Prof Vincent Aizebeoje Balogun and Olufemi, B. A., Temitayo, M. A.   (Published 2015)

Prof Aizebeoje Balogun
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This work aimed to develop an expert fault diagnostic system for the repair and maintenance of bulldozer work equipment faults. An Expert System, ES is one of the many quick and efficient repairs and maintenance strategy that can be used on these machines. ES is a C# computer based programming software that can be adopted to extend the life span of equipments and reduce the cost of human expert for their repairs. In this work, an expert system was developed as a tool that will detect, analyse and proffer respective solutions to the bulldozer work equipment faults. A flowchart (logic chart) was also developed. The flowchart is a logical sequence for characterising and troubleshooting the causes of bulldozer’s work equipment failure. In this report, the solutions to the detected faults: low or high hydraulic valve pressure, abnormal noise in the control valve was documented accordingly. The preferred solutions to the various faults observed were also included with snapshots from each interface of the developed program in the report. The ES developed can be adopted in the construction industries for carrying out repair and maintenance of equipment for optimum performance at a highly reduced cost. This can also be used as a teaching aid in the department of mechanical and mechatronics engineering and other fields of engineering institute. This study will enable automobile and maintenance workshops to proffer solutions to maintenance of bulldozer’s work equipment failure and at the same time avoid costly damage and optimize the economic objective.




Item Type: Journal article(non-copyrighted)
Format: PDF document,   865.08 KB
Copyright: Creative Commons LicenseCreative Commons license
Keywords: bulldozer, expert system, artificial intelligence, construction equipment, maintenance, software, work equipment failure
Department: Mechanical Engineering
Field of Study: Engineering- Mechanical
Uploaded By: Uddin Osemengbe Oyaimare
Date Added: 31 Oct 2017 11:00am
Last Modified: 22 Nov 2017
Journal URL:

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