AI-Driven Energy Centered Maintenance
by Fadi Alshakhshir
3rd Edition
Publisher: River Publishers
Book Details
| Print ISBN | 9788743801719 |
| eText ISBN | 9781040420928 |
| Publisher | River Publishers |
| Publishing Year | 2025 |
| Edition | 3rd Edition |
| Language | English |
| Pages | 308 |
AI-Driven Energy Centered Maintenance (3rd Edition) provides a technical reference on incorporating machine learning, predictive maintenance, and artificial intelligence within facility operations. Author Fadi S. Alshakhshir expands upon core energy-centered frameworks to guide energy engineers, facility managers, and maintenance personnel in connecting equipment maintenance routines with energy optimization goals.
The content outlines structured workflows for equipment identification, data gathering, physical inspections, performance measurement, and cost-benefit analysis. It details how to modify preventive maintenance plans using collected operational data. Dedicated sections focus on specialized facilities, presenting targeted practices for data centers and chilled water systems designed to avoid Low Delta T Syndrome.
Additional chapters detail equipment efficiency metrics, energy savings verification methods, and strategies for establishing an energy-conscious organizational culture. Formatted as a self-study guide and reference work, this volume supports maintenance professionals, students, and decision-makers seeking data-driven maintenance methodologies.
Table of Contents
Chapter 1: Energy Reduction
Chapter 2: Different Maintenance Types and the Need for Energy Centered Maintenance
Chapter 3: Energy Centered Maintenance Origin and Model
Chapter 4: ECM Process - Equipment Identification
Chapter 5: ECM Process - Data Collection
Chapter 6: ECM Process - ECM Inspections
Chapter 7: ECM Process - Measuring Equipment Current Performance
Chapter 8: ECM Process - Identifying Corrective/ Preventive Action & Cost Effectiveness
Chapter 9: ECM Process - Updating Preventative Maintenance Plans
Chapter 10: Energy Centered Maintenance to avoid Low Delta T Syndrome in Chilled Water Systems
Chapter 11: Energy Centered Maintenance in Data Centers
Chapter 12: Measures of Equipment and Maintenance Efficiency and Effectiveness
Chapter 13: Energy Savings Verification
Chapter 14: Building Energy Centered Behavior Leading to an Energy Centered Culture
Chapter 15: Data Driven Energy Centered Maintenance Model
Chapter 16: AI Driven Energy Centered Maintenance
Chapter 17: Conclusion
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- AI-Driven Energy Centered Maintenance
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