1st Edition

Quality Management and Operations Research Understanding and Implementing the Nonparametric Bayesian Approach

    138 Pages 15 B/W Illustrations
    by CRC Press

    Offering a step-by-step approach for applying the Nonparametric Method with the Bayesian Approach to model complex relationships occurring in Reliability Engineering, Quality Management, and Operations Research, it also discusses survival and censored data, accelerated lifetime tests (issues in reliability data analysis), and R codes.

    This book uses the Nonparametric Bayesian approach in the fields of quality management and operations research. It presents a step-by-step approach for understanding and implementing these models, as well as includes R codes which can be used in any dataset. The book helps the readers to use statistical models in studying complex concepts and applying them to Operations Research, Industrial Engineering, Manufacturing Engineering, Computer Science, Quality and Reliability, Maintenance Planning and Operations Management.

    This book helps researchers, analysts, investigators, designers, producers, industrialists, entrepreneurs, and financial market decision makers, with finding the lifetime model of products, and for crucial decision-making in other markets.

    1. Introduction. 2. Quality and Reliability. 3. Dirichlet Process. 4. Nonparametric Bayesian Approach in Accelerated Lifetime Tests. 5. Illustrative Examples and Results. Appendix A: Guide to Proofs. Appendix B: R Programming Codes. References.

    Biography

    Nezameddin Faghih is the UNESCO Chair Professor Emeritus, and the Founding Editor-in-Chief of the Journal of Global Entrepreneurship Research (Springer). He has published more than 50 books, 100 research articles, and presented more than 120 invited talks in academia, industry, and professional meetings.

    Ebrahim Bonyadi is an applied statistician in the areas of business and economics and is a researcher at the Global Entrepreneurship Monitor (GEM) Office of the Faculty of Entrepreneurship, University of Tehran. His scholarly research focuses on factors influencing entrepreneurship, business, and economic growth.

    Lida Sarreshtehdari is an applied statistician focusing on entrepreneurship, with expertise in the Global Entrepreneurship Monitor (GEM) dataset. She is a researcher at the Global Entrepreneurship Monitor (GEM) Office of the Faculty of Entrepreneurship, University of Tehran. She has published several reports on the domestic entrepreneurship since 2011.