One often-cited benefit of using metal additive manufacturing (AM) is the possibility to design and produce complex geometries that suit the required function and performance of end-use parts. In this context, laser powder bed fusion (LPBF) is one suitable AM process. Due to accessibility issues and cost-reduction potentials, such ‘complex’ LPBF parts should utilise net-shape manufacturing with minimal use of post-process machining. The inherent surface roughness of LPBF could, however, impede part performance, especially from a structural perspective and in particular regarding fatigue. Engineers must therefore understand the influence of surface roughness on part performance and how to consider it during design. This paper presents a systematic literature review of research related to LPBF surface roughness. In general, research focuses on the relationship between surface roughness and LPBF build parameters, material properties, or post-processing. Research on design support on how to consider surface roughness during design for AM is however scarce. Future research on such supports is therefore important given the effects of surface roughness highlighted in other research fields.

Laser Powder Bed Fusion (LPBF) brings the possibility to manufacture innovative near-net-shape part designs. But unfortunately, some designed surfaces suffer from rough surface finish due to characteristics of the LPBF process. This paper explores trends in managing surface roughness and through a space industry case study, a proposed process that uses Additive Manufacturing Design Artefacts (AMDAs) is used to investigate the relationship between design, surface roughness and fatigue. The process enables the identification of design uncertainties, however, iterations of AMDA's can be required.

Evaluation approaches are needed to ensure the development of effective design support. These approaches help developers ensure that their design support possesses the general design support characteristics necessary to enable designers to achieve their desired outcomes. Consequently, evaluating design support based on these characteristics ensures that the design support fulfils its intended purpose.

This work reviews design support definitions and identifies and describes 11 design support characteristics. The characteristics are applied to evaluate a proposed design support that uses additive manufacturing (AM) design artefacts (AMDAs) to explore design uncertainties. Product-specific design artefacts were designed and tested to investigate buildability limits and the relationship between surface roughness and fatigue performance of a design feature in a space industry component. The AMDA approach aided the investigation of design uncertainties, identified design solution constraints, and uncovered previously unknown uncertainties. However, the results provided by product-specific artefacts depend on how well the user frames their problem and understands their AM process and product. Hence, iterations can be required. Based on the evaluation of the AMDA process, setting test evaluation criteria is recommended, and the AMDA method is proposed.

Laser Powder Bed Fusion (LPBF) enables complex metal components for the space industry. However, as-built surface roughness affects material properties and is closely linked to design geometry. As computer-aided design tools struggle to model roughness accurately, this study explores Additive Manufacturing Design Artefacts (AMDAs) to investigate design-related roughness and its impact on fatigue performance. A space industry case study using AMDAs to replicate a 4 mm unsupported roof radius of a rocket engine component found fatigue performance reductions of 88% in horizontal builds and 65% in vertical builds compared to machined surfaces. Microstructural analysis confirmed the influence of roughness and grain structure on fatigue behaviour. Findings highlight how AMDAs provide design-specific insights and support engineers in investigating uncertainties.

Additive manufacturing (AM) enables the production of innovative, lightweight component designs in the aerospace industry. However, AM processes introduce new production feasibility considerations that must be addressed during product development. Therefore, engineers require effective design support and a new design approach to fully exploit AM’s capabilities while balancing its constraints. Through an interview study involving 20 AM aerospace industry professionals from nine countries and 10 organisations, this research identifies AM design opportunities and challenges and explores the design supports used to achieve and overcome them. The findings indicate that Laser Powder Bed Fusion is a predominant AM process in aeronautical and space applications. Further, the study identifies practical and computational design supports, describes how AM design is approached during product development and provides a model outlining a general AM design approach. Key AM design challenges identified include insufficient knowledge of material properties, limited sharing of design knowledge and a lack of understanding of the relationship between AM design and post-processing requirements. Consequently, skills gaps and educational needs for Design for AM in aerospace engineering are highlighted. Additionally, the study suggests that further AM aerospace standards, enhanced computer-aided engineering software for AM and artificial intelligence integration could improve design support.