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Today, Aerospace 3D Printing will discuss the R&D model of 3D printing companies. Compared to traditional manufacturing, the R&D in 3D printing is more flexible and innovative, but it also faces unique challenges—how to establish effective management processes in the highly uncertain technological exploration? There is no standard answer to this question, but we can draw on experiences from other industries and adjust them according to the characteristics of 3D printing.
I believe the core contradiction in R&D management lies in the struggle between “innovation” and “process”. Rigid processes can stifle creativity, while complete freedom may lead to resource waste or deviation in direction. This contradiction is particularly prominent in the field of 3D printing: on one hand, the rapid iteration of technology and diverse application scenarios mean many projects are at the forefront of exploration; on the other hand, industrialization demands reproducibility, reliability, and cost control. Huawei’s IPD model has provided a methodology for complex product development, but its success relies on specific conditions—a large R&D team, clear market demand, and mature technology modules. Many projects in 3D printing are still in the stages of technology validation or application incubation, and directly applying the standardized IPD process may be counterproductive.
Therefore, I believe that for 3D printing companies, R&D management needs to be designed in layers. For industrialization projects with higher technological maturity (such as standardized equipment or material development), we can draw on the narrow IPD approach, ensuring efficiency through stage reviews and cross-departmental collaboration; while for original technologies or disruptive applications (such as new bioprinting or space manufacturing), a more flexible “innovation sandbox” mechanism is needed, allowing for trial and error and rapid pivoting. General Electric has adopted a dual-track system in the R&D of 3D printed aerospace components: one team focuses on optimizing existing technology processes, while another explores the performance of new materials under extreme parameters, with different assessment standards and resource allocation methods for each.
Most importantly, demand management is also a key pain point in 3D printing R&D. Many failure cases stem from misunderstandings of user scenarios—for example, a company developed a high-precision industrial printer but did not consider the compatibility of post-processing, leading to substandard yield of the final product. Such issues can be avoided through “reverse demand analysis”: at the project initiation stage, not only should technical parameters be considered, but also the entire operational chain from design to production should be simulated, even inviting frontline operators to participate in prototype testing. A German 3D printing service provider has established a “use case library” that archives past project demand deviations and solutions, requiring new projects to check against a checklist of typical pitfalls.
At the same time, the interdisciplinary nature of 3D printing also requires an upgrade in the review mechanism. Traditional R&D reviews are often led by a single technical expert, but 3D printing involves multidimensional interactions across materials, mechanics, software, and processes. A metal printing equipment manufacturer once faced this issue: engineers focused on increasing laser power to speed up the forming process, but overlooked deformation issues caused by thermal stress. Later, they introduced a “full perspective review meeting,” mandating participation from materials scientists, thermodynamics engineers, and even supply chain representatives to challenge technical assumptions from different dimensions. Although this mechanism increases short-term costs, it significantly reduces the risk of rework later on.
The culture of engineering is an invisible pillar of R&D management. The technological boundaries of 3D printing are constantly expanding, and the breakthroughs are often driven by teams with an extreme pursuit of technology. However, in reality, many companies rigidly evaluate R&D personnel with KPIs, leading to a prevalence of short-term behavior—such as pursuing the number of patents while neglecting fundamental process improvements, or blindly following popular technology trends. A healthy R&D management system should provide engineers with a “safe zone”: allowing a certain proportion of free exploration time, establishing a fault tolerance mechanism, and evaluating long-term value through a technical committee (rather than purely administrative levels). One of the secrets to the early success of American 3D Systems was allowing core engineers to spend 20% of their time on self-selected projects, several of which eventually became pillar businesses.
Finally, R&D management in 3D printing needs to evolve dynamically. As technology transitions from the laboratory to the factory, and from prototype manufacturing to mass production, the management focus must adjust accordingly. Early on, the emphasis may be on technical feasibility, while the mid-stage needs to strengthen design-manufacturing collaboration, and later stages should focus on standardization and cost control. Practices in 3D printing under the German Industry 4.0 framework show that successful companies often reassess their R&D processes every 18 months, eliminating redundant steps and adding adaptive rules. This mindset of continuous iteration may be more important than any ready-made methodology.
Ultimately, there is no “best practice” in R&D management for 3D printing, only “most suitable practices.” It requires managers to respect the uncertainty of technological innovation while distilling reusable methodologies from the chaos. What do you think?
Note: This article was organized and edited by Aerospace 3D Printing. Unauthorized reproduction is prohibited.
