This book presents the state-of-the-art in quality and reliability engineering from a product life-cycle standpoint. Topics in reliability include reliability models, life data analysis and modeling, design for reliability as well as accelerated life testing and reliability growth analysis, while topics in quality include design for quality, acceptance sampling and supplier selection, statistical process control, production tests such as environmental stress screening and burn-in, warranty and maintenance. The book provides comprehensive insights into two closely related subjects, and includes a wealth of examples and problems to enhance readers´ comprehension and link theory and practice. All numerical examples can be easily solved using Microsoft Excel. The book is intended for senior undergraduate and postgraduate students in related engineering and management programs such as mechanical engineering, manufacturing engineering, industrial engineering and engineering management programs, as well as for researchers and engineers in the quality and reliability fields.
Dr. Renyan Jiang is a professor at the Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology, China.
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Integrates the subjects quality and reliability engineering
Focuses on practical issues and quantitative analysis
Includes a wealth of examples and exercises that can be conveniently solved using a spreadsheet program
Uses Microsoft Excel to conduct optimization, regression and simulation and calculate the values usually determined using statistical tables
Some topics are unique and cross-disciplinary, such as design for X and multi-criteria decision making and supplier selection
Part I Background materials.- Part II Product Quality and Reliability in pre-manufacturing phase.- Part III Product Quality and Reliability in manufacturing phase.- Part IV Product Quality and Reliability in post-manufacturing phase.
This book presents the state-of-the-art in quality and reliability engineering from a product life cycle standpoint. Topics in reliability include reliability models, life data analysis and modeling, design for reliability and accelerated life testing, while topics in quality include design for quality, acceptance sampling and supplier selection, statistical process control, production tests such as screening and burn-in, warranty and maintenance. The book provides comprehensive insights into two closely related subjects, and includes a wealth of examples and problems to enhance reader comprehension and link theory and practice. All numerical examples can be easily solved using Microsoft Excel. The book is intended for senior undergraduate and post-graduate students in related engineering and management programs such as mechanical engineering, manufacturing engineering, industrial engineering and engineering management programs, as well as for researchers and engineers in the quality and reliability fields.
Dr. Renyan Jiang is a Professor at the School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, China.
This book presents the state-of-the-art in quality and reliability engineering from a product life-cycle standpoint. Topics in reliability include reliability models, life data analysis and modeling, design for reliability as well as accelerated life testing and reliability growth analysis, while topics in quality include design for quality, acceptance sampling and supplier selection, statistical process control, production tests such as environmental stress screening and burn-in, warranty and maintenance. The book provides comprehensive insights into two closely related subjects, and includes a wealth of examples and problems to enhance readers' comprehension and link theory and practice. All numerical examples can be easily solved using Microsoft Excel. The book is intended for senior undergraduate and postgraduate students in related engineering and management programs such as mechanical engineering, manufacturing engineering, industrial engineering and engineering management programs, as well as for researchers and engineers in the quality and reliability fields.
Dr. Renyan Jiang is a professor at the Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology, China.
Part I. Background materials.- Part II. Product Quality and Reliability in pre-manufacturing phase.- Part III. Product Quality and Reliability in manufacturing phase.- Part IV. Product Quality and Reliability in post-manufacturing phase.
Inhaltsverzeichnis
Part I. Background materials.- Part II. Product Quality and Reliability in pre-manufacturing phase.- Part III. Product Quality and Reliability in manufacturing phase.- Part IV. Product Quality and Reliability in post-manufacturing phase.
Klappentext
This book presents the state-of-the-art in quality and reliability engineering from a product life-cycle standpoint. Topics in reliability include reliability models, life data analysis and modeling, design for reliability as well as accelerated life testing and reliability growth analysis, while topics in quality include design for quality, acceptance sampling and supplier selection, statistical process control, production tests such as environmental stress screening and burn-in, warranty and maintenance. The book provides comprehensive insights into two closely related subjects, and includes a wealth of examples and problems to enhance readers' comprehension and link theory and practice. All numerical examples can be easily solved using Microsoft Excel. The book is intended for senior undergraduate and postgraduate students in related engineering and management programs such as mechanical engineering, manufacturing engineering, industrial engineering and engineering management programs, as well as for researchers and engineers in the quality and reliability fields.
Dr. Renyan Jiang is a professor at the Faculty of Automotive and Mechanical Engineering, Changsha University of Science and Technology, China.
Integrates the subjects quality and reliability engineering
Focuses on practical issues and quantitative analysis
Includes a wealth of examples and exercises that can be conveniently solved using a spreadsheet program
Uses Microsoft Excel to conduct optimization, regression and simulation and calculate the values usually determined using statistical tables
Some topics are unique and cross-disciplinary, such as design for X and multi-criteria decision making and supplier selection
