Productivity improvement for smart manufacturing systems
Date of Issue2017-03-28
School of Mechanical and Aerospace Engineering
Operations research is one of the ground breaking areas in manufacturing as it solves the problems by improved decision-making techniques such as mathematical optimization, queuing theory, simulation and much more. The production systems, viz. push and pull systems was introduced to assist the manufacturing for the demand to be satisfied and to maintain the necessary inventory. In earlier days the production systems were used for job shops and flow shops. So the pull production system applications like Kanban, CONWIP played a major role in productivity improvement. As the growth in product design, manufacturing became very intricate; it resulted in low volume and high mix type of products to maintain the market leaders for manufacturing industries. On considering the improvements in manufacturing a product, this project aims to focus on developing a fundamental study that compares the infinite buffer and finite buffer settings for a production line and an assembly line. In an assembly line, queue ratio concept is introduced, that states, the parts from the upstream station is sent to two or more downstream stations for processing based on smallest queue ratio between two downstream stations. Apart from this fundamental study, a case study of a semiconductor fab is investigated, and the performance of queue ratio is analyzed with current fab system performances. The queue ratio concept shows a significant improvement in the fab throughput, and thus the objective of production system under stochastic conditions has been achieved.