Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
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Optimization of a Rubber based Colloidal Suspension Manufacturing Process Using Mixture Experimental Design

혼합물 실험계획법을 활용한 고무 교질 현탁액 제조 공정의 최적화

  • Yu, In Gon (Department of Information and Statistics, Chungnam National University) ;
  • Ahn, Seong Jae (Department of Information and Statistics, Chungnam National University) ;
  • Ryu, Sung Myung (Research Institute, INEM Co.,Ltd.) ;
  • Hong, Sung Hoon (Department of Industrial and Information Systems Engineering, Jeonbuk National University) ;
  • Lee, Min Koo (Department of Information and Statistics, Chungnam National University)
  • 유인곤 (충남대학교 정보통계학과) ;
  • 안성재 (충남대학교 정보통계학과) ;
  • 유성명 ((주)아이넴 부설연구소) ;
  • 홍성훈 (전북대학교 산업정보시스템공학과) ;
  • 이민구 (충남대학교 정보통계학과)
  • Received : 2024.05.03
  • Accepted : 2024.06.10
  • Published : 2024.06.30
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Abstract

Purpose: To derive the optimal conditions for the Rubber based colloidal suspension manufacturing process, which made using a stirrer, to apply the mixture design method. Methods: We used two process component and one process variable Mixture design to derive the optimal conditions for the process. The response variables were selected for rotational viscometer measures which can represent Rubber based colloidal suspension quality. The input variables were selected as the values of rubber-organic solvent expressed in proportions as process components and stirring amount as a process variable which are controllable factors in the process. Results: Based on the results of the experiment, rubber and organic solvent and the interaction between stirring amount and rubber and the interaction between stirring amount and rubber and organic solvent were significant. Reproducibility of the regression model was confirmed by the observation that the values obtained from the reproducibility experiment fell within the confidence interval. Additionally, the model predictions were found to be in close agreement with the field measurements. Conclusion: In this study, a regression model was developed to predict the viscosity change of colloidal suspensions based on the proportion of rubber based colloidal suspension. The developed regression model can lead to improved product quality.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF - 2022M3J6A1084 843).

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