The performance of group chain acceptance sampling plans (GChSP) for exponential distribution based on two different methods

Abstract

Acceptance sampling is a statistical quality control technique whereby the final decision to accept or reject a lot is based on the outcome from the inspection of its sample. A recent development in acceptance sampling includes the group chain acceptance sampling plan (GChSP) to rectify the problems with the single acceptance sampling plans (SSP) and chain acceptance sampling plans (ChSP). To date, the GChSP has been developed using two different approaches: minimizing the consumer’s risk (CR) and balancing both the CR and producer’s risk (PR) via minimum angle method. For both approaches, the GChSP has been developed by applying exponential distribution to the sampling plans. However, previous researchers only developed GChSP using these approaches without comparing their performance. Therefore, this article compares the performance of the GChSP using both approaches but considering the CR only. Both the GChSPs are developed via the same phases: (i) identifying the design parameters, (ii) developing operating procedures, (iii) deriving the probability of lot acceptance, (iv) deriving the probability of zero or one defective, (v) selecting lifetime distribution and (vi) measuring performance. The results reveal two interesting findings. The first finding shows that at the lower value of a, the minimum angle method has better protection for the consumer. The second finding shows that when the value of a increases, both approaches actually protect the consumer at the same level.