Reducing preventable downtime via predictive maintenance
Manufacturing machines typically run at a certain operating efficiency that is usually expressed in percentages. A machine running at 70% efficiency, for instance, can have 30% of downtime. During such downtime, no items are being produced.
A certain amount of downtime is in itself normal and to be expected as machines need to regularly undergo maintenance or calibration. However, there is also downtime caused by machine malfunctions, which can in turn decrease production quality, stop production completely, or even lead to machines being permanently damaged. Most of these malfunctions can be detected by the machine itself which then halts and notifies an operator; only after such an issue is resolved, production can resume as planned.
Those malfunctions that cannot be detected automatically, call for constant human supervision. Supervision is usually expensive, prone to error, introduces higher latency, and thus, can lead to a significant decrease in production quality.