4.1.1. AM opportunities

The respondents stated several reasons why AM was selected to manufacture these types of products. The main reasons highlighted were the freedom of design and geometry that AM provides over traditional manufacturing, enabling the creation of complex geometries that would not be feasible through traditional means, such as integrated cooling channels within thrust chambers (R6, 20) and topology-optimised brackets (R7, 14). The respondents commented on how the design complexity enabled by AM allows for component designs that focus on weight reduction (R3, 4, 9, 10, 13, 15, 19) and cost reduction (R3, 5, 15, 16). Emphasised by Respondent 6 that “…the business case of AM is the weight savings and the cost savings.” Further, Respondent 14 stated that for aerospace AM components, “…the most important points for now [are] lead time and cost.”

AM was particularly noted for the weight-saving benefits provided to space industry products (R10, 13, 14, 15, 16, 19). Respondent 10 provided an example where using AM in the production of an antenna cluster resulted in a 10% weight reduction, which they described as having a “huge impact.” They also noted the additional functionality enabled by AM, stating, “In a cluster that’s printed, you can have more horns in the same space as a cluster that’s made traditionally. So, more bang for your buck.” Further, they highlighted the advantages of AM part consolidation in transforming a complex assembly antenna design into one part. Hence, it creates a “much simpler system to manage, [with] less chance of failures, mistakes, or issues.” However, a balance needs to be considered when leveraging AM’s design capabilities for such products. As Respondent 14 explained, the benefits come at a cost, stating, “It’s probably a little bit more expensive, but the functionality and the weight reduction helps pay for this.”

Respondents noted how AM helps address product development challenges such as time-to-market, long lead times and supply chain issues in the aerospace industry (R1, 2, 6, 8, 15, 16). Respondent 6 compared AM to computer numerical control (CNC) manufacturing, describing AM as “incredibly fast” in comparison. They explained that CNC requires the development of numeric control software, whereas AM allows one to “go straight to production.” Respondents highlighted AM’s capability for part consolidation methods, emphasising its potential to streamline design and manufacturing processes (R6, 7, 10, 14, 16, 20). Respondent 16 explained that the freedom of shape offered by AM significantly reduces production time. It also enhances the functionality of thrust chambers by enabling the integration of cooling channels into the part. Respondent 16 stated that manufacturing a thruster previously required 3–6 months. However, with the design freedom enabled by AM, it is now possible to produce an engine more than 700 millimetres high in just 6 days. Hence, after post-processing, “in less than a month, you have a thrust chamber.” Respondent 9 echoed this statement, explaining that AM enables greater “agility” in product development, allowing for rapid iterations of designs and tests due to not having to wait for long lead-time items that require tooling. Respondent 7 provided an example of integrating electrical wiring into a satellite bracket, enabling electrical connectivity without requiring assembly. Similarly, cooling and flow channel integration was a key design freedom benefit identified for AM aerospace applications (R6, 9, 16, 20). Respondent 16 succinctly described the design freedom benefit as “it allows you to, instead of trying to fight against the problem, you can avoid it.” They provided an example of hydraulic manifold components, which require multiple cavities for fluid flow. Traditionally, these cavities are drilled or milled, leaving open holes that need to be plugged to ensure durability in extreme aerospace environments. Plugging these holes requires precision machining and specialised plugs designed to withstand such conditions. Respondent 16 said that using traditional methods leads to a 10–15% failure rate for the cavities, meaning high rework and scrap rates. With AM, the cavities and channels of these components can be built directly into the part. Eliminating the need for machining and plugs, reducing the assembly complexity, streamlining the manufacturing process and minimising the risk of rework or scrap while improving component performance.

While the respondents gave several examples of the benefits of AM for different aerospace applications, some noted that AM can be seen as a trend worthwhile to explore without a defined cost or performance benefit. Respondent 4 highlighted that for one of their products, the use of AM was “definitely not the business case” as its use was not financially justified. However, they acknowledged a long-term commercial perspective that it is important to be seen by customers as having AM capability, noting that having “additive parts [in] flight is a big hitter.” Respondent 2 explained that AM was primarily just exploring alternative manufacturing methods. Similarly, Respondent 8 describes it as “a way of introducing a new technology.” Acknowledging that in these cases, “it was not necessarily cost-effective” and was to “see how it performs with components that are relatively low risk.” Table 2 summarises the aerospace products where respondents reported applying AM, along with the specific advantages they identified as driving its selection for these applications.

Table 2.

Summary of AM aerospace product types and AM advantages

4.1.2. AM challenges

While the respondents discussed several performance, cost and time-saving benefits of adopting AM, they also highlighted several challenges in realising these opportunities. These challenges relate to technical, operational and economic issues, presenting barriers to adopting AM in the industry. The study identified four key themes of challenges: certification and qualification, design and manufacturing integration, material and process inconsistencies, and organisational and industrialisation issues.

4.1.2.4. Organisational and industrialisation

Additional challenges were identified concerning adopting AM within aerospace organisations and the industrialisation of the processes. The primary challenge identified in industrialisation is the lack of experience among aerospace engineers in designing for AM, leading to problems later in product development (R3, 13, 15, 17, 18). Respondent 18 stated that “the biggest challenge is the lack of knowledge within companies,” while Respondent 17 described a “massive skills gap” in the aerospace industry for AM. They further noted that in an organisation of 150 people, only two might have the knowledge required to operate an AM machine. Additionally, the lack of knowledge integration between departments was highlighted. Product designers often do not fully understand AM processes, while process specialists may have little experience with the products they are manufacturing (R13). Respondent 17 emphasised the need to involve design engineers in discussions with sales and business development experts to facilitate interdisciplinary knowledge sharing.

There are specific industrialisation challenges associated with scaling up and integrating AM machines within organisations. Respondent 16 highlighted the cost and complexity of AM technology as a significant barrier to implementation, advising that for AM to be effective at an industrial level, it must be vertically integrated within the organisation. Vertical integration entails multiple stages of AM production, such as design, manufacturing and post-processing, being conducted in-house. This integration reduces an organisation’s dependence on external suppliers for AM-related activities during product development. In turn, it improves production and development efficiency by minimising the need for external inputs, lowering transaction costs and optimising the flow of materials and information across the development process (Perry Reference Perry1989). Similarly, Respondent 8 noted that the absence of in-house AM machines hinders industrialisation efforts.

Operational challenges were also noted, including the handling of highly flammable metal powders. Respondent 16 stressed a lack of safety standards for dealing with these materials, requiring organisations to develop their own adaptations of the European Cooperation for Space Standardisation (ECSS) standards (R6). Lastly, respondent 18 highlighted “image factors” as a barrier to AM adoption. They noted that aerospace companies fear reputational damage if a product they specialise in is manufactured using AM and subsequently fails. Such an event could have severe consequences for the company’s business continuity. Table 3 summarises the challenges the respondents identified in implementing AM in aerospace, consolidating the thematic groupings and showing their relative frequency across the interviews.

Table 3.

Summary of identified challenges of AM aerospace application

This section has presented several opportunities, challenges and other factors that should be considered when designing aerospace components for AM, addressing the first research question. Despite the numerous challenges to implementing AM identified by the respondents, the potential benefits remain significant. Many companies have successfully flown and launched AM-produced components. (Berger Reference Berger2023; Relativity Space 2023). Respondents attributed their success in AM product development to the design support available to designers and engineers, enabling them to address and overcome the challenges identified and produce air- and space-worthy components. The following section details the various means and methods of support identified by the respondents during the AM design and PDP for aerospace applications.

4.2.1. Practical design support

Regarding practical design supports, respondents emphasised the importance of iterative testing and validation processes, such as using test coupons and prototyping, to identify and resolve design and manufacturing issues. Respondent 14 highlighted their use of prototypes for process and design validation. An initial prototype is used to confirm that the process can produce the part as expected, while subsequent prototypes validate the design and are used for testing. This iterative approach helps address design feasibility issues before advancing too far in the PDP. Other practices target specific design challenges, such as distortion. Respondent 10 noted how distortion can lead designers to “over-design” their parts to mitigate it, cautioning that one can “almost kill a project trying to mitigate this distortion.” They advocated for employing established aerospace practices, such as stress relief, alongside design adaptation techniques, like oversizing, to counter distortion.

Collaboration with the Original Equipment Manufacturer (OEM), experts such as senior design engineers and machinists, and certifying bodies like the European Union Aviation Safety Agency (EASA) and Nadcap was identified as a strategy for tackling AM-specific problems. Respondent 2 emphasised that close collaboration with certifying organisations helps ensure they are informed about “how the process has been developed and the material properties and the testing [conducted],” simplifying the certification process when the time comes. Respondent 17 observed that organisations like the American Society for Testing and Materials (ASTM) International are stepping in to establish set guidelines, commenting that, previously, “almost every single aerospace company was doing their own thing.” While some standards remain underdeveloped, collaboration with agencies, suppliers, customers and research institutions has helped advance AM design and process understanding, thereby addressing challenges in certification and qualification.

Additionally, team members’ practical experience and historical knowledge were cited as valuable resources for navigating challenges. Respondents noted the emergence of a new paradigm for AM engineers, who are now required to have a broader range of expertise. As Respondent 13 explained, “The AM engineer now has to be a very well-rounded person in terms of their experience,” due to the intricate connections between design, manufacturing and material properties. They added that “unless you’ve got an idea of how the material is going to be… you’re not going to succeed.”

The challenge of aerospace companies having enough knowledgeable engineers to overcome issues can be mitigated through cross-disciplinary collaborative workshops and resource pooling between manufacturers, suppliers and OEMs. Such activities contribute to the industrialisation of AM in aerospace by addressing both knowledge gaps and resource limitations. For instance, Respondent 13 highlighted the importance of education, stating, “We work closely with our AM engineers to ensure they have a deep understanding of the materials and processes.” Additionally, resource pooling was identified as a means of improving efficiency and reliability. As Respondent 6 described, “We’ve developed shared testing frameworks with partners to cut costs and improve reliability.” These collaborative efforts not only enhance the skill sets of engineers but also foster cost-effective and robust AM adoption strategies. Table 4 summarises the practical design support approaches to overcome some of the identified challenges for AM in aerospace applications.

Table 4.

Summary of practical design support approaches to overcome AM challenges

4.2.2. Computational design supports

In addition to conventional and practical methods, respondents highlighted several computational design supports that aid in AM design and product development. Budinoff, McMains & Shonkwiler (Reference Budinoff, McMains and Shonkwiler2024) highlight the role of software-based manufacturability analysis in enhancing AM design outcomes. Their study found that software tools help designers minimise manufacturability issues and boost creativity in design solutions. The respondents widely recognised simulation software as a critical tool for predicting potential issues during the AM process. Issues such as stress concentrations, distortions and manufacturing feasibility. Respondent 5 explained that simulation tools delve deeper into process aspects, such as simulating melt pools, cooling rates and material grain sizes, to determine whether the product will meet the required material properties. However, despite their usefulness, Respondent 4 acknowledged their limitations, stating that these tools “identify problem areas, but not the magnitude,” highlighting the need for additional data to support engineers in understanding and resolving design issues. One such support comes from digital material databases, which provide extensive information on materials and processes. As Respondent 11 suggested, such tools can help refine designs by providing a better understanding of material behaviours. Engineers can trace issues, modify build parameters, or determine heat treatments to improve properties through the knowledge in these databases. Respondent 16 stated that the effectiveness of computational design support depends on having “a very good database of material performance” covering variations in manufacturing methods, surface finishing and temperature. However, achieving the required level of detail would, as Respondent 6 remarked, require “either a huge database or an army of PhD students.”

CAE tools were identified as crucial for preparing parts designed and optimised for AM production. One example of CAE AM design support is build preparation software like Magics, which was widely used by Respondents 3, 4, 5, 15 and 17. These tools are designed specifically to address AM challenges, offering features such as support structure generation, part nesting and distortion compensation.

Respondent 10 highlighted its role in optimising part orientation: “It ensures we can avoid recoater collisions and minimise distortion while printing.” Similarly, Respondent 16 emphasised the broader impact: “Orientation impacts everything: material use, time, and final quality.” The effectiveness of these designs supports lies in their ability to address critical AM challenges. The design supports that highlight potential failure areas, such as material property issues, orientation concerns, or distortion predictions, are highly valued, even if their magnitude estimations are imperfect. Furthermore, support with cross-functional integration that seamlessly connects design, simulation and manufacturing workflows is considered essential for improving productivity and reducing errors. A summary of the computational design supports for AM identified from the respondents is presented in Table 5.

Table 5.

Summary of computational design support approaches to overcome AM challenges

4.3.1. Design collaboration community of practice

The primary gap and area for future development identified by respondents is the creation of a design collaboration community (R6, 8, 9, 10, 13, 16, 17, 19). Forty percent of respondents commented on the need to collate and share knowledge through documentation, workshops and collaboration between aerospace organisations and academia. Respondents argued that such a community of practice would help build the skills necessary for engineers and address the lack of operational experience, which often leads to over-engineered parts. As one noted, a catalogue of “intelligent and elegant solutions” would allow others to reference best practices (R10). However, concerns were also raised about the reluctance to share data between organisations (R9, 17) and the difficulty of ensuring data quality (R9). Despite this, respondents highlighted the openness of the additive community as a strength that could be leveraged to facilitate such collaboration (R13). Respondent 17 noted that a community of practice is beneficial given the high turnover of AM experts and the ongoing need for workforce training.

4.3.2. Integrated CAE and simulation environments

Respondents consistently emphasised deficiencies in current CAE and simulation support. Problems with file conversion, scalability, data loss and inefficiencies when transferring between tools were widely noted by respondent 5, with respondent 4 stating, “The transfer of files is poor. You get a lot of de-featuring, a lot of errors.” Additionally, due to the complexity of AM products, CAE software often struggles. Respondent 4 further explained, “Once you get to a certain level, it’s just painfully slow.”

Others highlighted traceability challenges, where each hand-off between tools “costs traceability and data quality” (R15). Respondents therefore expressed a strong need for an integrated AM CAE suite that combines simulation tools, databases and topology optimisation within a single package, enabling data integrity and direct export to AM machines (R5, 14, 15, 16, 18, 20). Improving simulation accuracy, particularly for stresses, microstructure, cooling rates and surface roughness, and addressing the “limited interoperability,” as highlighted by Respondent 16.

4.3.3. Simulation software and material properties data

Respondent 2 highlighted the need for co-development of AM software between engineers and providers to address aerospace challenges and enable design techniques such as topology optimisation. Respondent 10 bluntly stated that current AM “topology optimisation tools are s**t” for aerospace needs, while Respondent 16 noted that no topology optimisation software has yet been certified for aerospace. Respondent 18 further stressed that not only the AM material and process, but also the engineering method itself (i.e., the topology optimisation process), must be qualified.

Respondent 14 emphasised that improved software, robust simulations and extensive datasets can support quality assurance by enhancing traceability and managing variability between data, models and printed parts. They further underscored the role of digital twins in modelling AM product development and providing quality assurance.

The area’s most frequently suggested for development were data and simulation tools to predict and manage surface roughness issues in design and manufacturing (R6, R7, R12, R14, R16). Respondent 6 stated that surface roughness issues are currently time-consuming to overcome and that addressing them effectively during design largely depends on the engineer’s experience. Development of surface roughness measurement methods was also proposed (R14, R16). Respondent 14 commented that standard measures such as Ra and Rz are machining-centric and suggested Svk as an alternative, which may better capture fatigue-relevant properties (R14). Better modelling of roughness during design, combined with robust measurement methods, was seen as crucial to improving certification and qualification. Respondent 12 identified this as a key need for AM, given the close link between surface roughness and material properties.

4.3.4. AI generative design tools

Respondents highlighted the potential of developing design databases and artificial intelligence (AI)-driven generative design (R7, 10, 15, 3). Respondent 17 emphasised that AI will be the “key to success” for AM, as it could reduce reliance on specialists and extensive process and design education. Although generative AI tools are emerging, respondents noted several capability gaps. Respondent 19 highlighted the lack of support for transitioning between AM and traditional manufacturing, as well as the limited and immature integration of multiple processes in tools such as Fusion 360. High costs, reliance on proprietary tokens and dependence on cloud computing were also seen as barriers to adoption. Additionally, respondents raised concerns about ownership, expertise and the justification of AI-generated design decisions. Respondent 15 described fragmented workflows as the “Achilles’ heel” of generative design, noting that every data transition “costs traceability and data quality,” undermining certification. At the same time, they acknowledged the promise of these tools, observing that they can “quickly generate” complex geometries, such as lattices, that would otherwise take weeks to model in traditional CAD.

4.3.5. Summary of identified gaps and future developments

The insights provided by respondents suggest several other gaps for future development in AM knowledge and design support, including in situ monitoring (R2, 11), support structure design guides (R12) and the development of additional standards (R8, 11). The identified gaps, support development areas and future trends identified by the respondents are summarised in Table 6.

Table 6.

Summary of identified gaps and future trends

This section has detailed the various design supports aerospace professionals use to develop feasible and AM-suitable product designs. It highlights how these tools help in understanding AM benefits while accounting for the process’s unique constraints. Tables 4 and 5 summarise the features of these design supports, demonstrating how they effectively assist engineers in the design process. Additionally, Table 6 summarises the identified design support gaps, highlighting missing knowledge and areas for future development to create more effective design support. Thus, this section successfully addresses the second research question.

5.1.1. Material and process selection

In this initial stage, the AM design approach decisions focus on selecting the material for the product and the platform. Platform selection involves choosing the type of AM process and the specific AM machine that can produce the product, with early consideration for the size and orientation of the product. Respondent 11 stated that at this stage, an engineer considers the flow-down of system requirements and their specific component requirements and, based on these, conducts a detailed trade-off analysis of material selection and processes capable of forming those materials to evaluate AM process options.

Material selection was identified as a key initial consideration in the AM design process by respondents 1, 3, 4, 11 and 16. Respondent 1 remarked that material selection is “the first and foremost thing” because “every material in AM performs differently with certain designs.” This point was reinforced by Respondent 4, who stated, “some materials are harder to print in than others, so they require further thought.” Consequently, material selection is a topic that requires extensive discussion when defining the requirements for AM aerospace product development. Understanding how a material will behave in the AM process is essential for making appropriate design choices. This point was highlighted by Respondent 13, who emphasised that AM is “a very multidisciplinary technology.” They further explained that an AM designer must possess more than just AM design knowledge to succeed, stating, “A designer should not just be a designer. They should also have a fundamental understanding of the materials, the inspection, and all that type of good stuff.”

Material selection goes together with platform selection during the requirements definition stage. Respondent 4 described these two factors as “big hitters” that require early consideration, as they shape many of the discussions between the designer, product owners and manufacturing engineers. Respondent 11, who works for a governmental space agency, highlighted that their organisation has noted that their organisation has invested in “education on proper process selection and proper material selection” due to frequently encountering poor uses of AM, where inappropriate materials or processes were chosen because they were readily available. According to Respondent 11, it is “a very bad design philosophy” to base decisions solely on the materials and machines available within a company. Instead, designers should “select the [AM process] that makes sense for the application,” with due consideration for the material and the product size. As “size determines platform,” as stated by Respondent 3.

Process selection is a critical early consideration for AM products, with several factors to consider. Gradl et al. (Reference Gradl, Tinker, Park, Mireles, Garcia, Wilkerson and Mckinney2022) identified 12 attributes for aerospace component AM process selection that designers should consider. Gradl et al. (Reference Gradl, Tinker, Park, Mireles, Garcia, Wilkerson and Mckinney2022) noted that design requirements may limit the available process options, if not entirely dictate the selection. This limitation is particularly relevant when considering product size, material properties and process maturity requirements. To support designers in understanding the aerospace AM process selection process, Gradl et al. (Reference Gradl, Tinker, Park, Mireles, Garcia, Wilkerson and Mckinney2022) provide a graphic illustrating various AM aerospace processes and examples of their production capabilities. The graphic emphasises the trade-off between build/deposition rate and feature resolution of AM components.

5.1.2. Iterative requirement refinement

Respondents from different organisations highlighted material and process selection as critical early steps in the AM design approach. However, the way each organisation integrates AM-specific considerations into its design process was found to differ. Some organisations adopt a distinct approach for AM, emphasising process-specific requirements early. However, others integrate AM considerations into their existing design approach. Respondent 11 commented that they do not approach additive design differently from other manufacturing processes. Respondent 12 similarly stated that their company has design practices for developing a turbine rather than dedicated design practices specifically for AM. These responses highlight the variability in the AM design approach. Although AM has unique considerations, organisations may maintain a design approach across all manufacturing methods, integrating AM considerations into that approach instead of treating it distinctly. For example, Respondent 12 elaborated that their design approach is “mainly as [in] ordinary product development, but now we have a part with the design for AM as well,” explaining that AM-specific considerations may come later in their approach through defining requirements for different levels of testing due to selecting AM.

Once the requirements are set for the product, Respondent 13 explained that they then engage with the product owner and ask, “Did you mean these requirements, or did you actually mean this?” This next stage is where Respondent 13 states, “is what industry calls design for additive manufacturing,” as it marks the commencement of developing the product into a design optimised for AM, rather than merely a product produced using AM.

5.3.1. Verification and validation considerations

The initial conceptual designs are created and iterated to meet the requirements defined during the first stage. Designers focus on ensuring the design satisfies mechanical and thermal requirements and assessing whether it can meet the margins for these requirements (R11, 19). Hence, during this stage, designers must also consider how to verify and validate that the requirements will be met (R11). AM design verification is the confirmation that the specified requirements have been fulfilled, while validation is defined as confirming that the requirements or a specific intended use or application have been met, both requiring objective evidence (America Makes 2023). According to the ECSS standards, verification for space components is the process of demonstrating that a product has been designed and produced according to its specifications and is free of defects. While validation is the process of demonstrating that the product can accomplish its intended use in the intended operational environment (ECSS 2023).

At this stage, designers need to consider these aspects and evaluate how their design can achieve the benefits identified during the AM suitability evaluation (R10). With the requirements defining the value of AM from a product end-use perspective, designers in this stage focus on identifying the manufacturing opportunities provided by different concepts (R10). Respondent 10 noted that the initial concept phase can feel “all-encompassing” due to the numerous AM-specific considerations involved compared to traditional aerospace manufacturing processes. Stemming from the design-production integration of AM, as a designer tries to fully optimise their part for their process while ensuring it can be validated. Thus, the concept phase in the AM PDP may take longer than in traditional aerospace product development. However, the AM PDP allows for this additional time, as the design-production integration eliminates the time constraints associated with designing and manufacturing tooling once a concept is defined (R10).

5.3.2. New vs redesigned

This distinction between AM and traditional development also influences how new and redesigned products are approached in the PDP. Respondent 15 provided an example involving the early stages of designing concepts for custom AM space brackets. They begin by gathering requirements, boundary conditions and loads, then use algorithmic design in a CAE tool to create the initial concept geometry. Algorithmic approaches, such as topology optimisation, were found to be often employed as a starting point for structural components. Similarly, Respondent 16 explained that for structural components, they begin with their defined design space and collaborate with partners to perform topology optimisation. Once the topology-optimised design is generated, they then review it using aerospace-qualified FEA tools to develop the initial concept.

Similarly, Respondent 16 stated that their design philosophy for redesigned products is to create a design space that includes the original geometric volume and a test case before running a topology optimisation. This approach helps to avoid situations where they are “trying to optimise too many stuff all at once” and risk encountering a local minimum. Respondent 16 described breaking down mechanical environments into separate design and verification environments for the spacecraft actuator AM design. For example, in the initial mechanical design phase, they exclude vibration loads, and instead, the design focuses on proof loads, such as proof pressure for structural components or the ultimate load for electromechanical components. Then, they calculate other test cases in the verification design environment and make design adjustments as needed. This approach enables more targeted and efficient optimisation and is primarily based on the engineer’s practical experience.

For redesigned products, some respondents focused on keeping the product geometry as close to the original as possible while identifying areas where modifications could benefit the AM process. This review and modification process was often done in collaboration with the product owner through workshops to determine feasible changes. Respondent 3 suggested starting with the notional design, often a cast design, for redesigned products transitioning to AM production. Some of their customers favoured this approach as they were already changing the manufacturing method and, as noted by Respondent 3, “don’t want to add in two variables” in changing the design and the manufacturing process. As a result, their aerospace customers for redesign tended to take a conservative approach to their initial concept design during their implementation of AM, so only the manufacturing process needed recertification. Respondent 3 referred to this approach as adapting the product for AM, that the products are “redesigned for printability … not actually designed for AM.” This perspective was supported by Respondent 4, who described it as “design for printability,” and Respondent 5, who similarly referred to such designs as being “adapted to AM.” In this context, the initial concept design focuses on adapting the product to make it printable. For example, Respondent 4 described a scenario where AM was being used to replace a casting process, and the product required redesign because “some features easily castable are not easily additively manufactured.” Respondent 4 added that this approach requires continuous engagement with the product owner, asking questions such as, “If we were to make that change, does the part still retain its function?” Within this approach, designers have the freedom to modify elements like support structures to enable the manufacturing of the current design. A discussion with the product owner is then required to ensure that the designed support structures do not interfere with critical surfaces.

When the designer has greater design freedom to redesign a product, the extent to which a designer can modify the product can be constrained by the level of detail available in the original component design supplied by the product owner. This lack of detail can create challenges in determining how much adaptation is possible. Respondent 3 noted that they typically begin with drawings of the parts, which were often prepared for a casting manufacturing process. Consequently, designers “don’t necessarily get a great appreciation for what the actual endpoint is,” meaning they lack clarity on the final intended product being redesigned for AM. For example, if the casted product requires post-processing to drill holes, a designer may miss the opportunity to propose an AM-adapted design with integrated holes if this detail is not included in the original design. To address these challenges, Respondent 4 stressed the importance of asking design space-defining questions during workshops, such as identifying the product’s interfaces. Similarly, Respondent 2 emphasised the value of conducting workshops with key individuals designing the part before running simulation software. This collaborative approach enables design engineers to better understand where modifications can be made to simplify manufacturing in AM. It also ensures that manufacturers clearly understand the design’s constraints and what is feasible.

5.3.3. Balancing design expertise and hybrid manufacturing considerations

The quality of the initial concepts is heavily dependent on the knowledge and skills of the designer or engineer. At this stage, a review of the designs by multiple team members is necessary to ensure the optimal use of AM and confirm the feasibility of the concepts. However, a lack of AM knowledge among engineers can present challenges. Respondent 10 highlighted this issue by describing situations where a customer presents them with an AM aerospace part, and their immediate thoughts were, “This is a s**t design. What kind of idiot did this?” only for the customer to clarify later, “It was our AM expert.” This issue can arise when an engineer’s AM expertise and design focus too narrowly on mitigating a single AM design consideration or achieving a specific requirement without considering how a design choice impacts other requirements or AM-related constraints.

The interviews corroborated the process illustrated in Figure 1, as respondents evidenced that creating a product design involves a continual feedback loop to earlier stages and the parallel development of the manufacturing process. Designers must ensure their chosen process can reliably produce the product to meet requirements. Respondent 10 emphasised this point: “Even though we talk about design, you mainly talk about process as well… and all of a sudden, just talking about design isn’t just talking about design.” Respondent 17 viewed process selection as a part of the concept design phase due to the setup considerations required to get parts into production. These considerations included paperwork for powder management and the processes for material recycling.

At this stage, a designer should also consider how implementing a hybrid manufacturing process could facilitate the creation of a better product or improve the PDP. As Respondent 10 put it, “Stop trying to solve everything within the powder box,” highlighting that a design could, at times, be better achieved or improved in terms of cost, time, or performance by combining AM with traditional manufacturing or post-processing. Respondent 10 elaborated that designers should consider, “What are the bits that work well in the AM process, and what are the bits of design that could be done traditionally as an insert?”

Türk et al. (Reference Türk, Rüegg, Biedermann and Meboldt2019) provide an example of a hybrid manufacturing approach that combined the design freedom of AM with carbon fibre composites to produce lightweight, complex structures. Demonstrated on a robotic leg structure, their approach achieved a 55% weight reduction and significant lead time savings. With these considerations for a balanced and hybrid design approach, the next stage focuses on refining the design to fully integrate feasible DfAM principles and maximise AM’s advantages.

5.4.1. Leveraging design for X in AM

At this stage, respondents were found to follow or apply different Design for X (DfX) techniques to take advantage of AM’s interconnected design and production. DfX describes a range of product development techniques that can be applied to achieve concurrent improvements in a product’s cost, quality and cycle time (Huang & Mak Reference Huang and Mak1997). Well-established DfX tools like Design for Assembly (DfA), such as Boothroyd-Dewhurst Design for Assembly (Boothroyd Reference Boothroyd1994) and Lucas Design for Assembly (Miles Reference Miles1989), encourage designers to address manufacturing and assembly challenges during the design phase, reducing costs and time later in the PDP. DfAM is a subset of DfX, and the respondents noted how implementing AM made it easier to incorporate other DfX techniques. Enabling them to address their designs’ most critical success factors through AM’s alternative design freedoms. For example, AM complements DfA through enabling the use of part consolidation design methods, which can greatly reduce the number of parts needed to produce a component. Which in turn reduces the associated fasteners, interfaces, assembly operations and time. Such design changes are particularly advantageous for aerospace components, where each interface introduces potential failure points requiring inspection and qualification due to high safety and reliability requirements.

Respondent 1 called part consolidation one of the core elements of DfAM for aerospace, as it enables the removal of redundant weight by eliminating sub-assemblies. Additionally, Respondent 5 highlighted a key DfX consideration for AM, which they called “design for surface finish.” As highlighted in Section 4.1.2, surface roughness is a major consideration for AM products due to its potential impact on part performance, geometrical accuracy and downstream post-processing requirements, which increase time and costs (Obilanade et al. Reference Obilanade, Dordlofva and Törlind2021). The surface roughness condition is influenced by design and process factors, necessitating early consideration during design stages. A “design for surface finish” approach helps optimise surface roughness through considered design choices for features or orientation, improving part performance, meeting requirements, or minimising negative impacts on the PDP. However, Respondent 5 noted that such constraints “break the statement of design freedom” as the designer’s choices for design features or part orientations become limited.

Another approach noted by the respondents was Design for Functionality (DfF) (R7, 9, 10, 13). In the context of AM, DfF refers to a design approach in which the designer prioritises the intended function of the part over the constraints imposed by traditional manufacturing methods (Zhong, Ornelaz & Krishnan Reference Zhong, Ornelaz and Krishnan2017). Respondent 9 described DfF as a designer starting with the optimal design and then working backwards to accommodate constraints. They provided an example of an engine component, explaining that they “stripped [the design] back to first principles of what would the perfect cooling geometry look like for this application,” before determining how to achieve that geometry with their available manufacturing processes. In this approach, DfF focuses on designing the optimal cooling geometry for the application by first ensuring the best performance from a CFD and thermal dynamics perspective. Then, the part is refined to incorporate the constraints of the chosen AM process, ensuring manufacturability.

Respondent 10 explained that before implementing AM, their space antenna horn clusters were complex assemblies requiring welding, making them prone to discontinuities, failures and manufacturing errors. Using AM to consolidate the design, the final product achieved a 90% weight reduction compared to the original. This advantage is particularly significant in the space industry, where reducing weight translates to substantial cost savings. In 2020, the average launch cost per kilogram to Low Earth Orbit (LEO) was $10,313 for non-commercial satellites and $4,092 for commercial satellites (Adilov et al. Reference Adilov, Alexander, Cunningham and Albertson2022).

Respondent 7 noted that many customers realise they can integrate more functions into a single AM part, but this comes with trade-offs. Respondent 10 highlighted the compromise between manufacturing and functionality, explaining that AM, like all manufacturing processes, has rules and that “when you break the rules, you have to pay.” That payment is in cost, time or both, later in the PDP. For example, Respondent 10 explained that while AM may result in a slightly higher initialisation cost in the antenna cluster consolidation, improved functionality and weight reduction benefits justify the trade-off. One approach to optimising AM designs that requires trade-off considerations is topology optimisation. When implemented in AM, it presents unique challenges that require careful consideration, particularly in aerospace applications.

5.4.2. Topology optimisation and aesthetic constraints

For many traditional subtractive manufacturing processes, designers use topological optimisation to determine the most efficient material distribution geometry, treating the optimisation outputs as a conceptual design guide rather than a final design. Designers take the output and refine it to ensure feasibility for traditional manufacturing. This refinement is necessary due to the complexity of achieving the optimised design using conventional methods (Mirzendehdel, Behandish & Nelaturi Reference Mirzendehdel, Behandish and Nelaturi2020). With the design complexities offered by AM, some engineers attempt to print topological designs directly.

The outputted topology-optimised geometry can have imperfections due to factors such as mesh discretisation limitations and inaccurate density methods, leading to an inability to account for manufacturing-induced deviations (Pasini & Guest Reference Pasini and Guest2019). Respondent 10 noted that some organisations overly rely on these tools in AM, treating them as “black boxes,” inputting requirements and pressing print without refining the DfAM buildability or considering other AM performance impacts. Respondent 8 warned against design support that provides solutions in this manner, stating, “You don’t see why that solution was chosen or what could be the pitfalls in choosing this.”

Even when a topological design output meets the product requirements, aesthetic expectations in aerospace can present additional challenges. Algorithmic design techniques often produce organic-looking structures. Respondents noted that in aerospace, such structures can be viewed negatively due to preconceived notions about what a structurally sound part should look like and concerns about the difficulty of validating and verifying complex product designs. Respondent 10 provided an example where a chief engineer reviewed a customer-prepared part for printing and remarked, “This part will never fly. It’s too ugly!” Therefore, Respondent 10 coined the term “too ugly to fly” to describe designs that, despite effectively integrating AM design principles to meet requirements, are dismissed due to their aesthetic and require redesign. Respondent 10 elaborated that their organisation frequently redesigns their customers’ AM products to make them more acceptable for aerospace applications. A process they referred to as “two-and-a-half D optimisation,” in which they conduct the full 3D topology optimisation and then simplify the design to look like something that could have been machined, that is, it has smooth, flat surfaces and other aesthetic features that inspire greater structural confidence.

5.4.3. Balancing design optimisation and manufacturing constraints

AM design guidelines are applied to understand design limitations and process capabilities at this stage. These guidelines provide insight into constraints such as maximum buildable overhang angles and other process limits, helping designers navigate the many factors affecting a part’s design limitations.

Respondent 19 highlighted the various considerations and factors influencing the quality of an AM overhang, such as the bridge distance, print height and layer thickness. They emphasise that in implementing DfAM principles, one should approach the design from a “first-principles understanding of what can and cannot be done with the process.” Hence, during this DfAM principles integration stage, a designer becomes most aware of the design limitations for their product success imposed by the material, AM process and the specific printer (R10). An understanding of these limitations can be difficult to fully comprehend; thus, achieving optimal designs often requires iterative cycles of design, printing and refinement, providing valuable learning opportunities for new designers.

This stage of the design approach requires manufacturers to balance design limitations with optimisation while managing downstream impacts. These discussions on balancing typically occur during what Respondent 6 described as a “design for manufacturing review.” They elaborated that in this review, designers work with their machinists to establish “a certain number of rules regarding the parameters … [and] regarding the technology,” helping designers understand limits such as support structure types and sizes. At this stage, a designer with a strong understanding of AM and access to effective design support can leverage the AM process and its perceived limitations to enhance the product or more easily meet its requirements.

Respondent 11 provided an example of designing microchannels in rocket heat exchangers using laser powder DED processes. By understanding process characteristics, such as build angles and their resultant surface textures, designers can tailor these surfaces to benefit the application. For example, to meet specific requirements, such as achieving a specific pressure drop, designers might not need to prioritise designing to achieve as-built smooth internal surfaces or performing post-processing to ensure smoothness. Instead, as suggested by Respondent 11, by accounting for the expected as-built surface roughness within the channel, a designer can modify the channel design to augment the heat transfer or pressure drop by incorporating the surface roughness as a functional element. This approach allows the design to meet specified requirements without requiring adjustments away from the optimal design geometry or post-processing.

Respondent 10 provided an example of needing to assist customers in redesigning topology optimised parts because the client had not considered the post-processing’s impact. A topology-optimised part may be designed to handle a load in one direction, but once printed, it may need to be machined on a surface perpendicular to that load direction, where it lacks strength. Therefore, designers must account for how the post-processing machinery will handle the part during surface finishing when implementing DfAM principles and maximising their optimisation. This observation was supported by Respondent 17, who stated, “Just because something is topologically optimised, it’s not additive.” As designers integrate DfAM principles and balance design constraints, they must also anticipate the role of post-processing in achieving the final product requirements.

5.6.1. Pre-build simulation and process verification

At this fifth stage of the approach, designers use build preparation simulation tools to conduct these design iterations. Simulation will have been performed in earlier stages, including topological optimisation, CFD, stress analysis and other CAE simulations, to ensure the product functions while taking advantage of AM’s design complexities. The simulations at this stage are more focused on preparing for AM production, including modifications to the product’s design to ensure buildability, such as detailed design of support structures.

Although many considerations for buildability would have been addressed earlier, this stage verifies those decisions through AM pre-build CAE software, such as Magics by Materialise NV (R3, 4, 5, 15, 16, 17). Respondents 19 and 20 explained that during this stage, they conduct specific checks on the part geometry, using simulation tools to identify and highlight errors. Using both AM-specific tools like Magics or adapting traditional DfM systems to perform specific analyses. Slicing tools were also employed to examine design areas with uncertainties in more detail. Respondent 4 described this stage as “putting [the part design] through the process to get it onto the machine, as the machine likes it.”

The printing process is simulated here to identify potential issues that might impact the build’s success. As Respondent 3 stated, build simulations provide the user with “an indicative answer as to whether the build will be successful.” Respondent 2 gave examples of some factors they examine during this stage, such as features that have “sharp areas,” “stress raisers,” “recoater collisions,” “deflections,” “distortions,” or are at “risk of cracking.” The primary goal of using these simulations is to identify and address problems that could affect the build’s success. However, although these simulation tools help indicate the build success, as noted in 4.2.2 by Respondent 4, they help “identify problem areas, but not the magnitude.”

Respondent 3 explained that, for example, a simulation might identify an overhanging feature as challenging to build, but cannot specify whether it is entirely unbuildable by a process or will just lead to reduced geometrical accuracy or poor surface condition. Respondents 2 and 5 pointed out that this stage identifies and mitigates issues like distortion. Respondent 2 highlighted that pre-build simulation results allow designers to include pre-compensation in the design. Pre-compensation involves adjusting part features in the opposite direction of the expected distortion, so the part naturally corrects itself as it cools after printing. Similarly, Respondent 5 described addressing distortion by reinforcing supports or including “ghost parts” in overheating zones. Ghost parts are auxiliary structures or features added to manage thermal and mechanical stresses during the build process (Olleak et al. Reference Olleak, Adcock, Hinnebusch, Dugast, Rollett and To2024).

At this stage, designers collaborate closely with the OEM of the machine being used. Respondent 17 mentioned how they consult with their LPBF machine supplier to better understand the machine’s capabilities beyond what is available online or in user guides. They emphasised their need for more access to the OEM to ensure they had the correct material files to ensure accurate simulations and reliable production. Material files are digital representations of the physics-based behaviour of the material during the AM process, which help the pre-build software provide accurate simulations of part production.

5.6.2. Support structure design and build plate optimisation

Several respondents explained that simulations are conducted to explore the baseline support requirements automatically generated by CAE AM tools. These provide a starting point for feasibility assessment, after which engineers refine and optimise bespoke supports using their own design knowledge to minimise complexity and volume. This stage, where support structures are designed, was emphasised as one of the areas in which AM professionals have the greatest freedom to determine how to produce the part. This freedom in support structure design was emphasised as a key area for redesigned parts (R2, 3, 17), particularly when an OEM restricts a designer in how much they can adapt a part for AM. Respondent 4 stated they “create supports to avoid changing the part.” Respondent 3 highlighted their “flexibility in terms of adding stock material” because downstream manufacturing processes remove these supports. Designers use a combination of support structure design methods, including pre-build software-generated “block supports” and custom-designed CAD supports tailored to the part and process (R3).

When redesigning products for AM manufacturing, some engineers stated that before looking at the requirements, the first activity they do once they receive the part from the customer is to put it into the build preparation software. Respondent 4 stated, “Nine times out of ten – You probably won’t open CAD… you’d just open Magics.” This sentiment was echoed by Respondent 3, who stated that when redesigning products, “50% of the work’s done,” and their initial focus is determining “how you’re putting it [in the machine] … [and] how many will fit.” The respondents stated they wished to maximise the number of parts-per-build to fully utilise the AM machine’s capacity, either to reduce costs by achieving high output or to meet part orders without running multiple builds. Respondent 4 highlighted that orientation is a critical factor in maximising output but must be balanced against its impact on buildability. They explained that while one orientation might allow ten, another might only fit six, but could be the better choice to ensure successful builds.

Build simulation is a crucial process stage, requiring significant time and resources, even with expert knowledge and effective design support. Respondent 4 emphasised this, stating, “We shouldn’t underestimate that, because I would say if I look at a part… I’ll spend three days getting it ready,” adding, “I’ll spend a day at least having discussions and talking.” Highlighting the efforts involved in building a simulation, even after the part design is confirmed.

5.7.1. Design and process verification and qualification

The printing of prototypes helps provide confidence in the buildability of a design. However, Respondent 14 added that when prototyping, they often utilise in-line monitoring and inspection tools to gain more confidence in the part itself. Respondent 14 highlighted that underlying defects can go undetected, explaining that while a print may appear successful, “if there is nothing in the machine that tells us there is a lack of fusion, we can’t guess it.” Hence, there is a need for tools for verifying that the process has operated as planned.

Respondents 6 and 14 explained that they adhere to the ECSS material and process verification standards, citing standard procedures such as tensile and powder testing, including metallography and flowability. Respondent 6 described using a full engine thrust chamber prototype for water flow tests to verify that the pressure drops as expected, ensuring the surface roughness impact of the part aligns with the design. They further elaborated that the ultimate test of a part occurs during its use in the rocket. However, numerous qualification tests are conducted before an AM engine undergoes a hot fire test to ensure compliance with ECSS standards. Respondent 6 emphasises that even if the design is validated before the hot fire test, because it is an AM part, “It’s always a prototype.”

In addition to standard test coupons and ahead of full product printed prototypes, respondents 7, 14 and 16 highlighted the use of product-specific design artefacts that represent sections or features of their design. By isolating a part’s design feature into a representative design artefact, one can investigate specific material property issues, such as surface roughness at that feature. Respondent 14 explained that these artefacts act as “a prototype representative of the final shape of the hardware,” allowing them to inspect, test and validate the design. Describing a preference for a trial-and-error process or, as Respondent 16 terms, “learning by doing” through these artefacts, as they provide a better representation of the actual design than standard test coupons or simulation tools. As Respondent 7 conveys, “you can’t have a representation from like a tensile bar or a tube about the properties because it changes so much in the part.”

The use of product-specific artefacts to understand and assess uncertainties in AM design has been explored in the work of Dordlofva & Törlind (Reference Dordlofva and Törlind2020). Through a research collaboration with space industry companies, they studied three AM product development case studies and proposed the AM design artefact (AMDA) process, further developed into the AMDA method by Obilanade et al. (Reference Obilanade, Törlind and Dordlofva2024). This method describes how AMDAs can be used to investigate design, material properties and manufacturing uncertainties. Dordlofva & Törlind (Reference Dordlofva and Törlind2020) and Obilanade et al. (Reference Obilanade, Törlind and Dordlofva2024) provide detailed practical space industry-related examples of how these product-specific design artefacts help resolve AM-related uncertainties. Furthermore, although Respondent 7 identified this artefact-based approach as their preferred method for prototyping and testing, they also emphasised that it requires a “big cost of investment” in time and resources.