# Suggestion of Model Change Work Improvement by REBA and Therblig

• Lee, Sung-Koon (Department of Industrial Engineering, Ajou University) ;
• Park, Peom (Department of Industrial Engineering, Ajou University)
• Accepted : 2011.10.05
• Published : 2011.12.31

#### Abstract

Objective: The aim of this study was to provide a method to improve the compliance and reduce the time by reducing the workload during the model change work. Background: The enterprises are constructing the small quantity batch production system by increasing the number of model change and reducing model-changing. However, the compliance is low because the work is strenuous and high skills are needed, so the system management is facing with many difficulties. Method: After classifying the model change work according to the purposes(preparation, change and adjustment) with the target of mascara filling machine, element tasks time were measured and the motion analysis(therblig symbol) and REBA analysis were performed. The study incorporated 3 independent variables as the number of motion, REBA score and the element time. The dependent variable is the type of element work as preparation, change and adjustment. The statistical test was performed by one-way ANOVA(${\alpha}$ < 0.05). Results: For the preparation, the number of motions appeared in the order of Use(U), Transport Loaded(TL), and Position(P). The order appeared in change is Use(U), Release Load(RL), and Grasp (G). The adjustment appeared in the order of Position(P) and Use(U). The results of average motion time as the element work times divided by the number of motion appeared in the order of adjustment(1.85sec/motion), preparation(1.11sec/motion), and change(0.62sec/motion). The results of REBA showed that the average risk level of change and adjustment were medium, but 53.1% of change and 42.9% of adjustment were evaluated as high. Conclusion: Reducing the avoidance and improving the compliance of work could be expected if the job autonomy were improved by improving the working postures with high risk level. Application: It is expected to solve the problem of reducing the time of model change work in the small quantity batch production system. The future work is to carry out the improvement directions found in the results and compare the results after improvement.

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