Volume 68 Issue 4
Apr.  2024
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LI Liangbo, WANG Xue, LI Hairong, GUO Hai, ZHU Xinwang. MSA Analysis and Research on Automatic Verification Assembly Lines for Electric Energy Measuring Instruments[J]. Metrology Science and Technology, 2024, 68(4): 71-78. doi: 10.12338/j.issn.2096-9015.2023.0355
Citation: LI Liangbo, WANG Xue, LI Hairong, GUO Hai, ZHU Xinwang. MSA Analysis and Research on Automatic Verification Assembly Lines for Electric Energy Measuring Instruments[J]. Metrology Science and Technology, 2024, 68(4): 71-78. doi: 10.12338/j.issn.2096-9015.2023.0355

MSA Analysis and Research on Automatic Verification Assembly Lines for Electric Energy Measuring Instruments

doi: 10.12338/j.issn.2096-9015.2023.0355
  • Received Date: 2023-12-18
  • Accepted Date: 2024-01-23
  • Rev Recd Date: 2024-01-17
  • Available Online: 2024-04-01
  • Publish Date: 2024-04-01
  • The automatic verification assembly lines for electric energy measuring instruments can experience performance degradation or even malfunctions during long-term online high-load operation, leading to deviations in the test results of electric energy measurement errors. In order to accurately grasp the fluctuation patterns of the automatic verification assembly line measurement system for electric energy measuring instruments, determine the total variation from the measurement system and the differences in each variable, and improve the accuracy and reliability of the measurement system, an analysis plan for the assembly line measurement system was designed. Based on the analysis of the structural characteristics and working principles of the assembly line, a new experimental scheme is proposed, and a measurement system analysis plan is formulated. Taking the automated calibration assembly line of low-voltage current transformers as an example, the repeatability and reproducibility, bias and linearity, and stability of the measurement system were analyzed. The analysis results show that the variation of the measurement system accounts for 1.67% of the total variation, the variation index GR&R is 18.21%, the bias ratio is 5.4%, the linearity ratio is 8.7%, and there are 7 distinguishable categories. The measurement system has the required measurement ability and is in a conditionally acceptable state. Further analysis of the sources of variation reveals that reproducibility is the main factor of variation, and there are significant differences in the consistency of measurement systems at different workstations. Finally, based on the analysis results of the measurement system, production site management, and operation and maintenance experience, suggestions for improving the measurement system are proposed.
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