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(to be completed)

 


ThinkMind // International Journal On Advances in Software, volume 10, numbers 1 and 2, 2017 // View article soft_v10_n12_2017_12


A Motivation and Evaluation of Hierarchical Data Structures for Application in Automotive Demand and Capacity Management

Authors:
Konrad Pawlikowski
Daniel Fruhner
Katja Klingebiel
Michael Toth
Axel Wagenitz

Keywords: product structure; automotive production; demand and capacity management; optimization; complexity; BOM rules

Abstract:
The demand and capacity management (DCM) is an essential component of the automotive supply chain management. Resource requirements in the automotive supply chain result from future or already realized market demands. DCM synchronizes these requirements with capacities and restrictions of the supply chain and production system. Demand uncertainty and volatility are especially challenging for DCM. Product variety and supply chain complexity intensify this problem. Here, an efficient product data management may increase transparency and support the DCM processes effectively. This contribution analyses and evaluates the benefits of an integration of distributed product data into a hierarchical tree structure and its applications in DCM against the background of complexity reduction. Moreover, the underlying optimization algorithms are described. The results of this study prove that a hierarchical integrated information model provides a significantly improved basis for a scenario-based DCM planning process. Data from a German automotive manufacturer (OEM) has served as basis for this evaluation.

Pages: 155 to 166

Copyright: Copyright (c) to authors, 2017. Used with permission.

Publication date: June 30, 2017

Published in: journal

ISSN: 1942-2628

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