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Predictive Maintenance

Machines have maintenance and breakdown cycles. Fixing a broken machine is more costly than maintaining an operating machine. With statistical modeling and predictive machine learning, it is possible to predict the optimal repair schedule for a given machine.

Business Challenges

Manufacturers often have a large investment and repair cost in capital. When there are hundreds or thousands of machines, it is hard to keep track and schedule the repairs. When machines break down, firms often incur a huge loss to fix it, or worse, buy a new one for replacement.

Solution

We can analyse the timeline and the lift-cycle of the machine by using machine learning model and their historical data.

Deliverables

  • An alert system and scheduled maintenance for each machine to minimize the amount of machines breaking down in the long-run.

Expected
Outcome

Firms save cost in buying new machines and reduce their downtime.

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