Additive manufacturing provides a number of benefits in terms of infinite freedom to design complex parts and reduced lead-times while globally reducing the size of supply chains as it brings all production processes under one roof. However, additive manufacturing (AM) lags far behind conventional manufacturing in terms of surface quality. This proves a hindrance for many companies considering investment in AM. The aim of this work is to investigate the effect of varying process parameters on the resultant roughness of the down-facing surfaces in selective laser melting (SLM). A systematic experimental study was carried out and the effects of the interaction of the different parameters and their effect on the surface roughness (Sa) were analyzed. It was found that the interaction and interdependency between parameters were of greatest significance to the obtainable surface roughness, though their effects vary greatly depending on the applied levels. This behavior was mainly attributed to the difference in energy absorbed by the powder. Predictive process models for optimization of process parameters for minimizing the obtained Sa in 45° and 35° down-facing surface, individually, were achieved with average error percentages of 5% and 6.3%, respectively, however further investigation is still warranted.

The rise in popularity of Additive Manufacturing technologies and their increased adoption for manufacturing have created a requirement for their fast development and maturity. However, there is still room for improvement when compared with conventional manufacturing in terms of the predictability, quality, and robustness. Statistical analysis has proven to be an excellent tool for developing process knowledge and optimizing different processes efficiently and effectively. This paper uses a novel method for printing overhanging features in Ti-6Al-4V metal parts, by varying process parameters only within the down-facing area, and establishes a methodology for predicting dimensional errors in flat 45° down-facing surfaces. Using the process parameters laser power, scan speed, scan spacing, scan pattern, and layer thickness, a quadratic regression equation is developed and tested. An Analysis of variance (ANOVA) analysis concluded that, within the down-facing area, the laser power is the most significant process parameter, followed by the layer thickness and scan speed. Comparatively, the scanning pattern is determined to be insignificant, which is explained by the small down-facing area where the various scanning patterns play no role. This paper also discusses the interaction effects between parameters. Some thoughts on the next steps to be taken for further validation are discussed.

The eruption of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (corona virus disease, COVID-19) in Wuhan, China, and its global spread has led to an exponentially growing number of infected patients, currently exceeding over 6.6 million and over 390,000 deaths as of the 5th of June 2020. In this pandemic situation, health systems have been put under stress, and the demand for personal protective equipment (PPE) exceeded the delivery capabilities of suppliers. To address this issue, 3D printing was identified as a possible solution to quickly produce PPE items such as face shields, mask straps, masks, valves, and ear savers. Around the world, companies, universities, research institutions, and private individuals/hobbyists stepped into the void, using their 3D printers to support hospitals, doctors, nursing homes, and even refugee camps by providing them with PPE. In Germany, the makervsvirus movement took up the challenge and connected thousands of end users, makers, companies, and logistic providers for the production and supply of face shields, protective masks, and ear savers. The Karlsruhe Institute of Technology (KIT) also joined the makervsvirus movement and used its facilities to print headbands for face shield assemblies and ear savers. Within this paper, the challenges and lessons learned from the quick ramp up of a research laboratory to a production site for medium-sized batches of PPE, the limitations in material supply, selection criteria for suitable models, quality measures, and future prospects are reported and conclusions drawn.