Application of quality function deployment and genetic algorithm for replacement of medical equipment

The management of medical equipment raises a range of complex problems including those associated with replacement processes. One of the most significant challenges is to identify a proper list of medical equipment that requires replacement and then to optimize this list. In this article, we present a new approach to solve this problem by integrating Quality Function Deployment (QFD) and Genetic Algorithm (GA) in one framework. In a previous application, QFD has proven its validity to solve the priority problem; meanwhile GA is an optimization method. Hence, the proposed model, QFD-GA, was developed to prioritize the medical equipment for replacement process taking into account a set of criteria; in addition, the prioritized list is optimized according to the available budget of the hospital to maximize the number of replaced devices. The validation of the proposed model was carried out on sixty devices that include different types of medical equipment in one public hospital. Results show that the proposed model can efficiently classify the priority into four subcategories, and simultaneously maximize the number of medical equipment to be replaced considering the budget constraint.