A Study on Beta Glucan Production Optimization through a 2k Saturated Factorial Experiment

• 발행기관: 한국자료분석학회
• 저자명: Hyeong Chul Jeong
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.15 No.2, 575~583쪽, 전체 9쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2013.04.30

영문 초록

In this paper, we consider the 2k saturated factorial experiment design to find the optimal point of production for beta glucan. A 2k saturated factorial design does not allow the replication of any design point, thus the error term has zero degree of freedom, making it impossible to test statistically all possible model term. In this case, if only main effects are included in the model, statistical tests can be performed, but the powers of these tests may be weak. Here, it is recommended to use the normal probability plot in order to find the statistically significant factors. In this study, the significant factors were found first using the normal probability of the 2k saturated experiment data. Then, in order to find the optimal point of production for beta glucan, an orthogonal polynomial regression model with the significant factors were used to estimate the optimal point within the experiment conditions. Furthermore, the optimal point was re-verified using the Taguchi method.

목차

1. Introduction

2. 2k Saturated Factorial Experiment

3. Finding the Optimal Condition

4. Conclusion

References

키워드

Saturated factorial design Normal probability plot Orthogonal polynomial regression Taguchi method