Application of Statistical Design of Experiments in the Field of Chemical Engineering: A Bibliographical Review

화학공학 분야에서 통계적 실험계획법 적용에 대한 서지 검토

  • Yoo, Kye Sang (Department of Chemical & Biomolecular Engineering, Seoul National University of Science & Technology)
  • 유계상 (서울과학기술대학교 화공생명공학과)
  • Received : 2020.03.04
  • Accepted : 2020.03.23
  • Published : 2020.04.10


Design of experiments (DOE) is a method that has been applied in the industry to improve value for many decades. This study provides an overview of 115 cases of statistical DOE applications in the field of chemical engineering. All cases were published in important scientific journals for the last ten years. The applied design type, the experiment size, the number of factors and levels affecting the response variable, and the area of application for the design were all analyzed. Obviously, the number of publications related with statistical DOE increased over time.


Supported by : 서울과학기술대학교


  1. D. C. Montgomery, Design and Analysis of Experiments, 183-572, 8th ed., Wiley, New York, USA (2012).
  2. G. E. P. Box, J. S. Hunter, and W. G. Hunter, Statistics for Experimenters: Design, Innovation, and Discovery, 173-565, 2nd ed., Wiley, New York, USA (2005).
  3. S. Bisgaard, Industrial use of statistically designed experiments: Case study references and some historical anecdotes, J. Qual. Eng., 4, 547-562 (1992).
  4. T. Pravan and D. J. Street, An annotated bibliography of application papers using certain classes of fractional factorial and related designs, J. Stat. Plann. Inference, 106, 245-269 (2002).
  5. L. Lizarbe, M. J. Alvarez, E. Viles, and M. Tanco, Practical applications of design of experiments in the field of engineering: A bibliographical review, Qual. Reliab. Eng. Int., 24, 417-428 (2008).
  6. C. F. J. Wu and M. S. Hamada, Experiments: Planning, Analysis, and Optimization, 1-10, 2nd ed., Wiley, New York, USA (2009).
  7. R. H. Myers, D. C. Montgomery, G. G. Vining, C. M. Borror, and S. M. Kowalski, Response surface methodology: A retrospective and literature survey, J. Qual. Technol., 36, 53-77 (2004).
  8. T. J. Robinson, C. M. Borror, and R. H. Myers. Robust parameter design: A review, Qual. Reliab. Eng. Int., 20, 81-101 (2003).