• Arpit Tripathi
• Soniya Singh
• Srivaramangai R

The emergence of Industry 4.0 is to optimize production processes, increase efficiency and reduce costs[1]. The integration of big data analytics into smart design enables the collection and analysis of large volumes of data from multiple sources, including sensors, machines, and human input. This article provides a qualitative review of the existing literature on big data analytics in smart manufacturing, including challenges, implications, and future directions. We examine different methods and techniques used in big data analysis, such as machine learning, deep learning and natural language processing, and their applications at different levels of the manufacturing process, from product to after-sales service. We also discuss issues related to the use of big data analytics in smart design, including data quality, data security, and data management. Finally, we present future research directions and recommendations for the use of big data analytics in intelligent design, such as the development of hybrid algorithms and the integration of time analysis. This study will be beneficial for researchers, practitioners and policy makers who want to use big data analytics for smart manufacturing

Smart Manufacturing, Semiconductor, Big Data, Data Analysis, Big Data Architecture

"COMPREHENSIVE REVIEW OF USING BIG DATA ANALYTICS FOR SMART SEMICONDUCTOR MANUFACTURING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.f604-f608, May-2023, Available :http://www.jetir.org/papers/JETIR2305588.pdf

"COMPREHENSIVE REVIEW OF USING BIG DATA ANALYTICS FOR SMART SEMICONDUCTOR MANUFACTURING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppf604-f608, May-2023, Available at : http://www.jetir.org/papers/JETIR2305588.pdf