SOURCE:

Faculty: Engineering
Department: Industrial And Production Engineering

CONTRIBUTORS:

Umeozokwere, A.O;
Godwin, H.C;

ABSTRACT:

The challenges of intense international competition and market globalization have placed enormous pressure on maintenance system to improve efficiency and reduce operational costs such as high cost of procuring spare parts and inability to keep the vehicles till its life span. These challenges have forced maintenance managers to adopt tools, methods and concepts that could stimulate performance growth and minimize errors, and to utilize resources effectively. As a result, this study developed optimal vehicles preventive maintenance and replacement schemes for transportation industries with particular reference to Anambra State Transportation Sector (ATS).The data were collected based on vehicles types, maintenance costs, replacement costs, income generated, environmental factors, routes travelled by each vehicle measured in kilometers from 2005 2014. Thedata obtained were analyzed usingDynamic Programming recursive model to evaluate the operational costs of ATS vehicles as a recursive function and to solve forthe optimal replacement policy for replacing the company’s vehicles and was validated using Microsoft excel solver software. Selectedforecasting models were used to determine the future impact ofoperational costs on the case company vehicles. Main and cause effect tool wasdeployed to analyze the influence of environmental factors on the maintenance costs, replacement costs and income generation of ATS vehicles.Finally,Response surface method (Box-Benhken Design)was employed to optimize the operational costs of the company and to determine thedegree of significance of environmental factors on the operational costs of ATS vehicles via the rate of interactionof these factorson the response and was validated with numerical method. The application of dynamic programming techniquerevealed the vehicles optimal replacement policy of Nissan Urvan, Sienna, Peugeot Expert, J5, Ford Bus, Toyota Hiace and Taxi Cab at stage 12, 7, 8, 9, 8, 9 and 9 respectively.Non-adherence to the replacement policy model would make the company incur the loss of ₦21,894,500, ₦8,750,845, ₦ 8,616,176, ₦20,730,300, ₦23,295,750, ₦36,565,900, ₦18,438,288 for the said vehicles respectively. However, adherence to the policy year replace action would yield to the company the desired profit of ₦18,613,400, ₦7,264,015,₦5,862,286, ₦16,329,730,₦18,190,395,₦33,837,700 and ₦15,482,395 for the vehicles reviewed. Theforecasting results showed that the operational costs (maintenance and replacement) pattern increase as the age of the vehicles increase while the income generated decreases as the age of the vehicles increases. Besides, the results of main cause and effect model applied indicated that at the minimum environmental effect, the company would spend less on the maintenance of its vehicles, thereby making more profit and vice versa while that of response surface method applied specified the rate of interaction and level of significance of the control factors on the operational costs of ATS vehicles and the optimized values were ₦1, 916, 640, ₦1,971,390,₦10,040,000while the validation results showed the values of ₦2, 144, 240, ₦2,103,000,₦9,759,880for maintenance costs, replacement costs and income generated respectively which indicated that the outcome of the validation was an adequate approximation of the result obtained from the optimization plots.It is therefore, recommended that the company should employ dynamic recursive programming model for replacement analysis of its vehicles when they have reached their decline stage. The model would also help to develop standards and more accurate results with fewer errors in the estimation of future plans thereby enhancing the profitability and efficient utilization of the vehicles of the case study company.