03663nam 22006255 450 991059299270332120251113211444.09789811942150(electronic bk.)978981194214310.1007/978-981-19-4215-0(MiAaPQ)EBC7084544(Au-PeEL)EBL7084544(CKB)24819673500041(PPN)264958128(OCoLC)1344346980(DE-He213)978-981-19-4215-0(EXLCZ)992481967350004120220910d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAssembly Line Balancing under Uncertain Task Time and Demand Volatility /by Yuchen Li1st ed. 2022.Singapore :Springer Nature Singapore :Imprint: Springer,2022.1 online resource (164 pages)Engineering Applications of Computational Methods,2662-3374 ;8Print version: Li, Yuchen Assembly Line Balancing under Uncertain Task Time and Demand Volatility Singapore : Springer,c2022 9789811942143 Includes bibliographical references.Preface -- Chapter 1 Introduction -- Chapter 2 State of the art -- Chapter 3 Rebalancing an assembly line with disruptions -- Chapter 4 Two-sided assembly line balancing under uncertain task time attributes -- Chapter 5 System reliability optimization under uncertain task time attributes -- Chapter 6 Assembly line balancing under task learning and uncertain demand -- Chapter 7 A joint assembly line balancing and lot-sizing problem under uncertain demand -- References.This book introduces several mathematical models in assembly line balancing based on stochastic programming and develops exact and heuristic methods to solve them. An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In an assembly line balancing problem, tasks belonging to different product models are allocated to workstations according to their processing times and precedence relationships among tasks. It incorporates two features, uncertain task times, and demand volatility, separately and simultaneously, into the conventional assembly line balancing model. A real-life case study related to the mask production during the COVID-19 pandemic is presented to illustrate the application of the proposed framework and methodology. The book is intended for graduate students who are interested in combinatorial optimizations in manufacturing with uncertain input.Engineering Applications of Computational Methods,2662-3374 ;8Industrial engineeringProduction engineeringMathematical modelsMathematical optimizationIndustrial and Production EngineeringMathematical Modeling and Industrial MathematicsOptimizationIndustrial engineering.Production engineering.Mathematical models.Mathematical optimization.Industrial and Production Engineering.Mathematical Modeling and Industrial Mathematics.Optimization.670.427Li Yuchen1257648MiAaPQMiAaPQMiAaPQ9910592992703321Assembly Line Balancing under Uncertain Task Time and Demand Volatility2914330UNINA