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Stochastic Modelling in Production Planning = Methods for Improvement and Investigations on Production System Behaviour /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Stochastic Modelling in Production Planning/ by Alexander Hübl.
Reminder of title:	Methods for Improvement and Investigations on Production System Behaviour /
Author:	Hübl, Alexander.
Description:	XV, 139 p. 19 illus., 12 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Operations research. -
Online resource:	https://doi.org/10.1007/978-3-658-19120-7
ISBN:	9783658191207

Stochastic Modelling in Production Planning = Methods for Improvement and Investigations on Production System Behaviour /
Hübl, Alexander.

Stochastic Modelling in Production PlanningMethods for Improvement and Investigations on Production System Behaviour /[electronic resource] :by Alexander Hübl. - 1st ed. 2018. - XV, 139 p. 19 illus., 12 illus. in color.online resource.

Utilisation Concept -- Capacity Setting Methods -- Conwip -- Dispatching Rules.

Alexander Hübl 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 Hübl 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

Standard No.: 10.1007/978-3-658-19120-7doiSubjects--Topical Terms:

573517
Operations research.

LC Class. No.: HD30.23

Dewey Class. No.: 658.40301

Stochastic Modelling in Production Planning = Methods for Improvement and Investigations on Production System Behaviour /
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