Using intelligent technology and real-time feedback algorithm to improve manufacturing process in IoT semiconductor indu
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Using intelligent technology and real‑time feedback algorithm to improve manufacturing process in IoT semiconductor industry Bin Li1 · Ruey‑Shun Chen1 · C.‑Y. Liu2 Accepted: 14 October 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract To enable the Internet of things, the semiconductor manufacturing process has progressed from the micron to the deep submicron level. Quality improvement is one of the great challenges in wafer fabrication. Computer-integrated manufacturing (CIM) has arisen as a means by which to reduce wafer rework and continuously improve the semiconductor production process. This study uses statistical process control (SPC) and data mining technology to analyze the collected semiconductor process data. A real-time feedback algorithm is employed to ensure that each product lot is manufactured using optimized process parameters.This maximizes production capability, increases the semiconductor yield rate and reduces the cost of manufacturing. This paper focuses on wafer fabrication facilities (often called “fabs,” or “foundries”). The data mining architecture is implemented between CIM and the manufacturing execution system. Association rules and the k-means clustering algorithm are used together with real-time feedback control analysis to extract and analyze each parameter that affects the semiconductor production yield. This combination of realtime feedback and SPC using historical process data allows the system to predict the optimum process parameters for the next lot. The system compensates dynamically to accommodate differences among various machines and products, giving each machine a level of flexibility in manufacturing the product. The proposed semiconductor system can be applied to traditional manufacturing industry process analysis. Our results show how our system can improve the semiconductor manufacturing process in terms of processing capability, yield rate, stability and flexibility, while reducing costs, thus creating a competitive advantage for the wafer fab. Keywords Internet of things (IoT) · Intelligent technology · Manufacturing process · Semiconductor industry · Real-time feedback algorithm
* Ruey‑Shun Chen [email protected] Extended author information available on the last page of the article
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1 Introduction Traditional semiconductor information systems cannot provide effective solutions for today’s wafer manufacturing processes. To remain competitive, a company’s business operations must be run efficiently, and decisions regarding process improvements must be made quickly. These are the key success factors for modern businesses [1]. For the semiconductor industry, combining data mining methods with computer-integrated manufacturing (CIM) systems to analyze actual process data can increase the yield rate while reducing process cycle time, manufacturing costs and inventory [2, 3]. Moore’s law states that the processing power of a chip of a given size will double every 18 months, or the size of a chip of
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