Product Reliability, D. N. Prabhakar Murthy; Marvin Rausand; Trond ?ste

Benefit from improved safety, performance, and product deliveries to your customers. Achieve a higher rate of equipment availability, performance, product quality, and reliability. Integrated Reliability: Condition Monitoring and Maintenance of Equipment incorporates reliable engineering and mathematical modeling to help you move toward sustainable development in reliability condition monitoring and maintenance. This text introduces a cost-effective integrated reliability growth monitor, integrated reliability degradation monitor, technological inheritance coefficient sensors, and a maintenance tool that supplies real-time information for predicting and preventing potential failures of manufacturing processes and equipment.

The author highlights five key elements that are essential to any improvement program: improving overall equipment and part effectiveness, quality, and reliability; improving process performance with maintenance efficiency and effectiveness; training all employees involved; including operators in the daily maintenance and upkeep of the equipment; and implementing early equipment management and maintenance prevention design. He offers a sustainable solution with integrated reliability condition monitoring and maintenance of manufacturing processes, parts, and equipment in the IOFs with a technological inheritance model-based program.

This book contains 15 chapters that include details on:

• Improving the material-part-equipment system life cycle, reliability conditions, and manufacturing process productivity for wear, corrosion, and temperature resistance applications
• Maximizing the component and system reliability growth of parts and equipment
• Minimizing reliability degradation within the framework of a condition-based maintenance
• Analyzing the reliability degradation, wear, and other competing failure modes of nickel-based hard alloy-coated part mating surface with a technological inheritance model-based program
• Introducing a cost-effective integrated reliability monitor and maintenance strategy with a technological inheritance model-based software program

Integrated Reliability: Condition Monitoring and Maintenance of Equipment addresses potential failures from an asset manager, maintenance user, and operator's standpoint, and highlights the solutions to common failures and reliability problems for equipment in the IOFs.

• Understand the life-cycle approach to engineering reliability
• Explore failure analysis techniques and their importance in reliability engineering
• Learn the skills of linear programming, financial analysis, and budgeting for maintenance
• Analyze the application of key concepts through realistic Case Studies

This text will equip engineering students, engineers and technical managers with the knowledge and skills they need, and the numerous examples and case studies include provide insight to their real-world application. An Instructor's Manual and Figure Slides are available for instructors.

Section I contains a comprehensive overview of assessing and assuring reliability that is followed by discussions of:
- Concept of randomness and its relationship to chaos
- Uses and limitations of the binomial and Poisson distributions
- Relationship of the chi-square method and Poisson curves
- Derivations and applications of the exponential, Weibull, and lognormal models
- Examination of the human mortality bathtub curve as a template for components

Section II introduces the case study modeling of failure data and is followed by analyses of:
- 5 sets of ideal Weibull, lognormal, and normal failure data
- 83 sets of actual (real) failure data

The intent of the modeling was to find the best descriptions of the failures using statistical life models, principally the Weibull, lognormal, and normal models, for characterizing the failure probability distributions of the times-, cycles-, and miles-to-failure during laboratory or field testing. The statistical model providing the preferred characterization was determined empirically by choosing the two-parameter model that gave the best straight-line fit in the failure probability plots using a combination of visual inspection and three statistical goodness-of-fit (GoF) tests.

This book offers practical insight in dealing with single item reliability and illustrates the use of reliability methods to solve industry problems.