An Empirical Study on GR&R of AOI Machine in Packaging and Testing Industr
| Autor: | HUANG, YU-HSIANG, 黃鈺翔 |
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| Rok vydání: | 2019 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 107 This research is based on the Automatic Optical Inspection (AOI) machine of the company and conducts empirical research on Measurement System Analysis (MSA). The machine must have positioning errors that cannot be controlled. The temperature and humidity environment of the workplace where the equipment is parked, and the consistency of the measurement operations of different classes will affect the accuracy and precision of the measurement. Therefore, it is necessary to pay attention to whether there are some perfect measures in the measurement process, such as standards, procedures, calibrated and effective measuring instruments, productive parts, inspector training, environmental optimization, etc., after a controlled measurement process, measurement Data analysis will be acceptable and informative. The relationship between (Gauge Repeatability and Reproducibility, GR&R) and process capability indicators are used to explore the rationality of the GR&R criteria in QS9000/TS16949 and to establish the appropriate scope for the development of GR&R criteria. In addition, for the three estimation methods of GR&R research: Analysis of Variance (ANOVA), the traditional GR&R method (Classical GR&R) and Long Form method proposed by the control chart are used for comparative analysis. It is expected that the verification of product measurement equipment will be carried out through this research, and the research results will help case companies to conduct correct analysis and judgment of MSA mutations. Reward the quality assurance department to improve the machine or as a revised data specification to improve the quality of the product and win orders through customer verification. Key words: Automatic Optical Inspection machine, Measurement System Analysis, Gage Repeatability and Reproducibility. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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