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Chen-Fu Chien
Researcher at National Tsing Hua University
Publications - 275
Citations - 7469
Chen-Fu Chien is an academic researcher from National Tsing Hua University. The author has contributed to research in topics: Wafer fabrication & Semiconductor device fabrication. The author has an hindex of 38, co-authored 256 publications receiving 6137 citations. Previous affiliations of Chen-Fu Chien include Tsinghua University & TSMC.
Papers
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An AHP-based approach to ERP system selection
TL;DR: This study presents a comprehensive framework for selecting a suitable ERP system that can systematically construct the objectives of ERP selection to support the business goals and strategies of an enterprise, identify the appropriate attributes, and set up a consistent evaluation standard for facilitating a group decision process.
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Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry
Chen-Fu Chien,Li-Fei Chen +1 more
TL;DR: A data mining framework based on decision tree and association rules to generate useful rules for personnel selection is developed and can provide decision rules relating personnel information with work performance and retention.
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Circular economy meets industry 4.0: Can big data drive industrial symbiosis?
TL;DR: In this paper, the authors pointed out that despite the clear benefits of big data-driven industrial symbiosis, corporates have noted that social, environmental and economic perspectives are also highly appreciated in the cross-industry networks.
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Data mining for yield enhancement in semiconductor manufacturing and an empirical study
TL;DR: This study aims to develop a framework for data mining and knowledge discovery from database that consists of a Kruskal-Wallis test, K-means clustering, and the variance reduction splitting criterion to investigate the huge amount of semiconductor manufacturing data and infer possible causes of faults and manufacturing process variations.
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Hybrid data mining approach for pattern extraction from wafer bin map to improve yield in semiconductor manufacturing
Shao-Chung Hsu,Chen-Fu Chien +1 more
TL;DR: This study proposes a hybrid data mining approach that integrates spatial statistics and adaptive resonance theory neural networks to quickly extract patterns from wafer bin maps and associate with manufacturing defects.