Proactive demand and capacity management for automotive logistics using an efficient information model
Author(s) -
Gül Tekin Temur,
Daniel Fruhner,
Katja Klingebiel
Publication year - 2019
Language(s) - English
Resource type - Conference proceedings
DOI - 10.46354/i3m.2019.emss.020
Subject(s) - automotive industry , adaptation (eye) , capacity management , computer science , modular design , process (computing) , information management , process management , demand management , on demand , knowledge management , business , engineering , aerospace engineering , macroeconomics , optics , physics , multimedia , computer network , economics , operating system
The increasing technical complexity of cars and the high number of offered options lead to new challenges in the automotive industry and especially the mid-term demand and capacity management (DCM). This requires a procedural adaptation based upon an efficient information model. In this contribution, the state of the art is analysed for both the DCM process and the underlying information models. Promising concepts for managing the steadily increasing requirements in DCM are deducted, and a modular process kit for the procedural adaptation combined into the concept SmartDCM is introduced. Additionally, a new approach of an efficient information model for managing the increasingly complex information is presented.
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