Predictive Maintenance

Transition from reactive to proactive maintenance

Before the industrial IoT, unplanned downtime and production delays were considered part of the cost of doing business. But thanks to digitally enabled solutions like predictive maintenance, these problems have become largely avoidable.

Predictive analytics can identify meaningful trends, explain causal patterns, and make targeted predictions about the performance of an individual asset—or an entire production line. These analytics tools alert operators to issues before they happen, minimizing their impact on operations. Equipped with these insights, operators can either fix the problem, conduct further analysis, remediate, or temporarily shut down a line to prevent a major issue.

With this powerful data, your operators can make faster, better decisions to proactively maintain your assets and ensure optimal performance. Your downtime will be minimized, and the lifespan of your assets will increase.

E-book: Make Faster, Better Decisions

Unlock the value of your data

See how IoT data produces actionable insights that optimize operations, improve asset performance, and provide a competitive advantage.

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Predictive maintenance requires strong analytics

Analytics provide the insights that manufacturers need to move from reactive to proactive maintenance.

Analytics really do matter

LNS Research explores the power of IoT analytics and how they are driving change for manufacturers.

Make maintenance predictive with ThingWorx

The ThingWorx industrial IoT platform provides advanced, predictive analytics that move manufacturers from a reactive to a proactive maintenance model. Learn more about ThingWorx and the many benefits it can provide your business.

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