unsystematic way that makes data insights challenging to gather.

Instead, data-backed precision maintenance operates on a system that can be monitored remotely; and plant managers already possess the skills and knowledge needed to adjust notifications and schedule maintenance and repairs in an optimal way.

Hardware and software for easy precision maintenance

Industrial machine maintenance often requires specialised skills and knowledge. If there aren’t enough people on your team with these skills, it creates a significant obstacle as you work to improve your maintenance strategy.

Below are three examples of how using data to collect real-time information about your machinery can alleviate the need for these specialised skills. Leveraging data makes precision maintenance easier and allows you to monitor the condition of individual parts closely.

1. Software

Precision maintenance software solutions collect and analyse data. Using the cloud and embedded edge-analytics, production and operations managers have access to data visualisation tools and various widgets, allowing them to monitor and customise how their data is delivered in an accessible way.

The software is always listening, safely and securely collecting relevant data even outside of regular work hours. It is also highly customisable, allowing managers to set specific notifications for the condition thresholds that best suit their team and their facility.

2. Application: Gearbox condition monitoring

A common, complex and essential component for many industrial facilities, gearboxes are manually inspected manually and quite often. But the way they are monitored is not ideal because facilities typically only collect the data they gather during each manual inspection. This limited view can lead to huge oversights. Instead, gearboxes should be monitored constantly to avoid unexpected downtime or failure.

Through continuous monitoring of several methods including oil condition, in-depth vibration analysis and temperature, managers can gain insights into early signs of wear, changes in oil quality and whether the gearbox is being used efficiently in terms of running hours.

3. Application: Compressor condition monitoring

There are many different types of compressors, so your solution needs to have multiple options for sensors and vibration analysis as well as customisable terminals to ensure that each manager can find a condition monitoring set up that suits their specific needs.

Compressor condition monitoring delivers metrics to help detect signs of wear, user errors, temperature changes and more to help you combat machine ageing and, of course, avoid unscheduled downtime.

Your partner in machine health

How exactly does precision maintenance impact an industrial facility? In terms of cost, the average direct savings cover four months of running a solution like Condence.io.

Monitoring conditions in real-time through precision maintenance instead of relying on traditional methods can reduce repair time significantly, decrease overall equipment effectiveness losses by nearly half, and save around €99,625 per failure, according to McKinsey.

At Condence, we can confidently say that we haven’t missed a single machine failure in 12 months. Through cloud and edge computing, our solution listens, collects and analyses data for plant managers to easily apply to their machinery and facilities.

Book a demo to discover how Condence can revamp the way your organisation approaches maintenance.

The new product from KraftPowercon is part of delivering their customer promise, “we ensure that you can focus on optimizing your core business”. It uses Condence.io technology from Distence.

The new solution unveils hidden and potential issues in rectifiers, saves money by optimizing service visits and maintenance costs as well as offers quick response by on-line support and remote services.

The goal is to increase the reliability and the lifespan of rectifiers. Without proper continuous service and monitoring, productivity and the effectiveness of maintenance and operations is drastically decreased. The new sensing capabilities and analytical tools coupled with a modern cloud-based monitoring architecture makes it a powerful scalable solution.

“Thanks to the interactive interface with logs and diagrams, we can easily keep track via PC, mobile or tablet remotely. The ability to select time intervals, either real-time or anything over the past two years, gives us a good overview for example of long-term changes in production. By proactively monitoring our different processes, we can prevent any malfunctions and increase the product lifetime and prioritize maintenance of the rectifiers. Our professional service engineers can simultaneously provide tips and service advice and keep a watchful eye on the rectifiers.” Niklas Tillbrandt, Global product Manager, commenting on the Condence capabilities.

“Distence and KraftPowercon have worked together for some time to deliver this new product. The Distence team has been more than a technology vendor on this project. We are happy with the partnership they have shown to deliver this to the market”, Niklas Tillbrant comments on the collaboration.

KraftPowercon is a global company with production facilities in Sweden, China and India. They offer innovative solutions, products and services within industrial power supply that make their customers’ processes secure, more reliable, as efficient as possible and improves their availability. In short – by guaranteeing your power supply, KraftPowercon ensures that you can focus on optimizing your core business.

For more information on KraftPowercon and their solutions for rectifiers, please visit https://kraftpowercon.com/

Considering the importance to any production process, the complexity of almost any industrial operation and the effectiveness of proactive maintenance is hard make short and simple if you can exclude full production stoppage from your calculations. It is obvious that significant impact comes from avoidance of downtime, yet this is only part of the total value.

Understanding the relevance and impact to perform right operations at optimal time on a larger fleet of different industrial machinery requires a thorough look into both direct and indirect costs, the IT-infrastructure, the maintenance processes and above all the strategy that guides all the above. It is for this reason that senior management should take a careful look into the preventive maintenance effectiveness and value they deliver “when nothing happens”.

Some principle questions to prepare:

  • What is the impact effectiveness of the preventive team – how do we argue the value that was delivered by actions done at the optimal point?
  • Are we ahead of events or scrambling when the alert comes?
  • How do we make preventive maintenance decisions? How to make sure it’s not too early “just in case” repair?
  • Is my required service and maintenance planning horizon hours, days or months?
  • Where does my maintenance operation stand on utilising digital tools to automatise repetitive tasks like inspection routines?

After considering the answers to the above questions, the next question is: What costs do the decisions or operating models carry. What indirect costs are hidden in the way we operate?

Are we following up and arguing how good work our preventive teams and technologies are delivering? – Do we have a standard practise to do aftermath after a repair to evaluate:

Sum of actual repair cost VS potential repair cost

  • Production time/device stoppage
  • Spare parts + repair services
  • Maintenance work + overtime

On top of the delta between actual and potential repair cost, there is the efficiency of daily operations. When focusing on rotating machinery, we claim that many preventive maintenance teams consume a lot of resources on manually inspecting healthy machines (wasted resources) and in parallel find themselves on the situation of colliding priorities due to repairs, measurements and/or other scheduled tasks. This is mainly due we only observe the tip of the iceberg as the preventive process was designed.

The Iceberg model is a great starting point to introduce the depth of the topic. Depending on the size of the operation, the costs get multiplied as the complexity and the sheer volume of transactions increases. Let’s use a concrete example. In the life cycle cost of a pump, the initial cost of the pump represents some 10%-15% of the LCC. The rest include spare parts, maintenance costs and energy – if, we look at the direct costs only. But what lies below the surface? That depends on the maintenance strategy. In a simple exercise, anyone can run through their own operations, ice chunk by ice chunk, cost driver by cost driver. The results of this exercise will reveal very different results, depending on whether your strategy is reactive or proactive.

The Iceberg Model, Michael Wienker, Ken Henderson, Jacques Volkerts

Modern SaaS-based tools have several benefits for them. We can pick out a few that walk hand in hand with the Ice Berg Model. One, they run in the cloud + edge of the cloud, significantly lowering the need and the cost of IT infrastructure. They are available everywhere anytime, globally – fast to roll out. And so is the data and respective information – centralised by default – available to all interested stakeholders.

Sophisticated tools like Condence.io that have a wide range of methods to detect early symptoms of potential failures, e.g. frequency range in vibration analysis and a large toolkit of analysis tools and algorithms. These will move the detection of potentially failing components earlier, from days to months, and allow for forecasting and tracking, thus enabling a proactive strategy – again globally from one User Interface, moving the detection point earlier and automatic. The ability to track specific parameters translates to time – time for planning. This will help preventive teams to focus on machines and conditions that require attention and plan when to take actions.

Planning results in better resource allocation and cost management as well as budgeting and transparency for the future. Transparency to budding issues, the early symptoms of potential problems results in both less downtime, surprises and increases safety. Failing assets also consume more energy as the performance is not optimal. On top of this, it’s also possible that the root cause of failure creates collateral failures leading to reduced asset life or a replacement. It is generally noted that even only an 8% to 10% increase in temperature over normal working conditions reduces the useful life of an electric motor by half.

Depending on the asset and the nature of the operation, various components of the model apply or carry more weight. An unmanned asset, say a pumping station, is very different from a fully staffed manufacturing facility. They both carry the same issues, just weighted differently. Modern SaaS-based tools work, thanks to their extreme flexibility, in both.

Are you interested to hear more? – Follow up on Linkedin or get in touch with the @distence team. I’d also like to hear your comment and opinion.

 

References & further readings:

The Computerized Maintenance Management System, An Essential Tool for World Class Maintenance – Michael Wienker, Ken Henderson, Jacques Volkerts

It is the deep understanding of both the technology and life cycle of industrial gears and drive trains, that led DB Santasalo to choose their approach to condition monitoring for their GearWatch solution. Lubrication oil is the lifeline, the blood, that keeps the gears running. Just like with us humans, this fluid tells stories, gives signals and helps us trace origins to symptoms and faults. In their highly successful GearWatch solution, lubrication oil plays a key role in helping understand the health of an industrial gear. By measuring both oil particles and oil quality, using proprietary technology, GearWatch not only monitors and analyses industrial gears but warns and assists customers when a situation arises.

It is such a warning that helped save a Pulp Mill the cost of a new €100k gear box in addition to the €2,6 million potential production losses. GearWatch had been installed in this 15-year-old gear only some months earlier. The cloud-based service gave access 24/7 to the critical data from the gear and by using the solution together with the expertise of the ISO certified lubrication and vibration analysts from DBS, the customer was able to run the gear safely until the next scheduled shutdown.

The key value driver in this case is time. GearWatch gave an automatic early warning to the customer so they had time to react and plan and maximize the availability of the asset and thus avoid a costly interruption to production. Time is the key difference between predictive and reactive, run to failure, methods. The further the issue brews, the less time there is to plan and react and the higher the cost is. With GearWatch, DBS customers know the health of their assets and have a professional and controlled way to solve emerging issues. Another benefit is the ability to assign resources with surgical accuracy. “Maintain only when needed” saves costs, as does reduced need for redundancy.

You can learn more about the GearWatch solution at https://dbsantasalo.com/products/gearwatch-condition-monitoring/ or watch their great video at https://vimeo.com/400601132

Flowplus Oy specializes in the maintenance and operation of flow technology. The customer base consists mainly of operators in the industrial, energy and infrastructure sectors. The offering includes versatile service & maintenance services for valves, pumps, electric motors and other rotating machines. Flowplus, operating out of nine locations throughout Finland, has a proactive maintenance concept driving their customers’ maintenance costs down and reliability up.

“The Flowplus philosophy and way of working aligns perfectly with what condence.io has been built for, condition monitoring of multiple critical varying assets in multiple locations. Their focus in industries using rotating machines and the understanding of the benefits of managing and understanding machine health over the life cycle of the machine is an ideal environment for condence.io technology,” comments Janne-Pekka Karttunen, CEO at Distence.

Condence.io technology identifies growing problems early on due to its advanced features, including a wide range of vibration frequencies and long sample lengths. Using condence.io technology, Flowplus professionals get a tool that, with the help of its analysis and clear graphics, gives not only a comprehensive look into the health of the machines but also more time to plan and react accordingly thus increasing their operational excellence and contributing to higher value-add to their customers.

“Condence complement s our offering and will be integrated into our Flowdicator monitoring offering. We have several cases in the sales pipeline, and the first deliveries are already made. We are excited this to initiate this collaboration”

Jarmo Piippo, Founder & CEO, Flowplus Oy
Read more about Flowplus Oy and Condence at:

Flowplus Oy: https://www.flowplus.fi

Condence solution page: https://condence.io

Distence Oy: https://www.distence.fi/en/

Condence team is continually working on making updates and improvements to the sampling and visualisations of the asset health. Condence monitoring technology is built on taking samples of the assets health parameters and doing analysis and visualisations of it, continuously.

Example of how minimum, maximum and average values are visualized in the user interface.
On our latest release, we have improved both, the actual measurement and how the metric is visualised in the cloud UI. In other words, the user can get more out of each measurement. Users are now able to see the full range of values, meaning maximum, minimum and average value of the metric from the period between the current and previous sample.

The new feature enables fast analogue channel monitoring. For instance, we are now able to detect quick changes in important asset health parameters like torque or current draw of electric motors. The update allows for practically constant measurement of analogue channels lifting the resolution to millisecond level. Users are of course able to set notifications and alarms to any of the newly added values.

The driver for the feature was to enable torque measurement and other rapid phenomena measured with sensors in analogue channels. But the visual component is without a doubt useful in monitoring other health metrics and parameters such as vibration analysis as well. The feature is automatically in use on Condence T200 & T210 terminals with software version 2.3.0 and higher. Users can toggle the min/max/avg feature on in the metrics trend component, or it can set as the default selection in the view templates.

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As a plant production or operations manager, productivity and efficiency are your top priorities. Precision maintenance combined with data analysis makes these responsibilities more manageable, and enables you and your organisation to make more informed maintenance decisions.

What do we mean by precision maintenance? This concept comes from the idea of accurately pinpointing potential issues that signal the beginnings of anything from unexpected repair needs and downtime to catastrophic machine failure. Precision maintenance gives plant managers the information required to plan the best method of action, and helps them take that action at the optimal time.

In this blog post, we’ll cover:
●          How precision maintenance can help you solve common maintenance challenges
●          The benefits of leaving manual methods behind
●          The importance of leveraging data to make better decisions for your company

The traditional approach to industrial maintenance

Many companies in the energy, pulp and paper, steel and mining sectors still rely on manual maintenance and inspections. Although this is a longstanding practice, on average, only 8% of machinery is frequently inspected. This approach leaves a lot to chance in terms of unexpected downtime and faster machine deterioration.

With these risks in mind, it would be wise for plant managers to take a more proactive approach to industrial maintenance. However, with seemingly no systematic, data-backed way of determining when to inspect machinery or make repairs, these managers are left with a serious challenge.

Barriers to change

A reluctance toward investing in resources and technology, as well as a lack of awareness around precision maintenance methods can both be barriers to updating your maintenance approach. When asked about the main obstacles hindering their plant from improving maintenance methods, 48% of plant employees cited lack of resources or staff, while 38% cited a lack of understanding of new maintenance options and technologies.

However, relying heavily on mere routine check-ups often has costly consequences. It is well known by every operations and production manager that maintenance is crucial to machine health and the overall success of an industrial facility. In fact, maintenance costs account for 15 to 40% of total production costs according to Hans Löfsten, professor of Technology Management and Economics at Chalmers University of Technology.

With such a significant portion of a plant’s budget dedicated to maintenance, it’s imperative to take a cost-effective approach. A maintenance approach that lacks precision, or that relies on reacting to issues as they arise instead of trying to predict them, can result in prematurely ageing equipment and unplanned, costly downtime.

This reactive traditional maintenance method can often lead to repairing machinery once it has already failed or is beginning to fail, leaving little to no room for unexpected failures or monitoring machine wear and tear in between scheduled maintenance. Imagine the amount of energy and time that might be wasted when critical machinery requires extra downtime because you had no way of knowing the machine needed attention weeks or months before the usual scheduled time.

In fact, ageing machinery is the most significant pain point for operations and maintenance, followed closely by equipment failure. Fortunately, this is one of the major areas that precision maintenance is designed to address. Data-backed decision making for precision maintenance is essential for industrial sites because it allows plant managers to predict serious issues before they actually arise. Let’s explore how it works.

Addressing common challenges with precision maintenance

How does precision maintenance help production managers combat ageing machinery, equipment failure and the like? The foundation of precision maintenance is built around monitoring asset conditions and balancing your options.

This proactive approach to maintenance is essential to avoiding emergency shutdowns and ensuring that any shutdowns you do schedule are absolutely necessary. However, keep in mind that downtime needs to be planned well in advance and aligned with your production schedules to minimise production and revenue loss.

Overcoming common maintenance challenges is where precision maintenance and data come into play. By using data collection and analysis to monitor machine conditions in real-time, and predict downtime and repair needs, managers can use plant resources more wisely and delegate responsibilities to staff more effectively.

With precision maintenance software and hardware that automatically and consistently collects and analyses useful data, production managers can go far beyond the limitations of a computerized maintenance management system that only offers a small portion of the required data often collected manually, and stored in an unsystematic way that makes data insights challenging to gather.

Instead, data-backed precision maintenance operates on a system that can be monitored remotely; and plant managers already possess the skills and knowledge needed to adjust notifications and schedule maintenance and repairs in an optimal way.

Hardware and software for easy precision maintenance

Industrial machine maintenance often requires specialised skills and knowledge. If there aren’t enough people on your team with these skills, it creates a significant obstacle as you work to improve your maintenance strategy.

Below are three examples of how using data to collect real-time information about your machinery can alleviate the need for these specialised skills. Leveraging data makes precision maintenance easier and allows you to monitor the condition of individual parts closely.

1. Software

Precision maintenance software solutions collect and analyse data. Using the cloud and embedded edge-analytics, production and operations managers have access to data visualisation tools and various widgets, allowing them to monitor and customise how their data is delivered in an accessible way.

The software is always listening, safely and securely collecting relevant data even outside of regular work hours. It is also highly customisable, allowing managers to set specific notifications for the condition thresholds that best suit their team and their facility.

2. Application: Gearbox condition monitoring

A common, complex and essential component for many industrial facilities, gearboxes are manually inspected manually and quite often. But the way they are monitored is not ideal because facilities typically only collect the data they gather during each manual inspection. This limited view can lead to huge oversights. Instead, gearboxes should be monitored constantly to avoid unexpected downtime or failure.

Through continuous monitoring of several methods including oil condition, in-depth vibration analysis and temperature, managers can gain insights into early signs of wear, changes in oil quality and whether the gearbox is being used efficiently in terms of running hours.

3. Application: Compressor condition monitoring

There are many different types of compressors, so your solution needs to have multiple options for sensors and vibration analysis as well as customisable terminals to ensure that each manager can find a condition monitoring set up that suits their specific needs.

Compressor condition monitoring delivers metrics to help detect signs of wear, user errors, temperature changes and more to help you combat machine ageing and, of course, avoid unscheduled downtime.

Your partner in machine health

How exactly does precision maintenance impact an industrial facility? In terms of cost, the average direct savings cover four months of running a solution like Condence.io.

Monitoring conditions in real-time through precision maintenance instead of relying on traditional methods can reduce repair time significantly, decrease overall equipment effectiveness losses by nearly half, and save around €99,625 per failure, according to McKinsey.

At Condence, we can confidently say that we haven’t missed a single machine failure in 12 months. Through cloud and edge computing, our solution listens, collects and analyses data for plant managers to easily apply to their machinery and facilities.

Book a demo to discover how Condence can revamp the way your organisation approaches maintenance.

The new product from KraftPowercon is part of delivering their customer promise, “we ensure that you can focus on optimizing your core business”. It uses Condence.io technology from Distence.

The new solution unveils hidden and potential issues in rectifiers, saves money by optimizing service visits and maintenance costs as well as offers quick response by on-line support and remote services.

The goal is to increase the reliability and the lifespan of rectifiers. Without proper continuous service and monitoring, productivity and the effectiveness of maintenance and operations is drastically decreased. The new sensing capabilities and analytical tools coupled with a modern cloud-based monitoring architecture makes it a powerful scalable solution.

“Thanks to the interactive interface with logs and diagrams, we can easily keep track via PC, mobile or tablet remotely. The ability to select time intervals, either real-time or anything over the past two years, gives us a good overview for example of long-term changes in production. By proactively monitoring our different processes, we can prevent any malfunctions and increase the product lifetime and prioritize maintenance of the rectifiers. Our professional service engineers can simultaneously provide tips and service advice and keep a watchful eye on the rectifiers.” Niklas Tillbrandt, Global product Manager, commenting on the Condence capabilities.

“Distence and KraftPowercon have worked together for some time to deliver this new product. The Distence team has been more than a technology vendor on this project. We are happy with the partnership they have shown to deliver this to the market”, Niklas Tillbrant comments on the collaboration.

KraftPowercon is a global company with production facilities in Sweden, China and India. They offer innovative solutions, products and services within industrial power supply that make their customers’ processes secure, more reliable, as efficient as possible and improves their availability. In short – by guaranteeing your power supply, KraftPowercon ensures that you can focus on optimizing your core business.

For more information on KraftPowercon and their solutions for rectifiers, please visit https://kraftpowercon.com/

Considering the importance to any production process, the complexity of almost any industrial operation and the effectiveness of proactive maintenance is hard make short and simple if you can exclude full production stoppage from your calculations. It is obvious that significant impact comes from avoidance of downtime, yet this is only part of the total value.

Understanding the relevance and impact to perform right operations at optimal time on a larger fleet of different industrial machinery requires a thorough look into both direct and indirect costs, the IT-infrastructure, the maintenance processes and above all the strategy that guides all the above. It is for this reason that senior management should take a careful look into the preventive maintenance effectiveness and value they deliver “when nothing happens”.

Some principle questions to prepare:

  • What is the impact effectiveness of the preventive team – how do we argue the value that was delivered by actions done at the optimal point?
  • Are we ahead of events or scrambling when the alert comes?
  • How do we make preventive maintenance decisions? How to make sure it’s not too early “just in case” repair?
  • Is my required service and maintenance planning horizon hours, days or months?
  • Where does my maintenance operation stand on utilising digital tools to automatise repetitive tasks like inspection routines?

After considering the answers to the above questions, the next question is: What costs do the decisions or operating models carry. What indirect costs are hidden in the way we operate?

Are we following up and arguing how good work our preventive teams and technologies are delivering? – Do we have a standard practise to do aftermath after a repair to evaluate:

Sum of actual repair cost VS potential repair cost

  • Production time/device stoppage
  • Spare parts + repair services
  • Maintenance work + overtime

On top of the delta between actual and potential repair cost, there is the efficiency of daily operations. When focusing on rotating machinery, we claim that many preventive maintenance teams consume a lot of resources on manually inspecting healthy machines (wasted resources) and in parallel find themselves on the situation of colliding priorities due to repairs, measurements and/or other scheduled tasks. This is mainly due we only observe the tip of the iceberg as the preventive process was designed.

The Iceberg model is a great starting point to introduce the depth of the topic. Depending on the size of the operation, the costs get multiplied as the complexity and the sheer volume of transactions increases. Let’s use a concrete example. In the life cycle cost of a pump, the initial cost of the pump represents some 10%-15% of the LCC. The rest include spare parts, maintenance costs and energy – if, we look at the direct costs only. But what lies below the surface? That depends on the maintenance strategy. In a simple exercise, anyone can run through their own operations, ice chunk by ice chunk, cost driver by cost driver. The results of this exercise will reveal very different results, depending on whether your strategy is reactive or proactive.

The Iceberg Model, Michael Wienker, Ken Henderson, Jacques Volkerts

Modern SaaS-based tools have several benefits for them. We can pick out a few that walk hand in hand with the Ice Berg Model. One, they run in the cloud + edge of the cloud, significantly lowering the need and the cost of IT infrastructure. They are available everywhere anytime, globally – fast to roll out. And so is the data and respective information – centralised by default – available to all interested stakeholders.

Sophisticated tools like Condence.io that have a wide range of methods to detect early symptoms of potential failures, e.g. frequency range in vibration analysis and a large toolkit of analysis tools and algorithms. These will move the detection of potentially failing components earlier, from days to months, and allow for forecasting and tracking, thus enabling a proactive strategy – again globally from one User Interface, moving the detection point earlier and automatic. The ability to track specific parameters translates to time – time for planning. This will help preventive teams to focus on machines and conditions that require attention and plan when to take actions.

Planning results in better resource allocation and cost management as well as budgeting and transparency for the future. Transparency to budding issues, the early symptoms of potential problems results in both less downtime, surprises and increases safety. Failing assets also consume more energy as the performance is not optimal. On top of this, it’s also possible that the root cause of failure creates collateral failures leading to reduced asset life or a replacement. It is generally noted that even only an 8% to 10% increase in temperature over normal working conditions reduces the useful life of an electric motor by half.

Depending on the asset and the nature of the operation, various components of the model apply or carry more weight. An unmanned asset, say a pumping station, is very different from a fully staffed manufacturing facility. They both carry the same issues, just weighted differently. Modern SaaS-based tools work, thanks to their extreme flexibility, in both.

Are you interested to hear more? – Follow up on Linkedin or get in touch with the @distence team. I’d also like to hear your comment and opinion.

 

References & further readings:

The Computerized Maintenance Management System, An Essential Tool for World Class Maintenance – Michael Wienker, Ken Henderson, Jacques Volkerts

It is the deep understanding of both the technology and life cycle of industrial gears and drive trains, that led DB Santasalo to choose their approach to condition monitoring for their GearWatch solution. Lubrication oil is the lifeline, the blood, that keeps the gears running. Just like with us humans, this fluid tells stories, gives signals and helps us trace origins to symptoms and faults. In their highly successful GearWatch solution, lubrication oil plays a key role in helping understand the health of an industrial gear. By measuring both oil particles and oil quality, using proprietary technology, GearWatch not only monitors and analyses industrial gears but warns and assists customers when a situation arises.

It is such a warning that helped save a Pulp Mill the cost of a new €100k gear box in addition to the €2,6 million potential production losses. GearWatch had been installed in this 15-year-old gear only some months earlier. The cloud-based service gave access 24/7 to the critical data from the gear and by using the solution together with the expertise of the ISO certified lubrication and vibration analysts from DBS, the customer was able to run the gear safely until the next scheduled shutdown.

The key value driver in this case is time. GearWatch gave an automatic early warning to the customer so they had time to react and plan and maximize the availability of the asset and thus avoid a costly interruption to production. Time is the key difference between predictive and reactive, run to failure, methods. The further the issue brews, the less time there is to plan and react and the higher the cost is. With GearWatch, DBS customers know the health of their assets and have a professional and controlled way to solve emerging issues. Another benefit is the ability to assign resources with surgical accuracy. “Maintain only when needed” saves costs, as does reduced need for redundancy.

You can learn more about the GearWatch solution at https://dbsantasalo.com/products/gearwatch-condition-monitoring/ or watch their great video at https://vimeo.com/400601132

Flowplus Oy specializes in the maintenance and operation of flow technology. The customer base consists mainly of operators in the industrial, energy and infrastructure sectors. The offering includes versatile service & maintenance services for valves, pumps, electric motors and other rotating machines. Flowplus, operating out of nine locations throughout Finland, has a proactive maintenance concept driving their customers’ maintenance costs down and reliability up.

“The Flowplus philosophy and way of working aligns perfectly with what condence.io has been built for, condition monitoring of multiple critical varying assets in multiple locations. Their focus in industries using rotating machines and the understanding of the benefits of managing and understanding machine health over the life cycle of the machine is an ideal environment for condence.io technology,” comments Janne-Pekka Karttunen, CEO at Distence.

Condence.io technology identifies growing problems early on due to its advanced features, including a wide range of vibration frequencies and long sample lengths. Using condence.io technology, Flowplus professionals get a tool that, with the help of its analysis and clear graphics, gives not only a comprehensive look into the health of the machines but also more time to plan and react accordingly thus increasing their operational excellence and contributing to higher value-add to their customers.

“Condence complement s our offering and will be integrated into our Flowdicator monitoring offering. We have several cases in the sales pipeline, and the first deliveries are already made. We are excited this to initiate this collaboration”

Jarmo Piippo, Founder & CEO, Flowplus Oy
Read more about Flowplus Oy and Condence at:

Flowplus Oy: https://www.flowplus.fi

Condence solution page: https://condence.io

Distence Oy: https://www.distence.fi/en/

Condence team is continually working on making updates and improvements to the sampling and visualisations of the asset health. Condence monitoring technology is built on taking samples of the assets health parameters and doing analysis and visualisations of it, continuously.

Example of how minimum, maximum and average values are visualized in the user interface.
On our latest release, we have improved both, the actual measurement and how the metric is visualised in the cloud UI. In other words, the user can get more out of each measurement. Users are now able to see the full range of values, meaning maximum, minimum and average value of the metric from the period between the current and previous sample.

The new feature enables fast analogue channel monitoring. For instance, we are now able to detect quick changes in important asset health parameters like torque or current draw of electric motors. The update allows for practically constant measurement of analogue channels lifting the resolution to millisecond level. Users are of course able to set notifications and alarms to any of the newly added values.

The driver for the feature was to enable torque measurement and other rapid phenomena measured with sensors in analogue channels. But the visual component is without a doubt useful in monitoring other health metrics and parameters such as vibration analysis as well. The feature is automatically in use on Condence T200 & T210 terminals with software version 2.3.0 and higher. Users can toggle the min/max/avg feature on in the metrics trend component, or it can set as the default selection in the view templates.

Style 4

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi sagittis, sem quis lacinia faucibus, orci ipsum gravida tortor, vel interdum mi sapien ut justo. Nulla varius consequat magna, id molestie ipsum volutpat quis. Pellentesque ipsum erat, facilisis ut venenatis eu, sodales vel dolor.

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As a plant production or operations manager, productivity and efficiency are your top priorities. Precision maintenance combined with data analysis makes these responsibilities more manageable, and enables you and your organisation to make more informed maintenance decisions.

What do we mean by precision maintenance? This concept comes from the idea of accurately pinpointing potential issues that signal the beginnings of anything from unexpected repair needs and downtime to catastrophic machine failure. Precision maintenance gives plant managers the information required to plan the best method of action, and helps them take that action at the optimal time.

In this blog post, we’ll cover:
●          How precision maintenance can help you solve common maintenance challenges
●          The benefits of leaving manual methods behind
●          The importance of leveraging data to make better decisions for your company

The traditional approach to industrial maintenance

Many companies in the energy, pulp and paper, steel and mining sectors still rely on manual maintenance and inspections. Although this is a longstanding practice, on average, only 8% of machinery is frequently inspected. This approach leaves a lot to chance in terms of unexpected downtime and faster machine deterioration.

With these risks in mind, it would be wise for plant managers to take a more proactive approach to industrial maintenance. However, with seemingly no systematic, data-backed way of determining when to inspect machinery or make repairs, these managers are left with a serious challenge.

Barriers to change

A reluctance toward investing in resources and technology, as well as a lack of awareness around precision maintenance methods can both be barriers to updating your maintenance approach. When asked about the main obstacles hindering their plant from improving maintenance methods, 48% of plant employees cited lack of resources or staff, while 38% cited a lack of understanding of new maintenance options and technologies.

However, relying heavily on mere routine check-ups often has costly consequences. It is well known by every operations and production manager that maintenance is crucial to machine health and the overall success of an industrial facility. In fact, maintenance costs account for 15 to 40% of total production costs according to Hans Löfsten, professor of Technology Management and Economics at Chalmers University of Technology.

With such a significant portion of a plant’s budget dedicated to maintenance, it’s imperative to take a cost-effective approach. A maintenance approach that lacks precision, or that relies on reacting to issues as they arise instead of trying to predict them, can result in prematurely ageing equipment and unplanned, costly downtime.

This reactive traditional maintenance method can often lead to repairing machinery once it has already failed or is beginning to fail, leaving little to no room for unexpected failures or monitoring machine wear and tear in between scheduled maintenance. Imagine the amount of energy and time that might be wasted when critical machinery requires extra downtime because you had no way of knowing the machine needed attention weeks or months before the usual scheduled time.

In fact, ageing machinery is the most significant pain point for operations and maintenance, followed closely by equipment failure. Fortunately, this is one of the major areas that precision maintenance is designed to address. Data-backed decision making for precision maintenance is essential for industrial sites because it allows plant managers to predict serious issues before they actually arise. Let’s explore how it works.

Addressing common challenges with precision maintenance

How does precision maintenance help production managers combat ageing machinery, equipment failure and the like? The foundation of precision maintenance is built around monitoring asset conditions and balancing your options.

This proactive approach to maintenance is essential to avoiding emergency shutdowns and ensuring that any shutdowns you do schedule are absolutely necessary. However, keep in mind that downtime needs to be planned well in advance and aligned with your production schedules to minimise production and revenue loss.

Overcoming common maintenance challenges is where precision maintenance and data come into play. By using data collection and analysis to monitor machine conditions in real-time, and predict downtime and repair needs, managers can use plant resources more wisely and delegate responsibilities to staff more effectively.

With precision maintenance software and hardware that automatically and consistently collects and analyses useful data, production managers can go far beyond the limitations of a computerized maintenance management system that only offers a small portion of the required data often collected manually, and stored in an unsystematic way that makes data insights challenging to gather.

Instead, data-backed precision maintenance operates on a system that can be monitored remotely; and plant managers already possess the skills and knowledge needed to adjust notifications and schedule maintenance and repairs in an optimal way.

Hardware and software for easy precision maintenance

Industrial machine maintenance often requires specialised skills and knowledge. If there aren’t enough people on your team with these skills, it creates a significant obstacle as you work to improve your maintenance strategy.

Below are three examples of how using data to collect real-time information about your machinery can alleviate the need for these specialised skills. Leveraging data makes precision maintenance easier and allows you to monitor the condition of individual parts closely.

1. Software

Precision maintenance software solutions collect and analyse data. Using the cloud and embedded edge-analytics, production and operations managers have access to data visualisation tools and various widgets, allowing them to monitor and customise how their data is delivered in an accessible way.

The software is always listening, safely and securely collecting relevant data even outside of regular work hours. It is also highly customisable, allowing managers to set specific notifications for the condition thresholds that best suit their team and their facility.

2. Application: Gearbox condition monitoring

A common, complex and essential component for many industrial facilities, gearboxes are manually inspected manually and quite often. But the way they are monitored is not ideal because facilities typically only collect the data they gather during each manual inspection. This limited view can lead to huge oversights. Instead, gearboxes should be monitored constantly to avoid unexpected downtime or failure.

Through continuous monitoring of several methods including oil condition, in-depth vibration analysis and temperature, managers can gain insights into early signs of wear, changes in oil quality and whether the gearbox is being used efficiently in terms of running hours.

3. Application: Compressor condition monitoring

There are many different types of compressors, so your solution needs to have multiple options for sensors and vibration analysis as well as customisable terminals to ensure that each manager can find a condition monitoring set up that suits their specific needs.

Compressor condition monitoring delivers metrics to help detect signs of wear, user errors, temperature changes and more to help you combat machine ageing and, of course, avoid unscheduled downtime.

Your partner in machine health

How exactly does precision maintenance impact an industrial facility? In terms of cost, the average direct savings cover four months of running a solution like Condence.io.

Monitoring conditions in real-time through precision maintenance instead of relying on traditional methods can reduce repair time significantly, decrease overall equipment effectiveness losses by nearly half, and save around €99,625 per failure, according to McKinsey.

At Condence, we can confidently say that we haven’t missed a single machine failure in 12 months. Through cloud and edge computing, our solution listens, collects and analyses data for plant managers to easily apply to their machinery and facilities.

Book a demo to discover how Condence can revamp the way your organisation approaches maintenance.

The new product from KraftPowercon is part of delivering their customer promise, “we ensure that you can focus on optimizing your core business”. It uses Condence.io technology from Distence.

The new solution unveils hidden and potential issues in rectifiers, saves money by optimizing service visits and maintenance costs as well as offers quick response by on-line support and remote services.

The goal is to increase the reliability and the lifespan of rectifiers. Without proper continuous service and monitoring, productivity and the effectiveness of maintenance and operations is drastically decreased. The new sensing capabilities and analytical tools coupled with a modern cloud-based monitoring architecture makes it a powerful scalable solution.

“Thanks to the interactive interface with logs and diagrams, we can easily keep track via PC, mobile or tablet remotely. The ability to select time intervals, either real-time or anything over the past two years, gives us a good overview for example of long-term changes in production. By proactively monitoring our different processes, we can prevent any malfunctions and increase the product lifetime and prioritize maintenance of the rectifiers. Our professional service engineers can simultaneously provide tips and service advice and keep a watchful eye on the rectifiers.” Niklas Tillbrandt, Global product Manager, commenting on the Condence capabilities.

“Distence and KraftPowercon have worked together for some time to deliver this new product. The Distence team has been more than a technology vendor on this project. We are happy with the partnership they have shown to deliver this to the market”, Niklas Tillbrant comments on the collaboration.

KraftPowercon is a global company with production facilities in Sweden, China and India. They offer innovative solutions, products and services within industrial power supply that make their customers’ processes secure, more reliable, as efficient as possible and improves their availability. In short – by guaranteeing your power supply, KraftPowercon ensures that you can focus on optimizing your core business.

For more information on KraftPowercon and their solutions for rectifiers, please visit https://kraftpowercon.com/

Considering the importance to any production process, the complexity of almost any industrial operation and the effectiveness of proactive maintenance is hard make short and simple if you can exclude full production stoppage from your calculations. It is obvious that significant impact comes from avoidance of downtime, yet this is only part of the total value.

Understanding the relevance and impact to perform right operations at optimal time on a larger fleet of different industrial machinery requires a thorough look into both direct and indirect costs, the IT-infrastructure, the maintenance processes and above all the strategy that guides all the above. It is for this reason that senior management should take a careful look into the preventive maintenance effectiveness and value they deliver “when nothing happens”.

Some principle questions to prepare:

  • What is the impact effectiveness of the preventive team – how do we argue the value that was delivered by actions done at the optimal point?
  • Are we ahead of events or scrambling when the alert comes?
  • How do we make preventive maintenance decisions? How to make sure it’s not too early “just in case” repair?
  • Is my required service and maintenance planning horizon hours, days or months?
  • Where does my maintenance operation stand on utilising digital tools to automatise repetitive tasks like inspection routines?

After considering the answers to the above questions, the next question is: What costs do the decisions or operating models carry. What indirect costs are hidden in the way we operate?

Are we following up and arguing how good work our preventive teams and technologies are delivering? – Do we have a standard practise to do aftermath after a repair to evaluate:

Sum of actual repair cost VS potential repair cost

  • Production time/device stoppage
  • Spare parts + repair services
  • Maintenance work + overtime

On top of the delta between actual and potential repair cost, there is the efficiency of daily operations. When focusing on rotating machinery, we claim that many preventive maintenance teams consume a lot of resources on manually inspecting healthy machines (wasted resources) and in parallel find themselves on the situation of colliding priorities due to repairs, measurements and/or other scheduled tasks. This is mainly due we only observe the tip of the iceberg as the preventive process was designed.

The Iceberg model is a great starting point to introduce the depth of the topic. Depending on the size of the operation, the costs get multiplied as the complexity and the sheer volume of transactions increases. Let’s use a concrete example. In the life cycle cost of a pump, the initial cost of the pump represents some 10%-15% of the LCC. The rest include spare parts, maintenance costs and energy – if, we look at the direct costs only. But what lies below the surface? That depends on the maintenance strategy. In a simple exercise, anyone can run through their own operations, ice chunk by ice chunk, cost driver by cost driver. The results of this exercise will reveal very different results, depending on whether your strategy is reactive or proactive.

The Iceberg Model, Michael Wienker, Ken Henderson, Jacques Volkerts

Modern SaaS-based tools have several benefits for them. We can pick out a few that walk hand in hand with the Ice Berg Model. One, they run in the cloud + edge of the cloud, significantly lowering the need and the cost of IT infrastructure. They are available everywhere anytime, globally – fast to roll out. And so is the data and respective information – centralised by default – available to all interested stakeholders.

Sophisticated tools like Condence.io that have a wide range of methods to detect early symptoms of potential failures, e.g. frequency range in vibration analysis and a large toolkit of analysis tools and algorithms. These will move the detection of potentially failing components earlier, from days to months, and allow for forecasting and tracking, thus enabling a proactive strategy – again globally from one User Interface, moving the detection point earlier and automatic. The ability to track specific parameters translates to time – time for planning. This will help preventive teams to focus on machines and conditions that require attention and plan when to take actions.

Planning results in better resource allocation and cost management as well as budgeting and transparency for the future. Transparency to budding issues, the early symptoms of potential problems results in both less downtime, surprises and increases safety. Failing assets also consume more energy as the performance is not optimal. On top of this, it’s also possible that the root cause of failure creates collateral failures leading to reduced asset life or a replacement. It is generally noted that even only an 8% to 10% increase in temperature over normal working conditions reduces the useful life of an electric motor by half.

Depending on the asset and the nature of the operation, various components of the model apply or carry more weight. An unmanned asset, say a pumping station, is very different from a fully staffed manufacturing facility. They both carry the same issues, just weighted differently. Modern SaaS-based tools work, thanks to their extreme flexibility, in both.

Are you interested to hear more? – Follow up on Linkedin or get in touch with the @distence team. I’d also like to hear your comment and opinion.

 

References & further readings:

The Computerized Maintenance Management System, An Essential Tool for World Class Maintenance – Michael Wienker, Ken Henderson, Jacques Volkerts

It is the deep understanding of both the technology and life cycle of industrial gears and drive trains, that led DB Santasalo to choose their approach to condition monitoring for their GearWatch solution. Lubrication oil is the lifeline, the blood, that keeps the gears running. Just like with us humans, this fluid tells stories, gives signals and helps us trace origins to symptoms and faults. In their highly successful GearWatch solution, lubrication oil plays a key role in helping understand the health of an industrial gear. By measuring both oil particles and oil quality, using proprietary technology, GearWatch not only monitors and analyses industrial gears but warns and assists customers when a situation arises.

It is such a warning that helped save a Pulp Mill the cost of a new €100k gear box in addition to the €2,6 million potential production losses. GearWatch had been installed in this 15-year-old gear only some months earlier. The cloud-based service gave access 24/7 to the critical data from the gear and by using the solution together with the expertise of the ISO certified lubrication and vibration analysts from DBS, the customer was able to run the gear safely until the next scheduled shutdown.

The key value driver in this case is time. GearWatch gave an automatic early warning to the customer so they had time to react and plan and maximize the availability of the asset and thus avoid a costly interruption to production. Time is the key difference between predictive and reactive, run to failure, methods. The further the issue brews, the less time there is to plan and react and the higher the cost is. With GearWatch, DBS customers know the health of their assets and have a professional and controlled way to solve emerging issues. Another benefit is the ability to assign resources with surgical accuracy. “Maintain only when needed” saves costs, as does reduced need for redundancy.

You can learn more about the GearWatch solution at https://dbsantasalo.com/products/gearwatch-condition-monitoring/ or watch their great video at https://vimeo.com/400601132

Flowplus Oy specializes in the maintenance and operation of flow technology. The customer base consists mainly of operators in the industrial, energy and infrastructure sectors. The offering includes versatile service & maintenance services for valves, pumps, electric motors and other rotating machines. Flowplus, operating out of nine locations throughout Finland, has a proactive maintenance concept driving their customers’ maintenance costs down and reliability up.

“The Flowplus philosophy and way of working aligns perfectly with what condence.io has been built for, condition monitoring of multiple critical varying assets in multiple locations. Their focus in industries using rotating machines and the understanding of the benefits of managing and understanding machine health over the life cycle of the machine is an ideal environment for condence.io technology,” comments Janne-Pekka Karttunen, CEO at Distence.

Condence.io technology identifies growing problems early on due to its advanced features, including a wide range of vibration frequencies and long sample lengths. Using condence.io technology, Flowplus professionals get a tool that, with the help of its analysis and clear graphics, gives not only a comprehensive look into the health of the machines but also more time to plan and react accordingly thus increasing their operational excellence and contributing to higher value-add to their customers.

“Condence complement s our offering and will be integrated into our Flowdicator monitoring offering. We have several cases in the sales pipeline, and the first deliveries are already made. We are excited this to initiate this collaboration”

Jarmo Piippo, Founder & CEO, Flowplus Oy
Read more about Flowplus Oy and Condence at:

Flowplus Oy: https://www.flowplus.fi

Condence solution page: https://condence.io

Distence Oy: https://www.distence.fi/en/

Condence team is continually working on making updates and improvements to the sampling and visualisations of the asset health. Condence monitoring technology is built on taking samples of the assets health parameters and doing analysis and visualisations of it, continuously.

Example of how minimum, maximum and average values are visualized in the user interface.
On our latest release, we have improved both, the actual measurement and how the metric is visualised in the cloud UI. In other words, the user can get more out of each measurement. Users are now able to see the full range of values, meaning maximum, minimum and average value of the metric from the period between the current and previous sample.

The new feature enables fast analogue channel monitoring. For instance, we are now able to detect quick changes in important asset health parameters like torque or current draw of electric motors. The update allows for practically constant measurement of analogue channels lifting the resolution to millisecond level. Users are of course able to set notifications and alarms to any of the newly added values.

The driver for the feature was to enable torque measurement and other rapid phenomena measured with sensors in analogue channels. But the visual component is without a doubt useful in monitoring other health metrics and parameters such as vibration analysis as well. The feature is automatically in use on Condence T200 & T210 terminals with software version 2.3.0 and higher. Users can toggle the min/max/avg feature on in the metrics trend component, or it can set as the default selection in the view templates.

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Single line blockquote:

Stay hungry. Stay foolish.

Multi line blockquote with a cite reference:

People think focus means saying yes to the thing you’ve got to focus on. But that’s not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I’m actually as proud of the things we haven’t done as the things I have done. Innovation is saying no to 1,000 things. Steve Jobs – Apple Worldwide Developers’ Conference, 1997

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These supported tags come from the WordPress.com code FAQ.

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1 Infinite Loop
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United States

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The acronym ftw stands for “for the win”.

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These tests are a big deal, but this tag is no longer supported in HTML5.

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Getting our science styling on with H2O, which should push the “2” down.

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Still sticking with science and Isaac Newton’s E = MC2, which should lift the 2 up.

As a plant production or operations manager, productivity and efficiency are your top priorities. Precision maintenance combined with data analysis makes these responsibilities more manageable, and enables you and your organisation to make more informed maintenance decisions.

What do we mean by precision maintenance? This concept comes from the idea of accurately pinpointing potential issues that signal the beginnings of anything from unexpected repair needs and downtime to catastrophic machine failure. Precision maintenance gives plant managers the information required to plan the best method of action, and helps them take that action at the optimal time.

In this blog post, we’ll cover:
●          How precision maintenance can help you solve common maintenance challenges
●          The benefits of leaving manual methods behind
●          The importance of leveraging data to make better decisions for your company

The traditional approach to industrial maintenance

Many companies in the energy, pulp and paper, steel and mining sectors still rely on manual maintenance and inspections. Although this is a longstanding practice, on average, only 8% of machinery is frequently inspected. This approach leaves a lot to chance in terms of unexpected downtime and faster machine deterioration.

With these risks in mind, it would be wise for plant managers to take a more proactive approach to industrial maintenance. However, with seemingly no systematic, data-backed way of determining when to inspect machinery or make repairs, these managers are left with a serious challenge.

Barriers to change

A reluctance toward investing in resources and technology, as well as a lack of awareness around precision maintenance methods can both be barriers to updating your maintenance approach. When asked about the main obstacles hindering their plant from improving maintenance methods, 48% of plant employees cited lack of resources or staff, while 38% cited a lack of understanding of new maintenance options and technologies.

However, relying heavily on mere routine check-ups often has costly consequences. It is well known by every operations and production manager that maintenance is crucial to machine health and the overall success of an industrial facility. In fact, maintenance costs account for 15 to 40% of total production costs according to Hans Löfsten, professor of Technology Management and Economics at Chalmers University of Technology.

With such a significant portion of a plant’s budget dedicated to maintenance, it’s imperative to take a cost-effective approach. A maintenance approach that lacks precision, or that relies on reacting to issues as they arise instead of trying to predict them, can result in prematurely ageing equipment and unplanned, costly downtime.

This reactive traditional maintenance method can often lead to repairing machinery once it has already failed or is beginning to fail, leaving little to no room for unexpected failures or monitoring machine wear and tear in between scheduled maintenance. Imagine the amount of energy and time that might be wasted when critical machinery requires extra downtime because you had no way of knowing the machine needed attention weeks or months before the usual scheduled time.

In fact, ageing machinery is the most significant pain point for operations and maintenance, followed closely by equipment failure. Fortunately, this is one of the major areas that precision maintenance is designed to address. Data-backed decision making for precision maintenance is essential for industrial sites because it allows plant managers to predict serious issues before they actually arise. Let’s explore how it works.

Addressing common challenges with precision maintenance

How does precision maintenance help production managers combat ageing machinery, equipment failure and the like? The foundation of precision maintenance is built around monitoring asset conditions and balancing your options.

This proactive approach to maintenance is essential to avoiding emergency shutdowns and ensuring that any shutdowns you do schedule are absolutely necessary. However, keep in mind that downtime needs to be planned well in advance and aligned with your production schedules to minimise production and revenue loss.

Overcoming common maintenance challenges is where precision maintenance and data come into play. By using data collection and analysis to monitor machine conditions in real-time, and predict downtime and repair needs, managers can use plant resources more wisely and delegate responsibilities to staff more effectively.

With precision maintenance software and hardware that automatically and consistently collects and analyses useful data, production managers can go far beyond the limitations of a computerized maintenance management system that only offers a small portion of the required data often collected manually, and stored in an unsystematic way that makes data insights challenging to gather.

Instead, data-backed precision maintenance operates on a system that can be monitored remotely; and plant managers already possess the skills and knowledge needed to adjust notifications and schedule maintenance and repairs in an optimal way.

Hardware and software for easy precision maintenance

Industrial machine maintenance often requires specialised skills and knowledge. If there aren’t enough people on your team with these skills, it creates a significant obstacle as you work to improve your maintenance strategy.

Below are three examples of how using data to collect real-time information about your machinery can alleviate the need for these specialised skills. Leveraging data makes precision maintenance easier and allows you to monitor the condition of individual parts closely.

1. Software

Precision maintenance software solutions collect and analyse data. Using the cloud and embedded edge-analytics, production and operations managers have access to data visualisation tools and various widgets, allowing them to monitor and customise how their data is delivered in an accessible way.

The software is always listening, safely and securely collecting relevant data even outside of regular work hours. It is also highly customisable, allowing managers to set specific notifications for the condition thresholds that best suit their team and their facility.

2. Application: Gearbox condition monitoring

A common, complex and essential component for many industrial facilities, gearboxes are manually inspected manually and quite often. But the way they are monitored is not ideal because facilities typically only collect the data they gather during each manual inspection. This limited view can lead to huge oversights. Instead, gearboxes should be monitored constantly to avoid unexpected downtime or failure.

Through continuous monitoring of several methods including oil condition, in-depth vibration analysis and temperature, managers can gain insights into early signs of wear, changes in oil quality and whether the gearbox is being used efficiently in terms of running hours.

3. Application: Compressor condition monitoring

There are many different types of compressors, so your solution needs to have multiple options for sensors and vibration analysis as well as customisable terminals to ensure that each manager can find a condition monitoring set up that suits their specific needs.

Compressor condition monitoring delivers metrics to help detect signs of wear, user errors, temperature changes and more to help you combat machine ageing and, of course, avoid unscheduled downtime.

Your partner in machine health

How exactly does precision maintenance impact an industrial facility? In terms of cost, the average direct savings cover four months of running a solution like Condence.io.

Monitoring conditions in real-time through precision maintenance instead of relying on traditional methods can reduce repair time significantly, decrease overall equipment effectiveness losses by nearly half, and save around €99,625 per failure, according to McKinsey.

At Condence, we can confidently say that we haven’t missed a single machine failure in 12 months. Through cloud and edge computing, our solution listens, collects and analyses data for plant managers to easily apply to their machinery and facilities.

Book a demo to discover how Condence can revamp the way your organisation approaches maintenance.

The new product from KraftPowercon is part of delivering their customer promise, “we ensure that you can focus on optimizing your core business”. It uses Condence.io technology from Distence.

The new solution unveils hidden and potential issues in rectifiers, saves money by optimizing service visits and maintenance costs as well as offers quick response by on-line support and remote services.

The goal is to increase the reliability and the lifespan of rectifiers. Without proper continuous service and monitoring, productivity and the effectiveness of maintenance and operations is drastically decreased. The new sensing capabilities and analytical tools coupled with a modern cloud-based monitoring architecture makes it a powerful scalable solution.

“Thanks to the interactive interface with logs and diagrams, we can easily keep track via PC, mobile or tablet remotely. The ability to select time intervals, either real-time or anything over the past two years, gives us a good overview for example of long-term changes in production. By proactively monitoring our different processes, we can prevent any malfunctions and increase the product lifetime and prioritize maintenance of the rectifiers. Our professional service engineers can simultaneously provide tips and service advice and keep a watchful eye on the rectifiers.” Niklas Tillbrandt, Global product Manager, commenting on the Condence capabilities.

“Distence and KraftPowercon have worked together for some time to deliver this new product. The Distence team has been more than a technology vendor on this project. We are happy with the partnership they have shown to deliver this to the market”, Niklas Tillbrant comments on the collaboration.

KraftPowercon is a global company with production facilities in Sweden, China and India. They offer innovative solutions, products and services within industrial power supply that make their customers’ processes secure, more reliable, as efficient as possible and improves their availability. In short – by guaranteeing your power supply, KraftPowercon ensures that you can focus on optimizing your core business.

For more information on KraftPowercon and their solutions for rectifiers, please visit https://kraftpowercon.com/

Considering the importance to any production process, the complexity of almost any industrial operation and the effectiveness of proactive maintenance is hard make short and simple if you can exclude full production stoppage from your calculations. It is obvious that significant impact comes from avoidance of downtime, yet this is only part of the total value.

Understanding the relevance and impact to perform right operations at optimal time on a larger fleet of different industrial machinery requires a thorough look into both direct and indirect costs, the IT-infrastructure, the maintenance processes and above all the strategy that guides all the above. It is for this reason that senior management should take a careful look into the preventive maintenance effectiveness and value they deliver “when nothing happens”.

Some principle questions to prepare:

  • What is the impact effectiveness of the preventive team – how do we argue the value that was delivered by actions done at the optimal point?
  • Are we ahead of events or scrambling when the alert comes?
  • How do we make preventive maintenance decisions? How to make sure it’s not too early “just in case” repair?
  • Is my required service and maintenance planning horizon hours, days or months?
  • Where does my maintenance operation stand on utilising digital tools to automatise repetitive tasks like inspection routines?

After considering the answers to the above questions, the next question is: What costs do the decisions or operating models carry. What indirect costs are hidden in the way we operate?

Are we following up and arguing how good work our preventive teams and technologies are delivering? – Do we have a standard practise to do aftermath after a repair to evaluate:

Sum of actual repair cost VS potential repair cost

  • Production time/device stoppage
  • Spare parts + repair services
  • Maintenance work + overtime

On top of the delta between actual and potential repair cost, there is the efficiency of daily operations. When focusing on rotating machinery, we claim that many preventive maintenance teams consume a lot of resources on manually inspecting healthy machines (wasted resources) and in parallel find themselves on the situation of colliding priorities due to repairs, measurements and/or other scheduled tasks. This is mainly due we only observe the tip of the iceberg as the preventive process was designed.

The Iceberg model is a great starting point to introduce the depth of the topic. Depending on the size of the operation, the costs get multiplied as the complexity and the sheer volume of transactions increases. Let’s use a concrete example. In the life cycle cost of a pump, the initial cost of the pump represents some 10%-15% of the LCC. The rest include spare parts, maintenance costs and energy – if, we look at the direct costs only. But what lies below the surface? That depends on the maintenance strategy. In a simple exercise, anyone can run through their own operations, ice chunk by ice chunk, cost driver by cost driver. The results of this exercise will reveal very different results, depending on whether your strategy is reactive or proactive.

The Iceberg Model, Michael Wienker, Ken Henderson, Jacques Volkerts

Modern SaaS-based tools have several benefits for them. We can pick out a few that walk hand in hand with the Ice Berg Model. One, they run in the cloud + edge of the cloud, significantly lowering the need and the cost of IT infrastructure. They are available everywhere anytime, globally – fast to roll out. And so is the data and respective information – centralised by default – available to all interested stakeholders.

Sophisticated tools like Condence.io that have a wide range of methods to detect early symptoms of potential failures, e.g. frequency range in vibration analysis and a large toolkit of analysis tools and algorithms. These will move the detection of potentially failing components earlier, from days to months, and allow for forecasting and tracking, thus enabling a proactive strategy – again globally from one User Interface, moving the detection point earlier and automatic. The ability to track specific parameters translates to time – time for planning. This will help preventive teams to focus on machines and conditions that require attention and plan when to take actions.

Planning results in better resource allocation and cost management as well as budgeting and transparency for the future. Transparency to budding issues, the early symptoms of potential problems results in both less downtime, surprises and increases safety. Failing assets also consume more energy as the performance is not optimal. On top of this, it’s also possible that the root cause of failure creates collateral failures leading to reduced asset life or a replacement. It is generally noted that even only an 8% to 10% increase in temperature over normal working conditions reduces the useful life of an electric motor by half.

Depending on the asset and the nature of the operation, various components of the model apply or carry more weight. An unmanned asset, say a pumping station, is very different from a fully staffed manufacturing facility. They both carry the same issues, just weighted differently. Modern SaaS-based tools work, thanks to their extreme flexibility, in both.

Are you interested to hear more? – Follow up on Linkedin or get in touch with the @distence team. I’d also like to hear your comment and opinion.

 

References & further readings:

The Computerized Maintenance Management System, An Essential Tool for World Class Maintenance – Michael Wienker, Ken Henderson, Jacques Volkerts

It is the deep understanding of both the technology and life cycle of industrial gears and drive trains, that led DB Santasalo to choose their approach to condition monitoring for their GearWatch solution. Lubrication oil is the lifeline, the blood, that keeps the gears running. Just like with us humans, this fluid tells stories, gives signals and helps us trace origins to symptoms and faults. In their highly successful GearWatch solution, lubrication oil plays a key role in helping understand the health of an industrial gear. By measuring both oil particles and oil quality, using proprietary technology, GearWatch not only monitors and analyses industrial gears but warns and assists customers when a situation arises.

It is such a warning that helped save a Pulp Mill the cost of a new €100k gear box in addition to the €2,6 million potential production losses. GearWatch had been installed in this 15-year-old gear only some months earlier. The cloud-based service gave access 24/7 to the critical data from the gear and by using the solution together with the expertise of the ISO certified lubrication and vibration analysts from DBS, the customer was able to run the gear safely until the next scheduled shutdown.

The key value driver in this case is time. GearWatch gave an automatic early warning to the customer so they had time to react and plan and maximize the availability of the asset and thus avoid a costly interruption to production. Time is the key difference between predictive and reactive, run to failure, methods. The further the issue brews, the less time there is to plan and react and the higher the cost is. With GearWatch, DBS customers know the health of their assets and have a professional and controlled way to solve emerging issues. Another benefit is the ability to assign resources with surgical accuracy. “Maintain only when needed” saves costs, as does reduced need for redundancy.

You can learn more about the GearWatch solution at https://dbsantasalo.com/products/gearwatch-condition-monitoring/ or watch their great video at https://vimeo.com/400601132

Flowplus Oy specializes in the maintenance and operation of flow technology. The customer base consists mainly of operators in the industrial, energy and infrastructure sectors. The offering includes versatile service & maintenance services for valves, pumps, electric motors and other rotating machines. Flowplus, operating out of nine locations throughout Finland, has a proactive maintenance concept driving their customers’ maintenance costs down and reliability up.

“The Flowplus philosophy and way of working aligns perfectly with what condence.io has been built for, condition monitoring of multiple critical varying assets in multiple locations. Their focus in industries using rotating machines and the understanding of the benefits of managing and understanding machine health over the life cycle of the machine is an ideal environment for condence.io technology,” comments Janne-Pekka Karttunen, CEO at Distence.

Condence.io technology identifies growing problems early on due to its advanced features, including a wide range of vibration frequencies and long sample lengths. Using condence.io technology, Flowplus professionals get a tool that, with the help of its analysis and clear graphics, gives not only a comprehensive look into the health of the machines but also more time to plan and react accordingly thus increasing their operational excellence and contributing to higher value-add to their customers.

“Condence complement s our offering and will be integrated into our Flowdicator monitoring offering. We have several cases in the sales pipeline, and the first deliveries are already made. We are excited this to initiate this collaboration”

Jarmo Piippo, Founder & CEO, Flowplus Oy
Read more about Flowplus Oy and Condence at:

Flowplus Oy: https://www.flowplus.fi

Condence solution page: https://condence.io

Distence Oy: https://www.distence.fi/en/

Condence team is continually working on making updates and improvements to the sampling and visualisations of the asset health. Condence monitoring technology is built on taking samples of the assets health parameters and doing analysis and visualisations of it, continuously.

Example of how minimum, maximum and average values are visualized in the user interface.
On our latest release, we have improved both, the actual measurement and how the metric is visualised in the cloud UI. In other words, the user can get more out of each measurement. Users are now able to see the full range of values, meaning maximum, minimum and average value of the metric from the period between the current and previous sample.

The new feature enables fast analogue channel monitoring. For instance, we are now able to detect quick changes in important asset health parameters like torque or current draw of electric motors. The update allows for practically constant measurement of analogue channels lifting the resolution to millisecond level. Users are of course able to set notifications and alarms to any of the newly added values.

The driver for the feature was to enable torque measurement and other rapid phenomena measured with sensors in analogue channels. But the visual component is without a doubt useful in monitoring other health metrics and parameters such as vibration analysis as well. The feature is automatically in use on Condence T200 & T210 terminals with software version 2.3.0 and higher. Users can toggle the min/max/avg feature on in the metrics trend component, or it can set as the default selection in the view templates.

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As a plant production or operations manager, productivity and efficiency are your top priorities. Precision maintenance combined with data analysis makes these responsibilities more manageable, and enables you and your organisation to make more informed maintenance decisions.

What do we mean by precision maintenance? This concept comes from the idea of accurately pinpointing potential issues that signal the beginnings of anything from unexpected repair needs and downtime to catastrophic machine failure. Precision maintenance gives plant managers the information required to plan the best method of action, and helps them take that action at the optimal time.

In this blog post, we’ll cover:
●          How precision maintenance can help you solve common maintenance challenges
●          The benefits of leaving manual methods behind
●          The importance of leveraging data to make better decisions for your company

The traditional approach to industrial maintenance

Many companies in the energy, pulp and paper, steel and mining sectors still rely on manual maintenance and inspections. Although this is a longstanding practice, on average, only 8% of machinery is frequently inspected. This approach leaves a lot to chance in terms of unexpected downtime and faster machine deterioration.

With these risks in mind, it would be wise for plant managers to take a more proactive approach to industrial maintenance. However, with seemingly no systematic, data-backed way of determining when to inspect machinery or make repairs, these managers are left with a serious challenge.

Barriers to change

A reluctance toward investing in resources and technology, as well as a lack of awareness around precision maintenance methods can both be barriers to updating your maintenance approach. When asked about the main obstacles hindering their plant from improving maintenance methods, 48% of plant employees cited lack of resources or staff, while 38% cited a lack of understanding of new maintenance options and technologies.

However, relying heavily on mere routine check-ups often has costly consequences. It is well known by every operations and production manager that maintenance is crucial to machine health and the overall success of an industrial facility. In fact, maintenance costs account for 15 to 40% of total production costs according to Hans Löfsten, professor of Technology Management and Economics at Chalmers University of Technology.

With such a significant portion of a plant’s budget dedicated to maintenance, it’s imperative to take a cost-effective approach. A maintenance approach that lacks precision, or that relies on reacting to issues as they arise instead of trying to predict them, can result in prematurely ageing equipment and unplanned, costly downtime.

This reactive traditional maintenance method can often lead to repairing machinery once it has already failed or is beginning to fail, leaving little to no room for unexpected failures or monitoring machine wear and tear in between scheduled maintenance. Imagine the amount of energy and time that might be wasted when critical machinery requires extra downtime because you had no way of knowing the machine needed attention weeks or months before the usual scheduled time.

In fact, ageing machinery is the most significant pain point for operations and maintenance, followed closely by equipment failure. Fortunately, this is one of the major areas that precision maintenance is designed to address. Data-backed decision making for precision maintenance is essential for industrial sites because it allows plant managers to predict serious issues before they actually arise. Let’s explore how it works.

Addressing common challenges with precision maintenance

How does precision maintenance help production managers combat ageing machinery, equipment failure and the like? The foundation of precision maintenance is built around monitoring asset conditions and balancing your options.

This proactive approach to maintenance is essential to avoiding emergency shutdowns and ensuring that any shutdowns you do schedule are absolutely necessary. However, keep in mind that downtime needs to be planned well in advance and aligned with your production schedules to minimise production and revenue loss.

Overcoming common maintenance challenges is where precision maintenance and data come into play. By using data collection and analysis to monitor machine conditions in real-time, and predict downtime and repair needs, managers can use plant resources more wisely and delegate responsibilities to staff more effectively.

With precision maintenance software and hardware that automatically and consistently collects and analyses useful data, production managers can go far beyond the limitations of a computerized maintenance management system that only offers a small portion of the required data often collected manually, and stored in an unsystematic way that makes data insights challenging to gather.

Instead, data-backed precision maintenance operates on a system that can be monitored remotely; and plant managers already possess the skills and knowledge needed to adjust notifications and schedule maintenance and repairs in an optimal way.

Hardware and software for easy precision maintenance

Industrial machine maintenance often requires specialised skills and knowledge. If there aren’t enough people on your team with these skills, it creates a significant obstacle as you work to improve your maintenance strategy.

Below are three examples of how using data to collect real-time information about your machinery can alleviate the need for these specialised skills. Leveraging data makes precision maintenance easier and allows you to monitor the condition of individual parts closely.

1. Software

Precision maintenance software solutions collect and analyse data. Using the cloud and embedded edge-analytics, production and operations managers have access to data visualisation tools and various widgets, allowing them to monitor and customise how their data is delivered in an accessible way.

The software is always listening, safely and securely collecting relevant data even outside of regular work hours. It is also highly customisable, allowing managers to set specific notifications for the condition thresholds that best suit their team and their facility.

2. Application: Gearbox condition monitoring

A common, complex and essential component for many industrial facilities, gearboxes are manually inspected manually and quite often. But the way they are monitored is not ideal because facilities typically only collect the data they gather during each manual inspection. This limited view can lead to huge oversights. Instead, gearboxes should be monitored constantly to avoid unexpected downtime or failure.

Through continuous monitoring of several methods including oil condition, in-depth vibration analysis and temperature, managers can gain insights into early signs of wear, changes in oil quality and whether the gearbox is being used efficiently in terms of running hours.

3. Application: Compressor condition monitoring

There are many different types of compressors, so your solution needs to have multiple options for sensors and vibration analysis as well as customisable terminals to ensure that each manager can find a condition monitoring set up that suits their specific needs.

Compressor condition monitoring delivers metrics to help detect signs of wear, user errors, temperature changes and more to help you combat machine ageing and, of course, avoid unscheduled downtime.

Your partner in machine health

How exactly does precision maintenance impact an industrial facility? In terms of cost, the average direct savings cover four months of running a solution like Condence.io.

Monitoring conditions in real-time through precision maintenance instead of relying on traditional methods can reduce repair time significantly, decrease overall equipment effectiveness losses by nearly half, and save around €99,625 per failure, according to McKinsey.

At Condence, we can confidently say that we haven’t missed a single machine failure in 12 months. Through cloud and edge computing, our solution listens, collects and analyses data for plant managers to easily apply to their machinery and facilities.

Book a demo to discover how Condence can revamp the way your organisation approaches maintenance.

The new product from KraftPowercon is part of delivering their customer promise, “we ensure that you can focus on optimizing your core business”. It uses Condence.io technology from Distence.

The new solution unveils hidden and potential issues in rectifiers, saves money by optimizing service visits and maintenance costs as well as offers quick response by on-line support and remote services.

The goal is to increase the reliability and the lifespan of rectifiers. Without proper continuous service and monitoring, productivity and the effectiveness of maintenance and operations is drastically decreased. The new sensing capabilities and analytical tools coupled with a modern cloud-based monitoring architecture makes it a powerful scalable solution.

“Thanks to the interactive interface with logs and diagrams, we can easily keep track via PC, mobile or tablet remotely. The ability to select time intervals, either real-time or anything over the past two years, gives us a good overview for example of long-term changes in production. By proactively monitoring our different processes, we can prevent any malfunctions and increase the product lifetime and prioritize maintenance of the rectifiers. Our professional service engineers can simultaneously provide tips and service advice and keep a watchful eye on the rectifiers.” Niklas Tillbrandt, Global product Manager, commenting on the Condence capabilities.

“Distence and KraftPowercon have worked together for some time to deliver this new product. The Distence team has been more than a technology vendor on this project. We are happy with the partnership they have shown to deliver this to the market”, Niklas Tillbrant comments on the collaboration.

KraftPowercon is a global company with production facilities in Sweden, China and India. They offer innovative solutions, products and services within industrial power supply that make their customers’ processes secure, more reliable, as efficient as possible and improves their availability. In short – by guaranteeing your power supply, KraftPowercon ensures that you can focus on optimizing your core business.

For more information on KraftPowercon and their solutions for rectifiers, please visit https://kraftpowercon.com/

Considering the importance to any production process, the complexity of almost any industrial operation and the effectiveness of proactive maintenance is hard make short and simple if you can exclude full production stoppage from your calculations. It is obvious that significant impact comes from avoidance of downtime, yet this is only part of the total value.

Understanding the relevance and impact to perform right operations at optimal time on a larger fleet of different industrial machinery requires a thorough look into both direct and indirect costs, the IT-infrastructure, the maintenance processes and above all the strategy that guides all the above. It is for this reason that senior management should take a careful look into the preventive maintenance effectiveness and value they deliver “when nothing happens”.

Some principle questions to prepare:

  • What is the impact effectiveness of the preventive team – how do we argue the value that was delivered by actions done at the optimal point?
  • Are we ahead of events or scrambling when the alert comes?
  • How do we make preventive maintenance decisions? How to make sure it’s not too early “just in case” repair?
  • Is my required service and maintenance planning horizon hours, days or months?
  • Where does my maintenance operation stand on utilising digital tools to automatise repetitive tasks like inspection routines?

After considering the answers to the above questions, the next question is: What costs do the decisions or operating models carry. What indirect costs are hidden in the way we operate?

Are we following up and arguing how good work our preventive teams and technologies are delivering? – Do we have a standard practise to do aftermath after a repair to evaluate:

Sum of actual repair cost VS potential repair cost

  • Production time/device stoppage
  • Spare parts + repair services
  • Maintenance work + overtime

On top of the delta between actual and potential repair cost, there is the efficiency of daily operations. When focusing on rotating machinery, we claim that many preventive maintenance teams consume a lot of resources on manually inspecting healthy machines (wasted resources) and in parallel find themselves on the situation of colliding priorities due to repairs, measurements and/or other scheduled tasks. This is mainly due we only observe the tip of the iceberg as the preventive process was designed.

The Iceberg model is a great starting point to introduce the depth of the topic. Depending on the size of the operation, the costs get multiplied as the complexity and the sheer volume of transactions increases. Let’s use a concrete example. In the life cycle cost of a pump, the initial cost of the pump represents some 10%-15% of the LCC. The rest include spare parts, maintenance costs and energy – if, we look at the direct costs only. But what lies below the surface? That depends on the maintenance strategy. In a simple exercise, anyone can run through their own operations, ice chunk by ice chunk, cost driver by cost driver. The results of this exercise will reveal very different results, depending on whether your strategy is reactive or proactive.

The Iceberg Model, Michael Wienker, Ken Henderson, Jacques Volkerts

Modern SaaS-based tools have several benefits for them. We can pick out a few that walk hand in hand with the Ice Berg Model. One, they run in the cloud + edge of the cloud, significantly lowering the need and the cost of IT infrastructure. They are available everywhere anytime, globally – fast to roll out. And so is the data and respective information – centralised by default – available to all interested stakeholders.

Sophisticated tools like Condence.io that have a wide range of methods to detect early symptoms of potential failures, e.g. frequency range in vibration analysis and a large toolkit of analysis tools and algorithms. These will move the detection of potentially failing components earlier, from days to months, and allow for forecasting and tracking, thus enabling a proactive strategy – again globally from one User Interface, moving the detection point earlier and automatic. The ability to track specific parameters translates to time – time for planning. This will help preventive teams to focus on machines and conditions that require attention and plan when to take actions.

Planning results in better resource allocation and cost management as well as budgeting and transparency for the future. Transparency to budding issues, the early symptoms of potential problems results in both less downtime, surprises and increases safety. Failing assets also consume more energy as the performance is not optimal. On top of this, it’s also possible that the root cause of failure creates collateral failures leading to reduced asset life or a replacement. It is generally noted that even only an 8% to 10% increase in temperature over normal working conditions reduces the useful life of an electric motor by half.

Depending on the asset and the nature of the operation, various components of the model apply or carry more weight. An unmanned asset, say a pumping station, is very different from a fully staffed manufacturing facility. They both carry the same issues, just weighted differently. Modern SaaS-based tools work, thanks to their extreme flexibility, in both.

Are you interested to hear more? – Follow up on Linkedin or get in touch with the @distence team. I’d also like to hear your comment and opinion.

 

References & further readings:

The Computerized Maintenance Management System, An Essential Tool for World Class Maintenance – Michael Wienker, Ken Henderson, Jacques Volkerts

It is the deep understanding of both the technology and life cycle of industrial gears and drive trains, that led DB Santasalo to choose their approach to condition monitoring for their GearWatch solution. Lubrication oil is the lifeline, the blood, that keeps the gears running. Just like with us humans, this fluid tells stories, gives signals and helps us trace origins to symptoms and faults. In their highly successful GearWatch solution, lubrication oil plays a key role in helping understand the health of an industrial gear. By measuring both oil particles and oil quality, using proprietary technology, GearWatch not only monitors and analyses industrial gears but warns and assists customers when a situation arises.

It is such a warning that helped save a Pulp Mill the cost of a new €100k gear box in addition to the €2,6 million potential production losses. GearWatch had been installed in this 15-year-old gear only some months earlier. The cloud-based service gave access 24/7 to the critical data from the gear and by using the solution together with the expertise of the ISO certified lubrication and vibration analysts from DBS, the customer was able to run the gear safely until the next scheduled shutdown.

The key value driver in this case is time. GearWatch gave an automatic early warning to the customer so they had time to react and plan and maximize the availability of the asset and thus avoid a costly interruption to production. Time is the key difference between predictive and reactive, run to failure, methods. The further the issue brews, the less time there is to plan and react and the higher the cost is. With GearWatch, DBS customers know the health of their assets and have a professional and controlled way to solve emerging issues. Another benefit is the ability to assign resources with surgical accuracy. “Maintain only when needed” saves costs, as does reduced need for redundancy.

You can learn more about the GearWatch solution at https://dbsantasalo.com/products/gearwatch-condition-monitoring/ or watch their great video at https://vimeo.com/400601132

Flowplus Oy specializes in the maintenance and operation of flow technology. The customer base consists mainly of operators in the industrial, energy and infrastructure sectors. The offering includes versatile service & maintenance services for valves, pumps, electric motors and other rotating machines. Flowplus, operating out of nine locations throughout Finland, has a proactive maintenance concept driving their customers’ maintenance costs down and reliability up.

“The Flowplus philosophy and way of working aligns perfectly with what condence.io has been built for, condition monitoring of multiple critical varying assets in multiple locations. Their focus in industries using rotating machines and the understanding of the benefits of managing and understanding machine health over the life cycle of the machine is an ideal environment for condence.io technology,” comments Janne-Pekka Karttunen, CEO at Distence.

Condence.io technology identifies growing problems early on due to its advanced features, including a wide range of vibration frequencies and long sample lengths. Using condence.io technology, Flowplus professionals get a tool that, with the help of its analysis and clear graphics, gives not only a comprehensive look into the health of the machines but also more time to plan and react accordingly thus increasing their operational excellence and contributing to higher value-add to their customers.

“Condence complement s our offering and will be integrated into our Flowdicator monitoring offering. We have several cases in the sales pipeline, and the first deliveries are already made. We are excited this to initiate this collaboration”

Jarmo Piippo, Founder & CEO, Flowplus Oy
Read more about Flowplus Oy and Condence at:

Flowplus Oy: https://www.flowplus.fi

Condence solution page: https://condence.io

Distence Oy: https://www.distence.fi/en/

Condence team is continually working on making updates and improvements to the sampling and visualisations of the asset health. Condence monitoring technology is built on taking samples of the assets health parameters and doing analysis and visualisations of it, continuously.

Example of how minimum, maximum and average values are visualized in the user interface.
On our latest release, we have improved both, the actual measurement and how the metric is visualised in the cloud UI. In other words, the user can get more out of each measurement. Users are now able to see the full range of values, meaning maximum, minimum and average value of the metric from the period between the current and previous sample.

The new feature enables fast analogue channel monitoring. For instance, we are now able to detect quick changes in important asset health parameters like torque or current draw of electric motors. The update allows for practically constant measurement of analogue channels lifting the resolution to millisecond level. Users are of course able to set notifications and alarms to any of the newly added values.

The driver for the feature was to enable torque measurement and other rapid phenomena measured with sensors in analogue channels. But the visual component is without a doubt useful in monitoring other health metrics and parameters such as vibration analysis as well. The feature is automatically in use on Condence T200 & T210 terminals with software version 2.3.0 and higher. Users can toggle the min/max/avg feature on in the metrics trend component, or it can set as the default selection in the view templates.

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