Predictive Maintenance and its Role in Improving Efficiency
Predictive maintenance is a technique that evaluates the condition of an enterprise's machines and equipment to prevent failures during operation. It uses predictive algorithms with sensor data to estimate the possibility of equipment failure. It also identifies the root cause of complex machinery problems and helps determine which part requires repair or replacement.
This minimizes the downtime and maximizing the life of the equipment. Predictive maintenance is a process of monitoring equipment through the operation to identify any deterioration, which allows carrying out maintenance by reducing operating costs. It is commonly used in Industry 4.0 framework. The primary goal of predictive maintenance is to deliver the most precise maintenance planning in advance to avoid unforeseen failures.
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Growing need to reduce maintenance cost and downtimeis expected to support the growthof predictive maintenancemarket to growat 15.1%CAGR during 2019–2027
The adoption of predictive maintenance system can ensure numerous advantages such as potentially extended service life of the equipment or assets, increased plant safety, optimized handling of spare parts, and fewer breakdowns and outages. Predictive maintenance solutions are installed to monitor and detect faults or anomalies in equipment but are only engaged in critical failure possibilities. This helps deploy limited resources, maximize the uptime of the device or equipment, enhance quality and supply chain processes, and improve overall satisfaction for all involved stakeholders.
The equipment is monitored using traditional and advanced techniques that allow the machinery to be planned for maintenance before a failure. Both of these techniques are equipped with vibration monitoring, electrical insulation, infrared thermography, temperature monitoring, ultrasonic leak detection, and oil analysis tools.Most countries adopt condition-monitoring predictive maintenance to assess the performance of an asset in real time.
Advanced techniques are used significantly in developed economies such as the US, a few Western European countries, and some developed economies in Asia Pacific and the Middle East. The critical element of an advanced process is the Internet of Things (IoT) technology, which enables various assets and systems to connect, work together, share, and analyze the data.
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Hitachi, Ltd, Software AG,IBM Corporation, Microsoft Corporation, PTC Inc., Syncron AB, TIBCO Software Inc, Schneider Electric SE, SAS, and General Electric Company
To analyze IoT data, companies leverage AI and ML technologies to achieve incredible precision, accuracy, and speed over traditional business intelligence tools. With the advent of predictive maintenance, businesses can make operational predictions up to 20 times faster and more accurate than threshold-based surveillance systems.