Variables sampling inspection scheme for resubmitted lots based on the process capability index Cpk

This paper attempts to develop a sampling inspection scheme by variables based on process performance index for product acceptance determination, which examines the situation where resampling is permitted on lots not accepted on original inspection. The equations for plan parameters, the required sample size and the corresponding critical value, are derived based on the exact sampling distribution rather than an approximation approach hence the decisions made are more accurate and reliable. Moreover, the efficiency of the proposed variables resubmitted sampling plan is evaluated and compared with the existing variables single sampling plan. For illustrative purpose, an example is presented to demonstrate the use of the derived results for making a decision on product acceptance determination.     

Assessing process capability based on the lower confidence bound of Cpk for asymmetric tolerances

It has been proved that process capability indices provide very efficient measures of the capability of processes from many different perspectives. At the present time, the C_pk index is used more than any other index for measuring process capability. However, most existing research works for capability testing have focused on processes with symmetric tolerances, but not for asymmetric tolerances. A lower confidence bound estimates the minimum process capability, conveying critical information regarding product quality, which is essential to quality assurance. The sample size determination, which provides the sample sizes necessary to achieve a desired lower confidence bound, is directly related to the cost of the data collection plan. This paper provides explicit formulas with efficient algorithms to obtain the lower confidence bounds and sample sizes required for specified precision of the estimation on C_pk for processes with asymmetric tolerances. A Matlab computer program using a binary search method is developed. For the practitioners to use in their in-plant applications, we tabulate lower confidence bounds for some commonly used capability requirement and the sampling accuracy of C_pk for sample sizes determination. A realistic example of forging process is presented to illustrate the applicability of the proposed method.     

An efficient inspection scheme for variables based on Taguchi capability index

Acceptance sampling has been one of practical tools for quality assurance applications, which provide a general rule to the producer and the consumer for product acceptance determination. It has been shown that variables sampling plans requires less sampling compared with attributes sampling plans. Thus, variables sampling plans become more attractive and desirable especially when the required quality level is very high or the allowable fraction non-conforming is very small. This paper attempts to develop an efficient and economic sampling scheme, variables repetitive group sampling plan, by incorporating the concept of Taguchi loss function. The OC curve of the proposed plan is derived based on the exact sampling distribution and the plan parameters are determined by minimizing the average sample number with two constraints specified by the producer and the consumer. The efficiency of the proposed variables RGS is examined and also compared with the existing variables single sampling plan in terms of the sample size required for inspection. In addition, tables of the plan parameters for various combinations of entry parameters are provided and an example is presented for illustration.     

Variable sampling inspection for resubmitted lots based on process capability index Cpk for normally distributed items

In this article, a variables sampling inspection plan for resubmitted lot based on the process capability index C_pk is developed for normally distributed items with unknown mean and variance. The three plan parameters, sample size n, critical acceptance value k_a and the number of resubmissions m, are determined simultaneously by minimizing average sample number (ASN) with two conditions specified by the producer and the consumer. The advantages of the proposed resubmitted sampling plan over the variables single sampling plan are also discussed. Tables of plan parameters for selected values of acceptable quality level (AQL), limiting quality level (LQL), producer’s α-risk and consumer’s β-risk are provided and discussed with the help of an application example.