摘要(英) |
Testing system integration and graphical user interface play a pivotal role in the industry. This paper integrates the boomerang chart, yield, and B-score analysis, and introduces the system into the graphical user interface. This framework is more convenient for researchers to analyze.
The more complete the system, the more important of platform integration and graphical user interface. In addition to making the framework more humanize, it can greatly improve the convenience of operations. Use MATLAB data storage to build a database and GUIDE to build a graphical user interface. The establishment of the database makes the data to be prepared in advance. When needed for review, the database file can be selected according to the time, and the establishment of the database can also effectively reduce the running time; The graphical user interface is designed with an appropriate file management and a well-organized database to generate the required graphics. The establishment of the platform not only reduces the difficulty of operation, but also accelerates the research effectiveness.
This paper establishes a graphical analysis framework. Storing various data into a database which is used on boomerang analysis, and displaying the graphic through a graphical user interface. Researchers can avoid confusion because of the amount of data that is difficult to estimate and can experience better operating processes.
|
參考文獻 |
[1] J.E. Chen, M.J. Wang, Y.S. Chang, S.C. Shyu, and Y.Y. Chen, “Yield Improvement by Test Error Cancellation ”, Proceedings of the Fifth Asian Test Symposium (ATS’96), pp.258-262, Nov. 1996.
[2] C.K. Hsu, F. Lin, K.T. Cheng, W. Zhang, X. Li, J.M. Carulli, and K.M. Butler, “Test data analytics - Exploring spatial and test-item correlations in production test data”, in International Test Conference (ITC), pp.1-10, Sep. 2013.
[3] M.J. Wu, J.S.R. Jang, and J.L. Chen, “Wafer Map Failure Pattern Recognition and Similarity Ranking for Large-scale Datasets”, in IEEE Transactions on Semiconductor Manufacturing, vol.28, no.1, pp.1-12, Feb. 2015.
[4] F. Lin, C.K. Hsu, and K.T. Cheng, “Learning from Production Test Data: Correlation Exploration and Feature Engineering”, in Asian Test Symposium (ATS), pp.236-241, Nov. 2014.
[5] F. Lin, C.K. Hsu, and K.T. Cheng, “Feature engineering with canonical analysis for effective statistical tests screening test escapes”, in International Test Conference (ITC), pp.1-10, Oct. 2014.
[6] 林正田, “Wafer Map Analysis from a Random-Defect-Source Perspective” ,碩士論文,中央大學,2012.
[7] 曾國銓, “A Non-uniformly Distributed Defect Map Analysis by Quantification Model” ,碩士論文,中華大學,2013.
[8] 蕭寶威, “Wafer Map Analysis from Random Distributed Defects” ,碩士論文,中央大學,2016.
[9] 葉昱緯, “Application of Boomerang Chart to Real-World Mass Production Wafer Maps” ,碩士論文,中央大學,2016.
[10] 鄭育典, “An Accelerated C-Core for Calculating the Cluster Number in Wafer Map Analysis” ,碩士論文,中央大學,2018.
[11] 黃昱凱, “Accelerated Core for the Calculation of the Randomness Features of Wafer Maps” ,碩士論文,中央大學,2018.
[12] 曾聖翔, “Applications of Randomness and Homogeneity Test to Enhance the Systematic Error Resolution for Wafer Map Analysis” ,碩士論文,中央大學,2018.
|