Overview
- Modeling and quantitative methods give readers the tools to improve the supply chain process
- A thorough description of QM tools and techniques allows readers to select those that are appropriate to their needs
- Discussion of reverse logistics enables readers to apply this new scope to their work
- Includes supplementary material: sn.pub/extras
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Table of contents (8 chapters)
Keywords
About this book
Reviews
“The focus of this edited volume is to study and appraise quality management tools and methodologies, as well as its applications in the supply chain process. … The book includes many useful topics and techniques for practitioners and researchers equally. It can be served as a reference guide, and is expected to advance the knowledge in the field of reverse logistics, where quality management can be applied.” (S. E. Ahmed, Technometrics, Vol. 56 (4), November, 2014)
Editors and Affiliations
About the editor
Yiannis Nikolaidis earned his PhD from the Department of Mechanical Engineering, Polytechnic School, Aristotle University of Thessaloniki in 2001. He is currently an assistant professor at University of Macedonia, where his main research area is Quality Management (QM) which contributes greatly to the improvement of product and service quality and to the reduction of quality costs not only of forward manufacturing processes but also of reverse logistics.
Bibliographic Information
Book Title: Quality Management in Reverse Logistics
Book Subtitle: A Broad Look on Quality Issues and Their Interaction with Closed-Loop Supply Chains
Editors: Yiannis Nikolaidis
DOI: https://doi.org/10.1007/978-1-4471-4537-0
Publisher: Springer London
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag London 2013
Hardcover ISBN: 978-1-4471-4536-3Published: 09 October 2012
Softcover ISBN: 978-1-4471-5938-4Published: 09 November 2014
eBook ISBN: 978-1-4471-4537-0Published: 08 October 2012
Edition Number: 1
Number of Pages: XII, 160
Topics: Quality Control, Reliability, Safety and Risk, Engineering Economics, Organization, Logistics, Marketing, Operations Management, Mathematical Modeling and Industrial Mathematics, Simulation and Modeling, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences