A hybrid maintenance management model in decision support system for small and medium food processing industries - Tahir, Zulkifli (2010)
Small and medium industries have become an important aspect in economic growth for developing countries. Although smaller in size compared to larger industries, these industries have played an important role in improving the country’s economy. It is observed through empirical studies that the effectiveness of industrial process have been increased by a well organized of machines maintenance structure. Some maintenance techniques and optimization models are studied so that they are applicable as the decision support model to increase the machines effectiveness. The experimental maintenance data are collected from one of the food processing industry in Malaysia for the whole period 2004-2008. The data are stored and subsequently transformed into useful knowledge for decision making. The research examines the relationship of the multiple important maintenance criteria, breakdown frequencies and downtime of the individual machines. Pareto analysis is used to rank the top 10 problematic machines in the production line. Then, the right decision making model is applied to identify appropriate maintenance strategies to aid decision making for maintenance managers. The evaluation and development of hybrid decision making models with Decision Making Grid, Fuzzy Logic and Analytic Hierarchy Process are done. Finally, the application of maintenance Decision Support System is developed. The system can be used by decision makers to evaluate and benchmark the maintenance operations and to reveal important maintenance strategies such as Condition Based Maintenance, Service Level Upgrade, Design-out Maintenance, Operate to Failure, Fix Time Maintenance etc. This maintenance Decision Support System is suitable to be applied for small and medium food processing industries in Malaysia.