Reducing the warranty cost to increase profit is a major focus for most businesses. To achieve this goal, the acceptance sampling plan (ASP) can be an efficient tool to validate whether the product lifetimes meet their requirements. In the ASP practice, the single sampling plan (SSP) is widely used due to its administrative simplicity. Unfortunately, the SSP ignores the valuable sample information from preceding lots, which may reduce its efficiency and quality-discrimination power. Especially, the collection of lifetime information often consumes a significant amount of time and is expensive in today’s high product-yield and long-life environment. To address the drawbacks of the SSP, we propose a lifetime performance-qualified quick switch sampling (QSS) system under a Weibull distribution with failure-censoring. This system nimbly switches between the normal SSP and tightened SSP based on the previous lot-disposition result. Compared to the ordinary SSP and the recently proposed multiple-lot dependent sampling plan, the QSS system not only significantly reduces the required number of failures that need to be observed in the life testing but also exhibits a better discriminatory operating characteristic curve for the lot disposition. On the other hand, the QSS system helps the consumer to communicate to the supplier important messages that (i) only with reliable submissions the latter can persistently enjoy the benefits of the normal lot-sentencing standard; (ii) once the submitted lot is rejected, the supplier will have to spend more efforts to gain back the consumer trust. Moreover, we developed a web-based tool to help practitioners obtain the system criteria easily and quickly without the need for the traditional time-consuming table lookup. By operating the interactive interface of the web app, practitioners can quickly obtain the system criteria conforming to the requirements. Finally, the proposed QSS system is illustrated by a real-life application.

In the past few decades, various sampling strategies have been developed for different perspectives or occasions to benefit from cost reduction or time-saving when one performs lot disposition, particularly for those inspected items or expensive procedures. The quick switching sampling (QSS) system has been important in examining fewer samples under the same quality requirements and was designed with a dually flexible mechanism for varied qualities. However, most related studies considered only a fixed switching policy either critical value or sample-sized tightenings, which might neglect the collective effect of two types of QSS systems. In this study, we integrate two variables QSS (VQSS) systems in a generalized form, known as integrated VQSS (IVQSS), based on the C_pmk index, a non-scale process performance indicator considering centering, variation, and quality loss simultaneously to accommodate advantages of two individual systems. The operating characteristic function is derived using the Markov Chain theory. Furthermore, we developed a mathematical model to minimize the average sample number and limit two acceptable sampling risks under desirable submitted quality levels. The plan parameters are obtained for making a reliable judgment on submissions by solving this optimization problem. Finally, to illustrate the practicability of the proposed method, we demonstrated a numerical application obtained from a solar panel industry and provided the solved plan parameters under commonly used conditions for convenient use.

The quick-switch sampling system (QSS) and tightened-normal-tightened sampling system (TSS) are efficient schemes for dispositioning a series of lots. However, the QSS mechanism for switching decision rules is too simple to satisfy the requirements of suppliers and buyers. Conversely, the TSS is more flexible due to its adaptable switching mechanism. The TSS was recently developed based on process capability indices (PCIs) to help practitioners make more reliable and accurate decisions in practice. The existing PCI-based TSSs are the required sample-size type (TSS-n). However, the TSS-n requires a large sample size for the tightened inspection, which is costly and time-consuming. We propose the acceptance-benchmark type TSS (TSS-k) based on the most commonly used PCI, to improve the lot-disposition sampling efficiency. The TSS-k adjusts the acceptance benchmark instead of the sample size to constitute tightened and normal inspections. We investigated combinations of TSS-k switching mechanism parameters and provided managerial suggestions for practitioners. Compared with the existing TSS-n, the proposed TSS-k can reduce the average sample number by more than 60% and has superior discrimination power. Moreover, we developed a cloud-computing programme to calculate the optimal system design online. Finally, we illustrate an industrial case to demonstrate the applicability of the proposed TSS-k.