Using Simulation Optimization to Improve the Performance of an Automated Manufacturing Line

Abstract

As manufacturing capital equipment is expensive, it is necessary that the equipment once in operation is reliable and delivers to the business plan targets. Simulation along with an optimization system is an invaluable tool to confirm that an automated manufacturing line can produce to the required business objectives before and after it goes into operation. Simulation in manufacturing is often applied in situations where conducting experiments on a real system is very difficult often because of cost or the time to carry out the experiment is too long. Optimization is the organized search for such designs and operating modes to find the best available solution from a set of feasible solutions. It determines the set of actions or elements that must be implemented to achieve an optimized manufacturing line. As a result of being able to concurrently simulate and optimize equipment processes, the understanding of how the actual production system will perform under varying conditions is achieved. Implementing the actual changes to equipment to improve reliability can be both time consuming and expensive. Simulation in conjunction with optimization can be used to verify these improvements before the equipment is modified. This study has adopted an open-source simulation tool (JaamSim) to develop a digital model of an automated tray loader manufacturing system in the Johnson & Johnson Vision Care (JJVC) manufacturing facility. This paper demonstrates how this digital model was integrated with SimWrapper optimization and how both tools can be used for the optimization and development of an automated manufacturing line in the medical devices industry.