Digital Twin (DT) is considered a key approach to enhance the system reactivity to uncertain events due to its ability to getting data from the field and triggering actions on the physical asset. Given the modern technological and rapidly changing work environment, it is likely that in the next years companies will need to retrofit their manufacturing systems by integrating DTs. In this context, it is fundamental to define the necessary steps for the development of DTs and for their integration into manufacturing systems through a DT architecture. In response to this issue, a methodology based on Virtual Commissioning is proposed. A stepwise approach is illustrated in which the DT is designed, integrated and verified using a virtual environment. The methodology is validated through the integration of a DT into a flow shop for the implementation of a scheduling reactive to machine breakdown. By following the steps of the proposed methodology, a DT architecture able to improve the makespan of the studied flow shop is developed, suggesting the potential applicability of the approach to industrial manufacturing systems.

In today’s manufacturing environment the Industry 5.0 (I5.0) paradigm has emerged and the concept of human-centricity started to be integrated enhancing workers roles, prioritizing their physical health, mental health and well-being. In particular, to support humans in their workplace, the Digital Twin (DT) paradigm can serve for designing and/or analyzing manufacturing environments that improve workers’ well-being. Recently, this approach has evolved into the concept of Human Digital Twin (HDT) which aims at presenting a comprehensive representation of the human entity analyzing their behavior and understanding possible improvement approaches for workers status. The aim of this paper is to analyze, through a systematic literature review, DT solutions that support human-centric manufacturing systems, focusing also on the roles played by technological tools in assisting operators in their work environment. In this sense, attention will be devoted to improving human factors through modelling approaches and technological tools.