Material Flow Analysis And Improvement Of A Manufacturing System Under Stochastic Product Demand

Due to increasing competition in the manufacturing sector of haberdashery and handicraft accessories, there is a great need for companies involved in this sector to invest relentlessly in expansion and improvement to meet up the dynamic and growing demand of the customer. Therefore, the worldwide leading manufacturer and supplier in this sector is thereby forced to analyze its material flow system, factory production layout, and production line. Aimed at improving the quality of their production and efficiency in meeting stochastic demand. The concept of improving material flow is majorly accepted as one of the core challenges facing the manufacturing ·sector in the future. Especially when it has to involve factory expansion and optimization, which. is a fundamental goal for the manufacturing industry. This study is conducted in collaboration with Prym Consumer (M) Sdn. Bhd. The objectives of this project are; To analyze different options of improved layout for the factory expansion then select the best factory layout suitable and efficient to run the manufacturing production thereby meeting stochastic demands and enhancing productivity using a systematic layout planning procedure and simulation-based approach. The proposed alternative factory layout will be developed using the Systematic Layout Procedure (SLP), then simulated and analyzed using the Tecnomatix Plant Simulation Software. By developing the various proposed option layout, the distance, total production time, and throughput of the production process are analyzed and improved in comparison with the existing layout and process. The result therefore of this project was very distinctive its outcome. Option 2 as one of the proposed alternative option layout was found to be more efficient to meet stochastic demands if implemented. Its forklift total distance travelled, total manufacturing and production time, and total throughput rate was more improved which will be able to tackle the problem of Prym Consumer (M) Sdn. Bhd in meeting stochastic demands than the existing and the other option 1 layout

An optimization approach for predictive-reactive job shop scheduling of reconfigurable manufacturing systems

The manufacturing industry is now moving forward rapidly towards reconfigurability and reliability to meet the hard-topredict global business market, especially job-shop production. However, even if there is a properly planned schedule for production, and there is also a technique for scheduling in Reconfigurable Manufacturing System (RMS) but job-shop production will always come out with errors and disruption due to complex and uncertainty happening during the production process, hence fail to fulfil the due-date requirements. This study proposes a generic control strategy for piloting the implementation of a complex scheduling challenge in an RMS. This study is aimed to formulate an optimization-based algorithm with a simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. The predictive-reactive strategy was investigated, in which Genetic Algorithm (GA) and dispatching rules were used for predictive scheduling and reactivity controls. The results showed that the proposed optimization-based algorithm had successfully reduced the throughput time of the system. In this case, the effectiveness and reliability of RMS are increased by combining the simulation with the optimization algorithm