The Flexible Job Shop Scheduling Problem (FJSSP) has been widely studied in last decades. The emergence of technological advancements in the context of Industry 4.0 has brought many changes and made production scheduling more and more efficient. Today's Industry 5.0 paradigm pays a lot of attention to the human factors and the environmental considerations to enhance the systems sustainability and resilience. Since 2013, around 100 FJSSP articles have focused on environmental factors like the energy consumption or gas emissions. Among these papers, only 13 ones consider the human factors. However, recent literature on scheduling problems has shown that the workers well-being and skills affect considerably the scheduling performance. 
FJSSP can be static or dynamic. Dynamic scheduling differs from static scheduling in its ability to react to hazards or disturbances. Solving the dynamic FJSSP should improve the production system's efficiency and resilience but, unfortunately, increase the complexity of the problem regarding its solving and implementation. Most of the encountered articles in the FJSSP recent literature consider the human and environmental factors separately. Also, the resolution of these problems has been mostly done in a static way. To increase the production systems sustainability and resilience, we propose a MILP to model the human based green FJSSP (considering the total energy consumption and the workers well-being regarding the OCRA index).