Optimization Of High-Mix Low-Volume Manufacturing System Using Discrete Event Simulation

• Main Author: Kamarudin, Khairunnisa
• Format: Monograph
• Language: English
• Published: Universiti Sains Malaysia 2017
• Subjects: T Technology; TJ Mechanical engineering and machinery
• Online Access: http://eprints.usm.my/53732/1/Optimization%20Of%20High-Mix%20Low-Volume%20Manufacturing%20System%20Using%20Discrete%20Event%20Simulation_Khairunnisa%20Kamarudin_M4_2017.pdf; http://eprints.usm.my/53732/
• Institution: Universiti Sains Malaysia

The purpose of this project is to evaluate how Discrete-Event Simulation (DES) can be used as a decision support for production planning which is tested at a High-Mix Low-Volume (HMLV) manufacturing company, Coraza Systems Malaysia. The focus of this project is to improve the optimization in manufacturing system without reducing the productivity of the production system or making facility investments. The scope is focusing on the HMLV manufacturing system of four machines at the CNC machining shop. This study analyzes the current scheduling problem and generates possible solutions to improve the current manufacturing flow. Time study has been carried out to identify the actual production system performance. Current state modeling is created using probability distribution obtained from the historical data of daily production records. The current model is then verified and validated by conducting paired t-test to ensure the accuracy of the system built. To evaluate potential changes in the production system, a DES model is built and different scenarios are tested. The strategies are to change the current Earliest Due Date (EDD) dispatching rules to other type of dispatching rules. Comparison of performance measure is performed to assess which dispatching rule is the best with most improvements. It is found that changing the dispatching rule to Shortest Setup Time (SST) brings the most improvement in increasing the overall machines utilization and number of finished parts produced. The conclusion from this thesis is that it is possible to use DES as a decision tool as it is better for long term strategic decisions.