PIAM Editorial April 2023

I am delighted to present the latest issue of Progress in Additive Manufacturing, which highlights the impressive growth of Additive Manufacturing (AM) in both academic and industrial spheres. AM has evolved significantly, embracing a wide range of technologies, materials, applications, and sectors, resulting in a rapidly expanding global community. This issue features an array of research topics, with a specific emphasis on Material Extrusion. The papers investigate exciting research avenues, focusing on diverse materials, such as multimaterials, reinforced thermoplastic with continuous fiber, and Acrylic Butadiene Styrene. Furthermore, the issue examines process strategies and parameters, along with their impact on the final quality and performance of the printed parts. The issue also explores other AM processes for polymers, such as Digital Light Processing (DLP) and Selective Laser Sintering (SLS), as well as for metals, including electron- and laser-based Powder Bed Fusion and friction stir molding. As an Associate Editor of PIAM since 2022, I have observed a remarkable surge of interest in AM, as evidenced by the growing number of submissions in the last year. From my perspective, the future of AM is exceptionally bright, as we anticipate ushering in a new generation of eco-friendly products. AM will serve as a crucial enabler of this transition, as it allows for the production of green products, using its “complexity-for-free”. With AM, we can manufacture (and repair) lightweight, durable, and highly efficient products with superior thermomechanical properties. Furthermore, AM can significantly reduce the number of components, thereby reducing the environmental footprint of transportation. Once post-processing and finishing stages are streamlined, printing on demand will become the norm, and almost net-shape printing will be attainable. To support this green transition, we must enhance our process knowledge and engage in active optimization to minimize waste, scraps, and defective parts. In recent years, I have been exploring the advantages of in-situ data mining, monitoring, and control for zero-waste, zero-defect AM. I am confident that the convergence of big data, Artificial Intelligence (AI), machine learning, and AM will flourish in the coming years, provided we invest in robust and reliable tools to ensure repeatability and reproducibility of the newly developed solutions. AM will serve as the bridge that merges the green and digital aspects of the transition we are striving for. With these compelling avenues for future research, I am confident that the future of AM is bright and full of potential.