Designing an enhanced acceptance sampling strategy with the process loss index

To reconcile the differences between loose and stringent models and address product specifications sensitive to target value variations, a process loss index Le was introduced. This index assesses process capability by incorporating the concept of the quality loss function. Some researchers have integrated this index into variables sampling plans. In particular, Repetitive Group Sampling Plans (RGSP) offer cost advantages over single sampling plans, but their infinite sampling nature might lead to inefficiencies. To address this, our study introduces a modified RGSP with an adjustable lot disposition mechanism based on the process loss index. We establish an optimisation model to minimise the anticipated number of sample items, considering quality and risk constraints. Performance is compared to conventional methods using metrics such as average sample number, operating characteristic curve, and average run length. Ultimately, a practical demonstration is provided through an example to illustrate and validate the feasibility of the proposed plan. [Submitted: 22 January 2024; Accepted: 17 May 2024]

Authors

Institutions

Publication Details

Journal
European J of Industrial Engineering
Published
2025-01-01
DOI
https://doi.org/10.1504/ejie.2025.147830
Primary Topic
Advanced Statistical Process Monitoring
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Designing an enhanced acceptance sampling strategy with the process loss index

Chien‐Wei Wu, Armin Darmawan
European J of Industrial Engineering
Advanced Statistical Process Monitoring
article

Designing an enhanced acceptance sampling strategy with the process loss index

Chien‐Wei Wu, Armin Darmawan
article en

Abstract

To reconcile the differences between loose and stringent models and address product specifications sensitive to target value variations, a process loss index Le was introduced. This index assesses process capability by incorporating the concept of the quality loss function. Some researchers have integrated this index into variables sampling plans. In particular, Repetitive Group Sampling Plans (RGSP) offer cost advantages over single sampling plans, but their infinite sampling nature might lead to inefficiencies. To address this, our study introduces a modified RGSP with an adjustable lot disposition mechanism based on the process loss index. We establish an optimisation model to minimise the anticipated number of sample items, considering quality and risk constraints. Performance is compared to conventional methods using metrics such as average sample number, operating characteristic curve, and average run length. Ultimately, a practical demonstration is provided through an example to illustrate and validate the feasibility of the proposed plan. [Submitted: 22 January 2024; Accepted: 17 May 2024]

European J of Industrial EngineeringVol. 20(2)
National Tsing Hua University (TW), Hasanuddin University (ID)
Openalex Percentile: Top 81%
Advanced Statistical Process Monitoring
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Designing an enhanced acceptance sampling strategy with the process loss index — Chien‐Wei Wu, Armin Darmawan · European J of Industrial Engineering (2025) | TGRS Research Map | TGRS