Soft cover with perfect binding, Reliability Fundamentals by Michael D. Holloway is a comprehensive guide that equips engineers, technicians, and maintenance professionals with the foundational knowledge and tools necessary to understand, apply, and manage system reliability. Designed as both a learning manual and a practical reference, this book walks readers through core reliability concepts such as Mean Time Between Failures (MTBF), Mean Time to Failure (MTTF), Mean Time To Repair (MTTR), and Availability. Each chapter introduces key principles with real-world context, detailed formulas, worked examples, and concise summaries to support application and retention.
The book explores system configurations (series, parallel, hybrid), the Bathtub Curve, and structured reliability techniques such as Failure Modes and Effects Analysis (FMEA), Root Cause Analysis (RCA), Fault Tree Analysis (FTA), and Reliability-Centered Maintenance (RCM). It introduces advanced statistical tools including Weibull Analysis, Accelerated Life Testing (ALT), reliability growth modeling, and hypothesis testing, enabling readers to derive meaningful insights from life data and field failures.
In addition to the technical methods, the book addresses the human and organizational dimensions of reliability, including safety standards (ISO 31000, IEC 61508, MIL-STD-882), HAZOP studies, FRACAS workflows, warranty data analysis, and the promotion of a culture of reliability through training, SOPs, and leadership. With appendices containing ready-to-use templates, checklists, and calculation guides, it serves as a practical toolkit for professionals managing assets, designing robust systems, or seeking certification in reliability disciplines.
Whether applied on the plant floor, in design engineering, or within strategic asset management, Reliability Fundamentals delivers a balanced integration of theory, metrics, and implementation. It is ideal for those seeking to improve system uptime, reduce failure risk, and create sustainable reliability programs grounded in data and disciplined methodology.
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