An optimal joint maintenance and spare parts inventory model

Author(s):  
Parag Jafar Siddique ◽  
Huynh Trung Luong ◽  
Muhammad Shafiq
Author(s):  
Parag Jafar Siddique ◽  
Huynh Trung Luong ◽  
Muhammad Shafiq

2019 ◽  
Vol 31 (1) ◽  
pp. 69-80 ◽  
Author(s):  
Thembani Togwe ◽  
Timothy J. Eveleigh ◽  
Bereket Tanju

2013 ◽  
Vol 404 ◽  
pp. 808-814
Author(s):  
Kang Qu Zhou ◽  
Yan Xi Yu ◽  
Hui Zhen Zhao ◽  
Dai Quan Yu

As an important module of enterprise device management, spare parts inventory affects other strategies like equipment maintenance, overhauling, repairing etc. Furthermore, the normal production of enterprises and economic benefits are closely related with it. In this paper, spare parts are classified based equipment maintenance features [. After analyzing the dynamic and uncertain demand context, a probability inventory model which takes equipment downtime loss into account is presented [. A reasonable inventory costs is suggested through a lot of computing. The model and methodology have been demonstrated by a case study.


2021 ◽  
Vol 11 (2) ◽  
pp. 139-144
Author(s):  
Babatunde Omoniyi Odedairo

AbstractA key factor for motivating intending buyers of raw materials is vendor responsiveness. Therefore, to meet demand, a pre-approved level of stocks is often maintained. In contrast, the decision to keep an uncontrolled amount of stock could be counter-productive with cost components associated with holding often ignored unintentionally. In this study, the objective is to develop a spare parts inventory model that incorporates ignored holding costs with a storage constraint for a motorcycle assembly plant (MAP). The inventory policy, structure of holding costs, and spare parts sales reports were consulted for relevant data. The spare parts were categorized and selected using ABC analysis. A spare parts inventory model, which considers ignored holding cost, was formulated. The model was executed using Lingo optimisation software release 18.0.56 to determine the pair of the order quantity (Ɋ) and reorder point (Ɍ). 177 spare part items were identified using ABC analysis. The parts categorisation revealed that 21, 31, 125 part items belong to categories A, B, and C with 81, 15 and 4% of annual sales value, respectively. From category A, nine items contributed significantly to overall sales. The demand pattern for these items was probabilistic based on their coefficient of variation. The pair (Ɋ, Ɍ) for items N, Z, AY, K, AM, J, P, AL and AZ are (174,688), (71,147), (78,150), (86,163), (18,15), (88,170), (128,118), (33,43) and (87,152), respectively. These pairs yielded a total inventory cost of ₦2,177,363 when compared to the current total inventory investment of ₦6,800,000 resulting in a 67.9% cost reduction. A model to manage spare parts inventory with relevant holding cost components was developed for MAP to ensure the availability of items, maximize usage of storage space, and minimize total inventory cost.


Author(s):  
Dilay Celebi ◽  
Demet Bayraktar ◽  
Selcen Ozturkcan

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