How can TPM performance indicators help you avoid equipment downtime?

Total Productive Maintenance (TPM) performance indicators can help avoid equipment downtime through proactive maintenance and monitoring. (TMP) Here's how, -Overall Equipment Effectiveness (OEE) -Mean Time Between Failures (MTBF) -Mean Time to Repair (MTTR) -Predictive Maintenance -Autonomous Maintenance -Breakdown Analysis -Scheduled Inspections -Training and Skill Development

TPM performance indicators help reduce downtime by providing measurable targets for maintenance effectiveness - OEE (Overall equipment effectiveness) assesses how well equipment is performing against its capacity, highlighting areas needing improvement. - MTTR (mean time to repair) encourages minimizing the time it takes to repair equipment, thus reducing downtime. - MTBF (mean time between failures) tracks the average time between failures, with improvements indicating more reliable equipment. - Unplanned Downtime rates direct efforts towards preventive maintenance to avoid unexpected breakdowns. By monitoring these indicators, we can identify patterns, predict potential equipment failures before issues lead to significant downtime

One thing I found to be helpful in the age of the Internet of Things, is to measure TPM performance indicators in multiple ways. For instance, run time but also amperage totalizers. So that you can run maintenance at planned intervals, but also dig deeper when you need to if your equipment is gobbling up energy. Automatic work orders can be submitted by a well integrated system, reducing the scope of things to monitor for you team.

There are typically two buckets of performance indicators that are measured within TPM; leading and lagging indicators. Lagging indicators are typically reactive elements of production like case count or OEE. Leading indicators are the measures that help you maintain equipment and reduce machine downtime. For example, if you want high OEE, you could track operator owned preventative maintenance activities or number of machine abnormalities found and fixed, how many PMs were scheduled versus how many were completed and if changeovers happened within their planned allotment. If we monitor and improve the leading indicators (CIL, CL, PMs, etc.) machine downtime will decrease and the lagging indicators (OEE, etc.) will improve.

To effectively choose and use TPM performance indicators, we must define the KPI targets(Down time,UP time,UPH, etc..) based on the output requirements. Once target is established, we must have effective measurement and monitoring system in place. Machine Maintenance System (MMS) is one of the system in which machine performance recorded by software in all aspects like MTBF, MTTR, IDLE TIME,UPH, YIELD etc... and scope improvement actions to eliminate all possible wastes in manufacturing. As per me, effective use of TPM indicators is one of the lean manufacturing tool that requires in all manufacturing industries.

There are a multitude of performance indicators available, and most all of them can add value in specific ways. Often times metrics are selected without full consideration of the soft variables. What is the plants current maturity level? What skills do the employees have to investigate and improve? Do shop floor metrics reflect what the employees. have the opportunity to directly impact? What skills and resources are available to support improvement? What skills does management have to guide improvements? Measurement without corrective action has been proven to be long term unsuccessful (Hawthorn effect aside)

My reliability journey started with data analysis. Using two maintenance systems over 4 years provided the opportunity to implement a predictive maintenance item which was stacked with another on the same periodicity. Efficient improved reducing MTBF (or eliminating it) and lowering overall repair time. When there are 150 units and you’re saving 4 hours of labor a unit, more time was created to take on the next growth item. Periodicity was 400k miles.