Physical maintenance issues can cause costly disruptions in the manufacturing process. With predictive analytics tools, however, repairs and maintenance tasks are prioritized based on real-time probabilities of when various failures are likely to occur. This strategy of predictive maintenance saves time and money and helps minimize costly production downtime. It can also improve personnel safety and equipment longevity.
STATISTICA Decisioning Platform® manages a set of failure prediction models for each potential issue that could arise. With constant monitoring of such large sets of production variables, businesses are staying on top of maintenance needs and addressing them in strategic and effective ways. The STATISTICA Enterprise and MAS tools keep constant track of progress, send alerts, auto-update prediction models, and keep things running smoothly.
- Predict Impending Machine Failure: Build predictive models that indicate the likelihood of various machine failures at all stages of the manufacturing process.
- Prioritize Maintenance: Identify primary maintenance issues requiring immediate attention and secondary issues that can wait.
- Keep Predictive Models Up to- Date: Models are updated automatically to take advantage of new data in changing processes.
- Deploy Prescriptive Analysis: Develop a prescriptive analysis plan that suggests appropriate actions based on different failure types.
- Find Root Causes of Machine Failures: Find the key factors that contribute to machine wear and unscheduled maintenance.
See Decisioning Platform in action for predictive maintenance and prescriptive analysis in this webcast.