The downtime statistics reported by production differ from those reported by maintenance. On a couple of production lines, the difference is several hours per week. The plant manager insists that maintenance perform more preventive maintenance (PM) and predictive maintenance (PdM) work on those lines than analysis of the computerized maintenance management system (CMMS) reports can justify.
The plant engineer has argued this is a misallocation of resources that is increasing overall downtime and revenue loss. The plant manager points to the actual time that equipment is idle, noting these data are taken directly from the machines themselves while the CMMS data are entered manually. He attributes the difference to human error.
How can you correctly determine where the data difference comes from and then persuade the plant manager to trust the CMMS data?
Every story has more than one side. In this case, the plant manager isn’t looking beyond his initial impression. He is correct that the difference is due to human error, and he is that human.
Machines are down for many reasons other than insufficient maintenance. These can include: clearing a materials jam, doing a change-over, taking a break, making a shift change, changing a tool bit, or performing an in-process quality assurance check. All of these are normally operator actions.
Ensure the CMMS data are solid, then log the non-maintenance issues for one machine to illustrate the point that the raw figure of run time (or not running time) is easily misleading.
