Felix Beierle

Papers

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About

Felix Beierle is a researcher whose work sits at the intersection of software architecture and industrial data analytics. His primary research areas include microservices-based systems, decentralized manufacturing paradigms, and the application of data analytics to optimize industrial production. Beierle’s major contribution is the development of MAIA (Microservices-based Architecture for Industrial Data Analytics), a framework designed to help manufacturers transition from mass production to customized, decentralized operations. By leveraging microservices, MAIA enables more efficient, scalable, and flexible data processing in industrial settings. His most-cited paper, "MAIA: A Microservices-based Architecture for Industrial Data Analytics" (2019), has garnered 18 citations, reflecting its relevance in the growing field of Industry 4.0. This work addresses a critical challenge: how to harness data analytics in a modular, non-disruptive way. Beierle’s research is particularly notable for its practical orientation, offering a blueprint for real-world industrial digital transformation. For students and researchers exploring modern software architectures or smart manufacturing, Beierle’s work provides a clear, actionable example of how microservices can drive efficiency and customization in data-intensive environments.