Design of Experiments

Part I

Introductory Basics

Part II

Screening the Important Factors/Variables

Part III

Optimize the Important Factors/Variables

Part IV

Advanced Complex Mixed Factors

Design of Experiments

Part V

Taguchi Robust Parameter Design

Files Used in the Video

  1. Data Used in the Video for Robust Parameter Taguchi Design

  2. How to Construct Taguchi Orthogonal Arrays Bose Design Generator

  3. How to Construct Taguchi Orthogonal Arrays Plackett-Burman Design Generator

  4. Taguchi Linear Graphs Possible Interactions

  5. Taguchi Interaction Table Development How to

Video Demonstrations

  1. Robust parameter Taguchi Design Terms Explained

  2. Introduction To Robust Parameter Taguchi Design of Experiments Analysis Steps Explained

  3. Robust Parameter Taguchi Design Signal to Noise Ratio Calculation in MS Excel

  4. Robust Parameter Taguchi Design Example in MS Excel

  5. Robust Parameter Taguchi Design Example in Minitab

  6. How to Construct Taguchi Orthogonal Array L8(2^7) in MS Excel

  7. How to Construct Taguchi Orthogonal Array L9(3^4) in MS Excel

  8. How to Construct Taguchi Orthogonal Array L16(4^5) in MS Excel (MS Excel file for the Design)

  9. How to Construct Taguchi Orthogonal Array L16(2^15) in MS Excel

  10. How to Construct Taguchi Orthogonal Array L32(2^31) in MS Excel

  11. Construct Any (Taguchi) Orthogonal Arrays upto L36(2^35) in MS Excel

  12. Taguchi Linear Graphs Explained and How to Use Them

  13. Taguchi Triangular Interactions Table Explained and How to Use them in the Design of Experiments

  14. Taguchi Interaction Table Construction Design of Experiments How to

  15. Taguchi Linear Graphs, Interactions Table, Design Resolution, Alias Structure, & Fractional Factorial Design of Experiments

  16. How to Create Robust Parameter Taguchi Design in Minitab

  17. How to perform Robust Parameter Taguchi Static Analysis in Minitab

  18. How to perform Robust Parameter Taguchi Dynamic Analysis in Minitab

  19. How to perform Robust Parameter Taguchi Dynamic Analysis in MS Excel

  20. Robust Parameter Taguchi Dynamic Analysis Regress Method in MS Excel and Minitab

Recommended Texts

General Design of Experiments

[The order is based on the Use of the Book]

  1. Hinkelmann, K., & Kempthorne, O. (2007). Design and Analysis of Experiments, Introduction to Experimental Design (Volume 1). John Wiley & Sons. ISBN-13: 978-0471727569; ISBN-10: 0471727563.

  2. Hinkelmann, K., & Kempthorne, O. (2005). Design and Analysis of Experiments, Advanced Experimental Design (Volume 2). John Wiley & Sons. ISBN-13: 978-0471551775; ISBN-10: 0471551775.

  3. Montgomery, D. C. (2012). Design and analysis of experiments 8th/E. John Wiley & Sons. ISBN-13: 978-1118146927; ISBN-10: 1118146921

  4. Box, G. E., J. S. Hunter, et al. (2005). Statistics for experimenters: design, discovery and innovation, Wiley-Interscience.

  5. Kempthorne, O. (1952). The design and analysis of experiments, John Wiley & Sons Inc.

  6. Fisher, R. A., Bennett, J. H., Fisher, R. A., & Bennett, J. H. (1990). Statistical methods, experimental design, and scientific inference. Oxford University Press. ISBN-10: 0198522290; ISBN-13: 978-0198522294.

Regression & Response Surface

  1. Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2013). Applied linear statistical models.

  2. Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. (2019). Response surface methodology: Process and product optimization using designed experiments. Hoboken: Wiley.

Robust Parameter Optimization

Taguchi Design of Experiments

  1. Kacker, R. N., Lagergren, E. S., & Filliben, J. J. (1991). Taguchi’s orthogonal arrays are classical designs of experiments. Journal of research of the National Institute of Standards and Technology, 96(5), 577.

  2. Plackett, R. L., & Burman, J. P. (1946). The design of optimum multifactorial experiments. Biometrika, 305-325. (for Video #11)

  3. Taguchi, G., Chowdhury, S., Wu, Y., Taguchi, S., & Yano, H. (2011). Taguchi's quality engineering handbook. Hoboken, N.J: John Wiley & Sons.

  4. Chowdhury, S., & Taguchi, S. (2016). Robust Optimization: World's Best Practices for Developing Winning Vehicles. John Wiley & Sons.

Random-Effect Models, Mixed Models, Nested, Split-Plot & Repeated Measure Design of Experiments

  1. Kutner, M. H., Nachtsheim, C. J., Neter, J., & Li, W. (2013). Applied linear statistical models.

  2. Quinn, G. P., & Keough, M. J. (2014). Experimental design and data analysis for biologists. Cambridge: Cambridge Univ. Press.