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Abstract
DATA-DRIVEN MECHANICAL SYSTEM DESIGN USING SYSTEMS ENGINEERING AND BIG DATA PRINCIPLES
*Riyan Mohammed
ABSTRACT
In the evolving landscape of engineering, the integration of data-driven methodologies into mechanical system design is transforming traditional approaches. This paper presents a multidisciplinary case study that combines mechanical engineering principles—such as thermal analysis, structural design, and finite element modeling—with data science, systems engineering, and statistical techniques. Drawing from core concepts in CAD, FEM, and heat transfer, this workleverages Big Data and Systems Engineering Analysis to explore optimized workflows for predictive maintenance, performance simulation, and component validation. This study also highlights relevant frameworks, such as those used in autonomous vehicle validation pipelines [Sharfuddin, 2025], to emphasize the growing importance of cross-domain engineering knowledge. The findings advocate for a curriculum and research model that fuses mechanical fundamentals with computational intelligence for next-generation design applications.
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