Effective Resource Management in Manufacturing Systems [electronic resource] : Optimization Algorithms for Production Planning / by Massimiliano Caramia, Paolo Dell’Olmo.Material type: TextLanguage: English Series: Springer Series in Advanced Manufacturing: Publisher: London : Springer London, 2006Description: XXII, 216 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781846282270Subject(s): Engineering | Industrial engineering | Machinery | Business logistics | Engineering | Industrial and Production Engineering | Manufacturing, Machines, Tools | Operations Research/Decision Theory | Production/LogisticsAdditional physical formats: Printed edition:: No titleDDC classification: 670 LOC classification: T55.4-60.8Online resources: Click here to access online
Manufacturing Systems: Trends, Classification, and Behavior Patterns -- On-Line Load Balancing -- Resource Levelling -- Scheduling Jobs in Robotized Cells with Multiple Shared Resources -- Tool Management on Flexible Machines.
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.