A note on the operativeness of Neyman-Pearson tests with fuzzy information
Fuzzy Sets and Systems
A fuzzy statistical test of fuzzy hypotheses
Fuzzy Sets and Systems
Approximating &agr;-cuts with the vertex method
Fuzzy Sets and Systems
Bayesian sequential test for fuzzy parametric hypotheses from fuzzy information
Information Sciences—Intelligent Systems: An International Journal
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy quality and analysis on fuzzy probability
Fuzzy Sets and Systems - Special issue on fuzzy methodology in system failure engineering
Testing fuzzy hypotheses with crisp data
Fuzzy Sets and Systems
Fuzzy Probabilities: New Approach and Applications
Fuzzy Probabilities: New Approach and Applications
Uncertain probabilities II: the continuous case
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Uncertain probabilities III: the continuous case
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Fuzzy statistics: hypothesis testing
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Fuzzy estimation for process capability indices
Information Sciences: an International Journal
Estimating the quality of process yield by fuzzy sets and systems
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Hi-index | 12.05 |
The index S"P"K provides an exact measure of process yield for normally distributed processes, and has been widely used in manufacturing industry for measuring process performance. Most studies on estimating and testing process yield are based on crisp estimates involving precise output process measurements. However, it is not uncommon for measurements of product quality to be lack precision. This study designs a realistic approach for assessing process yield that considers a certain degree of imprecision on the sample data. By adopting an extended version of the approach of Buckley, the membership function of fuzzy estimator of S"P"K index is constructed. With normal approximation to the distribution of the estimated S"P"K, two useful criteria for fuzzy hypothesis testing, critical value and fuzzy p-value, are developed to assess process yield based on S"P"K. Finally, an application example is presented to demonstrate the application of the proposed approach.