THE IDENTIFICATION AND SELECTION OF AN OPTIMISED MAINTENANCE STRATEGY FOR CONVEYOR SYSTEMS USED IN THE TRANSPORTATION OF BULK MATERIALS: A CASE STUDY

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DOI:

https://doi.org/10.7166/33-1-2591

Keywords:

maintenance strategy, FMCA, failure analysis

Abstract

In recent years an increased number of conveyor failures has been experienced in a port in South Africa, which has directly impacted revenue through unachieved handling volumes. This research aimed to use conveyor failure data to: 1) review and identify the effects of the existing maintenance approach, 2) highlight failure causes and consequences, and 3) determine the most suitable optimised maintenance strategy for conveyors that would reduce failures, thereby reducing downtime and loss of revenue.

The results indicated that the current maintenance initiatives were directly linked to conveyor the failures and to cargo being changed without a design verification of the infrastructure. The research has provided useful insights that could lead to fault-finding activities with equipment that is not achieving its design life and, in particular, conveyor belting that has been failing prematurely. Further investigations are required to verify the design of the existing infrastructure in handling the changed cargoes. In addition, the research has shown that condition-monitoring devices will aid in co-ordinating maintenance actions and responses. It also recommended that training plans be updated to ensure that staff are up-to-date with existing maintenance practices before they use the optimised maintenance approach. In summary, this research study has provided essential results and recommendations to warrant the use of an optimised maintenance strategy on conveyor systems, particularly in the port of concern.

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Published

2022-05-06

How to Cite

Naidoo, L., Jones, J., & Sharma, V. (2022). THE IDENTIFICATION AND SELECTION OF AN OPTIMISED MAINTENANCE STRATEGY FOR CONVEYOR SYSTEMS USED IN THE TRANSPORTATION OF BULK MATERIALS: A CASE STUDY. The South African Journal of Industrial Engineering, 33(1), 177–189. https://doi.org/10.7166/33-1-2591

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Section

Case Studies