What if you could purchase a thermometer at the local drugstore that, after taking your temperature, would present you with several personalized wellness options after comparing the reading against your historical health data?
Or what if, during physical therapy after knee-replacement surgery, the leg machine provided three or more likely outcomes of your therapy session based on number of reps, prior PT sessions, and even a worst-case scenario if you simply decided to cease further therapy?
These are health-based examples of a technological wave that is starting to affect the way we think and talk about asset management: prescriptive maintenance, a form of asset health monitoring that is moving beyond predictive approaches and is focused on delivering outcome-based diagnostics.
As promised in this space last month, this issue kicks off our coverage of this topic. In this month’s cover story, Sheila Kennedy explains how the heart of the prescriptive maintenance is the ability to place real-time condition monitoring data in a much wider context than was previously possible, thanks primarily to the internet, wireless networks, and cloud-based storage and processing capabilities. She follows this with a look at how three organizations are already deploying prescriptive asset management approaches at their facilities.
We’re also pleased to share perspective from LNS Research’s Dan Miklovic on why the next wave of asset management innovation (what he terms “APM 4.0”) consists more of evolving aspirational objectives than a specific set of products, adding that the path toward a more prescriptive mindset will be unique to each organization.
How soon is prescriptive maintenance coming to your plant? The short answer is, as soon as your organization starts exploring the potential these technologies have to reduce unplanned downtime and positively affect the bottom line. In this regard, prescriptive maintenance could position you and your teams even further as a profit center rather than a cost center, layering ERP, CRM, and MES data alongside asset health information to underscore the power of the maintenance and reliability function to support the company’s business goals.
As it happens, the PT example above is more than just hypothetical – a family member of mine made the unfortunate choice to stop therapy ahead of schedule, and five years on is experiencing just as much knee pain now as she did before the surgery. Although the risks of stopping early were fairly well-known, I still wonder whether it would have made a difference if the machine itself had been able to deliver personalized health assessments to her, in real time, during the legwork sessions.
When it comes to asset health, whether personal or industrial, humans still get to make the final call. At least our physical assets will be driving a more informed conversation than ever on options and outcomes.