Effective Resource Management in Manufacturing Systems: Optimization Algorithms for Production Planning / Edition 1

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Overview

Manufacturing systems, regardless of their size, have to work with scarce resources in dynamic environments. Managers are asked to assign production facilities over time to parallel activities respecting operational constraints and deadlines while keeping resource costs as low as possible. Thus, classic scheduling approaches are not adequate when (i) a task simultaneously requires a set of different resources and (ii) a trade-off between different objectives (like time, cost and workload balance) should be reached. In such a case, more sophisticated models and algorithms should be brought to the attention of managers and executives of manufacturing companies.
Effective Resource Management in Manufacturing Systems aims to provide robust methods for achieving effective resource allocation and to solve related problems that occur daily and often generate cost overruns, specifically focusing on problems like resource levelling, sizing of machines and production layouts, cost optimization in production planning and scheduling. This approach is based on providing quantitative methods, covering both mathematical programming and algorithms, leading to high quality solutions for the analysed problems. Details of extensive experimentation is provided for the proposed techniques to put them in a practical perspective, so that, on the one hand, the reader can reproduce them, and, on the other hand, it appears clear how they can be implemented in real scenarios.
This book will be a valuable resource for postgraduate students studying business, engineering or computer science. It will also be of interest to researchers in the fore-mentioned areas.

The Springer Series in Advanced Manufacturing publishes the best teaching and reference material to support students, educators and practitioners in manufacturing technology and management. This international series includes advanced textbooks, research monographs, edited works and conference proceedings covering all subjects in advanced manufacturing. The series focuses on new topics of interest, new treatments of more traditional areas and coverage of the applications of information and communication technology (ICT) in manufacturing.

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Editorial Reviews

From the Publisher
Owing to its large operational impact, resource management is increasingly becoming an important function in manufacturing systems. Contributions on how to organize or manage this function are always appreciated. This book aims to provide robust methods for achieving effective resource allocation in dynamic environments, specially focussing on problems such as resource levelling, sizing of machines and production layouts, cost optimization in production planning and scheduling. Details of extensive experimentation are provided for the proposed techniques to put them in a practical perspective. This is particularly useful as it helps the reader to reproduce these techniques and implement them in real scenarios.

The book is well written and documented. It is a good reference for postgraduate students and practitioners who are working in the field of resource management and scheduling in manufacturing systems.

The book is well written and documented. It is a good reference for postgraduate students and practitioners who are working in the field of resource management and scheduling in manufacturing systems.

International Journal of Advanced Manufacturing Technology

Reviewer, A A Afify, MEC, Cardiff University

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Product Details

  • ISBN-13: 9781846280054
  • Publisher: Springer London
  • Publication date: 1/9/2006
  • Series: Springer Series in Advanced Manufacturing
  • Edition description: 2006
  • Edition number: 1
  • Pages: 216
  • Product dimensions: 0.56 (w) x 6.14 (h) x 9.21 (d)

Meet the Author

Massimiliano Caramia received his Laurea Degree in Management Engineering at the University of Rome "Tor Vergata", Italy in 1996, and his Ph.D. in Operations Research at the University of Rome "La Sapienza" in 2000. From 2000 to 2001 he was a research associate at the University of Rome "Tor Vergata", since then he has been a researcher at the Istituto per le Applicazioni del Calcolo "M. Picone" of the Italian National Research Council. His primary research interests include: combinatorial optimization, manufacturing, real life scheduling problems and logistics. He has published many papers in international journals such as Discrete Mathematics and SIAM Journal on Optimization, Networks, and has acted as a referee for many international journals, including: Journal of Discrete Algorithms, Transportation Science and International Transactions in Operational Research. His teaching subjects are Operations Research, Models and Analysis of Manufacturing Systems, Mathematical Methods for Management, Decision Support Systems, Quality and Performance Management, Project Management.

Paolo Dell’Olmo received his Laurea Degree in Electronic Engineering at the University of Rome "La Sapienza", Italy. He became a full professor in Operations Research in 2000. He has been a visiting scholar at the Department of Systems and Industrial Engineering of University of Arizona (1992-93), a visiting professor at the Operation Research Center of MIT (1998). Currently, he is: Head of the Department of Statistics, Probability and Applied Statistics at the University of Rome "La Sapienza", he is also a Director of the Masters degree in Data Intelligence and Strategic Decisions and coordinator of the PhD program in Operations Research of the University of Rome as well as a research fellow of the Istituto di Analisi dei Sistemi e Informatica. He has been responsible for several national and international research projects and author of more than 60 scientific papers published in international journals. His primary research interests include: combinatorial optimization and real life scheduling and routing problems.

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Table of Contents

Manufacturing Systems: Trends, Classification, Behaviour Patterns, and Functionalities

On-Line Load Balancing

Resource Levelling

Scheduling Jobs in Robotized Cells with Multiple Shared Resources

Tool Management on Flexible Machines

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