Case-based reasoning (CBR) is an alternative approach to rule case-based and object-oriented systems. CBR is based on the retrieval and adaptation of the old solutions to the new problems. There are five steps in CBR : introduction of a new problem, retrieval of the most similar cases, adaptation of the most similar solutions, validation of the current solution and updating of the system by adding the verified solution to the database of cases. Adaptation phase is a crucial element in obtaining a good quality solutions. Up to now, there were no proposals for the automatization of the adaptation phase in the systems for the equipment selection. In the presented system the retrieval search has been organized by using flat memory and serial search. The adaptation is realized by the fuzzy calculation of the membership function built on the basis of the most similar retrieved cases. The main advantage of this system is use of high quality, verified knowledge and easiness of updating.