\(C_{pk}\) index estimation using fuzzy numbers.

DOI10.1016/S0377-2217(99)00438-5zbMath1125.90366MaRDI QIDQ5928387

Hong Tau Lee

Publication date: 28 March 2001

Published in: European Journal of Operational Research (Search for Journal in Brave)

zbMATH Keywords

membership function for standard deviation of fuzzy numberProcess capacity indices

Mathematics Subject Classification ID

Decision theory (91B06) Management decision making, including multiple objectives (90B50) Statistical methods; economic indices and measures (91B82)

Related Items (19)

A note on \(C_{pk}\) index estimation using fuzzy numbers ⋮ Fuzzy process capability indices for simple linear profile ⋮ Measuring the manufacturing process yield based on fuzzy data ⋮ Fuzzy Testing for One-Sided Process Capability Indices ⋮ Measuring process capability index C_pkwith fuzzy data ⋮ A new generation of process capability indices based on fuzzy measurements ⋮ The revised algorithms of fuzzy variance and an application to portfolio selection ⋮ A modified method on estimating and assessing the process yield with imprecise multiple characteristics ⋮ The evaluation of educational systems: an application study ⋮ Fuzzy estimation for process capability indices ⋮ A new generation of process capability indices ⋮ Fuzzy process capability indices based on imprecise observations induced from non-normal distributions ⋮ Fuzzy multivariate process capability vector ⋮ Fuzzy inference to assess manufacturing process capability with imprecise data ⋮ Fuzzy confidence regions for the Taguchi capability index ⋮ Decision-making in testing process performance with fuzzy data ⋮ COA defuzzification method for evaluatingC_pkunder fuzzy environments ⋮ Fuzzy nonparametric estimation of capability index \( C _{pk}\) ⋮ Fuzzy nonlinear programming approach for evaluating and ranking process yields with imprecise data

Cites Work

• Unnamed Item
• Ranking fuzzy numbers with maximizing set and minimizing set
• A subjective approach for ranking fuzzy numbers
• Fuzzy sets and systems. Theory and applications
• The concept of a linguistic variable and its application to approximate reasoning. I
• The concept of a linguistic variable and its application to approximate reasoning. III
• Personnel selection using fuzzy MCDM algorithm
• Operations on fuzzy numbers
• Fuzzy sets
• Additions of interactive fuzzy numbers

This page was built for publication: \(C_{pk}\) index estimation using fuzzy numbers.