Abstract- The concept of group technology in conjunction with clustering algorithms is used to create preventive maintenance, PM,  virtual cells of equipment/machines based on the type of failure they encounter. The failure categories are paired or grouped together in similar categories using the similarity coefficient methods. These cells, then, are used to come up with more efficient planning and scheduling of preventive maintenance operations including inventory of parts and the execution of maintenance operations. This study is based on data collected from a manufacturer of circuit boards used for electronic devices. A t-test validation technique is used to see if the proposed methodology showing significant difference to conduct preventive maintenance between the proposed methodology and a current method used by this manufacturer of executing the preventive maintenance. The results obtained shows the proposed preventive maintenance approach would save more than 3% on the cost of the materials used to conduct PM. The study shows the opportunities for the application of the new methodology to conduct preventive maintenance, especially in the emerging nations where the material used to conduct the preventive maintenance can be imported in large quantities. Also, the study shows a positive impact on the storeroom when applying the methodology of similarity coefficient concept to conduct preventive maintenance, by taking advantage of large quantities discounts.

Keywords- Group Technology; Similarity Coefficient; Preventive Maintenance; Storeroom.