Description
Optimise maintenance, repair, and operations parts and equipment inventory
Linked Case Studies
Case Study
Korean Air
Korean Air reduces maintenance defect history analysis lead times by 90% and improves on-time performance with machine learning and natural language processing
Case Study
IBM
IBM launches Equipment Maintenance Assistant to predict equipment maintenance requirements and aid technicians in diagnosis and repair using machine learning
Case Study
UPS
UPS plans to streamline internal operations by tracking every package and asset in real-time using sensors and machine learning
Case Study
Sears
Sears Appliance Repair Unit gains 5 - 6% productivity by predicting parts required for field worker repairs
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Source: amazon.co.uk · Editor: original-sdg