spare part management
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PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247650
Author(s):  
Reza Barabadi ◽  
Mohammad Ataei ◽  
Reza Khalokakaie ◽  
Ali Nouri Qarahasanlou

Spare-part management has a significant effect on the productivity of mining equipment. The required number of spare parts can be estimated using failure and repair data collected under the name of reliability data. In the mining industry, failure and repair times are decided by the operational environment, rock properties, and the technical and functional behavior of the system. These conditions are heterogeneous and may change significantly from time to time. Such heterogeneity can change equipment’s reliability performance and, consequently, the required number of spare parts. Hence, it is necessary for effective spare-part planning to check the heterogeneity among the reliability data. After that, if needed, such heterogeneity should be modeled using an adequate statistical model. Heterogeneity can be categorized into observed and unobserved caused by risk factors. Most spare-part estimation studies ignore the effect of heterogeneity, which can lead to unrealistic estimations. In this study, we introduce the application of a frailty model for modeling the effect of observed and unobserved risk factors on the required number of spare parts for mining equipment. Studies indicate that ignoring the effect of unobservable risk factors can cause a significant bias in estimation.


2018 ◽  
Vol 24 (1) ◽  
pp. 79-100 ◽  
Author(s):  
Balasaheb Shahaji Gandhare ◽  
Milind M. Akarte ◽  
Pradip P. Patil

Purpose The purpose of this paper is to present an empirical investigation of maintenance performance (MP) management practices from the sugar industry in India. Design/methodology/approach Empirical data for this study were collected through field visits, interviews and published reports. Statistical methods including correlation, multiple regression and cluster analysis are utilized to accomplish the objective of the study. Findings Explanation with multiple regression analysis showed that the sugar industry MP is significantly and positively related to maintenance approach (MA), continuous improvement (CI), financial approach and spare part management (SPM). Cluster analysis showed that sugar industries focusing on MA, CI and policy development and organization are having higher MP. The cluster analysis also pointed out that there is a substantial variation in MP due to the type of ownership (private and cooperative) while no variation has been observed due to installed capacity (low and high). Research limitations/implications The generalization of the results obtained in this work for the sugar industry can be possible through a larger sample size. Practical implications The study contributes to the better understanding of maintenance measures in the sugar industry and provides insights on the role of maintenance managerial practices in enhancing the MP. Originality/value The findings provide empirical evidence that maintenance practices across the sugar industry are important to improve MP.


2018 ◽  
Vol 214 ◽  
pp. 04005
Author(s):  
Dongdong Guo ◽  
Xingwu Yu

Spare part management is one of the most important work for enterprises, especially for manufacturing enterprises; however, the spare part management problems trouble enterprise operators a lot. In this article, implementation methods of lean spare parts management are illuminated. Spare parts purchase process is declared to reduce the purchasing cost and inventory value. We had established a suitable lean spare parts inventory management model for consumable parts, wear parts, insurance parts and accident parts. In addition, methods of lean spare parts management had been created base on optimized supply chain, ERP and integrating repeated material inventory. We used SAP-iPro system and self-developed system to manage spare parts, so that warehouse management process, spare parts purchase process and maintenance process are standardized. According to theory analysis and practice, the remarkable economic benefit is created for enterprise by the means of optimizing spare parts distribution, standardizing and scientific spare parts management.


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