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

ISBN-13: 9783658191191 / Angielski / Miękka / 2017 / 139 str.

Alexander Hubl

Opis

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.

Spis treści

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

O autorze

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.  

Blurb

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.  ​