On April 2, 2025, the U.S. government announced a sweeping new tariff regime that impacts products produced from virtually every country in the world. In an official release, the White House says the move is meant to reprioritize manufacturing in the US. While many economists believe the new tariffs will not produce this result, it doesn’t change the fact that most US manufacturers will have some significant math in their immediate future.

If you buy finished goods, this is likely not a complicated feat. But if you buy raw materials and components from suppliers in other countries and then use those materials and components to make your products, you have a much heavier lift.

Hopefully your company has maintained a reasonable digital transformation investment strategy and you have one or even several digital assets that will make this process much easier and far more accurate than any manual process—especially once you have to deduce if you can absorb some of the costs or have to pass them on to customers.

If you are stuck scrolling through spreadsheets to figure out your exposure, have fun and good luck.

Here is a list of digital solutions commonly found in manufacturing, and how you can use them to find your tariff exposure, calculate your additional spend and decide if it’s worth eating any increase:

Enterprise Resource Planning (ERP)
Purpose: Centralized financial, inventory, and operational data management

Role in Tariffs:

• Provides financial visibility into product and material costs
• Tracks landed costs for imported components
• Supports decision-making on pricing adjustments
• Inventory tracking, but (near) real-time supply chain risk assessments may require additional risk management tools

Supply Chain Management (SCM)
Purpose: Optimizes procurement, logistics, and supplier management

Role in Tariffs:

• Models tariff impact on supply chain flows (e.g., supplier costs, lead times)
• Optimizes sourcing strategies to minimize cost increases
• Supports trade route and logistics adjustments to avoid tariff-heavy regions
• Tariff-specific impact simulations may require integration with ERP or specialized tariff analysis tools

Trade Compliance and Tariff Management Tools
Purpose: Ensures compliance with international trade laws and updates tariff classifications

Role in Tariffs:

• Tracks and updates tariff changes in response to regulatory updates
• Automates classification of goods under the correct Harmonized System (HS) codes
• Supports compliance audits and documentation for trade regulations
• Forecasting financial impact of tariff changes requires integration with ERP or BI systems

Business Intelligence (BI) and Predictive Analytics
Purpose: Data visualization and financial impact analysis

Role in Tariffs:

• Analyzes historical and real-time cost impacts of tariffs
• Models financial scenarios to predict margin impacts
• Integrates with ERP and trade compliance data to provide actionable insights
• Supports strategic decision-making on pricing adjustments and supplier shifts

Pricing Optimization Software
Purpose: Adjusts product pricing based on market conditions and cost fluctuations

Role in Tariffs:

• Determines whether tariff costs should be absorbed or passed on to customers
• Optimizes pricing strategies based on competitive market data
• Prevents margin erosion by aligning pricing with demand sensitivity

Product Lifecycle Management (PLM)
Purpose: Manages product design, BOMs, and supplier data

Role in Tariffs:

• Identifies which materials and components are subject to tariffs
• Supports product redesign efforts to reduce reliance on high-tariff materials
• Stores country-of-origin and trade compliance documentation
• Can be involved in redesigning products to mitigate tariff impacts

Digital Twins and Scenario Planning
Purpose: Virtual simulation of manufacturing operations for efficiency and resilience

Role in Tariffs:

• Simulates supply chain resilience strategies in response to tariff disruptions
• Models operational efficiencies to offset increased costs
• Tests alternative sourcing and logistics adjustments before implementation
• Less directly involved in product redesign than PLM tools

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The information and insight shared at AeroDef’s conference tracks will address topics critical for bolstering the aerospace and defense industry. Among the conference sessions scheduled for the event are:

• U.S. Army Col. Jeffrey Jurand, project manager for the XM30 Combat Vehicle at the Detroit Arsenal, will speak on his team’s experience leveraging CAD models on the XM30 project.
• Strengthening Cybersecurity in Machine Tools in Industry 4.0 by Siemens Industry on how machine tool builders and users can implement effective cybersecurity strategies to meet Defense Federal Acquisition Regulation Supplement requirements, including access control, system and communications protection, incident response, audit and accountability, and physical protection.
• Neo Stereolithography Models for Advanced Aerospace Wind Tunnel Testing by representatives from Stratasys and Embry-Riddle Aeronautical University. This session will explore how a collaboration between Stratasys and Embry-Riddle has generated stereolithography 3D-printed models for advanced wind tunnel testing that offer cost savings and shorter production timelines while maintaining important parameters for testing.
• AI Technical Data Packages: Learnings from the First Deployment by representatives from Boeing and Authentise on how AI has been used to assist in generating Technical Data Packages from engineering workflows to ensure essential specifications and compliance data are documented in a timely manner.

Attendees will also hear from additional experts directly on “The Deck,” a theater space adjacent to exhibitors. These presentations, with Q&A sessions, will bring to light current and future factors impacting national security. AeroDef Manufacturing’s Deck will feature topics including the future of land systems, quality standards (federal and commercial), U.S. Department of Defense sustainment gaps and solutions, workforce development, and other critical topics, including:

• Design for Manufacturing: Taking Innovation to Industrialization! by Kimberly Caldwell, senior director, Defense & Space Engineering and Global Research & Technology at Spirit AeroSystems.
• The Future of Composites in National Security, Energy, and Defense, a panel discussion featuring representatives from Michigan State University, U.S. Army DEVCOM, U.S. AFRL, and Nexight Group.
• Strengthening the Navy Industry Education Connection, a panel discussion featuring representatives from Tooling U-SME, Macomb Community College, the Maritime Industrial Base Program, and Dynasty Fab.

New sessions, as part of RAPID + TCT’s technical conference, include automation assembly and robotics; sustainment solutions for military equipment; design for manufacturing in an age of AI and Industry 4.0; cybersecurity for manufacturing operations; composite manufacturing and advanced materials; and digital engineering, modeling, and simulation.

Complimented by innovative suppliers like the Array of Engineers, the U.S. Army Combat Capabilities Development Command community, and the Air Force Research Lab, this year’s event will include discussions about funding opportunities, supply chain resiliency, and optimizing manufacturing techniques and processes. AeroDef Manufacturing will convene all stakeholders, including key leadership from the U.S. Army, U.S. Navy, U.S. Air Force, and U.S. Space Force, along with the companies supplying the next generation of A&D systems and equipment.  

Also new for 2025, the Michigan Alliance of APEX Accelerators will sponsor and host the Knowledge Bar to support suppliers looking to do business with the federal government. Attendees will receive hands-on guidance on SAM (System for Award Management) registrations, explore certifications and innovation programs, and learn actionable strategies for success in the federal marketplace.

For the first time, the event will be collocated with three other major industry events: SME and the Rapid New Group’s RAPID + TCT event for additive manufacturing (AM) and industrial 3D printing; SAE’s trademark mobility event — the World Congress Experience (WCX), which emphasizes innovation in advanced mobility; and America Makes’ Spring Technical Review and Exchange (TRX), a public-private partnership for AM technology and education.

To learn more about AeroDef Manufacturing 2025, visit aerodefevent.com. Stay tuned as Engineering.com covers this event live, April 8-10, 2025.

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In this context, polyether ether ketone (PEEK), polyetherketoneketone (PEKK) and polyetherimide (also known as PEI or ULTEM) are particularly notable for their excellent mechanical and chemical resistance properties, which are retained under high temperatures. In fact, the relatively high heat resistance of these thermoplastics is both a benefit for aerospace applications and a challenge for 3D printing, especially when comparing them to other standard plastics, such as polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS).

3D printed PEEK parts for aerospace

PEEK has several key properties that make it appealing for aerospace applications. These include its high strength-to-weight ratio, thermal resistance, chemical and corrosion resistance and low outgassing. The latter is particularly critical for spacecraft and satellite applications. In addition, PEEK meets the flame, smoke and toxicity (FST) requirements for the FAA and EASA.

With the advancement of 3D printing technologies, there are now several options for 3D printing PEEK aerospace components. Some fused filament fabrication (FFF) machines can process PEEK, though these need high temperature extruders capable of operating at 400˚C, as well as heated platforms and build chambers. Selective laser sintering (SLS) can produce parts from PEEK powder, and has the advantages over FFF of not requiring supports and operating at higher resolutions, though these also come at a higher cost.

Additive manufacturing with PEKK for aerospace

Like PEEK, PEKK offers a high strength-to-weight ratio, with some suppliers claiming that PEKK parts can be as strong as aluminum at less than half the weight. PEKK also has excellent wear and chemical resistance, in addition to being easier to 3D print than PEEK due to the former’s lower crystallization rate. This makes it less prone to cooling issues, such as warping. PEKK also meets the FAA and EASA FST requirements for use in commercial and military aircraft.

Although 3D printing PEKK parts with FFF requires a lower extruder temperature (340 – 360˚C), it still requires a heated platform and build chamber. PEKK can also be 3D printed using SLS, with some suppliers offering PEKK powders with carbon fiber compounded in to improve performance.

3D printing ULTEM for aerospace

Introduced to the market by General Electric in 1982, Ultem has similar characteristics to PEEK but with a lower impact strength and narrower temperature range. However, it’s also less expensive, with some copolymers, such as ULTEM 9085 CG (certified grade), meeting the FST requirements of the FAA and EASA. Other ULTEM copolymers incorporate recycled scrap or residue and are certified as renewable.

ULTEM 9085 is specifically designed for 3D printing processes, specifically FFF, though the material is sensitive to moisture, which can affect both extrusioTn and the properties of the printed part. Advice on the optimal nozzle temperature for extruding ULTEM varies but there is experimental evidence that resins and composites need a temperature range of 375 – 420˚C for best results.

3D printing thermoplastic aerospace components

Depending on the required material properties, PEEK, PEKK and ULTEM can be used to 3D print a variety of aerospace components. Examples include cabin interior parts (brackets, panel fasteners and ventilation ducts), structural components for unmanned aerial vehicles (UAVs) or satellites, electrical insulation (wire clamps and connectors); and fluid and pneumatic systems (fuel line supports, valve housings).

Deciding which material is the best option for your particular application will depend primarily on your budget and thermal/mechanical requirements. In any case, the ever-present demand to reduce weight without compromising safety for the sake of fuel efficiency means that the market for additive manufacturing of thermoplastics like PEEK, PEKK and ULTEM will continue to grow.

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The unmanned aircraft system (UAS) is designed to equip the Army’s Infantry Brigade Combat Teams with the ability to deliver accurate, long-range strikes against tanks, armored vehicles and fortified positions. According to Cummings, the drone achieved a speed of 384 mph during a series of tests in early January.

The demonstration, which occurred at Fort Moore, Georgia earlier this year, involved a GPS-guided tactical mission using an inert warhead. The company reports that all primary mission objects were met, with the airframe and key subsystems revalidated at Technology Readiness Level 7 (TRL-7). The demonstration follows 12 previous flight tests conducted on the Hellhound airframe over the past two years to establish the system’s core capabilities.

Cummings claims the entire system – vehicle, launch canister, and ground control system – weighs less than 25 pounds, making it deployable by a single soldier, who can also field-swap payloads without the need for tools in less than five minutes.

In the near future, Cummings plans to conduct additional flights tests of the Hellhound S3 to bring the entire system to TRL-7 and submit a proposal formally offering the system to the Army’s Low Altitude Stalking and Strike Ordinance (LASSO) program. The company also intends to conduct further demonstrations and tests for other (unnamed) customers.

“Hellhound’s performance at AEWE 2025 highlighted a fundamental reality — speed matters, and quadcopters and prop-driven drones take too long to get downrange,” said Sheila Cummings, CEO of Cummings Aerospace in a press release. “While quadcopters and propeller-driven drones will still be puttering along behind friendly lines, Hellhound will already be over the target area, giving IBCTs [Infantry Brigade Combat Teams] the ability to strike faster, reach deeper into the battlespace, and decisively engage fleeting, time-sensitive targets.”

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Altair solutions help JetZero connect high-fidelity CFD simulation with engineering processes, enabling faster and more efficient conceptual and preliminary design analysis of aerodynamic surfaces and structures. FlightStream offers high computational speeds and minimal hardware requirements, featuring a simplified user interface and an advanced aerodynamic solver to support early-stage design iterations and aerodynamic studies.

JetZero is also a member of the Altair Aerospace Startup Acceleration Program (ASAP). Through ASAP, JetZero gains affordable, flexible access to Altair’s entire portfolio of simulation, data analytics, and artificial intelligence (AI) tools, including solutions to conduct interior noise studies.

Blended wing airplanes differ from traditional tube-and-wing designs by integrating the wings with the body, allowing all surfaces to contribute to lift and reduce drag. A wider body provides more passenger space or increases payload capacity for a freighter variant. The blended wing structure is lighter and quieter than conventional aircraft. Top-mounted engines direct noise upward during takeoff and landing, reducing noise near airports. JetZero aims for a first full-scale flight in 2027.

For more information, visit altair.com.

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Survey results highlighted escalating trade conflicts, rising global tensions, and persistent supply chain disruptions are placing unprecedented pressure on manufacturing and supply chain leaders.

Despite these challenges, Fictiv says the report also shows momentum in onshoring, AI adoption, and increasing reliance on digital manufacturing platforms.

“Concerns about tariffs and trade wars are clearly top of mind for manufacturing and supply chain leaders,” says Dave Evans, co-founder and CEO of Fictiv. “We’re seeing a level of global uncertainty and supply chain disruption we haven’t seen since 2020. However, the report also shows that companies are embracing new technologies and strategies to build more resilient and agile supply chains.”

Key Findings

• Global Uncertainty on the Rise: 96% are concerned about the impact of current trade policies, and 93% believe trade wars will escalate in 2025.
• Supply Chain Disruptions Accelerating: 77% report a lack of resources limits their ability to manage the supply chain effectively, and 68% prioritize onshoring as a key strategy.
• Scaling Production More Difficult: 91% face barriers to product innovation, and 86% report sourcing parts takes time away from new product introduction. However, 90% see digital manufacturing platforms as essential.
• Sustainability Takes Hold: 95% report that weather and climate events impact their supply chain strategy, and 91% have sustainability initiatives and governance in place.
• AI Advances: 87% report advanced levels of AI maturity, and 94% use AI for manufacturing and supply chain operations.

Fictiv says its report underscores the need for manufacturers to embrace innovation and adaptability by building more resilient supply chains, leveraging digital manufacturing, embracing AI to transform operations from inventory management to product design, and prioritizing sustainability.

This is the tenth year Fictiv has commissioned the report.

Download the full 2025 State of Manufacturing & Supply Chain Report here.

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A team of researchers from the Johns Hopkins Applied Physics Laboratory (APL) and the Johns Hopkins Whiting School of Engineering have seized that opportunity by using artificial intelligence (AI) to identify AM processing techniques that improve both the speed of production and the strength of these advanced materials.

“The nation faces an urgent need to accelerate manufacturing to meet the demands of current and future conflicts,” said Morgan Trexler, program manager for Science of Extreme and Multifunctional Materials at APL in a press release. “At APL, we are advancing research in laser-based additive manufacturing to rapidly develop mission-ready materials, ensuring that production keeps pace with evolving operational challenges.”

The team leveraged AI-driven models to map out previously unexplored manufacturing conditions for laser powder bed fusion (L-PBF). According to the researchers, their results challenge long-held assumptions about process limits, revealing a broader processing window for producing dense, high-quality titanium with customizable mechanical properties. The findings focus on Ti-6Al-4V.

“For years, we assumed that certain processing parameters were ‘off-limits’ for all materials because they would result in poor-quality end product,” said Brendan Croom, a senior materials scientist at APL, in the same release. “But by using AI to explore the full range of possibilities, we discovered new processing regions that allow for faster printing while maintaining — or even improving — material strength and ductility, the ability to stretch or deform without breaking. Now, engineers can select the optimal processing settings based on their specific needs.”

The ability to manufacture stronger, lighter components at greater speeds could improve efficiency in shipbuilding, aviation and medical devices, in addition to contributing to a broader effort to advance additive manufacturing for aerospace and defense.

The team’s machine learning approach revealed a high-density processing regime previously dismissed due to concerns about material instability. With targeted adjustments, the team unlocked new ways to process Ti-6Al-4V.

“We’re not just making incremental improvements,” said Steve Storck in the press release. Storck is chief scientist for manufacturing technologies in APL’s Research and Exploratory Development Department. “We’re finding entirely new ways to process these materials,” he said, “unlocking capabilities that weren’t previously considered. In a short amount of time, we discovered processing conditions that pushed performance beyond what was thought possible.”

Instead of manually adjusting settings and waiting for results, the team trained AI models using Bayesian optimization, a machine learning technique that predicts the most promising next experiment based on prior data. By analyzing early test results and refining its predictions with each iteration, AI rapidly homed in on the best processing conditions — allowing researchers to explore thousands of configurations virtually before testing a handful of them in the lab.

This approach allowed the team to quickly identify previously unused settings — some of which had been dismissed in traditional manufacturing — that could produce stronger, denser titanium. The results overturned long-held assumptions about which laser parameters yield the best material properties.

“This isn’t just about manufacturing parts more quickly,” Croom said. “It’s about striking the right balance among strength, flexibility and efficiency. AI is helping us explore processing regions we wouldn’t have considered on our own.”

Storck emphasized that the approach goes beyond improving titanium printing — it customizes materials for specific needs. “Manufacturers often look for one-size-fits-all settings, but our sponsors need precision,” he said. “Whether it’s for a submarine in the Arctic or a flight component under extreme conditions, this technique lets us optimize for those unique challenges while maintaining the highest performance.”

Croom added that expanding the machine learning model to predict even more complex material behaviors is another key goal. The team’s early work looked at density, strength and ductility, and Croom said it has eyes on modeling other important factors, like fatigue resistance or corrosion.

“This work has been a clear demonstration of the power of AI, high-throughput testing and data-driven manufacturing,” he said. “It used to take years of experimentation to understand how a new material would respond in our sponsor’s relevant environments, but what if we could instead learn all of that in weeks and use that insight to rapidly manufacture enhanced alloys?”

The recently published paper focused on titanium but, according to Storck, the same AI-driven approach has been applied to other metals and manufacturing techniques, including alloys specifically developed to take advantage of additive manufacturing.

The research is published in the journal Additive Manufacturing.

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Initial investment costs

Digital prototyping requires advanced software, hardware, and integration with existing systems, which can be expensive and require a team of engineers with strong expertise in a number of disciplines. Companies must invest in high-performance computing (HPC) resources, VR/AR headsets, simulation software and cloud storage. Small and mid-sized manufacturers will need a focused plan to deal with the cost of licensing, training, and infrastructure upgrades necessary to support digital prototyping workflows.

Software and hardware compatibility

Integrating digital prototyping tools with existing CAD, PLM, and ERP systems is complex. Many companies rely on legacy software that lacks seamless compatibility with modern digital platforms. Additionally, hardware limitations, such as insufficient GPU power for real-time rendering or VR simulation, can hinder performance.

Ensuring interoperability across different systems requires extensive customization, middleware solutions, and adopting standardized file formats. Converting models between different software such as CAD to a simulation suite, may cause loss of parametric data, constraints, or surface definitions. And older versions of software may not support files created in newer versions, leading to workflow bottlenecks.

Learning curve and skill gaps

Digital prototyping tools involve complex 3D modeling, real-time simulation, and data analytics, which require specialized expertise. Many manufacturing engineers are trained in traditional CAD and FEA simulations but may lack experience with VR, AI-driven simulations, or generative design. Companies must invest in training programs and hire or upskill personnel, which can slow adoption.

Data management and cybersecurity

Digital prototypes generate vast amounts of data in the form of design files, simulation data, and testing results which require efficient storage and version control. Managing this data within PLM and cloud systems introduces risks related to cybersecurity, intellectual property theft, and compliance with industry regulations (such as ITAR for aerospace manufacturing). Companies must implement strong encryption, access control, and secure cloud storage solutions to protect sensitive information.

Computational limitations for simulations

Real-time physics simulations, fluid dynamics (CFD), and stress testing (FEA) require high computational power. Companies using VR-based digital prototyping may experience latency issues, especially with large, complex assemblies. Implementing Level of Detail (LOD) algorithms, cloud-based processing, and GPU acceleration can help mitigate performance bottlenecks.

Validation and regulatory compliance

Some industries, such as aerospace, automotive, and medical device manufacturing, require extensive physical testing for regulatory approvals. Digital prototypes, while highly accurate, may not always replace real-world durability tests, crash simulations, or clinical trials. Companies must ensure that their digital twin models are validated against physical results to comply with industry regulations.

Yes, there are always challenges when investing in next generation technology. However, companies that strategically invest in digital prototyping, train their workforce, and optimize data security and processing power can unlock substantial benefits. As cloud computing, AI, and VR technology continue to evolve, overcoming these obstacles will become more manageable, leading to faster product development, cost savings, and improved manufacturing efficiency.

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By integrating VR with CAD (Computer-Aided Design) software, PLM (Product Lifecycle Management) systems, and real-time physics simulations, engineers can gain unparalleled insights into product behavior before physical prototyping. But there are several technical intricacies of VR in relation to digital prototyping and its applications, integration challenges, and benefits to manufacturing.

Integration of VR with CAD and PLM

Modern VR-based digital prototyping heavily relies on CAD and PLM integration. CAD software exports 3D models in VR-compatible formats (such as FBX, OBJ, GLTF) that allow engineers to examine prototypes within the virtual environment. When paired with PLM systems, engineers can track version histories, collaborate in real-time, and integrate design modifications directly into the production workflow. This connectivity ensures that design iterations remain structured and accessible to all stakeholders.

To enhance VR compatibility, many CAD software solutions incorporate native VR apps or VR plug-ins, which allow direct visualization of engineering-grade 3D models in VR without cumbersome file conversions. These tools support parametric modeling and real-time geometric modifications, ensuring high fidelity in virtual environments.

Real-time physics-based simulations

VR goes beyond static visualization by enabling real-time physics-based simulations that engineers use to assess product performance under various conditions.

Simulations can include:

Structural Analysis: Finite Element Analysis (FEA) simulations are rendered in VR, allowing engineers to visually inspect stress distributions and failure points in a virtual space.

Fluid Dynamics: VR-integrated Computational Fluid Dynamics (CFD) simulations enable engineers to observe airflow patterns, heat dissipation, and liquid flow behaviors from a first-person perspective.

Material Deformation: Soft-body physics can replicate material flexing, bending, and breaking under applied forces, giving engineers an intuitive understanding of how materials respond to different loads.

Haptic feedback and realistic interaction

One limitation of traditional digital prototyping is the inability to physically interact with the model. VR overcomes this challenge by incorporating haptic feedback devices, which simulate tactile sensations and resistance. Such devices allow engineers to “feel” surfaces, textures, and resistances as they manipulate virtual components.

In addition to haptics, real-time rendering techniques such as ray tracing and shadow mapping improve visual realism in VR environments. High-performance GPUs enable photorealistic rendering, ensuring that materials, lighting conditions, and reflections closely mimic real-world properties. By integrating physics engines developed by a number of different companies, VR prototypes can react dynamically to user interactions, providing a near-physical testing experience before production.

Design validation and ergonomics testing

Manufacturing engineers can use VR for comprehensive design validation before committing to expensive tooling and fabrication. Dimensional accuracy checks assess tolerances and fitment by placing components in a simulated assembly line, while ergonomics assessment using VR simulations allow engineers to test human-machine interactions, ensuring that equipment is comfortable and efficient for operators.

Instead of relying on physical mock-ups, engineers can conduct virtual usability studies, allowing stakeholders to evaluate user experience and product functionality in various conditions.

Industry-specific applications of VR prototyping

Automotive: Car manufacturers use VR to perform full-scale vehicle prototyping, enabling designers to test aerodynamics, visibility, and cockpit ergonomics before building physical models.

Aerospace: Engineers visualize and test complex aircraft components, such as turbine blades and fuselage assemblies, in VR environments with real-world physics simulations.

Consumer electronics: Companies test user interfaces and device form factors in VR to refine designs based on virtual consumer feedback.

Medical device manufacturing: VR enables precise simulation of surgical instruments and implants, helping engineers refine designs for biomechanical compatibility.

Technical challenges and solutions in VR prototyping

Despite its advantages, VR prototyping presents several technical challenges. Combining multiple engineering datasets (FEA, CFD, PLM) into a cohesive VR simulation can be challenging, but standardized file formats (USD, STEP, and FBX) streamline data exchange across platforms.

Running detailed CAD models in VR can be costly, as the high computation output requires powerful GPUs and optimized software workflows. Using Level of Detail (LOD) algorithms and real-time model decimation can improve performance without sacrificing accuracy. These algorithms optimize performance by adjusting the complexity of 3D models based on their distance from the viewer or their importance in the scene. Here’s how they work:

Dynamic mesh simplification – LOD algorithms swap high-detail models for lower-poly versions when objects are further away, reducing GPU load without affecting perceived visual quality.

Adaptive rendering – By prioritizing detail only where needed (on user-interacted components), LOD ensures real-time rendering efficiency.

Improved frame rates – LOD prevents frame rate drops by decreasing the polygon count in non-critical areas, ensuring smooth VR interactions at 90+ FPS (critical for reducing motion sickness).

Memory optimization – Less-detailed models free up GPU memory, allowing for larger assemblies and complex simulations without performance bottlenecks.

Hybrid use with culling techniques – Combined with occlusion culling (hiding objects not in view), LOD further enhances computational efficiency.

Future trends

The future of VR-based digital prototyping in manufacturing is set to become even more powerful with advancements in AI-driven automation, cloud-based collaboration, and hybrid AR-VR environments.

AI-driven automation integrates machine learning algorithms that analyze designs in real time to detect structural weaknesses, suggest material optimizations, and even predict potential manufacturing defects before physical prototyping begins. By continuously learning from past designs and simulations, AI can help engineers refine product performance and reduce costly trial-and-error iterations. This capability will significantly shorten development cycles while improving the reliability and manufacturability of new products.

In addition, cloud-based VR collaboration will redefine how global engineering teams interact with digital prototypes. Instead of requiring high-end local hardware, cloud-rendered virtual workspaces will allow engineers to access and manipulate detailed VR models from anywhere in the world. This technology will enable real-time design reviews, remote troubleshooting, and seamless integration with PLM (Product Lifecycle Management) systems, ensuring that teams remain aligned even when working across different locations. Cloud-based VR will also facilitate large-scale manufacturing projects by enabling multiple stakeholders—from designers to production managers—to interact with virtual prototypes without needing specialized workstations.

Furthermore, the rise of AR-VR hybrid environments will bridge the gap between digital and physical prototyping. By overlaying VR-generated 3D models onto real-world objects using Augmented Reality (AR), engineers will be able to test virtual components in real-world settings without requiring a full digital or physical setup. This will be particularly useful for ergonomics testing, assembly validation, and factory layout optimization, where seeing how a virtual component interacts with real machinery or workspace constraints is crucial.

As these technologies continue to evolve, VR-based digital prototyping will become an intelligent, collaborative, and highly integrated system, streamlining manufacturing workflows and enabling faster, smarter product development.

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Let’s take a closer look at each one.

#1 – Regulatory challenges in additive manufacturing for space

As any aerospace engineer knows, this is an industry built around regulation. For space-based applications of AM, this is arguably the biggest challenge. “A lot of the time, we can get to the desired shape, but convincing the engineering bodies – the regulators – that it’s going to be fit for purpose, safe and reliable for highly critical missions is the real hurdle,” says Michael Shepherd, VP of aerospace and defense at 3D Systems. Part of the issue, as Shepherd explained, is that 3D printing processes have fewer years of historical data while the technology continues to evolve rapidly. That combination means regulators aren’t always satisfied with the available information.

#2 – Difficulties with testing 3D printed parts for space

The obvious solution to regulators’ concerns about additive manufacturing parts for space being relatively untested is to do more testing. Unfortunately, this isn’t as straightforward as it might seem. One of the biggest advantages 3D printed components have over their traditionally manufactured counterparts – geometric complexity – can be a significant challenge when it comes to part analysis and non-destructive testing (NDT).

“In a lot of aerospace applications, you’re really concerned about flaws that may be hidden in the interior of the component,” explains Shepherd. “So, you might be looking at various types of X-ray or computerized tomography, eddy current inspection or fluid penetrant to find very fine surface cracks. With 3D printing, all of that can get harder because the sections can be very complicated shapes which may or may not be amenable to the NDT techniques you’re using.”

Moreover, consolidating multiple components into a single, complex structure – another of 3D printing’s oft-touted benefits – exacerbates this issue further. Beyond the structures themselves, the materials used in additive present a unique set of challenges on their own.

#3 – Materials challenges in additive manufacturing for space

The variety of materials available for additive manufacturing has grown prodigiously over the past decade. This means aerospace engineers have increasingly more options from which to choose when designing 3D printed components destined for space. However, the additive process itself can complicate matters by changing the way even well-understood materials behave.

“We’re printing metals, polymers and composites, but even to the extent that those materials are mature in the aerospace portfolio, a lot of the time the manufacturing process is different,” Shepherd explains. “I got my PhD in Ti-64, and the microstructure you get from using an additive process is different from the old-school, heat-and-beat metallurgy because we’re not forging it; we’re creating it with a very complicated welding process in the form of laser powder bed fusion.”

Hence, even when the chemistry is the same, the mechanical behavior and failure modes of a 3D printed part can differ. This is why extensive testing is so important in AM applications but, as indicated above, that also presents a hurdle for space-based AM parts.

The future of additive manufacturing for space

One thing all three of these challenges have in common is that they can be lessened with time. As more space-based missions are run using 3D printed parts, organizations such as NASA, the FAA and EASA will accumulate more data demonstrating their reliability. Not only will this lower the regulatory hurdles additive parts need to clear, it will also inform future testing as well as materials development. Additive manufacturing has come a long way for space-based applications, and it still has a long way yet to go, but at least it’s moving in the right direction.

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