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Toward automated qualitative supply chain diagnoses

Abstract : Supply Chain (SC) stakeholders must manage continuous improvement projects in order to remain competitive in a sustainable way. These projects are necessarily based on a diagnosis phase to assess the current status of the SC and to identify rooms for improvements. A number of methods exist to support such a process, including: Lean Manufacturing, SCOR model, or Theory of Constraints (TOC). However, most of these methods are quantitative and do not apply the change management process. Therefore, their impacts are not guaranteed since there is also a need for additional qualitative diagnoses. With this objective, through the TOC, two tools of Thinking Processes and Web of Conflicts are developed. Unfortunately, these tools are manual, subjective, and time consuming, and consequently remain either less applied or their results are kept confidential. The aim of this research work is to first demonstrate the expected benefits of those methods for SC status diagnoses and then to define the functional requirements for a qualitative SC diagnosis decision support system. An illustrative case is described to support our proposed approach and a set of research perspectives is finally discussed.
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Contributor : IMT Mines Albi IMT Mines Albi Connect in order to contact the contributor
Submitted on : Tuesday, October 2, 2018 - 3:10:30 PM
Last modification on : Friday, August 5, 2022 - 11:42:07 AM


  • HAL Id : hal-01886041, version 1



Anthony Fouque, Matthieu Lauras, Hamideh Afsarmanesh, Frederick Benaben. Toward automated qualitative supply chain diagnoses. ILS 2018 - 7th International Conference on Information Systems, Logistics and Supply Chain, Jun 2018, Lyon, France. p.296-306. ⟨hal-01886041⟩



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