Predictive Maintenance (PdM) and Preventive Maintenance (PM) are twin pillars that elevate manufacturing operations to an unprecedented level of productivity. While PM entails scheduled inspections and interventions to pre-empt equipment failures, PdM harnesses a sophisticated blend of sensors, data analytics and Machine Learning (ML) to forecast potential issues before they cascade into operational disruptions.
Maintenance maturity
Embracing the technological ecosystem
Central to the success of predictive and preventive maintenance in manufacturing is the intricate web of technologies driving this transformation:
• Industrial IoT and sensor fusion for condition monitoring: The convergence of IoT and sensors equips machines with the ability to communicate and share real-time data. Sensors embedded in machinery monitor temperature fluctuations, vibration patterns and energy consumption, offering real-time insights into equipment health. Real-time facility monitoring solutions are proven to play critical role in such scenarios.
• Data analytics and Big Data over Cloud: The proliferation of data from sensors and other sources demands expandable storage and robust analytics solutions. Cutting-edge cloud-based data analytics platforms process massive datasets to unveil patterns, anomalies and trends that hint at impending issues.
• Advanced ML and Artificial Intelligence (AI): Machine learning algorithms dissect historical data to discern patterns and anomalies, enabling precise predictions. AI-driven systems scrutinise vast datasets, transforming raw information into actionable insights that augment decision-making prowess.
Denne historien er fra October 2023-utgaven av EM - Efficient Manufacturing.
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Denne historien er fra October 2023-utgaven av EM - Efficient Manufacturing.
Start your 7-day Magzter GOLD free trial to access thousands of curated premium stories, and 9,000+ magazines and newspapers.
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