Design and implementation of a method for determining the optimum maintenance policy in manufacturing sector

Maintenance planning is of crucial importance with regard to productivity of manufacturing systems. Effective maintenance planning ensures high productivity of manufacturing system. Increasing the efficiency of the manufacturing system will bring with it a high manufacturing amount. However, failure of a machine, especially in continuous-process type manufacturing systems, can adversely affect the operation of the entire system. The application of optimal maintenance policy is of crucial importance in these types of manufacturing systems. In this study, fuzzy expert system based opportunistic maintenance policy has been developed. Performance of this novel maintenance policy has been investigated for continous-process type manufacturing system in terms of output amount. In the scope of the study, the manufacturing process of a cement plant was examined and data were used. Simulation approach was used for modeling the manufacturing system. Taguchi method was used for design of experiment. At the end of the study, simulation results were evaluated by using variance of analysis and preventive maintenance and opportunistic maintenance policy were compared according to results. When the results are examined, it is seen that 25% control ratio opportunistic maintenance policy , β=4 for weibull distribution parameter, low system length, high buffer capacity, the small proportion of maintenance costs to preventive maintenance costs enable high output amount in continous-process type manufacturing systems. These results show that the 25% control ratio opportunistic maintenance policy provides better performance in terms of total output compared to preventive maintenance in continuous-process type manufacturing systems.