A large German/American producer of auto parts uses high-pressure pumps to deburr machined parts as a part of its production and quality check process. They decided to monitor these pumps to make sure they work properly and that they can see any indications leading to a potential failure before it affects their process.

Gary Bruner, the president of Carolina Precision Manufacturing, a contract manufacturer that specializes in small-diameter, close-tolerance CNC Swiss turned parts, had a problem. Over breakfast that morning, Gary had logged onto the MachineMetrics monitoring system on his laptop at home to check the status of his machines assigned to a lights-out operation, but saw immediately that two of his machines were not in production. “What’s wrong with machines 35 and 36?” he thought to himself. Upon arrival to the shop, Gary learned from his operator on duty that this type of hold up was nothing out of the ordinary, and was in fact a product of inefficient startup procedures that had simply never been analyzed or augmented previously. In an industry with razor thin margins, Gary understood that the keys to growth and success were in efficiency and quality. He understood the importance of keeping tabs on production stats, job status, uptime, and setup. However, there was no way to know how well machines were doing in real time. What was causing this additional downtime? Furthermore, CPM’s current methods of measurement and data collection were not only time consuming, but had quickly becoming outdated. Historically, CPM had an employee dedicated to the collection of utilization data. This employee would walk around to each of the machines, collect scrap tickets post-production, talk to operators, and record yesterday’s data into their current ERP system; not to mention that this manual data collection was prone to errors, and would take upwards of 2 hours per day. Without the ability to visualize their results, the recorded data was not very actionable.

Manufacturers require a centralised view on all its equipment and assets in order to enable capabilities such as RCM and TCM to maximise uptime and productivity. There is potential along the manufacturing process to reduce inventory redundancies, wastage in areas of MRO, and maximise utility of the different skill-sets among engineers, all of which are factors directly affecting the OEE of the manufacturing process.