Building a resource-efficient maintenance strategy to optimize parts
Asset maintenance poses significant challenges for enterprises, causing unnecessary downtime and increased costs. With the new cutting-edge technology available today, it is possible to shift from a routine, scheduled maintenance program to an insights-driven predictive maintenance solution. Manufacturers can develop and leverage an IoT-enabled prescriptive maintenance solution utilizing the following methodologies and tools:
- Reliability-centered maintenance: RCM can assist enterprises to analyze and establish what needs to be measured and decide the acceptable range of values for optimal machine performance. The process identifies critical equipment, causes of failures and mitigation, and defines a resource-efficient maintenance program.
- Overall equipment effectiveness: OEE measures how efficiently manufacturing operations utilize capacity by calculating uptime, productivity of equipment, and level of quality of parts, and maximizes uptime.
- Cloud analytics: This enables ideation, development of solutions, and realization of maintenance operations with a two-phase process: discovery phase, where the model is built and developed, and the production deployment phase, in which the predictive model is deployed in the production environment to ingest real time sensor and ERP maintenance data, and build a visual prescriptive analytics dashboard.