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This paper presents an experimental investigation in establishing the relationship between FDM process parameters and tensile strength of polycarbonate (PC) samples using the I-Optimal design.

I-optimal design methodology is used to plan the experiments by means of Minitab-17.1 software. Samples are manufactured using Stratsys FDM 400mc and tested as per ISO standards. Additionally, an artificial neural network model was developed and compared to the regression model in order to select an appropriate model for optimisation. Finally, the genetic algorithm (GA) solver is executed for improvement of tensile strength of FDM built PC components.

This study demonstrates that the selected process parameters (raster angle, raster to raster air gap, build orientation about Y axis and the number of contours) had significant effect on tensile strength with raster angle being the most influential factor. Increasing the build orientation about Y axis produced specimens with compact structures that resulted in improved fracture resistance.

The fitted regression model has a p-value less than 0.05 which suggests that the model terms significantly represent the tensile strength of PC samples. Further, from the normal probability plot it was found that the residuals follow a straight line, thus the developed model provides adequate predictions. Furthermore, from the validation runs, a close agreement between the predicted and actual values was seen along the reference line which further supports satisfactory model predictions.

This study successfully investigated the effects of the selected process parameters - raster angle, raster to raster air gap, build orientation about Y axis and the number of contours - on tensile strength of PC samples utilising the I-optimal design and ANOVA. In addition, for prediction of the part strength, regression and ANN models were developed. The selected ANN model was optimised using the GA-solver for determination of optimal parameter settings.

The proposed ANN-GA approach is more appropriate to establish the non-linear relationship between the selected process parameters and tensile strength. Further, the proposed ANN-GA methodology can assist in manufacture of various industrial products with Nylon, polyethylene terephthalate glycol (PETG) and PET as new 3DP materials.

International outbreak of the SARS-CoV-2 infection has fostered the Italian government to impose the FFP2 protective facial masks in closed environments, including bar, restaurants and, more in general, in the food sector. Protective facial masks are rocketing, both in mass and in costs, in the food sector imposing efforts in fostering reuse strategies and in the achievement of sustainable development goals. The scope of the present paper is to depict possible strategies in manufacturing and reuse strategies that can reduce the carbon footprint (CF) of such devices.

To implement circular economy strategies in the protective facial masks supply chain, it was considered significant to move towards a study of the environmental impact of such devices, and therefore a CF study has been performed on an FFP2 facial mask used in the food sector. Different materials besides the mostly used polypropylene (PP) (polyethylene (PE), polycarbonate (PC), poly (lactic acid) (PLA), cotton, polyurethane (PUR), polystyrene (PS) and nylon 6,6) and different sanitisation alternatives as reuse strategies (both laboratory and homemade static oven, ultraviolet germicidal irradiation) readily implemented have been modelled to calculate the CF of a single use of an FFP2 mask.

The production of textiles in PP, followed by disposal was the main contributor to CF of the single-use FFP2 mask, followed by packaging and transportations. PP and PE were the least impacting, PC, cotton and Nylon 6-6 of the same weight results the worst. PLA has an impact greater than PP and PE obtained from crude oil, followed by PUR and PS. Static laboratory oven obtained an 80.4% reduction of CF with respect to single use PP-made FFP2 mask, whereas homemade oven obtained a similar 82.2% reduction; UV cabinet is the best option, showing an 89.9% reduction.

The key strategies to reduce the environmental impacts of the masks (research for new materials and reuse with sanitisation) should ensure both the retention of filtering capacities and the sanitary sterility of the reused ones. Future developments should include evaluations of textile recycling impacts, using new materials and the evaluation of the life cycle costs of the reused masks.

This paper intends to provide to stakeholders (producers, consumers and policy makers) the tools to choose the best option for producing and reuse environmentally friendly protective facial masks to be used in the food sector, by using both different materials and easily implemented reuse strategies.

The reduction of the CF of protective facial masks in the food sector surely will have relevant positive effects on climate change contributing to reach the goals of reducing CO₂ emissions. The food sector may promote sustainable practices and attract a niche piece of clients particularly sensible to such themes.

The paper has two major novelties. The first one is the assessment of the CF of a single use of an FFP2 mask made with different materials of the non-woven filtering layers; as the major contribution to the CF of FFP2 masks is related to the non-woven textiles manufacturing, the authors test some other different materials, including PLA. The second is the assessment of the CF of one single use of a sanitised FFP2 mask, using different sanitation technologies as those allowed in bars or restaurants.