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Logistical assistant systems for effective supply chain planning

 
: Toth, Michael; Wagenitz, Axel

Australian Society For Operations Research -ASOR-:
Making the future better by operations research : 20th International Conference of Australian Society for Operations Research incorporating the 5th International Intelligent Logistics System Conference; Holiday Inn Surfers Paradise Gold Coast, Australia, September 27th - 30th, 2009
Brisbane: Queensland University of Technology Printery, 2009
ISBN: 978-0-646-52115-2
pp.126
Australian Society for Operations Research (National Conference) <20, 2009, Gold Coast>
International Intelligent Logistics System Conference <5, 2009, Gold Coast>
English
Conference Paper
Fraunhofer IML ()
supply chain management; DSS & expert systems; simulation

Abstract
Considering new challenges in global markets, companies are forced to plan their supply chains relating to more flexibility, effectiveness and cost reduction. Today, Advanced Planning Systems (APS) are applied to manage availability of supply goods (available/capable-to-promise ATP/CTP) and to smooth inventory levels due to fluctuating demands and insecure market forecasts. High-value-added branches, like the automotive industry, are characterized by complex, often sales-based product configurations resulting in millions of possible technical BOMs. Furthermore a high percentage of value creation is done by global supply networks with high order lead times, dynamic and risky transport relations and high transfer stocks. Today, the necessity of global ATP taking dynamic supply network behavior and collaborative partnerships into account is not covered by given APS-Software. This paper will introduce Logistical Assistant Systems (LAS) as a new generation of SCM-Software, which allow dynamic and collaborative supply chain planning by providing APS-like-functionalities with a simulation based approach. The developed simulation component is able to handle the complexity of high-value-added branches with efficient algorithms, to forecast the supply chain behaviour (future stock range monitoring, dynamic ATP and resulting costs) taking different scenarios into account. It has been demonstrated to produce convincing results e.g. in projects with Volkswagen AG.

: http://publica.fraunhofer.de/documents/N-226375.html