I recently spent several days at the Downstream 2019 Exhibition and Conference in Houston, where my colleagues Mike Strobel and Ashok Rao delivered a terrific workshop on predictive maintenance called “Turning Unplanned Downtime into Planned Downtime.”

 

Mike began his talk by saying he had first heard of this topic 37 years ago when he began his career in the reliability profession. It struck me how many instances like this I’ve encountered in my career. We’ve used a different nom de guerre for some of the more popular topics like “smart manufacturing” and “digitalization,” but they aren’t exactly new concepts, are they? So when does old become new again?  

 

There are evolutionary technologies, and then there are revolutionary technologies. I think what we’re witnessing in the area of predictive maintenance is revolutionary — and different than previous discussions on the topic.  

 

The success of low-touch machine learning in providing weeks of accurate warning of asset failures is enabling a new set of collaborative workflows to plan around those failures. Extending the warnings from hours or days to weeks — or even months — is creating an opportunity to revolutionize how the whole organization responds to the event. Maintenance, Operations, Scheduling, Supply Chain and maybe even Sales can all get involved to mitigate the impact. 

 

This is more than a new workflow; this is a change in the ownership of reliability, where the responsibility is shared by Maintenance and Operations. When that sense of shared ownership of the downtime problem is fostered at the highest levels, the result is more than just another chapter in the story — it’s a whole new ending.  

 

 

Safety and Sustainability Benefits

 

Solving the downtime problem has a direct and positive impact on the two most important issues companies are facing, safety and environmental responsibility. The data tells a clear story: when machines break, people get hurt, and the environment suffers too.

 

Uncontrolled emergency shutdowns are hard on the equipment, but as Mike Strobel pointed out in his presentation, 40% of injury accidents also happen in conjunction with those events. There are some notable examples of where companies have avoided safety issues through the power of predictive technology:

 

• A leading pulp and paper manufacturer detected and prevented a major fire with a nine-day advance warning.

• One LDPE producer received 27 days of advance warning for a central valve failure.

 

If you care about the planet at all, it’s hard not to be excited about the potential to reduce emissions by eliminating those unplanned shutdowns. Here are a couple specific areas where you can make a significant impact through predictive maintenance:

 

• You can identify past causes and prevent future environmental and safety failures by automating root cause analysis and leveraging information in the causal chain of events.
• You can understand and mitigate potential vulnerabilities by performing lifecycle analyses on assets using a complete system-level assessment of current risks and underlying costs.

 

The regulatory exposure to fines for exceeding allowances in these periods should be motivation enough to aggressively pursue the elimination of unplanned downtime. Beyond that, energy and water efficiency, along with air quality regulations are prime concerns for shareholders across industries — and should be at top of mind for corporate leaders as well.

 

These issues demand innovative approaches, and implementing predictive maintenance to eliminate unplanned downtime is a critical step in the right direction.

 

 

To learn how companies are using advanced technologies to achieve market leadership while maintaining their “social license to operate,” read our new executive brief: Next-Generation Operational Technologies Enable the Smart Enterprise in a Changing World.