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Dynamic simulation modelling for lean logistics

Disney, Stephen Michael ORCID:, Naim, Mohamed Mohamed ORCID: and Towill, Denis Royston 1997. Dynamic simulation modelling for lean logistics. International Journal of Physical Distribution & Logistics Management 27 (3/4) , pp. 174-196. 10.1108/09600039710170566

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The Law of Industrial Dynamics ensures that if a production control system can amplify then it will surely find a way of doing so despite the best efforts of production schedulers to take corrective action. In fact, practical studies show that such human intervention frequently aggravates the situation with both stock levels and order rates fluctuating alarmingly. The solution is to design an effective system via simulation. This requires the selection of the appropriate control system structure, agreement on the test cases to be used to mimic the operating environment, and finally setting the system parameters to achieve best performance for this scenario. Demonstrates a system which has three controllers utilizing sales, inventory and work in progress (WIP) data to set production order rates. The resulting decision support system (DSS) is a generic tool that can be used by production schedulers with confidence in the knowledge that the Law of Industrial Dynamics effects may be minimized. Simulation experiments can determine the best available trade-off in any particular situation such as achieving the lean logistics aim of minimum reasonable inventory (MRI) while retaining high customer service levels (CSL). The experimental facility available within the simulation model includes provision for assessing the impact of variable production lead times and information delays on system performance. Describes a specific application of the DSS and the specific improvements in a company’s performance. Places the DSS in the context of a case-based reasoning environment in which a knowledge base of system structures and their dynamic properties is achieved. Outlines the opportunity of utilizing the DSS in uncertain lead-time environments in a range of industry sectors.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HD Industries. Land use. Labor
H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Uncontrolled Keywords: Algorithms; Inventory control; Optimization; Simulation
Publisher: Emerald
ISSN: 0960-0035
Last Modified: 21 Oct 2022 09:54

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