Multi‐attribute classification method for spare parts inventory management

Abstract

Inventory constraints, costs of lost production, safety and environmental objectives, strategies of maintenance adopted, logistics aspects of spare parts are some of the criteria taken into account, and spare parts classification is thus defined with respect to multiple attributes. In virtue of the large number of the potential operational characteristics to be considered, the decision diagram is integrated with a set of analytic hierarchy process models used to solve the various multi‐attribute decision sub‐problems at the different levels/nodes of the decision tree. An inventory policy matrix is defined to link the different classes of spare parts with the possible inventory management policies so as to identify the “best” control strategy for the spare stocks. The principles of the theory and an actual application in a company operating in the paper industry are reported in the paper.

Spare parts criticality analysis using a fuzzy AHP approach

“…Thus, the eigenvector (with triangular values) is as follows: (1, 1, 3) (1/5, 1/3, 1) (1/6, 1/4, 1/2) (1/5, 1/3, 1) (1, 3, 5) (5, 7, 9) AT 2 (1, 3, 5) (1, 1, 3) (1/5, 1/3, 1) (1/6, 1/4, 1/2) (1, 3, 5) (7, 9, 9) AT 3 (2, 4, 6) (1, 3, 5) (1, 1, 3) (1/7, 1/5, 1/3) (1/7, 1/5, 1/3) (1, 3, 5) AT 4 (1, 3, 5) (2, 4, 6) (3, 5, 7) (1, 1, 3) (1/5, 1/3, 1) (3, 5, 7) AT 5 (1/5, 1/3, 1) (1/5, 1/3, 1) (3, 5, 7) (1, 3, 5) (1, 1, 3) (3, 5, 7) AT 6 (1/9, 1/7, 1/5) (1/9, 1/9, 1/7) (1/5, 1/3, 1) (1/7, 1/5, 1/3) (1/7, 1/5, 1/3) (1, 1, 3)…”

“…This six attributes are represented here by the six following symbols: AT 1 , AT 2 , AT 3 , AT 4 , AT 5 and AT 6 respectively. Once the decision makers performed the pair wise comparisons for the set of attributes A matrix is obtained (Tab.…”

“…; Vital, Essential or Desiderable. Braglia et al [5] proposed a spare parts classification scheme which uses a set of multiple attributes. In virtue of the large number of the potential operational characteristics to be considered, they established a decision diagram integrated with the analytic hierarchy process.…”

Managing the After Sales Logistic Network— A Simulation Study of a Spare Parts Supply Chain

“…Braglia et al [9], instead, develop a multi attribute spare tree analysis. The classification of a spare part according to one criterion (e.g.…”

“…Eaves and Kingsman [7] identify 5 groups in reason of their demand pattern: smooth, irregular, slow moving, mildly intermittent, highly intermittent. Gajpal et al [8] and Braglia et al [9] use the AHP methodology for spare parts classification. Gajpal et al [8] aim at assessing the spare part criticality, through a weighted measure of stock out implication, type of spare required (level of standardization) and of the lead time.…”