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A Framework for Identification of Complexity Drivers in Manufacturing Companies

Abstract : The initial issue of complexity management in companies is the identification of the drivers of complexity. However, current literature lacks methods for assisting practitioners in the initial identification of such drivers. This paper, therefore, presents a novel framework for assisting practitioners with identifying complexity drivers in manufacturing companies. The framework uses a generic value chain and a generic product structure as its two dimensions. Multiple workshops are then conducted with company representatives across different value chain fields focusing on two main parts: First, surveys are used to assign complexity ratings to different generic product structure elements. Secondly, the complexity ratings are elaborated on by workshop participants. The process provides valuable insights into the perceived complexity drivers. The framework is then verified through a case study in the process industry. Based on the case study, multiple complexity drivers were identified across both value chain fields and product structure elements. The case study findings show that the framework facilitates practitioners in identifying organization-wide perceived complexity drivers. The framework contributes to both industry and research by addressing a neglected aspect of complexity management. It achieves this by providing a comprehensive and structured approach for the initial identification of complexity drivers across product elements and value chain fields.
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Submitted on : Thursday, December 19, 2019 - 1:17:55 PM
Last modification on : Thursday, December 19, 2019 - 1:45:44 PM
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Rasmus Andersen, Thomas Brunoe, Kjeld Nielsen. A Framework for Identification of Complexity Drivers in Manufacturing Companies. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2019, Austin, TX, United States. pp.392-399, ⟨10.1007/978-3-030-30000-5_49⟩. ⟨hal-02419267⟩

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