Design of a new attribute chart based on inspection run length

The conventional np chart detects shifts in fraction nonconforming of the process depending on the total number of nonconforming units, which is obtained until all of the units within a sample are completely inspected. To improve the effectiveness of inspection capacity, this paper presents a new attribute control chart, namely the Inspection Run Length (IRL) control chart, which detects shifts in fraction nonconforming of the process depending on a novel inspection strategy. This strategy employs information about the number of conforming and nonconforming units and inspection run length during the inspection process to curtail the number of units that need to be inspected. The optimal design parameters of the proposed control chart are derived based on optimising average run length (ARL) properties. In addition, the performance of the proposed IRL chart is evaluated and compared with the np chart and CRL-type charts. Comparison studies show that the proposed chart achieves a significant reduction in inspection time and cost and an improvement in performance (a lower out-of-control ARL) while holding the false alarm rate ( in-control ARL) at a specified level. Finally, two industrial examples are given to illustrate how to simply apply the proposed chart to the manufacturing process.

Authors

Institutions

Publication Details

Journal
International Journal of Production Research
Published
2024-10-02
DOI
https://doi.org/10.1080/00207543.2024.2408764
Citations
2
Primary Topic
Advanced Statistical Process Monitoring
Type
article
Field-Weighted Citation Impact
0.92

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design of a new attribute chart based on inspection run length

Chunhui Liu, Zhibin Zheng, Haodong Liu, Wenhui Zhou
2 citations
International Journal of Production Research
Advanced Statistical Process Monitoring
0.92
article

Design of a new attribute chart based on inspection run length

Chunhui Liu, Zhibin Zheng, Haodong Liu, Wenhui Zhou
article en
2 citations

Abstract

The conventional np chart detects shifts in fraction nonconforming of the process depending on the total number of nonconforming units, which is obtained until all of the units within a sample are completely inspected. To improve the effectiveness of inspection capacity, this paper presents a new attribute control chart, namely the Inspection Run Length (IRL) control chart, which detects shifts in fraction nonconforming of the process depending on a novel inspection strategy. This strategy employs information about the number of conforming and nonconforming units and inspection run length during the inspection process to curtail the number of units that need to be inspected. The optimal design parameters of the proposed control chart are derived based on optimising average run length (ARL) properties. In addition, the performance of the proposed IRL chart is evaluated and compared with the np chart and CRL-type charts. Comparison studies show that the proposed chart achieves a significant reduction in inspection time and cost and an improvement in performance (a lower out-of-control ARL) while holding the false alarm rate ( in-control ARL) at a specified level. Finally, two industrial examples are given to illustrate how to simply apply the proposed chart to the manufacturing process.

International Journal of Production ResearchVol. 63(8)
Guangdong University of Technology (CN), Zhengzhou University (CN), South China University of Technology (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Science Fund for Distinguished Young Scholars of Fujian Province
Openalex Percentile: Top 21%
Advanced Statistical Process Monitoring
0.92
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.

Design of a new attribute chart based on inspection run length — Chunhui Liu, Zhibin Zheng, et al. · International Journal of Production Research (2024) | TGRS Research Map | TGRS