Predictive maintenance is a type of maintenance that uses technology and data analysis to predict when a piece of equipment is about to break down, or is in need of service. The purpose of predictive maintenance is to prevent breakdowns and increase the lifetime of machinery by planning maintenance before a problem arises.

The market for predictive maintenance is in rapid development, as production companies seek to improve efficiency and reduce costs associated with maintenance. According to a report from MarketsandMarkets, the market for predictive maintenance is estimated to reach a value of $4.5 billion globally by 2024.

One of the most effective methods when doing predictive maintenance is condition monitoring, where machines are monitored using sensors and data analysis. This can save production companies large sums by preventing breakdowns and thereby reduce production downtime. Condition monitoring makes it possible to identify potential problems at an early stage, so that maintenance can be planned for a low-activity period, further reducing maintenance costs.

Vibration analysis is a well-known practice within predictive maintenance. It makes it possible to detect faults such as component wear, misalignment or loose parts before they transition to bigger problems. For many years, vibration analysis has been done manually and on-premise, but it is now possible to send vibration data continously to the cloud for analysis. This evolution in technology makes it possible to monitor equipment conditions over long ranges, and it thereby saves costs on vibration experts and technician visits.

All in all, predictive maintenance can be a valuable investment for production companies, as it can help prevent expensive breakdowns and increase equipment lifetime. By applying new technologies such as AI for vibration analysis and IoT for data collection, and then pushing the result to a cloud-based platform, maintenance managers and technicians can save time and costs in their daily workflow, and thereby increase their productivity and efficiency.

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