Improving Multiple Dependent State Sampling Plan Based on Capability Index ST pk

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

AFSHARI R.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF STATISTICAL SCIENCES Year:2023 | Volume:16 | Issue:2 Page(s): 275-294

Download Full-Text

Persian Verion

View:

Download:

Cites:

Information Journal Paper

Title

Improving Multiple Dependent State Sampling Plan Based on Capability Index ST pk

Author(s)

AFSHARI R. | Issue Writer Certificate

Keywords

Acceptance sampling plan

Multiple dependent state sampling plan

Process capability

Abstract

Introduction Acceptance sampling plans (ASPs) are one of the statistical tools widely used by inspectors to evaluate the quality of productions. Depending on whether the desired quality characteristic of products can be measured on a numerical scale or not, the corresponding ASP is called variable and attribute ASP, respectively. Most ASPs only apply the current lot information to decide the quality of manufactured products. One of the drawbacks of such plans is that they need a large sample size to inspect the lot to judge its quality. To solve this problem, the methods of sampling in ASPs were developed, and conditional plans were presented (Montgomery, 2020). In addition to the current information, past information on the process is also used in decision-making. Although the variable multiple dependent state sampling (MDS) plan is preferred over the conditional plans due to the small sample size required, it is impossible to use it in a situation where the quality of manufactured products depends on more than one quality characteristic. In this study, to improve the performance of the mentioned method, ST pk-based MDS plan is proposed, which applies both current and past knowledge of the process and is applicable to inspect products with independent/dependent characteristics following a multivariate normal distribution. Material and Methods Let X = (X1,,,, ,Xv) ′,be a random vector of independent quality characteristics and follow a multivariate normal distribution. The proposed variable MDS multivariate (VMDSM) plan, designed under the Process capability index ST pk, has four parameters m,n,kr and ka. Applying a nonlinear optimization problem, optimal values of plan parameters are obtained. Also, to develop the application of the VMDSM plan in the presence of dependent variables, the principal component analysis technique is used. While comparing the performance of the proposed plan with variable single sampling (VSS), variable repetitive group sampling (VRGS) and modified VRGS (Modified-VRGS) plans based on the required sample size and operating characteristic (OC) curve. An industrial example is given to explain how to use the introduced plan. Results and Discussion To study the impact of the contracted values between customer and producer on the plan parameters, we consider several combinations of consumer’, s risk (, ) and manufacturer’, s risk (, ) as well as a different number of defective items in parts per million. The results demonstrate that the required sample size decreases when (, ) and (, ) become larger. Moreover, findings indicate that the OC curve of the proposed method is the best one among VSS, VRGS and Modified-VRGS plans. Also, compared to VSS and VRGS plans, the introduced plan needs a small sample size and is economical. Conclusion Today’, s, it is clear that production quality depends on many quality characteristics. So designing a multivariate ASP with small sample size, strong OC curve, and simple implementation is unavoidable. In this study, we proposed a plan suitable for a situation where the quality characteristics are mutually independent/dependent with multivariate normal distribution. The results showed that the introduced plan is better than the existing VSS and VRGS plans in terms of the required sample size and OC curve, and it is preferable to the Modified-VRGS method based on the OC curve.

Cites

No record.

References

No record.

Cite

APA: Copy

AFSHARI, R.. (2023). Improving Multiple Dependent State Sampling Plan Based on Capability Index ST pk. JOURNAL OF STATISTICAL SCIENCES, 16(2 ), 275-294. SID. https://sid.ir/paper/1021854/en

Vancouver: Copy

AFSHARI R.. Improving Multiple Dependent State Sampling Plan Based on Capability Index ST pk. JOURNAL OF STATISTICAL SCIENCES[Internet]. 2023;16(2 ):275-294. Available from: https://sid.ir/paper/1021854/en

IEEE: Copy

R. AFSHARI, “Improving Multiple Dependent State Sampling Plan Based on Capability Index ST pk,” JOURNAL OF STATISTICAL SCIENCES, vol. 16, no. 2 , pp. 275–294, 2023, [Online]. Available: https://sid.ir/paper/1021854/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops