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Future preparation prevents problems in the present – the value of predictive maintenance

Christine Declerck circle

November 2nd, 2021 

Christine Declerck

Global Service Manager division Measurement and Analytics

Measurement & Analytics


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As the frontline of any industrial process, instruments and analyzers provide an invaluable starting point for gauging performance, safety and compliance, as well as identifying areas for potential improvements. Christine Declerck, Global Service Manager for Measurement Products discusses the importance of predictive maintenance in ensuring that devices can be kept at their optimum.

The ability to tell in advance whether an instrument or analyzer is experiencing faults or is on the verge of failing is invaluable, especially in applications where accurate measurement is critical, either for quality, cost or safety purposes.

There are three maintenance strategies that instrumentation users could use – run to fail, preventive maintenance and predictive maintenance. Of these, predictive maintenance offers the advantage of knowing ahead of time when problems are likely to occur, allowing process owners to plan and prepare parts and maintenance to ensure disruption is avoided by keeping instruments at peak performance. It is one of several digital service solutions from ABB that provide support for our customers when and how they need it, from commisssioning solutions, through to training and troubleshooting.

With its power to identify when maintenance is needed, predictive maintenance is increasingly essential. Where at one time a maintenance engineer’s expertise could define a problem and when it will occur, now advanced data analysis provides detailed feedback on instrument health.

With its remote access, predictive maintenance is part of the growing move towards autonomous systems, such as self-driving cars and the lights off factory – the device is monitored and any problem will be detected within or around the device automatically. As well as identifying the problem itself, predictive maintenance technology can also highlight the root cause of the problem and calculate the timeframe within which it is likely to escalate, enabling informed decisions to be made on when and how to fix it.

When it comes to fixing a problem, the information provided by predictive maintenance can help to ensure that a correct spare part is dispatched automatically, and the customer is informed how to do the fix. Alternatively, an ABB service engineer, who is provided with the part can go to the site and performs the task.

ABB has already put many of the pieces into place to provide maintenance and service support, including ServIS, a system for storage and management of installed base information. This is connected to the contract management system, as well as to the ABB field service system to deploy an engineer to the job. This in turn is connected to an AR application, connected to the field service application to provide information about what the job is and how to carry it out.

Looking to the future – the ABB Measurement & Analytics Open Innovation Challenge

To help develop the next generation of predictive maintenance technology for instruments and analyzers, we created the Open Innovation Challenge to bring together some of the brightest minds from across the world to collaborate and co-create predictive maintenance solutions with ABB. The participants were invited to our Customer Experience Center in Ossuccio, Italy, where they were tasked with delivering a predictive maintenance solution that would deliver quality information that could be used to improve device performance. It also had to be flexible and be able to be replicated across multiple applications. Over the course of the challenge, which included a two day bootcamp where participantes worked with ABB experts to develop a range of solutions involving Digital Twins, IoT and even self-powered intelligence solutions, the various ideas and entries were whittled down, with three finalists chosen.

Find out more about the ABB Measurement & Analytics Open Innovation Challenge and the solutions that were developed by our finalists https://spark.adobe.com/page/6v8Xj7l8RXIJh/

To discover who won the challenge, visit our winner’s page 

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