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

Author:   Alexander Hübl
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   1st ed. 2018
ISBN:  

9783658191191


Pages:   139
Publication Date:   02 August 2017
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Stochastic Modelling in Production Planning: Methods for Improvement and Investigations on Production System Behaviour


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Overview

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.

Full Product Details

Author:   Alexander Hübl
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer Gabler
Edition:   1st ed. 2018
Weight:   2.105kg
ISBN:  

9783658191191


ISBN 10:   3658191198
Pages:   139
Publication Date:   02 August 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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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.  

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