Designing Simulation to Improve Production Efficiency of Batik Industry

Background The study deals with evaluating the production system for manufacturing batik, then developing a scenario for improving the system. Purpose The study aims to point out the possibilities of computerized simulations in designing , testing, and exploring scenario models of real production plants of Small-Medium enterprises (SMEs). Method The research is carried out as a case study , using a simulation approach to achieve the objectives. This study uses three data collection techniques: direct observation, qualitative interviews, and time study. The simulated model of the system is the basis for building improvement strategies. Results The simulation model yields more than 70% of the overall process time mainly consisting of idle time and waiting for the operator. It leads to an inefficient production system. Significant differences in processing time and assigning operators to workstations that are unbalanced cause inefficiency. Although most of the time was not efficient, the average utilization of the operator was 63.96%. The system has a good operator’s utility level because the average total utility value is higher than idle time. The operators are also responsible for other tasks that were included in the simulation . Discussion The study proves that simulation is a very promising approach that allows industrial owners to mimic the production process and resource assignments within the model. The production efficiency with existing resources can be enhanced with the balancing procedure between the workstations and the operators. The suggested system runs on the concept of assigning operators with lower utility to processes with high WIP queues. The operator can interact with multiple workstations. The proposed model reduces the total time required to produce the batik. Contribution The simulation helps the analyzed organization to evaluate the efficiency of the manufacturing process. Changing the parameters in the model can generate new utilization and efficiency for the system.