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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