developing a new fuzzy inference model for warehouse maintenance scheduling under an agile environment

Today, the military bodies of different countries have identified the existence of a condition assessment system in order to optimize the process of maintenance and repair of military buildings and equipment as a need and are looking for a suitable answer. the issue of less and/or outright lack of knowledge and uncertainty in modeling and decision-making plays a crucial part in many engineering and especially military difficulties, resulting in designers and engineers being unable to obtain definitive solutions for the problems under discussion. this study develops a fuzzy logic application for representing the uncertainty inherent in the problem of warehouse maintenance scheduling. the relative risk score (rrs) approach, one of the most prevalent methodologies for maintenance assessment, is combined with fuzzy logic to achieve the goal. based on expert knowledge, the suggested model is run on the matlab® fuzzy logic toolbox using the mamdani algorithm. a representative case study is used, and a comparison is made between the traditional risk assessment technique and the suggested model. the findings show that the suggested model produces more accurate, exact, and certain results, allowing it to be used as an intelligent risk assessment tool in many engineering settings.