MODELING AND OPTIMIZATION OF THE TV ASSEMBLING LINE USING ARENA SIMULATION SOFTWARE

Arena simulation model of a manufacturing system is used to estimate and appropriately represent the status of real system. This enable companies to easily measure approximate status and performance of the existing situation without incurring cost of disrupting the manufacturing system. So it is important to develop arena simulation model of the manufacturing system. For manufacturing industry to stay in market or to compete in local/global market the main requirement/influential factors are response time, production capacity, production cost, market price and the quality of the product they produce. In case of Hi-Tech Engineering industry the main problem corresponds with the response time, production capacity and production cost. These problems motivated for conducting this research in modeling and performance evaluation of manufacturing systems to find the main causes of the problems and to propose the possible alternative solutions among which the best preferable was chosen. To conduct this research, arena simulation software play a great role in designing a model of a real system and conducting experiments with this model for the purpose of understanding the behavior of the system and evaluating various strategies and scenarios for the operating or manufacturing system. To do so, Arena simulation software are used to model and measure performance of existing manufacturing system assembly/production lines by using the input data collected from the existing real system and low performance results which is 25.18% are obtained. Based on the simulation model result of the existing system, availability of different bottle necks are identified on the line and the causes of the bottle necks investigated. Depending on the causes different scenarios are proposed, analyzed and compared to solve/improve observed problems of the existing manufacturing system like, production capacity/volume, and production cost and response time. Finally the scenario with better performance measure which has the production efficiency of 98% has been selected and taken as the optimum model for the production/assembly line.