Strengthening the Sustainability of Additive Manufacturing through Data‐Driven Approaches and Workforce Development

Abstract

The additive manufacturing (AM) industry is rapidly developing and expanding, thereby becoming an important and integral component of the digital revolution in manufacturing practices. While the engineering aspects of AM are under intensive research, there still remain many chances to strengthen the sustainability of additive manufacturing (SAM). Cogently increasing the AM community's attention to SAM is vital for developing the AM industry sustainably from the bottom up. The digital nature of AM provides new opportunities for acquiring, storing, and utilizing data to strengthen SAM through data‐driven approaches. Herein, spotlight on SAM is shone upon and it is placed on a more concrete footing. The corresponding advances in data‐driven methods that can strengthen SAM are featured, such as optimizing designs for AM, reducing material waste, and developing databases. How the AM workforce can be developed and grown as a collaboration between the industry, government, and academia to extensively harness the full potential of AM as well as mitigate its adversarial social impact is discussed. Finally, several critical digital techniques that have the potential to further strengthen SAM in the factory of the future, including hybrid manufacturing, Internet of Things, and machine learning and artificial intelligence, are highlighted.

Application of machine learning in polymer additive manufacturing: A review

“…Therefore, a key objective during the design phase is to minimize the use of support structures to reduce material waste; this often depends on trialand-error and/or simulations, both of which are time consuming. 161 ML techniques are gradually being incorporated to help navigate these challenges. In this section, we discuss the potential of ML techniques to accelerate advances in polymer AM.…”

A DMAIC Framework to Improve Quality and Sustainability in Additive Manufacturing—A Case Study

“…Another related area of literature related to our work focusses on analyzing the sustainability of processes and manufacturing systems. In this domain, one of the most widely used methodologies is Life Cycle Assessment (LCA) which allows evaluating the life cycle environmental impact of a product systems [6]. A set of standards have been developed to support the LCA methodology.…”

“…The authors of [11] report on performance indicators for AM following the life cycle thinking and explain how to use each indicator depending on product type, application, and decision maker's goal. The literature also emphasizes the role of data-driven methods to enhance sustainability in AM [6]. From a value-driven perspective, concepts such as Circular Economy have been put forth as potential drivers of sustainability in AM [12].…”

Integrating Bioeconomy Principles in Bionic Production: Enhancing Sustainability and Environmental Performance

“…Additive Manufacturing significantly reduces material consumption by building products layer by layer. It enables precise customisation, rapid prototyping, and lightweight design, leading to resource-efficient manufacturing (Abdulhameed et al 2019;Bournias Varotsis 2021;Javaid et al 2022;Kokare et al 2023;Li and Yeo 2021).…”