TY - GEN
T1 - Interval Estimation of Process Capability Indices Based on the Quality Data of Supplied Products
AU - Cui, Yanhe
AU - Yang, Jun
AU - Huang, Shuo
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Process capability indices (PCIs) are employed to select an appropriate supplier for customers. However, data fraud events may lead to incorrect decisions on quality management, it is more reliable to assess the manufacturing process capability based on supplied products. According to the quality requirement of the specification limits, the quality data of supplied products are doubly truncated. Thus, process capability analysis from supplied products is adopted to evaluate the manufacturing process capability, supervise and check the quality data provided by suppliers. For this purpose, under normal assumption, EM algorithm is firstly adopted to estimate the unknown parameters of the quality distribution of supplied products. Then, a quantile-filling algorithm is proposed to convert the truncated data into the pseudo-complete data. Next, based on the pseudo-complete data, the interval estimation of PCIs is carried out by the generalized confidence interval method. Finally, a practical example is given to show the implement of the proposed method.
AB - Process capability indices (PCIs) are employed to select an appropriate supplier for customers. However, data fraud events may lead to incorrect decisions on quality management, it is more reliable to assess the manufacturing process capability based on supplied products. According to the quality requirement of the specification limits, the quality data of supplied products are doubly truncated. Thus, process capability analysis from supplied products is adopted to evaluate the manufacturing process capability, supervise and check the quality data provided by suppliers. For this purpose, under normal assumption, EM algorithm is firstly adopted to estimate the unknown parameters of the quality distribution of supplied products. Then, a quantile-filling algorithm is proposed to convert the truncated data into the pseudo-complete data. Next, based on the pseudo-complete data, the interval estimation of PCIs is carried out by the generalized confidence interval method. Finally, a practical example is given to show the implement of the proposed method.
KW - generalized confidence interval
KW - process capability indices
KW - quantile-filling algorithm
KW - supplied product
KW - truncated data
UR - https://www.scopus.com/pages/publications/85067001560
U2 - 10.1109/ICRMS.2018.00081
DO - 10.1109/ICRMS.2018.00081
M3 - 会议稿件
AN - SCOPUS:85067001560
T3 - Proceedings - 12th International Conference on Reliability, Maintainability, and Safety, ICRMS 2018
SP - 400
EP - 404
BT - Proceedings - 12th International Conference on Reliability, Maintainability, and Safety, ICRMS 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on Reliability, Maintainability, and Safety, ICRMS 2018
Y2 - 17 October 2018 through 19 October 2018
ER -