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Value engineering is an appropriate policy for creating and improving value, which reduces unnecessary costs and maintains core functionality. Despite the mentioned benefits, this approach has so far received little attention in the area of supply chain management. Although this approach is highly structured, limitations such as overemphasizing the cost criterion and failure to meet other criteria, utilizing team members’ votes to rank solutions, ignoring inherent uncertainty and ultimately disagreement between value engineering team members have reduced the effectiveness of this approach. The present study aims to provide a coherent framework for utilizing a value engineering approach to supply chain cost management and overcome the aforementioned limitations by utilizing gray multi-criteria decision-making. In this regard, in the first phase, the initial list of improvement solutions is determined, the criteria extracted from the literature are localized using value engineering team members’ opinion. These criteria are weighted using the gray stepwise weight assessment ratio analysis (SWARA-Gray) method. Then, the score of each solution is calculated by the value engineering team based on the list of criteria as a gray number. The scores are aggregated using the gray evaluation based on distance from average solution (EDAS-Gray) method, and the solutions are prioritized. Finally, the application of the proposed framework is investigated in a real case study in a power plant in Iran. The results of the research show that the final rankings of the solutions rarely changed for different methods; so the model used in this study has acceptable stability.
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