Statistical Inference for Process Capability Indices and 6 Sigma Qualify Levels

Title & Authors
Statistical Inference for Process Capability Indices and 6 Sigma Qualify Levels
Cho, Joong-Jae; Sim, Kyu-Young; Park, Byoung-Sun;

Abstract
Six sigma is the rating that signifies "best in clas", with only 3.4 defects per million units or operations. Higher sigma quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The process capability indices and the sigma level $\small{Z_{st}}$ have been widely used in six sigma industries to assess process performance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. In this paper, we consider statistical inference for process capability indices $\small{C_p}$, $\small{C_{pk}}$ and $\small{C_{pm}}$. Also, we study better testing procedure on assessing sigma level $\small{Z_{st}}$ and capability index $\small{C_{pm}}$, for practitioners to use in determining whether a given process is capable. The proposed method is easy to use and the decision making is more reliable. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on our proposed method is illustrated.
Keywords
Process capability index;quality level;test of hypothesis;bootstrap method;p-value;monte-carlo experiment;asymptotic normal distribution;
Language
Korean
Cited by
1.
공정능력지수 Cpmk를 평가함에서의 바람직한 가설검정,조중재;유혜경;한정수;

Communications for Statistical Applications and Methods, 2010. vol.17. 3, pp.459-471
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