resolve your manufacturing inefficiences

I started this blog in 2011 when I was with Emerson Automation Solutions (Emerson Process Management at the time). Since then I have moved to a role focused on SCADA, MES, manufacturing intelligence and IIoT. I still maintain that asset reliability and availability is a robust strategy in a global economy. However, reliability is just one aspect of overall manufacturing efficiency. Other aspects that should be considered are downtime and overall equipment effectiveness (OEE), genealogy (track & trace), work order tracking, and statistical process control (SPC) for quality. Moving forward, this blog will focus around identifying manufacturing inefficiencies and developing strategies to resolve them. To be sure, there will continue to be an emphasis on reliability.

Before I begin it is important to understand what manufacturing inefficiencies are. In a simple definition, it is a technology, process or method that hinders the performance of your manufacturing operations. As noted earlier, this can be downtime on your equipment (which could be related to your reliability strategy). It is also the process by which work orders move through the plant. Finally, it may be due to technology, or application of a technology, that does not provide a desired outcome.

There are a number of technology solutions to help improve manufacturing inefficiencies. A great first step is a process historians or simple manufacturing execution system (MES). The latter provides visibility for downtime, work-order tracking, and SPC. Tools such as real-time visualization platforms can assist with performance. These include support for trending, dashboards, reports and alerts. Asset managers and computerized management maintenance systems (CMMS), as part of a reliability centered maintenance (RCM) effort, can improve your overall reliability and availability.

Over the next few weeks I will write about topics such as not over-complicating your manufacturing intelligence technology or how data should be used for decision making. Furthermore, I will explore how well your data model fits your application and what your level for risk is around an artificial intelligence solution. Occasionally, the result is counter to conventional wisdom. I will also include specific cases studies to manufacturing problems, how it was solved and, most importantly, the overall benefits. The goal is to start a conversation or stimulate consideration around your manufacturing technology journey.

My tagline used to Reliable, Available and Profitable. Now I broaden it to include Efficient. I look forward to this journey with you.

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