Predictive maintenance is the use of data and algorithms to optimize high-value machinery that manufacture, transport, generate, or refine products. The high-value machines are equipped with numerous sensors that emit telemetry, which is the collective stream of measurements over time. That telemetry characterizes each machine’s state (i.e., temperature, pressure, oil level, operational settings, etc.) at all moments during its operational period.
The machine learning algorithm, when learnt on historical telemetry emitted by many machines over time, can then send a maintenance alert to the operator with sufficient time to action.
Predictive Maintenance is a popular application can help organziations in several industries to achieve high asset utilization and savings in operational costs.
Unplanned maintenance is a key issue specially in industries such as manufacturing , oil and gas and transportation. It can be extremely costly due to extended production downtimes. Not only due to the high urgency repairs and investment in new machinery and parts, but unexpected production loss that affect supplier obligation, resulting in significant unanticipated costs.