Simulating production and inventory control systems: a learning approach to operational excellence

The search for operational excellence includes both a thorough understanding of the nature of the manufacturing operations and a choice of the right production and inventory control system for the environment in which it will operate. Understanding the nature of manufacturing operations can be facilitated by simulating the manufacturing system, so that the interrelationships among parameters can be studied. Production and inventory control systems can be simulated together with the physical manufacturing environment in order to enhance the understanding of the behaviour of a particular control system and also to facilitate the selection of control systems for the manufacturing system under study. In this paper we report on the design and learning effects of using simulation for investigating the behaviour and impact of different production and inventory control systems in a manufacturing system. We discuss the structure and simulation perspectives of production and inventory control systems. We provide a review of the benefits of using simulation for learning the manufacturing environment, and the related testing of alternative control systems.

[1]  Joakim Wikner,et al.  Production planning and control tools , 2000 .

[2]  Benjamin S. Bloom,et al.  Taxonomy of Educational Objectives: The Classification of Educational Goals. , 1957 .

[3]  Jan Olhager,et al.  The effect of MRP lot sizing on actual cumulative lead times in multi-level systems , 1998 .

[4]  P. Scholtissek,et al.  Exploiting logistic potentials with a simulation-aided test of PPC methods , 1997 .

[5]  Jozef Maes,et al.  Functionalities of production-inventory control systems , 1991 .

[6]  Dingwei Wang,et al.  A simulation and comparative study of the CONWIP, Kanban and MRP production control systems in a cold rolling plant , 1998 .

[7]  Arnoldo C. Hax,et al.  Production and inventory management , 1983 .

[8]  S. Elmaghraby.  The Economic Lot Scheduling Problem (ELSP): Review and Extensions , 1978 .

[9]  David F. Pyke,et al.  Inventory management and production planning and scheduling , 1998 .

[10]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[11]  Ralf Hieber,et al.  Impacts of SCM order strategies evaluated by simulation-based 'Beer Game' approach: The model, concept, and initial experiences , 2003 .

[12]  Brian Shorrock,et al.  Material Requirements Planning , 1978 .

[13]  Riitta Smeds,et al.  Simulation for accelerated learning and development in industrial management , 2003 .

[14]  Jan Olhager,et al.  Supply chain impacts at Ericsson - from production units to demand-driven supply units , 2002, Int. J. Technol. Manag..

[15]  F. Persson,et al.  Performance simulation of supply chain designs , 2002 .