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Predictive Maintenance Goes Mainstream

by | Jul 16, 2024

Summary

Predictive Maintenance (PdM) has become routine for major manufacturers, with almost half now having a PdM team — double the number from five years ago.

Our detailed breakdown of what data firms capture shows that nine out of 10 manufacturers we surveyed collect at least some data that gives them a view of machine health. PdM is no longer just something frontrunners are trying out. It is a well-established and well-proven technology. Digitization strategies are now maturing.

This explains why the proportion of manufacturers saying PdM is a ‘strategic priority’ fell between 2019 and 2023: it is no longer a development priority but business as usual. To control the costs of downtime, PdM has become a must-have. It prevents sudden and unexpected equipment failures that lead to lengthy downtime while avoiding the opposite danger of over-maintenance.

Costs are cut further by allowing manufacturers to reduce the spares they need to hold ‘just in case’. It also allows them to calculate the likely Remaining Useful Life of machines, allowing industry to make full use of an asset lifespan without pushing machines so far that catastrophic and hugely costly failures become likely.

The pressure on supply chains in recent years has meant that unplanned downtime is a bigger and bigger headache. With the

costs of PdM falling simultaneously, the technology has entered the mainstream, becoming a must-have for manufacturers.

Read this article in full here.

Siemens

Dr. Che is a Professor and the Director of the School of Information Security and Applied Computing in the GameAbove College of Engineering and Technology at Eastern Michigan University. Before his academic career, he worked as a system and network engineer in the IT industry for approximately 20 years. Dr. Che received his BE in Electrical Engineering and ME in Computer Engineering from Zhejiang University, his MS in Software Engineering from Bowling Green State University, and his Ph.D. in Computer Science from Wayne State University. His main research interests are cybersecurity and computational intelligence. He is the author and co-author of multiple research publications and holds several IT and Cybersecurity professional certifications.‍

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