A Study on a Working Pattern Analysis Prototype using Correlation Analysis and Linear Regression Analysis in Welding BigData Environment

용접 빅데이터 환경에서 상관분석 및 회귀분석을 이용한 작업 패턴 분석 모형에 관한 연구

  • 정세훈 (순천대학교 멀티미디어공학과) ;
  • 심춘보 (순천대학교 광양만권SW융합연구소)
  • Received : 2014.08.05
  • Accepted : 2014.10.17
  • Published : 2014.10.31


Recently, information providing service using Big Data is being expanded. Big Data processing technology is actively being academic research to an important issue in the IT industry. In this paper, we analyze a skilled pattern of welder through Big Data analysis or extraction of welding based on R programming. We are going to reduce cost on welding work including weld quality, weld operation time by providing analyzed results non-skilled welder. Welding has a problem that should be invested long time to be a skilled welder. For solving these issues, we apply connection rules algorithms and regression method to much pattern variable for welding pattern analysis of skilled welder. We analyze a pattern of skilled welder according to variable of analyzed rules by analyzing top N rules. In this paper, we confirmed the pattern structure of power consumption rate and wire consumption length through experimental results of analyzed welding pattern analysis.


Supported by : 중소기업청


  1. W. Jeong, "A Study on the Optimization of Welding Precess for Guaranteeing the Weld Quality in Tandem GMA Welding," Ph.D's Thesis, Mokpo National University, 2014.
  2. G. Kim, Y. Jeong, and J. Choi, "A study on multi-functional welder remote control system using smart phone," J. of the Korea Institute of Electronic Communication Science, vol. 9, no. 3, 2014, pp. 351-357.
  3. J. Kim, J. Choi, and Y. Jeong, "A Study on control mode of hybrid multi-function welder," J. of the Korea Institute of Electronic Communication Science, vol. 8, no. 3, 2013, pp. 439-445.
  4. E. Kim, "Fabrication of shoes for analyzing human gait pattern using strain sensors," J. of the Korea Institute of Electronic Communication Science, vol. 8, no. 9, 2013, pp. 1407-1412.
  5. Y. Ko and J. Kim, "Analysis of big data using Rhipe," J. of Korean Data and Information Science Society, vol. 24, no. 5, 2013, pp. 975-987.
  6. E. Lee, "Bigdata analysis with R : Multidimensional data handling and visualization," Master's Thesis, Ewha Womans University, 2014.
  7. J. Zhang, J. Jang, S. Kim, H. Lee, and C. Lee, "A study on the efficient patent search process using big data analysis tool R," J. of the Korea safety management & science, vol. 15, no. 4, 2013, pp. 289-294.
  8. B. Lee, J. Lim, J. Yoo, B. Lee, J. Lim, and J. Yoo, "Utilization of Social Media Analysis using Big Data," J. of Korea Contents Association, vol. 13, no. 2, 2013, pp. 211-219.
  9. S. Kim, H, Shin, and S. Son, "A Study on Large-Scale Traffic Information Modeling using R," Conf. of the KIISE Korea Computer, Jeju, Korea, vol. 2013, no. 11, Nov. 2013, pp. 1-2.
  10. M. Cho and Y. Jeon "Simulation Modeling of Profit Optimization and Output Analysis using R," J. of the Korea Institute of Electronic Communication Science, vol. 9, no. 8, 2014, pp. 883-888.