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Developing an Integrated Optimization Inspection Scheme with A Flexible Sampling Mechanism for Quality Determination Based on the Process Loss Index.

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Title: Developing an Integrated Optimization Inspection Scheme with A Flexible Sampling Mechanism for Quality Determination Based on the Process Loss Index.
Authors: Darmawan, Armin1 darmawanarmin@gmail.com, Armayfa, Afirah1 afiraharmayfa@gmail.com, Sesa, Meti1 metisesa13796@gmail.com
Source: Journal of Industrial Engineering & Management. 2026, Vol. 19 Issue 1, p120-134. 15p.
Subjects: Adaptive sampling (Statistics), Sampling methods, Mathematical optimization, Quality assurance, Quality control
Abstract: Purpose: This study examines the quick switching sampling (QSS) system. This well-established sampling scheme incorporates two single sampling plans (SSPs) with adaptive transition rules between normal and tightened inspections. The QSS system dynamically adjusts inspection stringency in response to fluctuations in product quality, implementing normal inspection when quality meets satisfactory standards, and tightened inspection when quality deterioration is detected. Design/methodology/approach: Traditional acceptance sampling plans often evaluate product quality based on process yield, which overlooks subtle variations within specification limits. To address this limitation, a novel performance metric, the process loss index Le, was developed to quantify quality loss. This index is calculated as the ratio of expected quadratic loss to the square of half the specification width. Utilizing this index, two models of QSS sampling schemes were constructed by solving nonlinear optimization mathematical models and evaluated using general metrics. The efficacy and characteristics of these schemes were investigated, compared, and discussed. Findings: The results highlight the potential of QSS systems to enhance the effectiveness of quality control while maintaining stringent quality standards. Besides, the proposed plan demonstrates superiority over the conventional plan in terms of adaptability, particularly with sample size adjustments, when switching to a stricter inspection plan in response to deteriorating lot quality and improved efficiency. Originality/value: This study presents a novel approach to quality control by integrating the process loss index into the QSS system, offering a fresh perspective on sampling methodologies. The integration of QSS with the process loss index Le marks a significant contribution to the field of quality control, enabling more nuanced evaluations of product quality and providing a groundbreaking framework for optimizing quality control processes while minimizing sample sizes, thereby enhancing efficiency and effectiveness. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Industrial Engineering & Management is the property of Omnia Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Developing an Integrated Optimization Inspection Scheme with A Flexible Sampling Mechanism for Quality Determination Based on the Process Loss Index.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Industrial+Engineering+%26+Management%22">Journal of Industrial Engineering & Management</searchLink>. 2026, Vol. 19 Issue 1, p120-134. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Adaptive+sampling+%28Statistics%29%22">Adaptive sampling (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Sampling+methods%22">Sampling methods</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+assurance%22">Quality assurance</searchLink><br /><searchLink fieldCode="DE" term="%22Quality+control%22">Quality control</searchLink>
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  Label: Abstract
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  Data: Purpose: This study examines the quick switching sampling (QSS) system. This well-established sampling scheme incorporates two single sampling plans (SSPs) with adaptive transition rules between normal and tightened inspections. The QSS system dynamically adjusts inspection stringency in response to fluctuations in product quality, implementing normal inspection when quality meets satisfactory standards, and tightened inspection when quality deterioration is detected. Design/methodology/approach: Traditional acceptance sampling plans often evaluate product quality based on process yield, which overlooks subtle variations within specification limits. To address this limitation, a novel performance metric, the process loss index Le, was developed to quantify quality loss. This index is calculated as the ratio of expected quadratic loss to the square of half the specification width. Utilizing this index, two models of QSS sampling schemes were constructed by solving nonlinear optimization mathematical models and evaluated using general metrics. The efficacy and characteristics of these schemes were investigated, compared, and discussed. Findings: The results highlight the potential of QSS systems to enhance the effectiveness of quality control while maintaining stringent quality standards. Besides, the proposed plan demonstrates superiority over the conventional plan in terms of adaptability, particularly with sample size adjustments, when switching to a stricter inspection plan in response to deteriorating lot quality and improved efficiency. Originality/value: This study presents a novel approach to quality control by integrating the process loss index into the QSS system, offering a fresh perspective on sampling methodologies. The integration of QSS with the process loss index Le marks a significant contribution to the field of quality control, enabling more nuanced evaluations of product quality and providing a groundbreaking framework for optimizing quality control processes while minimizing sample sizes, thereby enhancing efficiency and effectiveness. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Journal of Industrial Engineering & Management is the property of Omnia Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3926/jiem.9061
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        Text: English
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        Type: general
      – SubjectFull: Sampling methods
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Quality assurance
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      – TitleFull: Developing an Integrated Optimization Inspection Scheme with A Flexible Sampling Mechanism for Quality Determination Based on the Process Loss Index.
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            NameFull: Armayfa, Afirah
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            – D: 01
              M: 01
              Text: 2026
              Type: published
              Y: 2026
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