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- Mohammed Hamed Ahmed Soliman
Mohammed Hamed Ahmed Soliman

Dernière sortie
AI for Predictive Maintenance in Industry 4.0: Extended PdM Methodologies: From Vibration & Thermal to Motor Current, Wear Debris, Pressure, and Efficiency Analysis
Unlike traditional PdM books that dive deeply into a single technique, this guide covers Extended PdM Methodologies in one practical volume. It explores not only classical methods such as vibration, thermal, and oil analysis, but also advanced and less common approaches including motor current analysis, wear debris, partial discharge, pressure, and efficiency monitoring. Rather than replacing specialist handbooks, this book focuses on how to integrate multiple PdM techniques with sensors, industrial data, and AI/ML tools to design Industry 4.0-ready predictive maintenance systems.
Inside, you will learn how to: Collect, preprocess, and analyze industrial data from IoT, SCADA, and sensors. Apply AI and ML models (Random Forest, LSTM, CNN, Autoencoders) to predict equipment failures. Use vibration, oil, thermal, and acoustic monitoring in AI-enhanced workflows. Incorporate advanced methods such as motor current, wear debris, partial discharge, pressure, and efficiency monitoring.
Build predictive workflows from model training to deployment and monitoring. Evaluate ROI and integrate PdM into Industry 4.0 ecosystems (Digital Twin, Cloud/Edge, 5G). With a balance of theory, case studies, and practical insights, this book serves as a broad, integrative roadmap for engineers, reliability professionals, and Industry 4.0 practitioners looking to harness AI-driven predictive maintenance across industries such as energy, aviation, automotive, petrochemicals, and manufacturing.
Inside, you will learn how to: Collect, preprocess, and analyze industrial data from IoT, SCADA, and sensors. Apply AI and ML models (Random Forest, LSTM, CNN, Autoencoders) to predict equipment failures. Use vibration, oil, thermal, and acoustic monitoring in AI-enhanced workflows. Incorporate advanced methods such as motor current, wear debris, partial discharge, pressure, and efficiency monitoring.
Build predictive workflows from model training to deployment and monitoring. Evaluate ROI and integrate PdM into Industry 4.0 ecosystems (Digital Twin, Cloud/Edge, 5G). With a balance of theory, case studies, and practical insights, this book serves as a broad, integrative roadmap for engineers, reliability professionals, and Industry 4.0 practitioners looking to harness AI-driven predictive maintenance across industries such as energy, aviation, automotive, petrochemicals, and manufacturing.
Unlike traditional PdM books that dive deeply into a single technique, this guide covers Extended PdM Methodologies in one practical volume. It explores not only classical methods such as vibration, thermal, and oil analysis, but also advanced and less common approaches including motor current analysis, wear debris, partial discharge, pressure, and efficiency monitoring. Rather than replacing specialist handbooks, this book focuses on how to integrate multiple PdM techniques with sensors, industrial data, and AI/ML tools to design Industry 4.0-ready predictive maintenance systems.
Inside, you will learn how to: Collect, preprocess, and analyze industrial data from IoT, SCADA, and sensors. Apply AI and ML models (Random Forest, LSTM, CNN, Autoencoders) to predict equipment failures. Use vibration, oil, thermal, and acoustic monitoring in AI-enhanced workflows. Incorporate advanced methods such as motor current, wear debris, partial discharge, pressure, and efficiency monitoring.
Build predictive workflows from model training to deployment and monitoring. Evaluate ROI and integrate PdM into Industry 4.0 ecosystems (Digital Twin, Cloud/Edge, 5G). With a balance of theory, case studies, and practical insights, this book serves as a broad, integrative roadmap for engineers, reliability professionals, and Industry 4.0 practitioners looking to harness AI-driven predictive maintenance across industries such as energy, aviation, automotive, petrochemicals, and manufacturing.
Inside, you will learn how to: Collect, preprocess, and analyze industrial data from IoT, SCADA, and sensors. Apply AI and ML models (Random Forest, LSTM, CNN, Autoencoders) to predict equipment failures. Use vibration, oil, thermal, and acoustic monitoring in AI-enhanced workflows. Incorporate advanced methods such as motor current, wear debris, partial discharge, pressure, and efficiency monitoring.
Build predictive workflows from model training to deployment and monitoring. Evaluate ROI and integrate PdM into Industry 4.0 ecosystems (Digital Twin, Cloud/Edge, 5G). With a balance of theory, case studies, and practical insights, this book serves as a broad, integrative roadmap for engineers, reliability professionals, and Industry 4.0 practitioners looking to harness AI-driven predictive maintenance across industries such as energy, aviation, automotive, petrochemicals, and manufacturing.
Les livres de Mohammed Hamed Ahmed Soliman

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Industrial Electric Motors: Installation, Running, Advanced Maintenance and Reliability. Maintenance Strategy & Reliability Series
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Design Review Based on Failure Mode: How Toyota Engineers Use an Advanced Model of FMEA to Improve Product Reliability (Toyota’s GD3)
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Application of Lean in Non - manufacturing Environments - Series Books 18 to 19. Toyota Production System Concepts
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Process and Value Stream Mapping the Toyota Way. Toyota Production System Concepts, #24
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Kata: The Toyota Way to Structured Improvement and Coaching. Toyota Production System Concepts, #23
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The Guidebook to Toyota's Corporate Strategy and Leadership – Series Books 1 to 6. Toyota Production System Concepts
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The Guidebook to Toyota's 13 Pillars System - Series Books 7 to 17. Toyota Production System Concepts
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The DNA of Toyota: What the Toyota Production System Is — and What It’s Not. Toyota Production System Concepts, #17
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5S - The True Mean to Enhance Productivity and Work Value for Customers. Toyota Production System Concepts, #16
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Lean Culture: How Toyota Builds Daily Habits of Improvement and Engagement. Toyota Production System Concepts, #6
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Poka Yoke - Design for Great Quality. Toyota Production System Concepts, #9
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How to Create Continuous Production Flow?. Toyota Production System Concepts, #13
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Toyota’s Approach to Developing and Coaching Leaders. Toyota Production System Concepts, #5
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Genchi Genbutsu Process – The Role of Gemba in Lean Management and Value Creation. Toyota Production System Concepts, #3
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5,49 €

Lean Cost - Benefit Analysis: Making Smarter Decisions with Less Waste. Toyota Production System Concepts, #22
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2,99 €

How to Develop Mission, Strategy, Goals and Values That Fit with Company’s Vision Statement. Toyota Production System Concepts, #2
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3,49 €