Dependent Mixed and Mixed Repetitive Sampling Plans for Linear Profiles

Abstract

In this paper, we present two new dependent mixed sampling plans and a mixed repetitive sampling plan based on the process yield index for linear profiles. A mixed sampling plan includes two stages; the first stage is a combined test by variables and by attributes, and the second stage is tested by attributes only. The first plan is based on the traditional mixed sampling scheme without marginal quality, and the second plan is based on the modified mixed sampling scheme with marginal quality. If a lot is very bad, the probability it can be rejected with the small initial sample is higher for dependent mixed sampling with marginal quality. We compare dependent mixed plans with other types of double sampling plans; the former outperforms the others with respect to average sample number. Additionally, the number of profiles required in the first stage is much smaller than in the second stage. When the inspection is costly and destructive, a mixed repetitive sampling plan includes one stage that combines the inspection by attributes and by variables and allows resampling in some conditions. We compare the mixed repetitive sampling plan with the repetitive sampling plans by attributes and by variables. The probability of acceptance using the mixed repetitive sampling plan performs better than the repetitive sampling plans by attributes and by variables. Three examples are used to illustrate the proposed methods. Copyright © 2017 John Wiley & Sons, Ltd.

Designing and Selection of Mixed Relational Complete Chain Sampling Plan Using Variance Principle (RCCSP‐VP)

“…Edna and Joyce [21] designed mixed two-sided CChsp based on the variance principle. For linear profles, Wang et al [22] have recently created dependent mixed and mixed repeated sampling designs. Te selection of a mixed sample plan with a double sampling plan as an attribute plan was explored by Sampath Kumar et al [23] and was indexed using MAPD and AQL utilizing IRPD.…”

Dynamic batch sentencing mechanisms for yield-based product acceptance determination with the simple linear profiles

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