Measuring the manufacturing process yield based on fuzzy data

DOI10.1080/00207540802555751zbMath1197.90170OpenAlexW2054964261MaRDI QIDQ3163693

Ming-Hung Shu, Hsien-Chung Wu

Publication date: 26 October 2010

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207540802555751

zbMATH Keywords

process controlfuzzy data analysisprocess capabilityquality engineering

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Production models (90B30) Fuzziness, and linear inference and regression (62J86)

Related Items (2)

A modified method on estimating and assessing the process yield with imprecise multiple characteristics ⋮ Fuzzy nonlinear programming approach for evaluating and ranking process yields with imprecise data

Cites Work

• Fuzzy estimation for process capability indices
• An alternative approach to fuzzy control charts: Direct fuzzy approach
• Using fuzzy sets theory and Black-Scholes formula to generate pricing boundaries of European options
• The concept of a linguistic variable and its application to approximate reasoning. I
• A note on \(C_{pk}\) index estimation using fuzzy numbers
• Testing hypotheses with fuzzy data: The fuzzy \(p\)-value
• Measuring production yield for processes with multiple quality characteristics
• Brocess capability with asymmetric tolerances
• Estimating process yield based on S_pk for multiple samples
• \(C_{pk}\) index estimation using fuzzy numbers.

This page was built for publication: Measuring the manufacturing process yield based on fuzzy data