<![CDATA[PT Insera Sena is a bicycles manufacturing company. The Insera produces various types of bicycle, e.g., urban, mountain, road, shop, junior and any others. Each type of bicycles has each own specification and needs specific type of spare-parts. These numerous types of spare-parts raise a problem in inventory, so called, dead-stock. To solve this problem, we need to find the common part, i.e., a part that can be used for several bicycles specifications. The common part is defined based on the requirement and frequency of each part. In this study, requirement is defined as the rate of a part being used in bicycles production within 15 months. While, frequency is defined as the number of bicycles’ variations that uses one type of part. Hereafter, we use K-Medoid clustering based on those two measurements to class the common parts. The type of parts that we cluster, particularly are the bottom bracket, chain wheel, front derailleur, rear derailleur, shifters and sprocket. As the result, the proposed method can reduce 162 parts (34%).]]>
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