"Improve" and "Control" tools in assembly of micro components: A case study

Abstract

The process of assembling micro components requires careful planning where precise and reliable data collecting is necessary due to a short production cycle time. After determining the shortages of the current data monitoring system, in this paper, by using the "Improve" and "Control" phases of DMAIC cycle, the development and later testing of a new tool for automatic capture and analysis of data obtained from the machine was done. SWOT analysis was used to establish the production site's and current manufacturing execution system strengths and weaknesses, opportunities and threats, which were then utilized to create the newly developed solution accurate and feasible. A tool calibration data was obtained on 9 machines in automotive company's micro component assembly unit. To confirm the accuracy of the data, a RunAtRate test was done on the machines, and by using hypothesis testing, the initial reliability of the new solution was determined. Further testing and comparison revealed that the newly proposed tool recorded 73-80% greater downtime and 40-50% more defective parts than the previously installed system. Accordingly, the usefulness of the proposed Lean Six SIGMA tool is confirmed, and for periodic accuracy checks and further improvement, it is necessary to apply the PDCA cycle.