A fuzzy decision support model for selecting and prioritising improvement initiatives in the context of operational excellence: Application to a mining company

In today's industrial environment, companies are constantly seeking to improve their operational performance and strengthen their competitiveness. However, selecting and prioritising improvement initiatives remains a complex task for decision-makers. Indeed, the diversity of criteria to be taken into account, combined with the multiplicity of actors involved and the subjectivity of their judgements, makes the process particularly delicate. Thus, this process falls squarely within the category of multi-criteria decision-making (MCDM) problems. This article proposes a decision support model based on fuzzy logic, designed to help companies select and prioritise their improvement initiatives. The model evaluates each initiative using an overall relevance score calculated on the basis of five input indicators: efficiency, feasibility, cost, implementation time and originality. The applicability of the approach is illustrated through a case study conducted within a mining company. The results obtained were compared with those from the method currently used by the company in order to assess the consistency and relevance of the proposed fuzzy model in relation to existing practices. The results confirm the relevance of using fuzzy logic for selecting and prioritising improvement initiatives. The model developed makes it possible to better manage the uncertainty and subjectivity inherent in managerial decisions. It is therefore an effective and flexible decision-making tool that can support companies in their continuous improvement and operational excellence initiatives.