Discovering Identical Parts with Different PNs in a large scale spare part inventory: A Fuzzy Clustering Approach

Ali Bonyadi Naeini¹ Alireza Nowrouzi² Mehdi Zamani³

1) Assistant Professor - A Member of the Management and Business Engineering Group, Progress Engineering Department, Iran University of Science and Technology (IUST) (Corresponding Author) Tehran, IR Phone: +989121056721 Email:
2) PHD Student of Technology Management, Progress Engineering Department, Iran University of Science and Technology (IUST) Tehran, IR Phone: +989125595345 Email:
3) Graduated of Executive Master of Business Administration (EMBA), Progress Engineering Department, Iran University of Science and Technology (IUST) Tehran, IR Phone: +989377997504 Email: ORCID ID: 0000-0002-9800-4426 Researcher ID: R-6718-2017

Publication : 4th International Conference on Applied Researches in Science & Engineering - Vrije Universiteit Brussel(4carse.com)
Abstract :
When the number of component parts kept in stocks of industrial corporations or in a spare part inventory becomes too large, need for a smart inventory management system becomes more vital and that is why such systems are developing quickly. One challenge that these systems face is the existence of identical parts with different part numbers (PNs) which results in inaccurate information about the inventory status. This article introduces a novel decision support system for discovering identical parts with different PNs in the inventory. The system proposed utilizes a fuzzy clustering approach and a practical data gathering method that results in several clusters which help experts recognize the identical parts more easily. A suitable cluster validity index was used in order to check whether the number of clusters was optimum or not. The suggested expert support system is employed by Amad Behine Saz Corporation where satisfying results were obtained.
Keywords : Fuzzy Clustering Fuzzy c-means (FCM) Weighted Fuzzy c-means Inventory Management