A lots-dependent variables sampling plan considering supplier’s process loss and buyer’s stipulated specifications requirement

Wu, Chien‐Wei; Wang, Zih‐Huei; Shu, Ming‐Hung

doi:10.1080/00207543.2015.1053580

Cited by 19 publications

(4 citation statements)

References 28 publications

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“…Wu [20] investigated the variables SSP based on Cpm index and this study was extended further for special purpose sampling plans such as RGS plan by Wu [21] and MDS sampling plan by Wu et al [22]. Wang and Wu [23] suggested a modified RGS plan based on the Cpm index.…”

Section: Process Capability Indicesmentioning

confidence: 96%

Implementation of Reinspection Scheme in Skip-lot Sampling Plan Based on the Taguchi Process Capability Index

Suthersan,

Balamurali

2023

Preprint

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In several industries, skip-lot sampling plans are utilised to reduce the need for inspection when a product has a history of high quality. These plans are regarded as being economically beneficial as they help to reduce the expense of the final lots examination. In this paper, we propose a designing methodology of the skip-lot sampling plans including resampling based on the Taguchi process capability index. In order to satisfy both producer and consumer risk, the plan parameters for the proposed plan are set by minimising the average sample number. The effectiveness of the proposed plan is discussed by comparing with the existing sampling plans. Moreover, the data from amplified pressure sensors is used to discuss the real life application of the proposed plan.

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Section: Process Capability Indicesmentioning

confidence: 96%

Implementation of Reinspection Scheme in Skip-lot Sampling Plan Based on the Taguchi Process Capability Index

Suthersan,

Balamurali

2023

Preprint

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“…If the OC curve of the acceptance sampling plan is closer to the ideal curve, it means that this plan has better discriminatory power. Therefore, this research is to examine the performance of the proposed VMChSP compared with the VSSP (proposed by Pearn and Wu 8 ) and VMDSSP (proposed by Wu et al 24 ), and further observe how the OC curve varies when m changes. The OC curves with three sampling plans under the same condition setting, that is, (𝑐 AQL , 𝑐 RQL ) = (1.33, 1.00) and (𝛼, 𝛽) = (0.01, 0.05), is illustrated in Figure 1.…”

Section: Comparison and Analysismentioning

confidence: 99%

Section: Comparison and Analysismentioning

confidence: 99%

Developing a variables modified chain sampling plan with Taguchi capability index

Wang

Lin

2021

Quality & Reliability Eng

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Acceptance sampling plan has been a practical tool in quality management, which provides both the producer and the consumer a general rule for sentencing lots. In recent years, a new strategy, chain sampling plan, considering disposition of historical lots for sentencing the current lot has been discussed. However, reviewing results of preceding lots only happens when the quality of current lot is on the undefined region, which may not be completely utilized. Therefore, in this study, we develop a variables modified‐ChSP (VMChSP) for variable inspection based on the Taguchi capability index to improve above situation. Optimization model of the proposed plan is formulated to solve plan parameters by minimizing the required sample size. Plan parameters under various allowable risks and quality levels are also provided for practical purpose. Finally, further analysis and comparisons between the proposed plan and conventional plans are provided and discussed in this research.

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“…Wu et al 11 proposed the variables MDS plans based on the commonly used PCI C pk . Wu et al 12 introduced the variables MDS plans based on the sample information of the PCI C pm , which incorporates the producer's process loss and the consumer's demanded specification requirements. Wu and Wang 13 designed the variables MDS plans for lot sentencing based on the advanced PCI C pmk , which was developed by combining the merits of the yield‐based index and the loss‐based index.…”

Section: Introductionmentioning

confidence: 99%

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

Wang

Hsu

et al. 2020

Quality & Reliability Eng

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Acceptance sampling plan is widely used for the inspections of incoming or outgoing products to provide the producer and the consumer a general benchmark for lot sentencing. To reduce the inspection cost, the multiple‐dependent‐state (MDS) plan that takes account of the preceding lots' quality history into the current lot disposition has been proposed. However, recent studies overlook the fact that the MDS plan's performance needed to reach target compliance decreases with an increase in the number of preceding lots considered. This unawareness makes the MDS plan fall into a conflictive situation. To overcome the drawback of the MDS plan, in this paper, we introduce a modified MDS plan to accommodate an adjustable mechanism, called adjustable MDS (AMDS) sampling plans. The presented AMDS plans are designed on the basis of the advanced process capability index, which is cognizant of both the process yield and the process loss. This established process‐capability‐qualified AMDS plan efficiently solves the conflictive situation of the MDS plan when encompassing more preceding lots in the lot‐disposition decision. Notably, its efficacy has been shown on high improvements in terms of the required sample size for the inspection, the discriminatory power, and the average run length for lot sentencing.

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A lots-dependent variables sampling plan considering supplier’s process loss and buyer’s stipulated specifications requirement

Cited by 19 publications

References 28 publications

Implementation of Reinspection Scheme in Skip-lot Sampling Plan Based on the Taguchi Process Capability Index

Implementation of Reinspection Scheme in Skip-lot Sampling Plan Based on the Taguchi Process Capability Index

Developing a variables modified chain sampling plan with Taguchi capability index

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

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