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The Fatal Flaws of First-Gen Production Monitoring

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Manufacturers have been adding production monitoring software to their technology stack to better understand what’s happening in their factories, but with varying degrees of success. The first generation of production monitoring uses CNC machine data and focuses on reporting machine utilization. This is an interesting metric, but not an actionable one. If the software tells you utilization is at 42%, without any context there’s no way to tell if that number should be higher, or how you might be able to increase utilization.

The traditional fix is to augment CNC machine data with human input, often in the form of reason codes. Operators enter setup, breaks, maintenance issues, no operator, measuring parts, and more to explain why a machine is not producing a part at that time. But, most of these reasons are part and parcel of a complex milling process, so the insights you seek just don’t exist in the reason code data. Add in the fact that operators quickly tire of entering reason codes, and compliance falls off the table in as little as 45 days.

Instead, a new generation of production monitoring solutions is automating actionable insights. Next-gen production monitoring uses machine learning to analyze and benchmark every job on every machine in your shop, then scores each job against the benchmark so you have a standard that shows if you are performing well. Installing large-screen TVs around the shop lets the entire team know what’s happening right now so your most experienced personnel flow to the jobs that need help. And, out-of-the-box reports and dashboards use the data to help with continuous improvement, quoting, and understanding overall factory trends.

In this Tech Talk, learn about the flaws in first-generation production monitoring software and how next-generation production monitoring solutions help companies realize the promise of automated production intelligence and gain a virtual window to their shop floor.