Design of moving average chart and auxiliary information based chart using extended EWMA
Muhammad Naveed1, Muhammad Azam2, Muhammad Shujaat Nawaz3
1Department of Statistics, Govt Graduate College (B) Gulberg, Lahore, Pakistan.
Scientific Reports
|April 5, 2023
Summary
This study introduces novel Extended EWMA (EEWMA) and EWMA control charts for enhanced process monitoring. These charts effectively detect shifts in manufacturing processes, outperforming existing methods.
Area of Science:
- Industrial Engineering
- Statistical Process Control
Background:
- Control charts are vital for monitoring manufacturing processes.
- Improving control chart efficiency involves using memory-based estimators or auxiliary information.
Purpose of the Study:
- To present Extended EWMA (EEWMA) and EWMA control charts for process location monitoring.
- To evaluate charts using moving average (MA) statistics with known and unknown auxiliary information.
- To propose an EEWMA control chart incorporating auxiliary information.
Main Methods:
- Development of EEWMA and EWMA monitoring charts.
- Utilizing moving average (MA) statistics.
- Comparison based on Average Run Length (ARL) to assess performance.
- Evaluation under conditions of known and unknown auxiliary information.
Main Results:
- The proposed EEWMA and EWMA charts demonstrate superior performance in detecting process location shifts.
- The EEWMA chart with auxiliary information shows significant improvements.
- The developed charts outperform existing control charts in terms of ARL.
Conclusions:
- The novel EEWMA and EWMA control charts offer enhanced capabilities for process monitoring.
- These charts provide a practical framework for identifying sustainable improvements in industrial settings.
- The proposed methods are effective in detecting various types of process shifts.
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