Data Management in Semiconductor Manufacturing
                                Equipment: Current State and Challenges
                                Manuel Fritz1
                                1
                                    Carl Zeiss SMT GmbH, Rudolf-Eber-Straße 2, D-73447 Oberkochen, Deutschland


                                                  Abstract
                                                  Semiconductor industry is a key-enabler for technological advancements such as AI and Industry 4.0 by providing ever
                                                  shrinking transistor sizes, more storage and more computing power for less energy and less costs. The production of
                                                  semiconductor manufacturing equipment relies on machines which achieve high yield and high output, thus relying on
                                                  ultra-precise manufacturing processes. In this talk, we look at how a lithography system is produced and unveil the
                                                  interdependency with data management and analytics. We present data management as an enabler for automated, robust,
                                                  high-end manufacturing processes, and show how data analytics can support the overarching company goals on a technical
                                                  and organizational level to achieve competitive benefits, such as increased product output, reduced costs, improved processes,
                                                  and even longer product lifespan.

                                                  Keywords
                                                  Data Management, Semiconductor Manufacturing, Data Analytics




                                34th GI-Workshop on Foundations of Databases (Grundlagen von Daten-
                                banken), June 7-9, 2023, Hirsau, Germany
                                Envelope-Open manuel.fritz@zeiss.com (M. Fritz)
                                GLOBE https://www.zeiss.de (M. Fritz)
                                Orcid 0000-0003-4640-8477 (M. Fritz)
                                            © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License
                                            Attribution 4.0 International (CC BY 4.0).




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Workshop      ISSN 1613-0073
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