Production Health and Becoming Prescriptive

Scott Reed
Scott Reed ✭✭✭
edited June 2023 in Share Your Ideas

Afternoon to the Community!

Many of my posts to this community have been about the power and value of Production Health (prior post included at the bottom). It is a subject that can be a bit abstract especially to those that are primarily focused on the very necessary maintenance function. However, I wanted to raise this topic to the top of the thread again and try to get some engagement on Production Health and why I consider this to be the path to "becoming prescriptive".

Many of us in manufacturing are accustomed to working within many of the digital platforms that enable us to run the business. These platforms may be related to maintenance, production planning, supply chain managment, process control, quality management, etc.. These may all be disguised within the acronyms of MRP, WMS, ERP, CMMS, MES, LMS, QMS, DCS/SCADA/PLC. What is typically common about all of these systems is they tend to be teated as disparate, stand alone systems with minimal tie-in or link between them. While many of us live and breathe by the configuration, enablement and "uptime" of these systems, we don't give much thought as to how these can be all leveraged together.

Recently, Terry Ledoux's post asked about who had linked their CCMS with Augury and the experiences they had gained. There is no doubt that closing this loop between maintenance practices and realtime condition based monitoring can be very powerful in terms of providing a basis for cause and effect as related to asset health and the maintenance of the asset itself - not just a predictive benefit but a prescriptive benefit as well. But what about the affects of the rest of the manufacturing environment and it's operation, manufacturing/process controls, preferential settings, adaptive corrections, material supply changes, people/shift changes, product changes, production cycles, batch material cycles, fall/winter/spring/summer conditions, startup/shutdown, machine changes and turnaround cycles and…on and on…

It is the ability to capture many if not all of these operational conditions that turns "condition based monitoring" into something more powerful by adding "event based detection". The areas above can be characterized into other "health" domains. We are already familiar with Machine Health, but I also like to think about Material Health (raw materials and consummable supplies), Process Health (machine controls & settings, PID outputs, SPC/contol charts, process sensors, PLC outputs), Product Health (quality system compliance, specification conformance, quality audits, VOC, claims/warranty performance) and finally People Health (training, job skills assessment, engagement, institutional knowledge transfer & management, on/offboarding). Every Ishikawa component (man, machine, methods, materials, measures, environment) is covered by these healths and collectively, the umbrella that encompasses this is Production Health. By linking their associated and seemingly disparate digital platforms, manufacturers now have many prescriptive paths from which to drive their trusted CI programs based upon defined organizational goals and objectives (think Pareto). Augury has such a Production Health Platform called Seebo.

Now getting back to that focused and necessary maintenance function; think about the variability that still exists in our predictive maintenance programs. How can we reduce this variation? What was unique about last quarter's asset performance? Was the lubricant up to spec? Was the proper lubricant used? Was it filtered after receipt (oil)? These are all examples where the additional information from the other health domains may provide greater insights and learnings by simply utilizing a common benchmarking exercise.

Finally, I'll leave these thoughts: 1.) too often we think about solving the small problems and struggle with determining and investing in the right resources; 2.) Many times we are myopic in our functional world (unscheduled downtime) and don't consider the bigger picture (service to the customer); and 3.) In the world of Digital/Industrial Transformation, we have become fixated on incremental value and ROI. Again, think big picture. What is the value of every production shift performing like your benchmark shift? What is the value of 95% of your production days meeting the prescription of your best day? What if you could understand the "burn in" requirement for each asset and enable every maintenance/turnaround startup to meet a best day prescription? These are the use cases I find not just to be more thought provoking but also what helps set that navigational North Star.

I welcome your thoughts and questions.