Predictive Maintenance

Prevent unplanned downtime using AI

Challenges

Keeping up and running the manufacturing plant is costly and time-consuming. According the International Society of Automation, a typical factory loses between 5% and 20% of its manufacturing capacity due to downtime. Besides, it runs a high risk of equipment failure, taking an enormous hit on the production schedule and decreasing productivity. However, predicting when a machine is likely to fail long before it happens is the most important way to avoid downtime.

Opportunities

With help of AI, unplanned downtime is preventable with predictive maintenance. The manufacturers can make an asset viability protection plan, identifying when it will be the most viable to upgrade the plant by responding to the alerts and resolving minor issues. AI models can look for patterns in data that indicate failure modes for specific components or generate more accurate predictions of the lifespan for a component given environmental conditions. When specific failure signals are observed, or component aging criteria are met, the components can then be replaced during scheduled maintenance windows.

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