An artificial intelligence transformation model – pod redesign of photomasks in semiconductor manufacturing

Abstract

ABSTRACTThis paper proposes a new enterprise intelligentization framework, by making the transition from process transformation to artificial intelligence (AI) transformation. The novel transformation framework can be decomposed into the conceptual model of AI strategic planning, the procedural model, the operational model, and the analytics model. For leading-edge microchip production, a new AI transformation project regarding the reticle SMIF pod (RSP) transport system designed by a medium-sized semiconductor tool vendor in Taiwan is presented. The technical advantages, gained from the implementation of the presented AI transformation project, over the existing RSP systems are manifold. The throughput and yield rate significantly increase on a semiconductor-fabrication-plant basis. The clean room construction costs less by approximately 3 million dollars per FAB, mainly attributed to the redesigned automatic optical inspection flow. The proposed model-based framework proves to be a viable tool from the process transformation to the AI transformation in the semiconductor manufacturing.KEYWORDS: Process transformationAI transformationassisted intelligencesemiconductor manufacturingreticle SMIF pod (RSP) Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsShu-Kai S. FanShu-Kai S. Fan received the Ph.D. degree in Industrial, Manufacturing and Systems Engineering from the University of Texas at Arlington in 1996. He is currently a professor in the Department of Industrial Engineering and Management, National Taipei University of Technology (NTUT), Taiwan, R.O.C. Dr. Fan now serves as Editor-in-Chief of Engineering Optimization published by Taylor and Francis. His research interests include quality engineering, image processing, big data analytics, machine/deep learning, and advanced process control of semiconductor manufacturing.Ming-Shen ChenMing-Shen Chen received his M.S. degree in Information and Financial Management from National Taipei University of Technology (NTUT), Taiwan, R.O.C. His research interests include advanced process control of semiconductor manufacturing, and deep learning applications in industry. He now works in Stek Co. Ltd as the general manager.Chia-Yu HsuChia-Yu Hsu is a professor in the Department of Industrial Management, National Taiwan University of Science and Technology (NTUST). He received B.S. in Statistics from National Chung Kung University (2002), M.S. in Industrial Engineering and Engineering Management from National Tsing Hua University (2004) and Ph.D. in Industrial Engineering and Engineering Management from National Tsing Hua University (2009). His current research interests include big data analytics, machine learning & deep learning, manufacturing intelligence, defect inspection, fault detection, time series data analysis and predictive maintenance.You-Jin ParkYou-Jin Park is currently a professor in the Department of Industrial Engineering and Management, National Taipei University of Technology (NTUT), Taiwan, R.O.C. He received the Ph.D. degree in Industrial Engineering from Arizona State University, Tempe, AZ, US. His research interests include quality engineering, advanced process control and few shot learning.