A Conceptual Digital Engineering Framework for Intelligent and Sustainable Engineering Systems
DOI:
https://doi.org/10.54518/jaei.1.2.2023.1238Keywords:
Artificial Intelligence, Big Data Analytics, Digital Engineering, Digital Twin, Internet of ThingsAbstract
Digital transformation has reshaped modern engineering by integrating digital technologies that enable data-driven decision-making throughout the engineering system life cycle. This study aims to develop a conceptual digital engineering framework integrating the Internet of Things, Big Data Analytics, Artificial Intelligence, Digital Twin, ontology engineering, and trustworthy artificial intelligence principles to support intelligent, adaptive, and sustainable engineering systems. A qualitative descriptive library research approach was employed by synthesizing scientific publications published over the last five years. The findings indicate that effective digital engineering implementation requires seamless integration among digital technologies, data interoperability, virtual system representation, and transparent, trustworthy decision-making mechanisms. The proposed conceptual framework illustrates the systematic relationship between data acquisition, data management, artificial intelligence-based analytics, Digital Twin representation, and the application of trustworthy artificial intelligence as the foundation of digital transformation. The framework contributes theoretically by strengthening digital engineering as an integrated engineering paradigm while providing practical guidance for organizations in designing digital transformation strategies to improve operational efficiency, system reliability, and long-term sustainability across engineering applications.
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