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Avoid Full Operations Shutdown with Predictive Maintenance

Learn how simple repairs and maintenance can have massive downstream implications. This manufacturer was able to drastically reduce the risk of plant shutdown, with each avoidance saving $20+ million per day cost.

The Challenge

  • Must reduce plant out-of-service times
    • Results directly in lost revenue
    • Reduce unnecessary service crew travel costs
  • Predict life-time of factory components & machines
  • Predict machine failures that result in plant shutdown
    • Service needs before they become problems
    • Optimize maintenance schedule & crew utilization
  • Anticipate needs for replacement components
    • On-hand as needed, without extra carrying costs

The Solution

  • Unify data in end-to-end tire lifecycle
    • Raw material to finished product
  • Range of data sources in their models:
    • Sensor data from the plant operations
    • Log entries
      • Error and failure messages
      • Repair and maintenance service reports

The Impact

  • Drastically reduce risk of shutdown as result of:
    • Critical equipment failure
    • Parts for repair being unavailable
  • Each avoidance $20+ Million per/day cost
    • Likely to avoid 1-2 shutdowns per year

Schedule a free AI assessment and learn how data science can help improve core operations so your organization can better drive revenue, cut costs, and avoid risks.

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