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Stochastic modelling in production p...
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Hubl, Alexander.
Stochastic modelling in production planningmethods for improvement and investigations on production system behaviour /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Stochastic modelling in production planningby Alexander Hubl.
Reminder of title:
methods for improvement and investigations on production system behaviour /
Author:
Hubl, Alexander.
Published:
Wiesbaden :Springer Fachmedien Wiesbaden :2018.
Description:
xv, 139 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Decision making.
Online resource:
http://dx.doi.org/10.1007/978-3-658-19120-7
ISBN:
9783658191207$q(electronic bk.)
Stochastic modelling in production planningmethods for improvement and investigations on production system behaviour /
Hubl, Alexander.
Stochastic modelling in production planning
methods for improvement and investigations on production system behaviour /[electronic resource] :by Alexander Hubl. - Wiesbaden :Springer Fachmedien Wiesbaden :2018. - xv, 139 p. :ill., digital ;24 cm.
Utilisation Concept -- Capacity Setting Methods -- Conwip -- Dispatching Rules.
Alexander Hubl develops models for production planning and analyzes performance indicators to investigate production system behaviour. He extends existing literature by considering the uncertainty of customer required lead time and processing times as well as by increasing the complexity of multi-machine multi-items production models. Results are on the one hand a decision support system for determining capacity and the further development of the production planning method Conwip. On the other hand, the author develops the JIT intensity and analytically proves the effects of dispatching rules on production lead time. Contents Utilisation Concept Capacity Setting Methods Conwip Dispatching Rules Target Groups Researchers and students in the fields of logistics and operations management Practitioners in production planning, logistics, capacity planning The Author Alexander Hubl holds a PhD in logistics and operations management from University of Vienna, Austria. He leads the research group Supply Chain Planning at the department Logistikum at the University of Applied Sciences Upper Austria. His research interests include discrete event simulation, agent-based simulation, queuing theory, stochastic modelling and their applications in logistics and operations management.
ISBN: 9783658191207$q(electronic bk.)
Standard No.: 10.1007/978-3-658-19120-7doiSubjects--Topical Terms:
183849
Decision making.
LC Class. No.: HD30.23
Dewey Class. No.: 658.403
Stochastic modelling in production planningmethods for improvement and investigations on production system behaviour /
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by Alexander Hubl.
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ill., digital ;
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Utilisation Concept -- Capacity Setting Methods -- Conwip -- Dispatching Rules.
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Alexander Hubl develops models for production planning and analyzes performance indicators to investigate production system behaviour. He extends existing literature by considering the uncertainty of customer required lead time and processing times as well as by increasing the complexity of multi-machine multi-items production models. Results are on the one hand a decision support system for determining capacity and the further development of the production planning method Conwip. On the other hand, the author develops the JIT intensity and analytically proves the effects of dispatching rules on production lead time. Contents Utilisation Concept Capacity Setting Methods Conwip Dispatching Rules Target Groups Researchers and students in the fields of logistics and operations management Practitioners in production planning, logistics, capacity planning The Author Alexander Hubl holds a PhD in logistics and operations management from University of Vienna, Austria. He leads the research group Supply Chain Planning at the department Logistikum at the University of Applied Sciences Upper Austria. His research interests include discrete event simulation, agent-based simulation, queuing theory, stochastic modelling and their applications in logistics and operations management.
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Business and Management (Springer-41169)
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000000149345
電子館藏
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EB HD30.23
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1
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http://dx.doi.org/10.1007/978-3-658-19120-7
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