(untitled) (Journal of Engineering, 2010)
The planning engineering is considered a vital part in the industrial operations series that leads to achieve the proposed production plan. Because of scientific advancement and technical development in the industrial field, the managements of the companies and job shops start to automate the engineering and management activities for the aim of quickness and accuracy in making proper decisions for the production process in order to get final product in a better quality and minimum cost. This is achieved by the future estimation of production plan. The research concern with evaluating the size of work arrival to the manufacturing shops and determining the amount of capacity that is required to perform these evaluated job volume in a manner that warrant decreasing the cost of orders and machines waiting. To achieve this aim, a constructation of simulation system by using Visual Basic computer program that helps the user in future estimation of job volume and determination of the best process capacity of the job shop which through it the job can be accomplished. Actual and realistic data that are collected from the documents of Electrical Industrial Company (EICO) factories is in random orders arriving to factories in one man-day and also the actual time to perform number of these orders. Through the designed software which is used as a tool for simulating of the target production system in this research, the best simulation daily process capacity was obtained for the job shop to be 130 hr per day where as, it achieved the minimum value of the total cost. There is a great effect for this increment of job shop daily process capacity in decrement of waiting of orders and this lead to optimal exploitation for these presented capacities. To verify simulation results and obtain the optimum selection for these results, the researcher used a modern technique called R-Technique or Response Surface Methodology (RSM), which the desirability function which is used as a dual-purpose standard to obtain the optimum value of job shop process capacity.