Spare parts storage improvement with association rules

Abstract

This paper presents an application of association rule, one of the most widely used data mining algorithms, to improve spare parts storage in motorcycle repair shop. As there are approximately 290 parts to be stored, there are difficulties in storing and retrieving parts in the storage room. Spare parts are stored in the room based on part code which is a number indicating type of part, product type and materials type. Storing spare parts by this part code has some potential problems, for instance it does not provide information regarding parts that are frequently used together which might results in parts often requested together to be stored separately. This research applies association rules, to improve shelf allocation in spare parts storage room. After improvement, the time used to search for spare part was founded to be reduced significantly.