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Design of a Framework for Inventory Control - Evaluation of Forecasting and Inventory Control Systems
University of Skövde.ORCID iD: 0000-0002-0382-1387
University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.ORCID iD: 0000-0002-8305-4412
University of Skövde, The Virtual Systems Research Centre. University of Skövde, School of Technology and Society.
2009 (English)In: Flexible Automation andIntelligent Manufacturing 2009 (FAIM 2009) / [ed] Farhad Nabhani, Catherine Frost, Sara Zarei, Munir Ahmad, William G. Sullivan, Curran Associates, Inc., 2009, 573-580 p.Conference paper, (Refereed)
Abstract [en]

Managing inventories so that overall costs are kept low, while service levels are maintained is the central issue of inventory control, which only regulates two things: the size and the timing of orders. This is typically executed through a planning method, such as the reorder point system or, less frequently, the periodic order quantity system. These take into account a forecast, supposed to gauge the average future demand, and a predetermined safety stock, buffering against forecast errors and demand uncertainty. Pure demand also influences the system, as transactions affect the inventory level. It is crucial to understand how a complete system of demand, forecasts, safety stock calculations and planning methods work together to measure service level and overall cost of the system. This paper outlines a framework for the unambiguous representation of the relations between methods that interpret environmental parameters to plan orders. A number of simulations based on the framework are run to show, how the integration of the inventory control functions may affect the overall performance of the system. The usefullness of the framework lies in its ability to make a system duplicable (i.e. to transfer an inventory control system to a simulation model, or vice versa). Not only is this property important for creating simulation models that exactly depict the system being analysed, it also enables the study of a complete system for order planning, as opposed to optimising individual methods. Studying an inclusive system allow the same metrics to be used to evaluate changes to any method in the system. Another benefit of this approach is that the system's metrics directly reflect changes in the environment. Simulations based on this framework are precise and substantially easier to evaluate than models not adhering to any standard.

Place, publisher, year, edition, pages
Curran Associates, Inc., 2009. 573-580 p.
National Category
Engineering and Technology
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-3432ISBN: 978-0-9562303-3-1 (print)ISBN: 978-1-61567-627-9 (print)OAI: oai:DiVA.org:his-3432DiVA: diva2:272973
Conference
19th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2009, July 6th - July 8th, 2009, Teesside University, Middlesbrough, UK
Available from: 2009-10-19 Created: 2009-10-15 Last updated: 2017-04-27Bibliographically approved

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