Authors:
Padmaja Pulivarthy

Addresses:
1Department of Semiconductor Senior Software Engineer & Architect IT Infrastructure, Samsung, Austin, Texas, USA. p.pulivarthy@samsung.com1

Abstract:

The semiconductor industry has made significant advancements in wafer assembly, necessitating the evolution of Database Management Systems (DBMS) to handle increasingly complex and voluminous data. This paper examines the specializations of DBMS tailored for the semiconductor industry, showcasing innovations that integrate advanced data analytics with real-time processing on scalable storage solutions. These innovations enhance Effectiveness, Precision, and Efficiency (EAP) by 40%, reducing defect rates by one-fifth from 2021 to 2025. The study explores modern DBMS designs and their role in predictive maintenance, quality control, and process optimization. Leveraging big data and machine learning, these systems can swiftly analyze large datasets to identify patterns and outliers for improved decision-making. Additionally, modern DBMS offers robust data security features, such as anomaly detection and encryption, which have minimized breaches and increased compliance. However, challenges remain, including integrating new technologies with legacy systems and addressing the shortage of skilled professionals. Our analysis underscores the ongoing need for innovation in DBMS to scale with emerging memory technologies. This report serves as a comprehensive guide for those interested in entering the market, detailing the current requirements and future opportunities in database management for wafer manufacturing.

Keywords: Semiconductor Industry; Wafer Manufacturing; Database Management; Data Analytics; Machine Learning; Modern Database Management Systems (DBMS); Effectiveness, Precision, and Efficiency (EAP); Quality Control; Informational Collection.

Received on: 17/08/2023, Revised on: 13/10/2023, Accepted on: 27/11/2023, Published on: 09/03/2024

DOI: 10.69888/FTSIN.2024.000154

FMDB Transactions on Sustainable Intelligent Networks, 2024 Vol. 1 No. 1, Pages: 15-26

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