Steven Lengieza

Papers

Total Citations

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About

Steven Lengieza is a researcher at the forefront of smart manufacturing, with a focus on integrating edge and cloud computing to transform industrial data into actionable intelligence. His most-cited work, "A Data Transformation Adapter for Smart Manufacturing Systems with Edge and Cloud Computing Capabilities" (2018, 13 citations), addresses a critical bottleneck in Industry 4.0: the seamless processing of vast plant floor data. Lengieza’s major contribution lies in designing adaptive data pipelines that bridge legacy manufacturing equipment with modern, distributed computing architectures, enabling real-time decision-making and improved productivity. By tackling the challenge of data heterogeneity and latency in smart factories, his work supports the shift toward more agile, data-driven production systems. While his citation count reflects a growing niche impact, Lengieza’s research is notable for its practical engineering focus, offering scalable solutions that resonate with both academic and industrial audiences. His achievements underscore a commitment to operationalizing digital transformation in manufacturing, making him a valuable voice for students and researchers exploring the intersection of IoT, cloud computing, and cyber-physical systems.