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Yeonju Lee, Youngju Kim, Bogyeong Lee & Chang Ouk Kim. (2024) Discovery of fault-introducing tool groups with a numerical association rule mining method in a printed circuit board production line. International Journal of Production Research 62:9, pages 3305-3319.
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Thanh Van Nguyen, Hien Thu Pham, Hiep Minh Ha & Trang Thi Thu Tran. (2024) An integrated model of supply chain quality management, Industry 3.5 and innovation to improve manufacturers' performance – a case study of Vietnam. International Journal of Logistics Research and Applications 27:2, pages 261-283.
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Ruaa Hasan, Muhammad Mustafa Kamal, Ahmad Daowd, Tillal Eldabi, Ioannis Koliousis & Thanos Papadopoulos. (2024) Critical analysis of the impact of big data analytics on supply chain operations. Production Planning & Control 35:1, pages 46-70.
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Elisa Verna, Gianfranco Genta, Maurizio Galetto & Fiorenzo Franceschini. (2023) Zero defect manufacturing: a self-adaptive defect prediction model based on assembly complexity. International Journal of Computer Integrated Manufacturing 36:1, pages 155-168.
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Eduardo e Oliveira, Vera L. Miguéis & José L. Borges. (2022) On the influence of overlap in automatic root cause analysis in manufacturing. International Journal of Production Research 60:21, pages 6491-6507.
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Zhen He, Hao Hu, Min Zhang & Xiaofei Yin. (2022) Product quality prediction based on process data: Taking the gearbox of Company D as an example. Quality Engineering 34:3, pages 409-422.
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Laurie Hughes, Yogesh K. Dwivedi, Nripendra P. Rana, Michael D. Williams & Vishnupriya Raghavan. (2022) Perspectives on the future of manufacturing within the Industry 4.0 era. Production Planning & Control 33:2-3, pages 138-158.
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Ajit Sharma, Zhibo Zhang & Rahul Rai. (2021) The interpretive model of manufacturing: a theoretical framework and research agenda for machine learning in manufacturing. International Journal of Production Research 59:16, pages 4960-4994.
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Didier Grimaldi, Vicenc Fernandez & Carlos Carrasco. (2021) Exploring data conditions to improve business performance. Journal of the Operational Research Society 72:5, pages 1087-1098.
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Chen-Fu Chien, Yun-Siang Lin & Sheng-Kai Lin. (2020) Deep reinforcement learning for selecting demand forecast models to empower Industry 3.5 and an empirical study for a semiconductor component distributor. International Journal of Production Research 58:9, pages 2784-2804.
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Byunghoon Kim, Young-Seon Jeong, Seung Hoon Tong & Myong K. Jeong. (2020) A generalised uncertain decision tree for defect classification of multiple wafer maps. International Journal of Production Research 58:9, pages 2805-2821.
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Dominik Kozjek, Rok Vrabič, Borut Rihtaršič, Nada Lavrač & Peter Butala. (2020) Advancing manufacturing systems with big-data analytics: A conceptual framework. International Journal of Computer Integrated Manufacturing 33:2, pages 169-188.
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Yong-Hong Kuo & Andrew Kusiak. (2019) From data to big data in production research: the past and future trends. International Journal of Production Research 57:15-16, pages 4828-4853.
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Seokho Kang, Eunji Kim, Jaewoong Shim, Wonsang Chang & Sungzoon Cho. (2018) Product failure prediction with missing data. International Journal of Production Research 56:14, pages 4849-4859.
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Steven A. Melnyk, Barbara B. Flynn & Amrou Awaysheh. (2018) The best of times and the worst of times: empirical operations and supply chain management research. International Journal of Production Research 56:1-2, pages 164-192.
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Tianhui Wang, Jaeseung Baek, Myong-Kee Jeong, Seongho Seo & Jaekyung Choi. Multi-source AdaBoost with cross-weight method for virtual metrology in semiconductor manufacturing. International Journal of Production Research 0:0, pages 1-16.
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Mahdi Mokhtarzadeh, Jorge Rodríguez-Echeverría, Ivana Semanjski & Sidharta Gautama. (2024) Hybrid intelligence failure analysis for industry 4.0: a literature review and future prospective. Journal of Intelligent Manufacturing.
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Chen-Fu Chien & Jia-Yu Peng. (2024) Bayesian inference for multi-label classification for root cause analysis and probe card maintenance decision support and an empirical study. Journal of Intelligent Manufacturing.
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Seolhye Park, Jaegu Seong, Yoona Park, Yeongil Noh, Haneul Lee, Namjae Bae, Ki-Baek Roh, Rabul Seo, Bongsub Song & Gon-Ho Kim. (2024) Data-driven plasma science based plasma etching process design in OLED mass production referring to PI-VM. Plasma Physics and Controlled Fusion 66:2, pages 025014.
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Nayem Hossain, Md Hosne Mobarak, Mariam Akter Mimona, Md Aminul Islam, Amran Hossain, Fatema Tuz Zohura & Mohammad Asaduzzaman Chowdhury. (2023) Advances and significances of nanoparticles in semiconductor applications – A review. Results in Engineering 19, pages 101347.
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Young-Mok Bae, Young-Gwan Kim, Jeong-Woo Seo, Hyun-A Kim, Chang-Ho Shin, Jeong-Hwan Son, Gyu-Ho Lee & Kwang-Jae Kim. (2023) Detecting abnormal behavior of automatic test equipment using autoencoder with event log data. Computers & Industrial Engineering 183, pages 109547.
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Eduardo e Oliveira, Vera L. Miguéis & José L. Borges. (2022) Automatic root cause analysis in manufacturing: an overview & conceptualization. Journal of Intelligent Manufacturing 34:5, pages 2061-2078.
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Chiara Acciarini, Francesco Cappa, Paolo Boccardelli & Raffaele Oriani. (2023) How can organizations leverage big data to innovate their business models? A systematic literature review. Technovation 123, pages 102713.
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Youjin Lee & Yonghan Roh. (2023) An Expandable Yield Prediction Framework Using Explainable Artificial Intelligence for Semiconductor Manufacturing. Applied Sciences 13:4, pages 2660.
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Sachin S. Kamble, Rahul S. Mor & Amine Belhadi. 2023. Digital Transformation and Industry 4.0 for Sustainable Supply Chain Performance. Digital Transformation and Industry 4.0 for Sustainable Supply Chain Performance
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Hong-Wei Xu, Wei Qin, You-Long Lv & Jie Zhang. (2022) Data-Driven Adaptive Virtual Metrology for Yield Prediction in Multibatch Wafers. IEEE Transactions on Industrial Informatics 18:12, pages 9008-9016.
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Dae Woong An, Seung Kim, Hyun Kyu Kim & Chang Ouk Kim. (2022) Commonality Analysis for Detecting Failures Caused by Inspection Tools in Semiconductor Manufacturing Processes. IEEE Transactions on Semiconductor Manufacturing 35:4, pages 596-604.
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Zhen He, Hao Hu, Min Zhang, Yang Zhang & An-Da Li. (2022) A decomposition-based multi-objective particle swarm optimization algorithm with a local search strategy for key quality characteristic identification in production processes. Computers & Industrial Engineering 172, pages 108617.
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Chen-Fu Chien, Wei-Tse Hung, Chin-Wei Pan & Tran Hong Van Nguyen. (2022) Decision-based virtual metrology for advanced process control to empower smart production and an empirical study for semiconductor manufacturing. Computers & Industrial Engineering 169, pages 108245.
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Wenhan Fu, Chen-Fu Chien & Lizhen Tang. (2020) Bayesian network for integrated circuit testing probe card fault diagnosis and troubleshooting to empower Industry 3.5 smart production and an empirical study. Journal of Intelligent Manufacturing 33:3, pages 785-798.
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Lukas Longard, Lara Schiborr & Joachim Metternich. (2022) Potentials and obstacles of the use of data mining in problem-solving processes. Procedia CIRP 107, pages 252-257.
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Michael Baron, Emmanuel Yashchin & Asya Takken. 2022. Artificial Intelligence, Big Data and Data Science in Statistics. Artificial Intelligence, Big Data and Data Science in Statistics
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Tingting Luo, Guangyao Li & Naijiang Yu. (2021) Application of Artificial Intelligence and Collaborative Knowledge for Manufacturing Design. Scientific Programming 2021, pages 1-7.
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Ding Tan, Xingyu Xu, Kaixiang Yu, Sihai Zhang & Tianchi Chen. (2021) Multi-Feature Shuffle Algorithm for Root Cause Detection in Semiconductor Manufacturing. Multi-Feature Shuffle Algorithm for Root Cause Detection in Semiconductor Manufacturing.
Seolhye Park, Jaegu Seong, Yeongil Noh, Yoona Park, Yongsuk Jang, Taeyoung Cho, Jae-Ho Yang & Gon-Ho Kim. (2021) Micro-range uniformity control of the etching profile in the OLED display mass production referring to the PI-VM model. Physics of Plasmas 28:10, pages 103505.
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Jaewoong Shim, Seokho Kang & Sungzoon Cho. (2021) Active inspection for cost-effective fault prediction in manufacturing process. Journal of Process Control 105, pages 250-258.
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Chen-Fu Chien & Chia-Cheng Chen. (2021) Adaptive parametric yield enhancement via collinear multivariate analytics for semiconductor intelligent manufacturing. Applied Soft Computing 108, pages 107385.
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Gorkem Sariyer, Sachin Kumar Mangla, Yigit Kazancoglu, Ceren Ocal Tasar & Sunil Luthra. (2021) Data analytics for quality management in Industry 4.0 from a MSME perspective. Annals of Operations Research.
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Seokho Kang. (2020) Product failure prediction with missing data using graph neural networks. Neural Computing and Applications 33:12, pages 7225-7234.
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Pedro Espadinha-Cruz, Radu Godina & Eduardo M. G. Rodrigues. (2021) A Review of Data Mining Applications in Semiconductor Manufacturing. Processes 9:2, pages 305.
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Dan Jiang, Weihua Lin & Nagarajan Raghavan. (2021) A Gaussian Mixture Model Clustering Ensemble Regressor for Semiconductor Manufacturing Final Test Yield Prediction. IEEE Access 9, pages 22253-22263.
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Chen-Fu Chien, Yin-Hung Chen & Mei-Fang Lo. (2020) Advanced Quality Control (AQC) of Silicon Wafer Specifications for Yield Enhancement for Smart Manufacturing. IEEE Transactions on Semiconductor Manufacturing 33:4, pages 569-577.
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Chieh-Yu Chen, Shi-Chung Chang & Da-Yin Liao. (2020) Equipment Anomaly Detection for Semiconductor Manufacturing by Exploiting Unsupervised Learning from Sensory Data. Sensors 20:19, pages 5650.
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Tianteng Wang, Xuping Wang, Ruize Ma, Xiaoyu Li, Xiangpei Hu, Felix T. S. Chan & Junhu Ruan. (2020) Random Forest-Bayesian Optimization for Product Quality Prediction With Large-Scale Dimensions in Process Industrial Cyber–Physical Systems. IEEE Internet of Things Journal 7:9, pages 8641-8653.
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Hung-Kai Wang & Chen-Fu Chien. (2020) An inverse-distance weighting genetic algorithm for optimizing the wafer exposure pattern for enhancing OWE for smart manufacturing. Applied Soft Computing 94, pages 106430.
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Yuting Sun & Liang Zhang. (2020) Parameter Identification for Multiple-Machine Bernoulli Lines using Statistical Learning Methods. Parameter Identification for Multiple-Machine Bernoulli Lines using Statistical Learning Methods.
Chen-Fu Chien, Chung-Jen Kuo & Chih-Min Yu. (2018) Tool allocation to smooth work-in-process for cycle time reduction and an empirical study. Annals of Operations Research 290:1-2, pages 1009-1033.
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Chia-Yu Hsu, Wei-Ju Chen & Ju-Chien Chien. (2020) Similarity matching of wafer bin maps for manufacturing intelligence to empower Industry 3.5 for semiconductor manufacturing. Computers & Industrial Engineering 142, pages 106358.
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Chien-Chun Ku, Chen-Fu Chien & Kang-Ting Ma. (2020) Digital transformation to empower smart production for Industry 3.5 and an empirical study for textile dyeing. Computers & Industrial Engineering 142, pages 106297.
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Seokho Kang. (2018) Joint modeling of classification and regression for improving faulty wafer detection in semiconductor manufacturing. Journal of Intelligent Manufacturing 31:2, pages 319-326.
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Hongling Liu & Wan Di. (2020) Application of Differential Privacy in Location Trajectory Big Data. Application of Differential Privacy in Location Trajectory Big Data.
Dasol Kim, Mintae Kim & Wooju Kim. (2020) Wafer Edge Yield Prediction Using a Combined Long Short-Term Memory and Feed- Forward Neural Network Model for Semiconductor Manufacturing. IEEE Access 8, pages 215125-215132.
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Dan Jiang, Weihua Lin & Nagarajan Raghavan. (2020) A Novel Framework for Semiconductor Manufacturing Final Test Yield Classification Using Machine Learning Techniques. IEEE Access 8, pages 197885-197895.
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Seokho Kang. (2020) Rotation-Invariant Wafer Map Pattern Classification With Convolutional Neural Networks. IEEE Access 8, pages 170650-170658.
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Jrjung Lyu, Chia Wen Liang & Ping-Shun Chen. (2020) A Data-Driven Approach for Identifying Possible Manufacturing Processes and Production Parameters That Cause Product Defects: A Thin-Film Filter Company Case Study. IEEE Access 8, pages 49395-49411.
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Ahmed Ismail, Hong-Linh Truong & Wolfgang Kastner. (2019) Manufacturing process data analysis pipelines: a requirements analysis and survey. Journal of Big Data 6:1.
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Amine Belhadi, Karim Zkik, Anass Cherrafi, Sha'ri M. Yusof & Said El fezazi. (2019) Understanding Big Data Analytics for Manufacturing Processes: Insights from Literature Review and Multiple Case Studies. Computers & Industrial Engineering 137, pages 106099.
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Yun-Chia Chen, Chen-Fu Chien & Chun-Yao Wang. (2019) Empirical Study of Multi-Objective Parameter Optimization in Wire Bonding Process. Empirical Study of Multi-Objective Parameter Optimization in Wire Bonding Process.
Dorina Weichert, Patrick Link, Anke Stoll, Stefan Rüping, Steffen Ihlenfeldt & Stefan Wrobel. (2019) A review of machine learning for the optimization of production processes. The International Journal of Advanced Manufacturing Technology 104:5-8, pages 1889-1902.
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Chin-Yi Lin, Yu-Ming Hsieh, Fan-Tien Cheng, Yu-Ru Yang & Muhammad Adnan. (2018) Interaction-Effect Search Algorithm for the KSA Scheme. IEEE Robotics and Automation Letters 3:4, pages 2778-2785.
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Pramod Govindaraju, Sebastian Achter, Thomas Ponsignon, Hans Ehm & Matthias Meyer. (2018) Comparison of two clustering approaches to find demand patterns in semiconductor supply chain planning. Comparison of two clustering approaches to find demand patterns in semiconductor supply chain planning.
Marzieh Khakifirooz, Chen Fu Chien & Ying-Jen Chen. (2018) Bayesian inference for mining semiconductor manufacturing big data for yield enhancement and smart production to empower industry 4.0. Applied Soft Computing 68, pages 990-999.
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Pengfei Tong, Junguo Lu & Kihyeon Yun. (2018) Fault detection for semiconductor quality control based on Spark using data mining technology. Fault detection for semiconductor quality control based on Spark using data mining technology.
Shengping Lv, Hoyeol Kim, Binbin Zheng & Hong Jin. (2018) A Review of Data Mining with Big Data towards Its Applications in the Electronics Industry. Applied Sciences 8:4, pages 582.
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