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Saturday, October 20, 2018

Industrial Predictive Maintenance

Part one of three I am following.  Good.  It was, long ago,  a specialty of mine.  Then, as now its all about the data.   Here Data, IOT and ML are brought together to address the  problem.  Parts I and II are available.

A strategy for implementing industrial predictive maintenance: Part I   By Prashant Dhingra   Machine Learning Lead, Advanced Solutions Lab, Google Cloud
October 5, 2018

A recent phenomenon called Industry 4.0 marks an industry-wide shift in manufacturing: factories are becoming smarter. Accordingly, plant operators strive for increased productivity, improved operational efficiency, and better safety, given the technological tools newly available to them. Many manufacturing facilities maintain a combination of both new and old machines. The first step to make a factory smarter is enable predictive maintenance (PdM) capabilities.  

Predictive maintenance focuses on identifying patterns in both sensor and yield data that indicate changes in equipment condition, typically wear and tear on specific equipment. With predictive maintenance capabilities, companies can determine the remaining value of assets and accurately determine when a manufacturing plant, machine, component or part is likely to fail, and thus needs to be replaced.

In this first post in our three part series, we’ll explain how predictive maintenance can function to reduce downtime, reduce maintenance costs and improve operational effectiveness and safety, by identifying impending failures before they occur.  ... " 

Part II is here.

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