Numerical Modeling of a Sustainable Solid-State Recycling of Aluminum Scraps by Means of Friction Stir Extrusion Process.

One of the most important purposes of the modern industry is a sustainable production, considering the minimization of the energy and of the raw materials used, together with the reduction of polluting emissions. In this context, Friction Stir Extrusion stands out, since it allows to obtain extrusions starting from metal scraps deriving from traditional mechanical machining processes (e.g.

Discrete-event simulation study of a COVID-19 mass vaccination centre.

The global spread of COVID-19 and the declaration of the pandemic status made by the World Health Organization (WHO) led to the establishment of mass vaccination campaigns. The challenges posed by the request to immunise the entire population necessitated the set-up of new vaccination sites, named Mass Vaccination Centres (MVCs), capable of handling large numbers of patients rapidly and safely. The present study focused on the evolution of MVC performances, in terms of the maximum number of vaccinated patients and primary resource utilisation ratio, while involving statistics belonging to the patient dimension.

Special Issue of Materials focusing on "Finite Element Analysis and Models of Sustainable Manufacturing Processes".

We believe that the chosen topic is nowadays extremely current and of great interest [...

A Comparison between Finite Element Model (FEM) Simulation and an Integrated Artificial Neural Network (ANN)-Particle Swarm Optimization (PSO) Approach to Forecast Performances of Micro Electro Discharge Machining (Micro-EDM) Drilling.

Artificial Neural Network (ANN), together with a Particle Swarm Optimization (PSO) and Finite Element Model (FEM), was used to forecast the process performances for the Micro Electrical Discharge Machining (micro-EDM) drilling process. The integrated ANN-PSO methodology has a double direction functionality, responding to different industrial needs. It allows to optimize the process parameters as a function of the required performances and, at the same time, it allows to forecast the process performances fixing the process parameters.