Development of a simulation-based decision support model for high precision component manufacturer

In this age of global competition, the key to the success and even survival of many manufacturing firms is the ability to respond quickly to the needs of the customers. In the real world, performance measurements are difficult to determine because of the complexity of the manufacturing systems. Simulation has become an indispensable tool which enables engineers, designers, planners and managers, to study, analyze and evaluate complex situations that would not be otherwise possible. In this study the case company operates in a job shop environment characterized by fixed machine configurations but process routes that are different for each job. There are more than 800 different orders with different specifications (process routes, cycle times and lot sizes) that need to be completed for each month. In such configurations, a job may undergo operations only in certain orders of machines and not necessarily at every machine. The complexity is further compounded by the indefinite batch size for each product. With such complex scenario, determination of throughputs, identifications of bottlenecks, completion dates of customer orders and total cost of the customer orders constitute a real challenge to the planners and production managers in the company. Currently the planner of the case company plans the due dates of customer orders by using the manual approach and this has resulted in the inability of the company to meet the due date of all customers’ demands. In the face of the difficulties associated with analytic techniques, this research propose the development of a novel simulation-based decision support model (SDSM) to improve the performance in a job shop environment based on the economic approach. This model will account for the intrinsic characteristics and complexities of the job shop by allowing for usage of judgmental decision making and cost-estimation based on the current job shop status. The SDSM is useful to calculate the waiting cost which is too complicated if modelled by mathematical modeling or algorithms. By incorporating the Activity Based Costing (ABC) system into the simulation model, the costing for customer orders is greatly improved. The developed model shows that the company underestimated the cost of the customer orders. Incorporating ABC system into simulation model helps the company to evaluate costs of customer orders more effectively than Traditional Costing (TC) approach. Moreover, the use of simulation enables the study and investigation of the interactive effect of individual components or variables. The model will allow experimentations by changing the overtime and shift pattern in the company. Throughput of the case company was improved by 20.63% by identifying the bottleneck workstation (Wire Cut and Milling workstation). Waiting times at, utilization of, these workstation are improved by adding 4 hours overtime for all milling technicians and 2 hours overtime for all wire cut technicians with total additional cost of RM5700 per month. In addition, the SDSM is also able to determine the completion date of customer orders and the manpower requirement to achieve the demand by indentifying the bottleneck candidates in the production system. The accuracy for predicting the completion dates of customer orders was improved to 80% by using the simulation model. This because the simulation model provided better understanding about the capacity and the condition of the production flow by including the waiting times