Abstract
Customer ordering behaviorin the form of size and timing of orders are critical for manufacturing systems such as make-to-order or assemble-to-order systems. To be competitive a Make-to-order manufacture must be flexible, both with regards to volume and product mix. A particularly critical parameter in determining the flexibility needs in the case of responsive manufacturing environments is the distribution of order sizes. In this paper several methods for describing the volatility of order sizes are presented. A discrete event simulation of a single server batch manufacturing system is subsequently conducted using various distributions of order sizes. The aim is to investigate 1) which measures for order size volatility best relates to the volatility of the output rate from the manufacturing system 2) how does the output stability from the system deteriorate as order sizes become more volatile.
Chapter PDF
Similar content being viewed by others
References
Berry, W.L., Hill, T.: Linking Systems to Strategy. International Journal of Operations & Production Management 12, 3–15 (1992)
Box, G.E.P., Jenkins, G.: Time Series Analysis: Forecasting and Control. Holden-Day (1976)
Brander, P., Levén, E., Segerstedt, A.: Lot sizes in a capacity constrained facility-a simulation study of stationary stochastic demand. International Journal of Production Economics 93-94, 375–386 (2005)
Nicholas, J.: Competitive Manufacturing Management: Continuous Improvement. Lean Production and Customer-focused Quality. McGraw-Hill, New York (1998)
Nielsen, P., Eriksen, T.: Towards an analysis methodology for identifying root causes of poor delivery performance. In: Conference Proceedings of IESM 2011, International Conference on Industrial Engineering and Systems Management (2011)
Nielsen, P., Nielsen, I., Steger-Jensen, K.: Analyzing and evaluating product demand interdependencies. Computers in Industry 61, 869–876 (2010)
Olhager, J.O.: Strategic positioning of the order penetration point. International Journal of Production Economics 85, 319–329 (2003)
Olhager, J., Wikner, J.: Master Production Scheduling. In: Beyond Manufacturing Resource Planning (MRPII): Advanced Models and Methods for Production Planning, pp. 3–20. Springer (1998)
R-project.org (webpage) (2012)
Silver, E.A., Pyke, D.F., Peterson, R.: Inventory Management and Production Planning and Scheduling, 3rd edn. John Wiley & Sons (1998)
Vollmann, W., Berry, D., Whybark, T.E., Jacobs, F.: Manufacturing Planning and Control for Supply Chain Management. McGraw-Hill, Singapore (2005)
Wijngaard, J.: On Aggregation in Production Planning. Engineering Costs and Production Economics 6, 259–266 (1982)
Zotteri, G., Kalchschmidt, M., Caniato, F.: The impact of aggregation level on forecasting performance. International Journal of Production Economics 93-94, 479–491 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Nielsen, P., Bocewicz, G. (2012). Simulation Study of the Volatility of Order Sizes and Their Impact on the Stability of a Simple Manufacturing Environment. In: Frick, J., Laugen, B.T. (eds) Advances in Production Management Systems. Value Networks: Innovation, Technologies, and Management. APMS 2011. IFIP Advances in Information and Communication Technology, vol 384. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33980-6_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-33980-6_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33979-0
Online ISBN: 978-3-642-33980-6
eBook Packages: Computer ScienceComputer Science (R0)