Predictive Management System
IOT Enabled Condition Monitoring System
Predictive maintenance is a proactive approach to monitoring equipment health, aiming to prevent future failures during operation. By utilizing predictive algorithms and data from equipment sensors, it forecasts potential equipment failures and identifies root causes within complex machinery. This enables timely repair or replacement of faulty parts, thereby minimizing downtime and maximizing equipment lifespan.
Condition monitoring involves continuously monitoring machinery parameters such as vibration and temperature to detect significant changes indicating potential faults. Scheduled maintenance based on condition monitoring helps prevent consequential damages and their associated costs.
The data collected through condition monitoring can be analyzed to establish trends, predict failure, and estimate the remaining life of an asset. This innovative approach to vibration monitoring technology complements traditional vibration analysis by detecting early-stage machine problems that are often challenging to identify using conventional techniques, such as gear and bearing damages.
Goal of CBM
The primary objective of condition-based maintenance (CBM) is to streamline maintenance resources by executing maintenance tasks solely when necessary. CBM leverages predictive maintenance tools to identify, monitor, analyze, and detect anomalies in machinery.
Measurement Method
Two types of vibration measurement methods exist: the “Permanent online vibration monitoring system” and the “Portable offline monitoring system.” The selection typically depends on the importance rank of the equipment.
How does predictive maintenance work?
Predictive maintenance leverages historical and real-time data from various operational areas to predict potential issues before they occur. It encompasses three main aspects within your organization:
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Real-time monitoring of asset condition and performance
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Analysis of work order data
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Benchmarking maintenance, repair, and operations (MRO) inventory usage
Key elements of predictive maintenance include technology and software, such as the Internet of Things (IoT), artificial intelligence, and integrated systems. These components enable seamless connectivity, data sharing, analysis, and action across different assets and systems.
Predictive maintenance tools, including sensors, industrial controls, and business systems, capture information and analyze it to identify areas requiring attention. Examples include vibration analysis, oil analysis, thermal imaging, and equipment observation. Visit our condition-based maintenance page to delve deeper into these methods.
Cloud Based Predictive/Prescriptive Maintenance
Our IIoT solutions facilitate predictive and prescriptive maintenance strategies for critical industrial assets.
Advanced analytics identify trends and issue alerts before failure occurs.
Real-time gathering of mechanical, thermal, and electrical parameters through advanced sensors.
Predictive condition monitoring is effective for simpler systems, while prescriptive condition monitoring is employed for complex systems, requiring a deeper contextual understanding and more accurate diagnosis.
Benefits
When predictive maintenance is working effectively as a maintenance strategy, maintenance is only performed on machines when it is required. That is, just before failure is likely to occur.
Cost Savings
Minimizing the time.
The equipment is being maintained
Minimizing the production hours lost to maintenance
Minimizing the cost of spare parts and supplies