Intelligent Optimal Replacement Model For Hostel Facilities Maintenance

Abstract

This paper is part of an on-going research on the development of intelligent optimal replacement model for Hostel facility maintenance in Malaysia where the case study is conducted at Kolej Universiti Islam Melaka (KUIM). The model is developed to analyze the total cost and downtime for various values of the uncertain parameter by using Artificial Intelligence (AI) method, namely, Ant Colony Optimization (ACO), noting the effect of this variation on the optimal solution. The decision areas addressed is based on the replacement action. The study is aimed to assist maintenance engineers in deciding an appropriate replacement policy. This is usually useful to plot the total cost and downtime per unit time curve. The advantage of the curve is that, along with giving the optimal value, it shows the total cost and downtime around the optimum. If the curve is fairly flat around the optimum, it is not really very important that the maintenance engineers should plan for the replacements exactly at the optimum. However, if the curve rapidly decreased, then the maintenance decision should be made to find the optimal solutions. The result shows that the weeks to decide a replacement is during the semester break, which is suitable because students are not in the hostel.