ABSTRACT
To increase machine tool reliability and overall product quality, process quality must be increased for all parts and components. Aside from quality, processing efficiency is also a crucial indicator of machine tools, which has brought about various customized machine tools with high processing efficiency. As broaching machines offer high production efficiency and are simple in structure and operation, we used broaching machines as a case study to construct a model for process capability evaluation, analysis, and improvement. Furthermore, the Six Sigma quality index directly reflects process yield as well as process quality levels. We then derived the relationships between the quality level of the product and those of individual quality characteristics to establish quality assessment standards and created a process quality analysis chart for products with multiple quality characteristics. We used a mathematical programming model to find the corresponding coordinate point of the upper confidence limit for Six Sigma quality indices. Process engineers need only check whether the corresponding coordinate points fall in the acceptable-quality zone or the poor-quality zone to identify critical-to-quality characteristics. Finally, we used a cause-and-effect diagram to determine the causes of poor process quality and formulate suggestions for improvement.
Nomenclature
CTQscritical-to-quality characteristics
E
ELh
EUh
Ehevents in which process specifications are met for quality characteristic h
events in which process specifications are not met for quality characteristic h
dh(USLh − LSLh)/2
hquality characteristic
k; process quality of the product
NTBnominal-the-best
LTBlarger-the-better
LSLhlower specification limits of quality characteristic h
accuracy index of quality characteristic h
precision index of quality characteristic h
process mean of quality characteristic h
process standard deviation of quality characteristic h
ThProcess target of quality characteristic h
Qphthe assessment indices of the quality characteristic h
defect rate of products …
the cumulative distribution function of the standard normal distribution Z
Xhrandom variable of the quality characteristic h
Nnormal distribution of the quality characteristic h
nsample size
estimator of
estimator of
the estimators of
significance level
K
chi-square distribution with n - 1 degrees of freedom
the estimators of
the estimators of
CRconfidence region
xhjthe observed value of Xhj
the observed value of
the observed value of
the observed value of
the observed value of
lower limit of
the corresponding coordinate point of upper confidence limit UQph
pkthe least process yield when Qph = k
p(Eh)probability of Eh
probability of
P(E)
p(ELh)probability of events ELh
p(EUh)probability of events EUh
STBsmaller-the-better
SSQISix Sigma quality index
Phyield of products that meet process specifications for quality characteristic h
upper limit of
UQphupper confidence limit of Qph
USLhupper specification limits of quality characteristic h
ZAa triangular acceptable-quality zone
Z
inadequate accuracy for the quality characteristic in question and is skewed to the right
inadequate accuracy for the quality characteristic in question and is skewed to the left
inadequate precision and excessive variance for the quality characteristic in question
inadequate accuracy and precision for the quality characteristic in question and is skewed to the right
inadequate accuracy and precision for the quality characteristic in question and is skewed to the left
Disclosure of interest
No potential conflict of interest was reported by the author(s).