<![CDATA[The increasing integration of artificial intelligence into intelligent engineering systems has created a critical need for approaches that balance computational capability with human autonomy, transparency, accountability, and sustainable operational performance. This study aims to develop an integrative Human-Centered Artificial Intelligence (HCAI) framework capable of supporting trustworthy human–AI collaboration in complex engineering environments. The research employs a non-empirical system-design methodology grounded in design science, systems engineering, socio-technical systems theory, and human-centered AI principles. The proposed framework consists of four interdependent layers comprising human, intelligence, interaction, and governance components that collectively facilitate collaborative decision-making and responsible system operation. Analytical evaluation was conducted through architecture-conformance analysis, requirements-traceability assessment, and scenario-based simulations involving intelligent manufacturing, predictive maintenance, and AI-assisted engineering decision environments. The findings indicate that the framework strengthens human autonomy preservation, explainability capability, collaborative decision efficiency, and governance robustness while maintaining alignment with Industry 5.0 objectives. The study contributes a theoretically integrated architectural model and a reproducible methodological approach for designing intelligent engineering systems that enhance human capabilities, promote trustworthy AI adoption, and support sustainable socio-technical innovation.]]>
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