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
- Chunhui Liu (ORCID: https://orcid.org/0000-0002-4462-0602)
- Zhibin Zheng
- Haodong Liu (ORCID: https://orcid.org/0000-0001-8533-0882)
- Wenhui Zhou (ORCID: https://orcid.org/0000-0002-5078-9041)
Institutions
- Guangdong University of Technology (CN)
- Zhengzhou University (CN)
- South China University of Technology (CN)
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
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Science Fund for Distinguished Young Scholars of Fujian Province