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논문 국내 국내전문학술지(KCI급) TOC와 통계적 분석에 의한 플라스틱보트 제조공정 개선에 관한 연구

  • 학술지 구분 국내전문학술지(KCI급)
  • 게재년월 2016-03
  • 저자명 김태구공동(참여),이동형,윤건구
  • 학술지명 산업경영시스템학회지
  • 발행처명 한국산업경영시스템학회
  • 발행국가 국내
  • 논문언어 외국어
  • 전체저자수 3

논문 초록 (Abstract)

The purpose of this paper is to analyze the problems and the sources of defective products and draw improvement plans in a small plastic boat manufacturing process using TOC (Theory Of Constraints) and statistical analysis. TOC is a methodology to present a scheme for optimization of production process by finding the CCR (Capacity Constraints Resource) in the organization or the all production process through the concentration improvement activity. In this paper, we found and reformed constraints and bottlenecks in plastic boat manufacturing process in the target company for less defect ratio and production cost by applying DBR (Drum, Buffer, Rope) scheduling. And we set the threshold values for the critical process variables using statistical analysis. The result can be summarized as follows. First, CCRs in inventory control, material mix, and oven setting were found and solutions were suggested by applying DBR method. Second, the logical thinking process was utilized to find core conflict factors and draw solutions. Third, to specify the solution plan, experiment data were statistically analyzed. Data were collected from the daily journal addressing the details of 96 products such as temperature, humidity, duration and temperature of heating process, rotation speed, duration time of cooling, and the temperature of removal process. Basic statistics and logistic regression analysis were conducted with the defection as the dependent variable. Finally, critical values for major processes were proposed based on the analysis. This paper has a practical importance in contribution to the quality level of the target company through theoretical approach, TOC, and statistical analysis. However, limited number of data might depreciate the significance of the analysis and therefore it will be interesting further research direction to specify the significant manufacturing conditions across different products and processes.