Production engineering and management involve a series of planning and control activities in a production system. A production system can be as small as a shop with only one machine or as big as a global operation including many manufacturing plants, distribution centers, and retail locations in multiple continents. The product of a production system can also vary in complexity based on the material used, technology employed, etc. Every product, whether a pencil or an airplane, is produced in a system which depends on good management to be successful. Production management has been at the center of industrial engineering and management science disciplines since the industrial revolution. The tools and techniques of production management have been so successful that they have been adopted to various service industries, as well. The book is intended to be a valuable resource to undergraduate and graduate students interested in the applications of production management under fuzziness. The chapters represent all areas of production management and are organized to reflect the natural order of production management tasks. In all chapters, special attention is given to applicability and wherever possible, numerical examples are presented. While the reader is expected to have a fairly good understanding of the fuzzy logic, the book provides the necessary notation and preliminary knowledge needed in each chapter.

Supply Chain Management Under Fuzziness presents recently developed fuzzy models and techniques for supply chain management. These include: fuzzy PROMETHEE, fuzzy AHP, fuzzy ANP, fuzzy VIKOR, fuzzy DEMATEL, fuzzy clustering, fuzzy linear programming, and fuzzy inference systems. The book covers both practical applications and new developments concerning these methods. This book offers an excellent resource for researchers and practitioners in supply chain management and logistics, and will provide them with new suggestions and directions for future research. Moreover, it will support graduate students in their university courses, such as specialized courses on supply chains and logistics, as well as related courses in the fields of industrial engineering, engineering management and business administration.

This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

After an introductory chapter explaining recent applications of fuzzy sets in IE, this book explores the seven major areas of IE to which fuzzy set theory can contribute: Control and Reliability, Engineering Economics and Investment Analysis, Group and Multi-criteria Decision-making, Human Factors Engineering and Ergonomics, Manufacturing Systems and Technology Management, Optimization Techniques, and Statistical Decision-making. Under these major areas, every chapter includes didactic numerical applications.

This work is by two of the leading researchers in the field of fuzzy set theory and fuzzy logic. It deals with the notions of fuzzy numbers with levels of perception and levels of presumption. Many new results, examples and novel applications in engineering and management science are presented. This approach makes the book interesting and easy to understand, and provides mathematical tools which readers may find useful in the study of their own problems. Of particular interest are the discussions of applications in areas employing zero-based budgeting, the Delphi method, critical path optimization, reliability modelling, filtering and transportation. The first section is devoted to the theoretical basis for these mathematical models. The second part deals with a variety of applications in engineering and management science. There are also seven appendices which contain some special mathematical operations (Minkowaski's operations) on fuzzy quantities and detailed biographical material.

Every year, Captain Kangaroo sets the contestants on their way in the great balloon race. All the animals are there the platypus, the wombats, the koalas and the emus are all there. But when the contestants bump into a dust cloud, Captain Kangaroo has to step in to steer them back on course. Which of his emergency aircraft will he choose? And can you find the animals who have stowed away inside each basket?

This volume prepared by Roman Slowinski and Maciej Hapke is welcome because it is representative of the current state of the art in fuzzy set-based scheduling. Its publication proves that some operational research scientists start to consider fuzzy sets seriously as a bridge for a reconciliation between mathematical modeling and human scheduling practice. A difficulty for the reader of the fuzzy set scheduling literature is to understand the precise role of fuzzy sets in the various published papers. More often than not, the meaning of fuzzy sets remain unclear or must be guessed from the context of the problem. A major contribution of this volume is to try and clarify this issue through a suitable ordering of the papers, telling apart those where fuzzy sets is mainly a matter of representing preference, and those where the problem is one of scheduling under uncertainty. Taken from the foreword by Didier Dubois and Henry Prade

The objectives of Human Reliability are to build reliability into the job, into the machine, and into the environment, and to let man perform naturally. In this book the author shows how these objectives can be achieved by concentrating on human reliability issues during the design stage. This is done by illustrating the relationships between various design features and some aspect of human performance, e.g. human errors.

Very Good,No Highlights or Markup,all pages are intact.