Practical Information Diffusion Techniques to Accelerate New Product Pilot Runs

  • 陳 文智

Student thesis: Doctoral Thesis


Under the increasing pressure of global competition product life cycles are becoming shorter and shorter This means that better methods are needed to analyze the limited information obtained at the trial stage in order to derive useful knowledge that can aid mass production Machine learning algorithms such as data mining techniques are widely applied to solve this problem However a certain amount of training samples is usually required to determine the validity of the information that is obtained This study uses only a few data points to estimate the range of data attribute domains with a data diffusion method in order to derive more useful information Then based on practical engineering experience we generate virtual samples with a noise disturbance method to improve the robustness of the predictions derived from multiple linear regression (MLR) One real dataset obtained from a large TFT-LCD company is examined in the experiment and the results show that the proposed approach is effective
Date of Award2015 Apr 16
Original languageEnglish
SupervisorDer-Chiang Li (Supervisor)

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