International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Process Optimization in Semiconductor Manufacturing: The Role of Big Data Analytics in Yield Improvement

Author(s) Tarun Parmar
Country United States
Abstract The semiconductor industry faces increasing challenges in maintaining high yields and reducing costs as manufacturing processes become more complex. Big-data analytics has emerged as a powerful tool for process optimization, enabling manufacturers to extract valuable insights from vast amounts of production data and make data-driven decisions. This review explores the role of big data analytics in semiconductor manufacturing, focusing on its applications in yield improvement. We discuss traditional approaches to process optimization, such as Six Sigma and Design of Experiments, and highlight their limitations in addressing the complexity of modern semiconductor manufacturing. We then delve into the transformative potential of big data analytics, examine key data sources in semiconductor fabs, and integrate advanced analytical techniques, such as machine learning and deep learning, for fault detection, classification, and predictive maintenance. This review also covers the importance of real-time analytics and edge computing in reducing latency and improving process control, as well as the challenges associated with data integration and management across manufacturing systems. We present case studies demonstrating the successful implementation of big data analytics in semiconductor fabrication, showing quantitative improvements in yield, cycle time, and overall equipment effectiveness. Finally, we discuss the technical and organizational challenges in implementing big data analytics and highlight emerging trends and future research directions, such as quantum computing and AI-driven process design. This review provides a comprehensive overview of the transformative potential of big data analytics in semiconductor manufacturing and its critical role in driving innovation and efficiency in the industry.
Keywords Semiconductor manufacturing, Yield improvement, Big-data analytics, Process optimization, Machine learning, Predictive maintenance, Defect detection
Field Sosiologi > Pendidikan
Published In Volume 1, Issue 2, September-October 2019
Published On 2019-09-11
DOI https://doi.org/10.36948/ijfmr.2019.v01i02.23444
Short DOI https://doi.org/g82jbs
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E-ISSN 2582-2160
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