Machine learning technology can now predict equipment failures weeks in advance. But once you know a major failure is imminent, what next? How do you decide when and how to perform the repair to maximize productivity and minimize risk? Maintenance wants to carry out the repair quickly in the safest, most well-planned way. Operations wants to maintain production and is resistant to shut down until necessary. Planning and scheduling seek to assure timely product deliveries to assure customer satisfaction, and avoid costs associated with delayed shipments. Reliability staff question tradeoffs. Is it an emergency safety issue, or can lightening the load on the equipment enable you to wait until a more convenient time for maintenance?
With competing and conflicting priorities, the right answer is not so obvious. In this session, we’ll explore how new technology advances are enabling decision-makers to quickly evaluate hundreds of possible future scenarios, and understand the financial consequences and risk involved in different operational decisions. Join us to learn how to quickly balance these conflicting interests to determine the best time for repair—maximizing system-wide productivity and minimizing risk.
“R.A.I.” the Reliability.aiTMChatbot
You can ask "R.A.I." anything about maintenance, reliability, and asset management.