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.
Unlock the value of your data
See how IoT data produces actionable insights that optimize operations, improve asset performance, and provide a competitive advantage.
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.
Improve performance with analytics
Tech Clarity outlines the ROI that companies can expect when they use IoT analytics to optimize performance.
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.