A good downtime tracking system must consider all of these factors.ĭowntime data is valuable for many reasons. Logging the actual time the equipment is down is important, but what about other losses attributed to this event? In many cases, product losses due to equipment failures, employee overtime and other bottom-line factors outweigh the direct maintenance costs for downtime. However, a more descriptive failure cause will lead to a more accurate analysis of downtime later. Other managers may prefer more descriptive cause definitions such as 'blown fuse(s),' 'operator error' or 'water in electrical.' Either way is acceptable if it suits the maintenance manager's requirements. Examples might include 'electrical,' 'mechanical,' 'operational,' etc. Are downtime cause fields user-defined and easy to understand? Some maintenance operations prefer a more general failure cause naming convention. When collecting downtime data, it is important to determine how the downtime is logged. Nevertheless, an instance of work and an instance of failure should be kept as separate records. Of course, a corresponding work order is usually created to correct the failure. It doesn't make sense to record an instance of equipment failure as work. Although many of these programs use a work order system to track downtime, a CMMS with a dedicated downtime module can result in better analysis and reporting of equipment problems and trends. The best way to track equipment downtime is with a computerized maintenance management system (CMMS). In extreme cases, this can eventually lead to a chaotic 'run-to-fail' cycle. These consequences may result in expensive overtime hours and reduced PM completion rates. Downtime may also divert personnel from their preventive maintenance (PM) duties.

Unexpected equipment failures can cause costly interruptions in your process flow, damage to equipment and product losses.

Production downtime reporting