scholarly journals A Rectifying Acceptance Sampling Plan Based on the Process Capability Index

Mathematics ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 141
Author(s):  
Ching-Ho Yen ◽  
Chun-Chia Lee ◽  
Kuo-Hung Lo ◽  
Yeou-Ren Shiue ◽  
Shu-Hua Li
Keyword(s):  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Superior Performance ◽  
Acceptance Sampling ◽  
Total Quality ◽  
Quality Cost ◽  
Capability Index ◽  
Acceptance Sampling Plan ◽  
Failure Cost

The acceptance sampling plan and process capability index (PCI) are critical decision tools for quality control. Recently, numerous research papers have examined the acceptance sampling plan in combination with the PCI. However, most of these papers have not considered the aspect of rectifying inspections. In this paper, we propose a quality cost model of repetitive sampling to develop a rectifying acceptance sampling plan based on the one-sided PCI. This proposed model minimizes the total quality cost (TQC) of sentencing one lot, including inspection cost, internal failure cost, and external failure cost. In addition, sensitivity analysis is conducted to investigate the behavior of relevant parameters against TQC. To demonstrate the advantages of the proposed methodology, a comparison is implemented with the existing rectifying sampling plan in terms of TQC and average outgoing quality limit. This comparison reveals that our proposed methodology exhibits superior performance.

scholarly journals Economic Design of Acceptance Sampling Plans in a Two-Stage Supply Chain

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Lie-Fern Hsu ◽  
Jia-Tzer Hsu
Keyword(s):  
Supply Chain ◽  
Computer Software ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Optimal Sampling ◽  
Total Quality ◽  
Two Stage ◽  
Quality Cost ◽  
Acceptance Sampling Plan ◽  
Acceptance Sampling Plans

Supply Chain Management, which is concerned with material and information flows between facilities and the final customers, has been considered the most popular operations strategy for improving organizational competitiveness nowadays. With the advanced development of computer technology, it is getting easier to derive an acceptance sampling plan satisfying both the producer's and consumer's quality and risk requirements. However, all the available QC tables and computer software determine the sampling plan on a noneconomic basis. In this paper, we design an economic model to determine the optimal sampling plan in a two-stage supply chain that minimizes the producer's and the consumer's total quality cost while satisfying both the producer's and consumer's quality and risk requirements. Numerical examples show that the optimal sampling plan is quite sensitive to the producer's product quality. The product's inspection, internal failure, and postsale failure costs also have an effect on the optimal sampling plan.

The economic design of variable acceptance sampling plan with rectifying inspection

Kybernetes ◽  
2015 ◽  
Vol 44 (3) ◽  
pp. 440-450 ◽  
Author(s):  
Ching-Ho Yen ◽  
Heng Ma ◽  
Chi-Huang Yeh ◽  
Chia-Hao Chang
Keyword(s):  
Sampling Plan ◽  
Acceptance Sampling ◽  
Total Quality ◽  
Quality Cost ◽  
Content Type ◽  
Acceptance Sampling Plan ◽  
Variable Sampling ◽  
Capability Indices ◽  
Sampling Cost ◽  
The One

Purpose – The purpose of this paper is to develop an economic model, which could determine the acceptance sampling plan that minimizes the quality cost for batch manufacturing. Design/methodology/approach – The authors propose a variable sampling plan based on one-sided capability indices for dealing with the quality cost requirement. Findings – The total quality cost is much more sensitive to process capability indices and inspected cost than internal and external failure costs. Research limitations/implications – The experimental data were randomly generated instead of real world ones. Practical implications – The proposed model is specifically designed for manufacturing industries with high sampling cost. Originality/value – The one-sided capability indices were utilized for the first time to be suitable for the purpose.

Mixed Acceptance Sampling Plans for Product Inspection Using Process Capability Index

2014 ◽  
Vol 26 (4) ◽  
pp. 450-459 ◽  
Author(s):  
Muhammad Aslam ◽  
Chien-Wei Wu ◽  
Muhammad Azam ◽  
Chi-Hyuck Jun
Keyword(s):  
Process Capability ◽  
Process Capability Index ◽  
Acceptance Sampling ◽  
Sampling Plans ◽  
Capability Index ◽  
Acceptance Sampling Plans

Multiple Dependent State Sampling Plan Based on Process Capability Index

2013 ◽  
Vol 41 (2) ◽  
pp. 20120012 ◽  
Author(s):  
Muhammad Aslam ◽  
Muhammad Azam ◽  
Chi-Hyuck Jun
Keyword(s):  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Capability Index ◽  
Dependent State

scholarly journals A mixed repetitive sampling plan based on process capability index

2013 ◽  
Vol 37 (24) ◽  
pp. 10027-10035 ◽  
Author(s):  
Muhammad Aslam ◽  
Muhammad Azam ◽  
Chi-Hyuck Jun
Keyword(s):  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Capability Index

scholarly journals Inspection Plan Based on the Process Capability Index Using the Neutrosophic Statistical Method

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 631 ◽  
Author(s):  
Aslam ◽  
Albassam
Keyword(s):  
Production Process ◽  
Statistical Method ◽  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Capability Index ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The Process Capability Index (PCI) has been widely used in industry to advance the quality of a product. Neutrosophic statistics is the more generalized form of classical statistics and is applied when the data from the production process or a product lot is incomplete, incredible, and indeterminate. In this paper, we will originally propose a variable sampling plan for the PCI using neutrosophic statistics. The neutrosophic operating function will be given. The neutrosophic plan parameters will be determined using the neutrosophic optimization solution. A comparison between plans based on neutrosophic statistics and classical statistics is given. The application of the proposed neutrosophic sampling plan will be given using company data.

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