Predictive maintenance solutions access multiple data sources in real time in order to predict asset failures or quality problems so that your organization can reduce maintenance costs and avoid expensive downtimes.
Data mining is the engine that runs these solutions. As such, it can detect anomalies, calculate failure probabilities and identify the assets and operational processes that are the most at risk.
This early detection of potential issues enables you to deploy your resources in a more profitable manner, to maximize equipment availability, to improve the supply chain and ultimately, to improve customer satisfaction.
Predictive maintenance allows you to:
- Predict where, when and why asset failures are likely to occur
- Identify the primary variables responsible for the failures
With a better understanding of asset performance and product quality, organizations can:
- Minimize quality and reliability issues in order to meet the customer delivery schedules
- Optimize spare parts inventory to reduce costs associated with out-of-stocks or overstocking
- Predict warranty claims to increase customer satisfaction
- Improve management of operations and reduce costs
Industries where these analyses can apply:
- Rail transport