Asia-Pacific Journal of Business Venturing and Entrepreneurship (벤처창업연구)

The Korean Society of Business Venturing (한국벤처창업학회)
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ALC(Autoclaved Lightweight Concrete) Hardness Prediction by Multiple Regression Analysis

다중회귀분석을 이용한 ALC 경도예측에 관한 연구

  • Kim, Kwang-Soo (Dept. of Industrial Management & Engineering, Korea National University of Transportation) ;
  • Baek, Seung-Hoon (Quality Management Team, Sung Eun Ltd.) ;
  • Chung, Soon-Suk (Dept. of Industrial Management & Engineering, Korea National University of Transportation)
  • 김광수 (한국교통대학교 산업경영공학과) ;
  • 백승훈 ((주)성은 품질경영실) ;
  • 정순석 (한국교통대학교 산업경영공학과)
  • Received : 2012.05.14
  • Accepted : 2012.06.11
  • Published : 2012.06.30
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Abstract

In the ALC(Autoclaved lightweight concrete) manufacturing process, if the pre-cured semi-cake is removed after proper time is passed, it will be hard to retain the moisture and be easily cracked. Therefore, in this research, we took the research by multiple regression analysis to find relationship between variables for the prediction the hardness that is the control standard of the removal time. We study the relationship between Independent variables such as the V/T(Vibration Time), V/T movement, expansion height, curing time, placing temperature, Rising and C/S ratio and the Dependent variables, the hardness by multiple regression analysis. In this study, first, we calculated regression equation by the regression analysis, then we tried phased regression analysis, best subset regression analysis and residual analysis. At last, we could verify curing time, placing temperature, Rising and C/S ratio influence to the hardness by the estimated regression equation.

ALC(Autoclaved lightweight concrete) 제조공정 중에서 예비양생이 완료된 반 경화제품(cake)인 상태에서 탈형을 실시할 때 적절한 탈형 시기가 지난 후에 탈형을 하게 되면 보습력이 떨어지고 절단 시 피아노선이 절단되어 제품에 균열이 발생할 우려가 있다. 이에 본 연구에서는 탈형 시기의 관리기준이 되는 경도(hardness)에 관한 예측을 하기 위해 관련된 변수들 간에 상호관련성을 찾고자 다중회귀분석(multiple regression analysis)을 이용한 연구를 진행하였다. ALC 제조공정의 V/T(Vibration Time)대기, V/T동작, 발포 높이, 경화시간, 타설 온도, Rising, C/S비의 독립변수(Independent variables)들이 종속변수(Dependent variables)인 경도(hardness)에 어떠한 관련성이 있는지를 다중 회귀분석을 이용한 연구를 진행하였다.

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