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Predictive maintenance services improve key efficiency metrics for field services like first-call repair rate, costs to serve, and customer lifetime value.
These services also increase customer loyalty and satisfaction by preventing costly downtime.
Predictive maintenance strategies center around anticipating equipment faults and failures, reducing maintenance and operating costs by optimising time and resources, and improving the performance and reliability of equipment.
Productivity can be increased by reducing inefficient maintenance operations, enabling a faster response to problems via intelligent workflows and automation, and equipping technicians, data scientists, and employees across the value chain with better data with which to make decisions
Predictive maintenance services continually assess the health of equipment in real-time using data from sensors and advanced analytical tools and processes such as machine learning.
These services help businesses optimise maintenance scheduling by predicting the future potential state of equipment and anticipating problems in advance.
Various condition monitoring techniques such as sound, temperature, lubrication, and vibration analysis can be used to identify anomalies and provide advance warnings of potential problems.
Predictive maintenance services improve key efficiency metrics for field services like first-call repair rate, costs to serve, and customer lifetime value.
Predictive Maintenance is a proactive maintenance strategy that involves assessing the condition of equipment by performing continuous (real-time) equipment condition monitoring. The aim of Predictive Maintenance is to predict when equipment failure might occur, and to prevent the occurrence of the failure by performing maintenance.
AI enhances Predictive Maintenance by providing effective tools for implementing it. Machine Learning (ML), a subset of AI, can be used to predict potential downtimes seven days in advance. Moreover, ML can find unknown correlations between certain data sets and downtimes, which helps to understand what causes those downtimes.
Predictive Maintenance has several benefits such as improved efficiency metrics for field services like first-call repair rate, costs to serve, and customer lifetime value. It also increases customer loyalty and satisfaction by preventing costly downtime.
Predictive Maintenance works by using AI and ML algorithms to continually assess the health of equipment in real-time using data from sensors. When the algorithms detect a potential issue, an alert can be generated so that maintenance can be scheduled
Almost any industry that uses machinery can benefit from Predictive Maintenance. This includes manufacturing, oil and gas, utilities, transportation, and more.
