Assessing the Impact of Changes and their Knock-on Effects in Manufacturing Systems
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Author(s)
Plehn, Christian
Stein, Florian
Reinhart, Gunther
de Neufville, Richard L
Date Issued
January 2017
Journal
Procedia CIRP
Publisher
Elsevier
Citation
Plehn, Christian, Florian Stein, Richard de Neufville, and Gunther Reinhart. “Assessing the Impact of Changes and Their Knock-on Effects in Manufacturing Systems.” Procedia CIRP 57 (2016): 479–486. © 2016 The Authors.
Version
Final published version
Abstract
Manufacturing systems are subject to frequent changes caused by technology and product innovation, varying demand, shifted product mix, continuous improvement initiatives, or regular substitutions of outworn equipment and machines. Elements within a manufacturing system are connected by a complex network of relations such as material flow, technological dependencies, infrastructure, and intangible cause-and-effect-chains. Depending on the scale of changes they may also interfere with engineering, procurement, logistics, or even manufacturing strategy. Thus, the total impact in terms of expected costs and required time for planning and implementation of those “manufacturing changes” is hard to predict. The objective of this paper is to provide a decision support for manufacturing change management and to enable a thorough analysis of changes in manufacturing systems. Although the topic of change propagation received considerable attention in product development in order to quantify the knock-on effects of engineering changes, comparable endeavors have not yet been made in the field of manufacturing science. Following a review of prevailing approaches from product development and manufacturing literature, a model-based approach for the prediction and assessment of change propagation in manufacturing systems is presented. Applied structural modeling techniques, the derived graph algorithm, and the proposed procedure of the approach are outlined. Finally, an industrial case study is presented to demonstrate the potential but also the limitations in practice.
MIT Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Massachusetts Institute of Technology. School of Engineering
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
https://doi.org/10.1016/J.PROCIR.2016.11.083
