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Process True Capability Evaluation with the Consideration of Measurement System Variability and Expected Quality Loss
Author(s) -
Ben Amara Souha,
Dhahri Jamel,
Ben Fredj Nabil
Publication year - 2017
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2070
Subject(s) - taguchi methods , process capability index , process capability , process (computing) , reliability engineering , measure (data warehouse) , function (biology) , quality (philosophy) , system of measurement , computer science , point (geometry) , statistics , engineering , work in process , mathematics , data mining , operations management , epistemology , astronomy , evolutionary biology , biology , operating system , philosophy , physics , geometry
Process capability indices are widely computed under the assumption that the measurement system is free from errors. However, measurement variability is unavoidable and has a significant impact in process capability evaluation. From an economic point of view, Taguchi loss function is an effective tool to measure the quality loss of a product characteristic deviated from target value that is extensively used without taking into account the effect of the measurement system. This paper investigates the influence of measurement system variability on the process capability analysis through the calculation of process capability indices. A new quality loss function, integrating the measurement system errors, is developed to compute the optimal true process capability regarding to the expected mean value of the Taguchi loss function and the loss resulting from the control of the true process capability. Copyright © 2016 John Wiley & Sons, Ltd.