The capability indices are widely used by quality professionals as an estimate of process capability. Many process indices have been proposed and developed with Cp, Cpk and Cpm among the most widely used. More recently, techniques have been developed to construct lower 95 percent confidence limits for each index. These techniques are based on the assumption that the underlying process is normally distributed. The non‐parametric but computer intensive method called Bootstrap is utilized and the Bootstrap confidence limits are calculated for these indices. A simulation using three distributions (normal, log‐normal and chi‐squared) was conducted and a comparison was made of the performances of the Bootstrap and the parametric estimates.
In 1955, Lieberman and Solomon introduced multi-level (MLP) continuous sampling plans. Derman et al . then extended the multi-level plans as tightened multi-level plans (MLP-T). In this paper, a generalization of MLP-T with two sampling levels is presented. Using a Markov chain model, expressions for the performance measures of the general MLP-T plans are derived. Tables are also presented for the selection of general MLP-T plans with two sampling levels when the acceptable quality level, limiting quality level, indiff erence quality level and average outgoing quality level are specified.
In this paper, a new sampling scheme called the 'conditional double sampling scheme' (CDSS) has been proposed. A compact table is presented for the selection of a CDSS indexed by various combinations of entry parameters. Advantages of the CDSS over the single sampling scheme have been discussed. The basis for the construction of the table is given.
In this paper, procedures and tables for the selection of a variable-lot-size attribute sampling plan for continuous production are given, and the advantages of this plan relative to a fixed-lot-size plan are also discussed.
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