Turn Predictive Maintenance into a Success Story for Your Manufacturing Company
Manufacturing companies that implement predictive maintenance have reduced downtime by 50% while also saving up to 30% on maintenance costs.
To achieve similar results, you need to get started with predictive maintenance right.
This 21-page white paper tells manufacturers how to shift to PdM in industrial services and ensure organizational growth and future competitiveness.
You’ll read about:
- Massive costs of industrial downtime and how predictive maintenance can solve this
- What is predictive maintenance and how to implement it
- Machine learning techniques for predictive maintenance
- How to build machine learning expertise in your organization
- Challenges that manufacturers face when implementing predictive maintenance
And many more, with cases, real-life examples, and unique industry insights.
FAQ
Based on historical and failure data, predictive maintenance helps to detect anomalies and predict any potential health state issues in advance in order to fix them before the actual damage occurs.
When talking about maintenance, we distinguish between reactive, preventive, and predictive maintenance. As its name suggests, reactive maintenance happens after the failure occurs. Preventive maintenance intends regularly scheduled maintenance activities to keep equipment in working condition. Predictive maintenance monitors and analyzes equipment health state and predicts potential defects to make them fix earlier.
Some use cases of predictive maintenance in manufacturing include vibration analysis, equipment monitoring, thermal imaging, infrared technology, oil analysis, acoustic monitoring, and others.