A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification

Yigit F., Esnaf S.

JOURNAL OF INTELLIGENT MANUFACTURING, 2020 (SCI İndekslerine Giren Dergi) identifier identifier


ABC analysis is an efficient and easy-to-use methodology to classify inventory based on a single or multi-criteria basis that may consist of thousands of items. The first study by Dickie (Fact Manag Maint 109(7):92-94, 1951), based on a single criterion, is considered to be limited now. New studies focus on Multi-Criteria-Inventory Classification (MCIC) since such an extension of the criteria fits the realities of modern business decisions. The proposed approach in this study uses three-phased MCIC incorporating analytical hierarchy process (AHP), Fuzzy C-Means (FCM) algorithm, and a newly proposed Revised-Veto (Rveto) phase to meet the ABC classification principles and increase its applicability and flexibility. This new approach is called AHP-FCM-Rveto and proposed in this study for the first time. A numerical example taken from the literature is used to compare AHP-FCM-Rveto with other methods, and the results also show that the proposed methodology performs better. In the real-life example, the main advantage of compliance with the Pareto principle of the proposed method is shown.