A data-based investigation of vehicle maintenance cost components using ANN

2nd International Conference on Engineering for Sustainable World

Adekitan, Aderibigbe Israel^1 ; Bukola, Adetokun^2 ; Kennedy, Okokpujie^1

Department of Electrical and Information Engineering, College of Engineering, Covenant University, Ota, Nigeria^1

Department of Electrical Engineering, Pan African University of Basic Sciences, Technology and Innovation, Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya^2

关键词: ANN modeling;    Artificial neural network models;    Cost analysis;    Optimum performance;    Road transportation;    Tropical countries;    Vehicle maintenance;    Vehicle reliability;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/413/1/012009/pdf
DOI  :  10.1088/1757-899X/413/1/012009

来源: IOP

【 摘 要 】

Vehicle maintenance is a critical and vital operational component that determines vehicle performance and service longevity. The severity of vehicle usage has been defined as one of the key factors that determine vehicle maintenance requirements. Nigeria is a tropical country with intense heat, poor road network and quality. These factors severely affect car performance and raises maintenance demands toward ensuring vehicle reliability and optimum performance. In this study, vehicle maintenance cost and fuel consumption data in terms of cost and volume, together with the mileage coverage as the vehicle usage data, for two corporate organizations were analyzed. The data was collected and systematically analyzed. The common faults were categorized and their frequency of occurrence was determined. An artificial Neural Network (ANN) model was developed for predicting future maintenance cost, given a set of anticipated vehicle usage inputs. The model has an overall correlation R-value of 0.76645.