While many Additive Manufacturing (AM) users rely on AM for prototyping purposes, the ultimate dream remains to achieve (series/high-volume) production in a repeatable and viable way. Most AM users looking to achieve production with AM, repeatedly ask software companies the same question: “Does your software enable production?” – A difficult yet pivotal question when one realizes that the AM software landscape is complex and often not well understood.
First and foremost, in the wide range of AM software solutions that can be used along the process chain, we have been able to identify:
- Software solutions used for part identification and application screening
- Software solutions used for production planning – Different categories fall into this group: Manufacturing Execution Systems (MES), Enterprise Resource Planning (ERP), and Product Lifecycle Management (PLM). Industrial additive manufacturing (AM) operators also rely on workflow software to manage extensive fleets of various printers across multiple production sites. In such cases, AM workflows need to be seamlessly integrated into the broader supply chain.
- Software solutions that can support different tasks of the actual manufacturing process. These tasks include the design, simulation, pre-processing, distribution, manufacturing, inspection, or quality assurance (QA) to name a few.
- Software solutions that support different areas of the manufacturing chain. This includes software solutions related to data preparation, in-process monitoring and analysis. While some solutions handle basic tasks like tracking machine parameters and monitoring data systematically, others focus on assessing print quality layer by layer by analyzing data from cameras or other sensors. These solutions have become practical for operators, particularly in production environments where similar parts are printed in larger quantities, to monitor quality throughout the build process.
- Other peripheral software solutions related to quote and order management, LCA solutions or IP protection for 3D printing files that can still support AM users.
- Software-driven workflows formalized into secure, end-to-end systems. Such platforms tackle every link on the AM production chain.
As you can see, the AM software landscape is large and complex. These categories do not always fit together in an AM workflow. However, depending on the user’s profile and production requirements, each of these categories can play a small role in achieving production with AM.
The question is: how?
To answer this question, we invited four contributors from industry and research as key contributors to this dossier.
- trinckle 3D GmbH, a company that focuses on streamlining and simplifying the design process, making it accessible even to those with minimal CAD experience. As per the words of Dr Ole von Seelen, Chief Commercial Officer, “This accessibility is key to enabling production at scale. By reducing design times by up to 95% and making the design process accessible to non-CAD experts, [trinckle]’s software not only facilitates the creation of production-ready designs but also empowers companies to scale their AM operations efficiently. This capability is essential for moving from prototyping to full-scale production, making [this] software a critical enabler in the AM production ecosystem.”
- Phase3D is a company that provides real-time inspection solution that uses structured light and data processing to help customers reach production faster. “In-situ inspection is a growing area in the software space for AM. The greatest challenge is high-quality input data that can be traceable and does not rely on AI-trained models,” Noah Mostow, Business Development Manager at Phase3D explains. The company that has decided to address this in its core business, provides unit-based measurements of the entire build process to identify anomalies and predict build failures in real-time.
- Formware that provides a CAM package, print job preparation of 3D print files. The company also provides a lot of highly automated algorithms and an SDK.
- And RWTH Aachen University – Digital Additive Production (DAP) Chair provides a wide range of digital solutions, including design automation algorithms, data preparation tools, and cybersecurity solutions for secure data sharing within distributed supply chains. Their data preparation tools are key in streamlining the transition from design to efficient production. In terms of cybersecurity, the Chair has developed software that streams manufacturing information, enabling design owners to utilize the production capabilities of a service provider without having to share their 3D designs. This streaming approach fosters a more connected production network and lowers the barriers to entry for additive manufacturing.
Interestingly, since achieving cost-efficient high-volume production and industrialization in AM requires a comprehensive digital end-to-end workflow that covers each process step from ideation to delivery, Moritz Kolter, Chief Engineer of the Digital Additive Production unit, believes that all software solutions that can support the different tasks of the actual manufacturing process from design to QA are of paramount importance.
The “up to 95%” design-time reduction is a supplier claim, not a universal production saving. In its Audi Sport case study, trinckle describes fixture design falling from hours to minutes. Results depend on the task and baseline. Phase3D’s measurements concern layer height and anomalies, rather than direct proof of every finished-part property.
For Kolter, and in general, “the barriers we face are more commercial than technological. First, certification remains a significant yet time-consuming and expensive process. By integrating quality assurance with printer OEM software, we could significantly enhance our digital capabilities, allowing for certification through in-situ monitoring. This approach could reduce both costs and the need for extensive external quality assurance testing.
Second, cybersecurity and intellectual property protection are still significant issues. These concerns limit many advantages associated with additive manufacturing (AM), such as innovative supply chain strategies. […]”
These comments describe possible improvements. In-situ monitoring does not by itself certify a part or eliminate application-specific inspection and qualification requirements. Data streaming also needs a defined security model, access controls and protection of the receiving equipment.
When focusing exclusively on software solutions that can support different tasks of the actual manufacturing process from design to QA, Dr Ole von Seelen, Chief Commercial Officer at trinckle 3D GmbH, said:
“ The most crucial software category to achieve production in additive manufacturing (AM) is the design automation and optimization category. This is because the design phase directly impacts the entire production process. Effective design automation allows for faster iterations, optimized structures, and cost-efficient production, which are critical for scaling up AM. Without robust design software, the other stages, such as simulation, processing, and quality control, would struggle to deliver the efficiencies needed for mass production. […]”
“In the design automation category, one of the primary challenges is balancing ease of use with the complexity of design requirements. Many AM users are not necessarily CAD experts, yet they need to create intricate designs that meet specific industrial standards. Another challenge is the need for iterative design processes, where multiple adjustments are often necessary before achieving the final product. This can be time-consuming and demands a high level of precision. Our software aims to address these challenges by automating repetitive tasks, reducing the design time significantly, and allowing users to achieve high-quality results with less manual intervention,” he adds.
For Noah Mostow, “without in-situ inspection, AM is producing parts without knowing the quality until time-consuming, expensive post-inspection is completed. This is not a scalable process nor does it meet true production standards, at least for critical or near-critical use applications” – hence the importance of real-time QA or in-situ inspection software to reach production.
According to Mostow, three main challenges hamper in-situ inspection: the fact that the data is too large to process or be used; the fact that outputs were not based on true, objective units and were subjective, and the fact that providers did not create a production-ready product. For this reason, Phase3D provides digestible data to facilitate the decision-making process. “Like any other form of manufacturing, data is the backbone to an efficient production process,” Mostow said.
In Elco Jongejans’s view, achieving production with AM software should involve a level of automation. Whether one deals with one-off items, small quantities or applications that are more evolved to production lines like jewelry production, the dental industry or the hearing aid industry, “the advantage of AM is that you can print 1000 unique items with the same effort as 1000 similar ones. So, there will always be some kind of manual/software labor involved. The generation of the 3D model (scanning teeth, CAD design of a jewelry piece or wax filling an ear canal) will take up most of the work. And this is hard to automate fully. The CAM part, converting the models to a 3D print file is already optimized and highly automated,” Jongejans explains.
The importance of cloud-based platforms
Cloud platforms can support shared storage, computing and collaboration across production sites. Their suitability depends on connectivity, latency, data governance, cybersecurity and integration requirements; local or hybrid deployment may be appropriate for some workflows.
According to Dr Ole von Seelen, “Cloud-based platforms should be relied upon when scalability, collaboration, and flexibility are key requirements. For companies looking to scale their AM operations across multiple locations, cloud-based platforms offer centralized control, easy access to data, and the ability to collaborate in real-time across different teams. Additionally, cloud solutions are ideal when integrating third-party applications, such as quality control or workflow management tools, as they provide a more seamless integration process. Cloud-based platforms also allow for quick updates and scaling without the need for significant infrastructure investment, making them a practical choice for expanding AM workflows.”
“From what we have seen in the market, some companies have built their own software or at least a custom version of third-party software. I believe this is caused by certain functionalities missing due to the unique applications specific companies have, but also because the AM software landscape is still evolving. However, relying on custom solutions can limit scalability in operations. With the growing capabilities and flexibility of cloud-based software, there are compelling reasons to adopt these solutions,” Moritz Kolter adds.
A few examples of solutions popped up in the market in recent years. They include for instance, the CO-AM platform from Materialise, or the ProCloud3D platform, developed by the German-Chinese consortium led by the Chair of Digital Additive Production (DAP) at RWTH Aachen University.
The ProCloud3D research platform architecture, for this purpose, is fundamentally based on the Open Vector Format (OVF), developed by the DAP Chair and the Fraunhofer Institute for Laser Technology ILT. Building on the OVF, a streaming protocol was developed to ensure efficient real-time transport of PBF-LB production data and relevant metadata for various PBF machines. The protocol includes both secure data transport and data encryption. With a high-performance nester developed by DAP, manufacturing jobs consisting of multiple parts can be automatically generated. In a cloud-based user interface, the functionalities are fully integrated and visualized. The project describes a route towards distributed manufacturing; the demonstration is not evidence that the platform has reached mass-market deployment.
The walls between AM and traditional manufacturing – from a software standpoint
Several companies are reluctant to fully integrate AM into their operations due to factors such as a lack of expertise, concerns over higher equipment costs, perceived complexity, material consumption, and overall resistance to change—these being the most common challenges. For this reason, certain companies prefer to explore a combination of AM and traditional manufacturing in their production to increase efficiency and reduce costs.
Kolter is one of the experts who believe in the complementarity of these manufacturing processes. Given the AM software landscape, he clarifies: “AM requires a different mindset regarding product design, supply chain setups, and the establishment of effective workflows. To successfully integrate AM, manufacturers should first determine the strategy for its use and then consider the necessary adjustments to the existing manufacturing process chain. Attempting to implement AM in isolation can lead to missed synergies and create friction within an organization. For instance, if a company engages in high-volume production using AM for only a few different components, there might not be a need for an AM-specific MES.”
In this vein, we can only agree with von Seelen who believes 5 key steps should be considered to reach production using AM software: education and training; pilot projects, design-automation-adoption, integration with existing workflows and scaling up gradually.
For Dr Ole von Seelen, pilot projects allow one to start with low-risk applications which can demonstrate quick ROI; while investment in design automation software not only streamlines the design process but it also helps in “reducing the complexity of transitioning from traditional to additive manufacturing.”
As you can see, the approach to integrating a software solution includes a few steps similar to the implementation of a 360° AM strategy. No matter how complex this transition from traditional manufacturing to AM is, one should be aware of the specific jobs that only certain AM software solutions can do and the specific ones that can be done for conventional manufacturing operations.
Software supports the AM production chain, but a production-ready workflow also depends on qualified equipment, materials, people and processes. Evaluation should focus on a defined application, integration effort and measurable improvements in quality, time or cost.
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