## 5 Discussion: Industry 5.0 Framework and Complex Systems Simulations
### Industry 5.0 Workflow Design and Process Simulation  
The works selected from the state of the art literature allow us to define a possible framework of how Industry 5.0 could involve a lot of previously mentioned technologies. The hypotheses of possible improvements of processes in Industry 5.0 frameworks allowed us to design the production layout, while including the main important variables found in the literature. A modern framework is characterized by a large number of variables, so we structured a complex system characterized by a \"capillary\" information flux between all the variables named nodes. An approach used to simulate complex models [103] is the calculation of the diffusion heat parameter [152; 153; 154]. The diffusion heat parameter is a probabilistic definition of the information flux distribution flowing between all nodes. Diffusion is typically a phenomenon associated to \"particles\" moving in an environment. In the specified case, the environment is modelled by nodes, and edges connecting all the nodes of the complex model. The probability of the distribution of the diffusion heat parameter is the position distribution of particles, which simulates the information flux, after a time \\(t\\). In the analyzed model, a parameter of \\(t\\) = 0.038 s is enough for the transient calculation of the simulated complex Industry 5.0 manufacturing network. The hypothesized network is assumed to be a single production line consisting of three production machines and a robot, connected in a series configuration as illustrated in Figure 3a. The raw materials are processed by a first machine (_Machine 1_ node indicated by M1), then the workpiece is handled by a robot (_Robot 1_ node indicated by R1), sent to be processed by a second machine (_Machine 2_ node indicated by M2), which realizes a semi-product, which is then processed by a final, third machine (_Machine 3_ node indicated by M3), which produces the final product. As illustrated in Figure 3a, the machines define a first operating level named _Production Line Level_ which is interconnected to a second one associated to sensing and actuation processes (_Sensing and Actuator Level_ made up of sensors \\(S\\) and actuators \\(A\\)). A third level, named _Industry 5.0 Level_, represents the upgrade from Industry 4.0 to the Industry 5.0 scenario, and is consists of the following main elements (nodes): _Quantum Computer, Big Data, External Big Data, AI Edge Computing_, and an _Actuator Engine_ (all the elements suggested for an upscale in production). The simulated network is better modelled by the graph of Figure 3b, which indicates nodes and edges. The simulated nodes are:  
* _Machine 1_ (M1): the first machine, processing raw materials loaded at the input of the production line. * _Sensor M1_1_: sensor monitoring _Machine 1_. * _Sensor M1_2_: sensor monitoring _Machine 1_. * _Actuator M1_: actuator that relays the sensing and actuation processing of from _Machine 1_. * _Power Meter_M1_: power meter reading the electrical power of _Machine 1_. * _Robot 1_ (R1): robot handling the workpiece processed by _Machine 1_. * _Sensor R1_1_: first sensor monitoring _Robot 1_. * _Sensor R1_2_: second sensor monitoring _Robot 1_. * _Actuator R1_: actuator which relays sensing and actuation processing from _Robot 1_ (includes sensing of from both the sensors _Sensor R1\\(1\\) and _Sensor R1_2_). * _Machine 2_ (M2): second machine processing the workpiece after robotic manipulation. * _Sensor M2_1_: sensor monitoring _Machine 2_. * _Sensor M2_2_: sensor monitoring _Machine 2_. * _Actuator M2_: actuator relaying sensing and actuation processing from _Machine 2_. * _Power Meter_M2_: power meter reading the electrical power of _Machine 2_. * _Semi-Product_ (SP): semi-product output of _Machine 2_. * _Image Vision SP_: camera implementing image vision algorithms to detect the defects of the _Semi-Product_. * _Machine 3_ (M3): third machine processing the semi-product. * _Sensor M3.1_: sensor monitoring _Machine 3_. * _Sensor M3.2_: sensor monitoring _Machine 3_.