Operating environment-based spare parts forecasting and logistics: a case study

Operating environment-based spare parts forecasting and logistics: a case study

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Article ID: iaor2006477
Country: United Kingdom
Volume: 8
Issue: 2
Start Page Number: 95
End Page Number: 105
Publication Date: Jun 2005
Journal: International Journal of Logistics
Authors: ,
Keywords: inventory
Abstract:

In today's highly dynamic and constantly changing industrial environment, issues relating to product support are becoming increasingly important. However, the extent of attention given to these issues varies considerably depending on the perspective of the interested person or profession. These are likely to vary from design engineers at the conceptual stages of product development to manufacturers and users in the latter stages. Additionally, the make up a particular product support package varies according to type of system/mission, application and stages of machine/system life. The lack of timely or incomplete support is likely to cause unexpected downtimes, which in turn will lead to losses for which one is unable to compensate. Falling within the definition of product support items are spare parts. The lack of a critical spare part can cause untimely stoppage of machine/system. Forecasting of product support and spare parts requirements based on reliability and maintainability (R&M) characteristics of system/components together with system operating environment(s) is one of the most effective strategies for prevention of unplanned stoppages. In this paper the effects of environmental factors on hydraulic brake pump used in mine loaders are presented and analysed. The reliability of this non-repairable part and its operational impact are assessed for both when the environmental factors are considered and when they are ignored. From the study, it is found that the forecasting for brake pump inventory is more accurate when environmental factors are included in the calculations. These results demonstrate the value of the inclusion of environmental factors data in the product support logistics' optimisation process.

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