Test Regions Using Two or More Correlated Product Characteristics

Abstract

For inspection of manufactured parts, one can use the information of two or more product characteristics that are strongly related to the characteristic of interest. Under the condition that at most a given, typically very small, fraction of the accepted parts does not satisfy the specification limit, test regions are determined such that the number of accepted products is maximized. The methods are illustrated by Monte Carlo results and a numerical example from semiconductor industry.

Spline‐Based Drift Analysis for the Reliability of Semiconductor Devices

“…[11] The studies of Hofer et al, [12] Healy et al, [13] Albers et al, [14] and Albers et al [15] are related to the present study. While Al-bers et al [15] and Albers et al [14] present models for the computation of test limits for features that are difficult or costly to measure, Healy et al [13] review and extend existing models for setting test limits while maximizing manufacturers' yield. Hofer et al [12] use multivariate extensions of Archimedean copulas with skew-normally distributed marginals to implicitly describe the time dependencies between the measurements of HTOL stress test.…”

“…Also, the necessity of providing probability distributions required for the computation of the desired reliability targets, ruled out the usage of methods for the analysis of variance for repeated measurements, as introduced by Davis. [11] The studies of Hofer et al, [12] Healy et al, [13] Albers et al, [14] and Albers et al [15] are related to the present study. While Al-bers et al [15] and Albers et al [14] present models for the computation of test limits for features that are difficult or costly to measure, Healy et al [13] review and extend existing models for setting test limits while maximizing manufacturers' yield.…”

A variety of criteria for setting test limits

“…For the more realistic situation that the model is (partly) unknown, the test limits should be modi®ed. For more details see ALBERS et al (1995ALBERS et al ( ), (1996.…”