The research aims to thoroughly examine the incorporation of human-digital twins (HDT) into the Industry 5.0 framework to comprehend its applications, challenges and possible advantages. This research aims to clarify the revolutionary impact of HDT in the manufacturing sector by examining representative case studies spanning various phases of product development and production. The current deficiency in research concerns the necessity for a comprehensive analysis of HDT, encompassing its organisational, technological, application, and societal dimensions, as well as its implementations in production, design, and other phases of the lifecycle.
To bridge this divide, a comprehensive literature review, analysis of representative case studies, and discussion of challenges and opportunities comprised the systematic research methodology. The results indicate that HDT substantially contributes to Industry 5.0 in user-centric design, real-time collaboration, safety improvement, and efficiency enhancement. Significantly, obstacles recognised encompass the implementation of an authentically human-centric methodology and the resolution of security concerns. The adaptability of HDT is better comprehended through a comparative analysis of case studies, and its theoretical framework, HDT = (HE, VE, and IS), is consistent with the objectives of Industry 5.0, which envision a manufacturing ecosystem that is interconnected, intelligent, and centred around human beings.
The research contributes to the field by providing industry practitioners with practical implications that inform and direct strategies for effectively implementing HDT. This study first examines how the relationship between people and digital twins is changing, including ethical issues and societal effects. The findings strengthen the ideas behind HDT and Industry 5.0. Overall, this research contributes to advancing HDT discourse by providing industry and academia with invaluable insights.
Key words: Human Digital Twin(HDT), Industry 5.0, smart manufacturing, human-machine collaboration
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