Process‐capability‐qualified adjustable multiple‐dependent‐state sampling plan for a long‐term supplier–buyer relationship

Wang, To‐Cheng; Wu, Chien‐Wei; Hsu, Bi‐Min; Shu, Ming‐Hung

doi:10.1002/qre.2750

Cited by 19 publications

(12 citation statements)

References 23 publications

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“…In recent years, many scholars have developed numerous variables sampling plans based on various PCIs for different scenarios, such as Wu, 5 Wu et al, 6 Seifi and Nezhad, 7 Wu et al, 8 Lee et al, 9 Wu and Liu, 10 Wang and Wu, 11 Arizono et al, 12 Wu et al 13 and Wang et al. 14 Many popular PCIs, such as 𝐶 𝑝 , 𝐶 𝑝𝑘 , 𝐶 𝑝𝑚 , and 𝐶 𝑝𝑚𝑘 , are based on the following assumptions: (i) the process must be stable and not easily altered due to any factors. That is, it is under statistical control; (ii) the process data are independent; (iii) the quality characteristic of interest follows a normal distribution.…”

Section: Introductionmentioning

confidence: 99%

A repetitive group sampling plan based on the lifetime performance index under gamma distribution

Lee

Liu

2022

Quality & Reliability Eng

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As technology and living standards improve, people are becoming more concerned with the importance of quality. Quality, thus, becomes the key to company competitiveness, and process capability indices (PCIs) are effective means of measuring process performance. Most PCIs have been developed under the assumption that the quality characteristics are normally distributed; however, the lifetime of products generally possesses a non‐normal distribution. A lifetime performance index (LPI) CL has been proposed and used for measuring product lifetime performance. In this high‐quality era, the use of traditional testing methods incurs very high costs, so acceptance sampling plans have been widely used by industry to perform the inspection. This study considers the product lifetime with a gamma distribution and uses the uniformly minimum‐variance unbiased estimator (UMVUE) of the LPI to develop a repetitive group sampling plan (RGSP). For the practical purpose, this study presents a step‐by‐step procedure and tabulates the plan parameters for various combinations of acceptable and rejectable quality levels, producer's and consumer's risks, and shape parameter. Thus, practitioners can easily know the sample size and the corresponding critical values for decision making. This study also uses the results of the proposed plan to compare with the single sampling plan. Lastly, a practical example is used to illustrate how to apply this acceptance sampling plan.

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Section: Introductionmentioning

confidence: 99%

A repetitive group sampling plan based on the lifetime performance index under gamma distribution

Lee

Liu

2022

Quality & Reliability Eng

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“…There are many studies on PCIs in the literature. See, for example, Ciupke 7 ; Piña-Monarrez et al 8 ; Scagliarini 9 ; Meng et al 10 ; Wang et al 11 among others. The 𝐶 𝑝𝑚 is one of the most frequently used indices for normal processes, which was initially introduced by Hsiang and Taguchi 1 and Chan et al 3 It is investigated by Boyles 12 ; Pearn et al 6 ; Subbaiah and Taam 13 ; Wright 14 ; Zimmer et al 15 ; and Kuş and Öksüz.…”

Section: Introductionmentioning

confidence: 99%

On the confidence intervals of process capability index Cpm based on a progressive type‐II censored sample

Akdoğan

2022

Quality & Reliability Eng

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This paper is concerned with the process capability index in the case of the progressively type‐II censored sample. In particular, the asymptotic distribution of maximum likelihood estimators of the process capability index is derived and it is used to construct the approximate confidence intervals with the delta rule. In addition, five parametric bootstrap confidence intervals for the Cpm${C_{pm}}$ index are discussed, in contrast to approximate confidence intervals, do not require second derivatives of the likelihood function. A Monte Carlo simulation study is performed to observe the coverage probabilities and the average width of these intervals. Simulation results indicate that the approximate confidence interval is better than the bootstrap based confidence intervals in terms of the coverage probabilities. Two practical examples are presented to illustrate the usability of the method discussed here.

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“…A single sampling plan (SSP) is the most basic ASP because of its straightforward lot-disposition mechanism [9][10]. Nevertheless, since the lot-disposition mechanism of SSP only considering the current lot's information that cannot accommodate the historical lot-quality levels information, it requires a large sample size for inspection to validate the submitted lot's process capability [11][12]. With the rapid development of manufacturing technology, the supplier has widely adopted continuous-flow production processes [13][14].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Supplier-Buyer Lots Sampling Plan With Quality Traceability Based on Process Loss Restricted Consideration

2021

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Supplier-buyer relationships have been the focus of considerable supply chain management and marketing research for decades. To validate the process capability of a supplier, practitioners usually operate the acceptance sampling plan (ASP). The most basic ASP is a single sampling plan (SSP) due to its straightforward lot-disposition mechanism. However, since the lot-disposition mechanism of SSP cannot accommodate the historical lot-quality levels information, it requires a large sample size for inspection to validate the submitted lot's process capability. To obtain these benefits from historical information, multiple-lot dependent state (MDS) sampling plans have been proposed. The MDS plans have manufacturing traceability of historical lot-quality levels information to sentence the submitted lot. However, the MDS plan's manufacturing traceability has a drawback that cost-efficiency decreases as more historical lot-quality levels information are considered, which contradicts its initial development goal. To overturn this contradictory situation, we proposed the adaptive MDS (AMDS) plans based on the process loss restricted consideration with combinatorial mathematical treatment that can correct the MDS plans manufacturing traceability of historical lot-quality levels information that help practitioners to adopt more historical information into lot-disposition freely without bearing the reduction of cost-efficiency. Meanwhile, their performances are superior to existing MDS plans in terms of cost-effectiveness and discriminatory power. Moreover, we further developed a web-based app for our proposed plans to improve the convenience of applying them in practice. By operating the web-based app, practitioners can quickly obtain the optimal plan criteria without bearing the burdens of table-checking or mathematical model solving. These improvements can genuinely help buyers distinguish reliable suppliers efficiently and build up a strong partnership with them. Finally, the applicability of the proposed plan is demonstrated in a realworld case study.INDEX TERMS Lot tracing, process loss restricted, lot-dependent sampling plans, supplier-buyer relationships, historical lot-quality levels information.

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Process‐capability‐qualified adjustable multiple‐dependent‐state sampling plan for a long‐term supplier–buyer relationship

Cited by 19 publications

References 23 publications

A repetitive group sampling plan based on the lifetime performance index under gamma distribution

A repetitive group sampling plan based on the lifetime performance index under gamma distribution

On the confidence intervals of process capability index Cpm based on a progressive type‐II censored sample

An Integrated Supplier-Buyer Lots Sampling Plan With Quality Traceability Based on Process Loss Restricted Consideration

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