Parametric Investigation and Optimization to Study the Effect of Process Parameters on the Dimensional Deviation of Fused Deposition Modeling of 3D Printed Parts.

Fused deposition modeling (FDM) is the most economical additive manufacturing (AM) technology available for fabricating complex part geometries. However, the involvement of numerous control process parameters and dimensional instabilities are challenges of FDM. Therefore, this study investigated the effect of 3D printing parameters on dimensional deviations, including the length, width, height, and angle of polylactic acid (PLA) printed parts. The selected printing parameters include layer height, number of perimeters, infill density, infill angle, print speed, nozzle temperature, bed temperature, and print orientation. Three-level definitive screening design (DSD) was used to plan experimental runs. The results revealed that infill density is the most consequential parameter for length and width deviation, while layer height is significant for angle and height deviation. The regression models developed for the four responses are non-linear quadratic. The optimal results are obtained considering the integrated approach of desirability and weighted aggregated sum product assessment (WASPAS). The optimal results include a layer height of 0.1 mm, a total of six perimeters, an infill density of 20%, a fill angle of 90°, a print speed of 70 mm/s, a nozzle temperature of 220 °C, a bed temperature of 70 °C, and a print orientation of 90°. The current study provides a guideline to fabricate assistive devices, such as hand and foot orthoses, that require high dimensional accuracies.

Risk factors in the assessment of suppliers.

The need to evaluate suppliers from the perspective of risk analysis by purchasing companies is increasing. Such evaluation of suppliers is conducted primarily by production companies with implemented quality (QMS), environmental (EMS), health and safety management systems (H&SMS), as well as Toyota Production System (TPS). This article aims to examine latent factors for suppliers' evaluation and to describe the intensity of these factors by the implemented management system. The article provides the results of empirical research conducted with the computer-assisted telephone interviewing (CATI) technique in 151 medium and large manufacturing companies operating in Poland. The risk was classified into three main groups to deepen the research process: management system risks, environment risks, and process risks. This allowed for the formulation of some original conclusions. The results showed that companies implementing standardized management systems take the issue of risk analysis and management more seriously than organizations that do not implement such systems. The research also highlighted the differences in the perception of risk caused by implementing various management systems. The study also found that the industry and business profile specificity also affect the risk assessment in cooperation with suppliers.

Factors that influence the expansion of electric delivery vehicles and trucks in EU countries.

As one of the possibilities of reducing exhaust emissions, the article takes into account infrastructure and electric vehicles used in road transport. Taking into account the goal to achieve a 30% share of vehicle electric, the number of charging stations available in the entire European Union is not sufficient. There has been a slight increase in sales of electric vans and trucks in the EU in recent years. This may be due to the lack of available infrastructure which would render it possible to power them, and also from the lack of available delivery vehicles in the market. What is interesting, the number of electric vehicles in a country is not necessarily in proportion to the number of available charging stations. It is the authors' intention as well to indicate the potential directions of the development of a low-emission cargo transport in the European Union. Upon the basis of the results, it is ascertained that there is a strong correlation between the value of a country's GDP and the number of electric vehicle charging stations. A moderate correlation is also observed in the case of a country's population, as well as in the case of the market share of registered electric delivery vehicles in a country.