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<h2>Key Takeaways</h2><ul><li>The surface finish chart below converts between Ra in micrometers, Ra in microinches, and ISO N-grades.</li><li>For most machined surfaces, Rq (RMS) is about 11% higher than the Ra value, but you cannot obtain an accurate Rq from Ra alone.</li><li>N-grades come from ISO 1302, which ISO records as withdrawn and replaced by ISO 21920-1:2021. But they still appear on drawings, so you still need to read them.</li></ul><h2>The Surface Finish Chart</h2>This is the core conversion table, with the first three columns taken directly from ISO 1302.[1] Ra is the reference column, because every other unit here is derived from it or maps onto it.<div><table><tbody><tr><td>N-grade</td><td>Ra (µm)</td><td>Ra (µin)</td><td>Typical Rq/RMS (µin)</td><td>Notes</td></tr><tr><td>N1</td><td>0.025</td><td>1</td><td>1.1</td><td> </td></tr><tr><td>N2</td><td>0.05</td><td>2</td><td>2.2</td><td> </td></tr><tr><td>N3</td><td>0.1</td><td>4</td><td>4.4</td><td> </td></tr><tr><td>N4</td><td>0.2</td><td>8</td><td>8.9</td><td> </td></tr><tr><td>N5</td><td>0.4</td><td>16</td><td>17.8</td><td>Finest as-machined finish[2]</td></tr><tr><td>N6</td><td>0.8</td><td>32</td><td>35.5</td><td> </td></tr><tr><td>N7</td><td>1.6</td><td>63</td><td>69.9</td><td> </td></tr><tr><td>N8</td><td>3.2</td><td>125</td><td>138.8</td><td>Standard as-machined finish[2]</td></tr><tr><td>N9</td><td>6.3</td><td>250</td><td>277.5</td><td> </td></tr><tr><td>N10</td><td>12.5</td><td>500</td><td>555</td><td> </td></tr><tr><td>N11</td><td>25.0</td><td>1000</td><td>1110</td><td> </td></tr><tr><td>N12</td><td>50.0</td><td>2000</td><td>2220</td><td> </td></tr></tbody></table></div>The Rq column is computed as Ra × 1.11 for reasons explained below.Note that the microinch and micrometer columns are the conventional rounded pairs, not exact conversions.<h2>How to Read This Surface Finish Chart</h2>Ra, Rq, Rz, and Rt are all roughness parameters computed from the same measured roughness profile, so one measurement can report several of them at once.<h3>Ra</h3>Ra is the arithmetic mean of the absolute height deviations of the roughness profile from the mean line, measured over the evaluation length.[3] ASME B46.1-2019 gives the discrete form used by digital instruments as:[3]Ra = (|Z1| + |Z2| + |Z3| ... |ZN|) / NWhere each Z value is a measurement of an absolute deviation (either a peak or a valley) from the mean line. N represents the total number of measurements taken.The abbreviations on older drawings all mean the same measurement:<div><table><tbody><tr><td>Abbreviation</td><td>Stands for</td><td>Notes</td></tr><tr><td>Ra</td><td>Roughness average</td><td>Current ISO and ASME designation</td></tr><tr><td>CLA</td><td>Center line average</td><td>Older British usage. Numerically identical to Ra in µin</td></tr><tr><td>AA</td><td>Arithmetic average</td><td>Older American usage. Same measurement</td></tr><tr><td>Rq</td><td>Quadratic mean</td><td>A different calculation, not a different name. See below</td></tr><tr><td>RMS</td><td>Root mean square</td><td>The same as Rq</td></tr></tbody></table></div><h3>Rq</h3>Rq, sometimes written as RMS, is the square root of the mean of the squared height deviations. Squaring before averaging weights large peaks and valleys more heavily than Ra does, so Rq always reads slightly higher than Ra on the same surface profile.[4]For most machined surfaces, Rq is approximately 11% higher than Ra, giving the rule of thumb Rq ≈ Ra × 1.11.[5] That factor is exact only for an idealized sinusoidal profile—a surface that rises and falls with perfectly consistent repetition. Real surfaces depart from it, and the rougher and less regular the surface, the less reliable it becomes. In other words, you cannot get an exact Rq value from your Ra value; you need data from the measured profile to calculate it.<h3>N-grades</h3>N-grades, defined by ISO 1302, compress a roughness specification into a single number from N1 to N12, and each step roughly doubles Ra.[1]However, ISO 1302:2002 has been withdrawn and replaced by ISO 21920-1:2021.[1][6]So N-grades are a notation from a superseded standard. They have not vanished from drawings, which is why the chart includes them, but a new drawing is better served by an explicit Ra value with its cutoff stated. If you are updating drawing templates, note that ISO 21920-1 also changed the default acceptance rule to the maximum rule.[6]<h3>Rz</h3>Ra and Rz describe different things. Ra averages every deviation from the mean line, while Rz averages the most extreme deviations from each sampling length, so it is more sensitive to pronounced peaks and valleys.[4] Two surfaces with the same Ra value can have very different Rz values depending on whether the roughness profile is uniform or punctuated by isolated scratches and burrs. One value cannot be converted from the other.Recommended reading: <a href="https://www.wevolver.com/article/ra-vs-rz-understanding-surface-roughness-parameters-in-engineering" target="_blank" rel="noopener noreferrer">RA vs RZ: Understanding Surface Roughness Parameters in Engineering</a><h3>Cutoff λc</h3>A surface roughness value is incomplete without its filter cutoff, and this is the single most common reason two parties measuring the same part disagree.The cutoff separates roughness from waviness. ASME B46.1-2019 demonstrates the effect on one measured profile: at a 0.8 mm cutoff it reports Ra 0.057 µm, at 0.25 mm it reports 0.044 µm, and at 0.08 mm it reports 0.028 µm.[3]When the drawing does not state a cutoff, B46.1-2019 gives guideline values selected from the measured Ra.[3]<div><table><tbody><tr><td>Ra (µm)</td><td>Cutoff λc (mm)</td><td>Evaluation length L (mm)</td></tr><tr><td>up to 0.02</td><td>0.08</td><td>0.40</td></tr><tr><td>0.02 to 0.10</td><td>0.25</td><td>1.25</td></tr><tr><td>0.10 to 2.0</td><td>0.80</td><td>4.0</td></tr><tr><td>2.0 to 10.0</td><td>2.5</td><td>12.5</td></tr><tr><td>over 10.0</td><td>8.0</td><td>40.0</td></tr></tbody></table></div>Most machined work falls in the 0.10 to 2.0 µm band, which is why a 0.8 mm cutoff and a 4.0 mm evaluation length is the common default. The sampling length equals the cutoff when a filter is used.[3]<h3>Lay</h3>Lay, the predominant direction of the surface pattern, is specified separately from the roughness number.[3] It is called out with its own symbol set, including R for radial and C for circular. Surface finish symbols indicate lay, the parameter, the limit, and the cutoff together on the drawing.Recommended reading: <a href="https://www.wevolver.com/article/surface-finish-standards" target="_blank" rel="noopener noreferrer">Surface Finish: Parameters, Standards, and How to Specify It</a><h2>Ra Values by Manufacturing Process</h2><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzkwODIwNzIxODI3LXNodXR0ZXJzdG9ja18xOTcyNjAxNTM3LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width:100%px" class="fr-fic fr-dib" />Grinding can produce a fine surface finishDifferent processes can achieve different levels of surface smoothness. However, which exact finish a manufacturing process can reach depends on the material, the tooling, the machine, and the parameters.<div><table><tbody><tr><td>Process</td><td>Typical Ra (µm)</td><td>Quality band</td></tr><tr><td>Lapping</td><td>0.1 to 0.2[7]</td><td>Very fine</td></tr><tr><td>Honing</td><td>0.2 to 0.4[7]</td><td>Fine</td></tr><tr><td>Grinding</td><td>0.4[7]</td><td>Fine</td></tr><tr><td>CNC turning</td><td>3.2[2]</td><td>Medium to fine</td></tr><tr><td>CNC milling</td><td>3.2[2]</td><td>Medium</td></tr><tr><td>Rough machining</td><td>25[5]</td><td>Rough</td></tr><tr><td>Sand casting</td><td>50[5]</td><td>Rough</td></tr></tbody></table></div>Within any one process, the finish is driven by the details. In <a href="https://www.wevolver.com/tag/cnc-machining" target="_blank" rel="noopener noreferrer">CNC machining</a>, feed rate, spindle rpm, tool nose radius, rigidity and tool wear all affect the achievable finish, which is why the same nominal operation on two machines will not give you the same surface texture.Secondary operations are equally important. Honing refines a bore beyond what boring alone reaches, deburring removes the burrs left at cut edges, and bead blasting produces a uniform matte non-directional texture. Powder coating and similar coatings add a layer that inherits and modifies the texture underneath.Bulk-forming processes sit at the coarse end, and the surface roughness values of processes like forging and rolling are usually a starting condition to be machined away rather than a finish to be met.<h2 id="isPasted">The Price of Lower Ra Values</h2>Surface finish generally becomes more expensive as the required Ra decreases. Rough machining can achieve relatively high Ra values with standard cutting tools and short cycle times, while finer finishes require slower feeds, sharper or more specialized tooling, and better machine stability.[5] Once conventional machining approaches its practical limit, processes such as grinding, honing, lapping, polishing, or superfinishing may be needed, adding both processing time and setup costs.[7]The relationship is not linear. Reducing Ra from 3.2 to 1.6 µm may require only a modest change in machining conditions, while reducing it from 0.8 to 0.4 µm can require a substantially different process. For this reason, specifying a finer surface finish than the function of the part requires can increase manufacturing cost without providing a corresponding benefit.<h2>Abrasive Grit to Ra</h2>Abrasive grit numbers map onto Ra only loosely, and the mapping depends on which grit scale is being quoted. The bands below are on the FEPA P-scale for coated abrasives, standardized as ISO 6344.[6]<div><table><tbody><tr><td>Grit (FEPA P)</td><td>Ra (µm), approx.</td><td>Ra (µin), approx.</td><td>Typical use</td></tr><tr><td>P40 to P60</td><td>3 to 5</td><td>120 to 200</td><td>Stock removal, weld knock-down</td></tr><tr><td>P80 to P120</td><td>1.5 to 3</td><td>60 to 120</td><td>Blending, coarse shaping</td></tr><tr><td>P150 to P240</td><td>0.8 to 1.5</td><td>32 to 60</td><td>Pre-finish smoothing</td></tr><tr><td>P320 to P600</td><td>0.3 to 0.8</td><td>12 to 32</td><td>Finishing, sealer scuff</td></tr><tr><td>P800 to P1200</td><td>0.1 to 0.3</td><td>4 to 12</td><td>Polish preparation</td></tr><tr><td>P1500 and finer</td><td>under 0.1</td><td>under 4</td><td>Pre-buff, high-gloss start</td></tr></tbody></table></div><h2>How the Measurement Is Taken</h2><img src="https://images.wevolver.com/eyJidWNrZXQiOiJ3ZXZvbHZlci1wcm9qZWN0LWltYWdlcyIsImtleSI6ImZyb2FsYS8xNzkwODIwNzY1NzA5LXNodXR0ZXJzdG9ja18xMzcyNjQ3NjI5LmpwZyIsImVkaXRzIjp7InJlc2l6ZSI6eyJ3aWR0aCI6OTUwLCJmaXQiOiJjb3ZlciJ9fX0=" style="width:100%px" class="fr-fic fr-dib" alt="A contact surface roughness tester" />A contact roughness tester or profilometerSurface finish measurement varies depending on the equipment used.A contact surface roughness tester drags a stylus of known tip radius across the surface at fixed speed and records height data at a set interval.[3] These instruments, generally called profilometers, produce the surface profile that every parameter in the chart is computed from.A non-contact method uses optical interaction instead: focus variation, confocal microscopy or interferometry. Optical instruments capture an area rather than a single line, which matters when the texture of a surface is directional.<h2>Conclusion</h2>A surface finish chart is a unit converter, but it cannot tell you what Rz corresponds to your Ra, because that depends on the shape of the roughness profile. Use the chart to translate between units, then specify the parameter, the limit, the cutoff, and the standard explicitly on your technical drawings. Then the number will mean the same thing to you and to whoever makes the part.<h2>Frequently Asked Questions</h2>What does a 32 surface finish mean?Ra 32 µin, equivalently Ra 0.8 µm or N6, a general engineering finish.What is the difference between Ra and Rq?Ra averages the absolute deviations from the mean line; Rq squares them first, which weights large peaks and valleys more heavily. On the same profile Rq typically reads about 11% higher, so RMS ≈ Ra × 1.11 as a rule of thumb.[5] They are two calculations on one measurement, not two measurements.Is CLA the same as Ra?Yes. Center line average is an older name for the same arithmetic average measurement.How do I convert Ra to Rz?You cannot do it reliably, as the Ra value has already “smoothed out” the extremes of which Rz is a measure.Are N-grades still valid?They come from ISO 1302, which ISO lists as withdrawn and replaced by ISO 21920-1:2021.[1][6] They remain common on existing drawings, so you still need to read them, but new drawings are better served by an explicit Ra value with its cutoff.Why do two shops measure the same part differently?Usually the filter cutoff. ASME’s own example gets Ra 0.057 µm and Ra 0.028 µm from one profile by changing the cutoff.[3]What Ra can CNC machining reach?Roughly 3.2 µm as machined, down to about 0.4 µm with further finishing passes.[2]<h2>References</h2>[1] International Organization for Standardization. <a href="https://www.iso.org/standard/28089.html" target="_blank">ISO 1302:2002: Geometrical Product Specifications (GPS) — Indication of surface texture in technical product documentation</a>. Geneva: ISO; 2002.[2] Protolabs Network. <a href="https://www.hubs.com/knowledge-base/surface-finishes-cnc-machinings/#surface-finishes-explained-as-machined" target="_blank">What are the types of surface finishes for CNC machining?</a> [Internet]. Protolabs Network; [cited 2026 Sep 30].[3] American Society of Mechanical Engineers. <a href="https://www.asme.org/getmedia/f22128e5-acad-429d-bc75-0ac4bdffdf44/b46-1-2019-11x17-poster.pdf" target="_blank">B46.1-2019: Surface texture (surface roughness, waviness, and lay): reference poster</a>. New York: ASME; 2019.[4] Keyence. <a href="https://www.keyence.com/products/microscope/laser-microscope/resources/laser-microscope-resources/how-surface-height-is-quantified-from-ra-to-rz.jsp" target="_blank">How surface height is quantified, from Ra to Rz</a> [Internet]. Keyence; [cited 2026 Sep 30].[5] Astro Pak. <a href="https://astropak.com/surface-roughness-average-ra/" target="_blank">Surface roughness average (Ra): chart, formula, and conversion calculator</a> [Internet]. Astro Pak; [cited 2026 Sep 30].[6] International Organization for Standardization. <a href="https://www.iso.org/obp/ui/#iso:std:iso:21920:-1:ed-1:v1:en" target="_blank">ISO 21920-1:2021: Geometrical Product Specifications (GPS) — Surface texture: Profile — Part 1: Indication of surface texture</a>. Geneva: ISO; 2021.[7] Grzesik W, Kruszynski B, Ruszaj A. <a href="https://link.springer.com/chapter/10.1007/978-1-84882-874-2_5" target="_blank">Surface integrity of machined surfaces</a>. In: Grzesik W, editor. Surface integrity in machining. London: Springer London; 2010. p. 143-179.[8] Whitby Abrasives. <a href="https://whitbyabrasives.ca/blogs/news/grit-to-surface-finish-ra-chart" target="_blank">Grit-to-surface-finish (Ra) chart</a> [Internet]. Whitby Abrasives; [cited 2026 Sep 30].

Surface finish can be specified in many different ways

A reference chart for converting between surface finish units, plus Ra values by manufacturing process and the relationship between surface

Surface Finish Chart: Ra, Rq, and N-Grade Conversions

Surface finishes can be altered with methods like coating and conversion

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GD&T uses tolerance zones tied to a datum reference frame

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<h2 id="isPasted">Hardware Made Live, on the Floor</h2>Hackaday is bringing the Keychain Hack to TCT Shenzhen 2026, a shared, multi-sponsor booth built around one idea: put real 3D printers to work in front of attendees and send everyone home with something they built themselves.This isn't a display of finished parts behind glass. Sponsor machines run for all three days of the show, each producing a different enclosure variant for the badge that attendees assemble on site. The printers are the demo.Hackaday's first activation in China sits inside TCT Shenzhen's wider Hackaday Program, which also includes a hackathon and a run of maker project showcases.Date: October 14–16, 2026 Location: Shenzhen World Exhibition &amp; Convention Center, Hall 15, Shenzhen<h3>What to Expect</h3><ul><li>Sponsor 3D printers running live on the show floor, all three days</li><li>A hands-on badge build: a 3D-printed enclosure plus a small electronics kit</li><li>A photo booth kiosk where attendees upload a logo, photo, QR code, or custom graphic</li><li>A personalized, sponsor-branded keychain to take home</li><li>Open to everyone; no 3D printing or electronics background needed</li></ul><h3>How the Keychain Hack Works</h3>Attendees start at a sponsor's printer, which produces a distinct 3D-printed frame.Assembly is simple: slot in the display module, snap the enclosure together, attach the keychain loop.Then at the photo booth kiosk, attendees upload a logo, photo, QR code, or custom graphic that gets built into the piece itself.Everyone leaves with a working, personalized keychain that has sponsor branding baked into the object, not simply printed on top of it. Produced with reprogrammable e-ink, attendees can continue to add personalized content to their keychains far beyond the event.<h3><a href="https://85458006.beschannels-plus.com/forms/71U4ZP1" target="_blank" rel="noopener noreferrer"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1790701778532-roll-out-33x79+copy.jpg" style="width:100%px" class="fr-fic fr-dib" /></a></h3><h3>Event Partners and Sponsors</h3>The Keychain Hack is sponsored by Snapmaker, Polymaker, and TCT Shenzhen.<a href="https://www.snapmaker.com">Snapmaker</a> supplies the desktop 3D printers running the badge build live on site. The company built its name on 3-in-1 machines combining 3D printing, laser engraving and CNC carving, and has shipped to more than 100,000 users worldwide.<a href="https://polymaker.com">Polymaker</a> supplies the filament. The Shanghai-headquartered materials company has been developing 3D printing filaments and composites since 2013, with distribution across North America, Europe and Asia.<a href="https://www.3dprint-expo.com/">TCT Shenzhen</a> is hosting the program as part of its own show, South China's exhibition for additive manufacturing and 3D printing, held in the heart of the Greater Bay Area.<h3 id="isPasted"><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1790701787256-roll-out-33x79+copy+2.jpg" style="width:100%px" class="fr-fic fr-dib" /></h3>Why ShenzhenShenzhen sits at the intersection of electronics manufacturing, rapid prototyping and hardware supply chains, alongside a fast-growing additive manufacturing scene. That combination is what makes a build mixing 3D printing and electronics feel native to the city rather than bolted on.<h2>Attend TCT Shenzhen 2026</h2>TCT Shenzhen runs October 14 to 16, 2026, at the Shenzhen World Exhibition &amp; Convention Center, Hall 15. Visitor <a href="https://finderexpo.com/tickets/m0lk634f3e6u">registration for TCT Shenzhen</a> is free until October 13, 2026.<a href="https://85458006.beschannels-plus.com/forms/71U4ZP1">Register for Hackaday Keychain Hack here.</a>Find the Keychain Hack on the show floor.

Snapmaker, Polymaker, and TCT Shenzhen put working 3D printers on the show floor for a hands-on badge build that mixes electronics with additive manufacturing.

The Keychain Hack: Hackaday at TCT Shenzhen 2026

Solar energy is one of the most important technologies of our time, and understanding how it works can be… enlightening! Julián Caro Linares, Senior Field Technology Evangelist at Qualcomm Europe, built a project that helps learn about this topic with a hands-on approach: a fully functional, fully open-source smart solar panel system that adjusts to optimize solar exposure in real-time, built with <a href="https://store.arduino.cc/products/uno-q-4gb?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content">UNO Q</a> and a handful of Arduino® <a href="https://store.arduino.cc/pages/modulino?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content">Modulino™ nodes</a>. The best part? He explains every step so you can 3D print, assemble, and program it yourself, too! <iframe width="804" height="603" src="https://www.youtube.com/embed/w9L78aqJsKc" frameborder="0" class="fr-draggable"></iframe> <h2 id="isPasted">A shining moment for UNO Q! <iframe id="6a3c254c6d19a31976afd60b" width="250" class="specs-iframe" height="440" src="https://wevolver.com/iframe/specs/arduino-uno-q-4gb?iframe=true" frameborder="0" scrolling="no"> </iframe></h2>The system does a surprising amount for something you can build at home or in a classroom. Two servo motors move the solar panel continuously, orienting it toward the best position to capture energy from the sun based on a sky scan the board runs automatically. A live dashboard – served directly from the Linux side of UNO Q to any browser on your local network – shows panel orientation, a solar heatmap, real-time energy readings, infrared light levels, and local weather data. Just watching it update is pretty cool!And the system doesn’t just chase the sun, it also protects itself. If temperatures climb too high, the panel adjusts to avoid damage. If a snowstorm or sandstorm is forecast, it moves to a protective vertical position. If it gets too dark to generate meaningful energy, it returns to a resting position and waits. And when dust or debris accumulates, it vibrates – just like NASA’s Mars rovers do – to shake itself clean.All of this runs on UNO Q thanks to its dual-brain architecture: the Linux side handles the dashboard, weather data, and higher-level logic, while the real-time microcontroller reads sensors and drives the motors. The Modulino nodes do the sensing: Modulino Light reads both visible and infrared light, Modulino Thermo monitors temperature and humidity, Modulino Movement detects anomalous vibrations, and Modulino Vibro handles the self-cleaning function. Everything was easily orchestrated through Arduino® App Lab, using three ready-to-use Bricks: <ul><li>weather_forecast: for an online API that always has the latest weather information;</li><li>web_ui: to build and host the webpage;</li><li>dbstorage_tsstore: to store and get data using a time series database.</li></ul><h2>Try it as a bright classroom project</h2>Julián designed this explicitly as an educational tool, and it shows. The project is fully open-source – 3D files, code, and a complete step-by-step tutorial are all available on <a href="https://projecthub.arduino.cc/jcarolinares/arduino-uno-q-smart-solar-panel-system-ab8c80">Arduino® Project Hub</a>. On the hardware side, a small solar panel and two servo motors are all you need to add. For the software, Arduino App Lab handles the whole setup.What makes it particularly compelling as a teaching tool is how many real concepts it touches at once. Students can explore renewable energy, sensor fusion, weather data integration, edge AI decision-making, real-time data visualization, and basic robotics – all within a single, coherent project that actually does something. Just observe when the panel tilts toward the sun, or switches to emergency mode before a storm: the logic behind is visible and understandable. “It’s a very interesting project to do at home and to apply in the classroom,” he says, “to show how we can use UNO Q to solve real-life problems in actual solar panel installations.”Check out the <a href="https://projecthub.arduino.cc/jcarolinares/arduino-uno-q-smart-solar-panel-system-ab8c80">full tutorial on Arduino Project Hub</a>.In addition to the <a href="https://store.arduino.cc/products/uno-q-4gb?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content">Arduino Store</a>, UNO Q is available to order from DigiKey, Farnell, Mouser, Newark, RS Components, and <a href="http://robu.in/">Robu.in</a>, along with our other authorized distributors and resellers.Arduino, UNO, Modulino and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.

Discover solar energy through a hands-on, open-source smart solar panel system built with UNO Q and Arduino® Modulino™ nodes. Designed to optimize solar exposure in real time, the project lets you 3D print, assemble, and program your own system.

A smart solar panel system you can 3D print, build, and learn from – with the Arduino® UNO™ Q board

On October 14, 2026, under the towering canopy of the Shenzhen World Exhibition &amp; Convention Center (Shenzhen World for short), thousands will come together for the third edition of <a href="https://en.tctasia.cn/tctshenzhen.shtml">TCT Shenzhen</a>, an event focused on the growing 3D printing industry in South China’s Greater Bay Area. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789757540429-1789757540429.jpeg" width="554" height="303" class="fr-fic fr-dii" />The region, which comprises tech hub Shenzhen, as well as Hong Kong, Macao, and Guangzhou, is becoming increasingly important within the broader additive manufacturing sector by driving innovation in the consumer and electronics subsegments and establishing large-scale AM factories to meet growing demand for 3D printed products in Southeast Asia and beyond. TCT Shenzhen is a reflection of the region’s significance as a global 3D printing hub, and serves as a place for industry players to connect, to showcase the latest innovations, and to create new business opportunities. Notably, for Chinese companies, TCT Shenzhen acts as a gateway into international markets, while international buyers and visitors of the event can see firsthand the region’s cutting-edge manufacturing capabilities.As we’ll cover, the three-day event has a full schedule and a diversity of things to discover, from over 250 exhibitors showcasing hundreds of new products, to over 80 sessions covering key industry trends, to various programs like the 3D Genius Hub and a Hackaday hackathon. <h2>Driving the New Wave of 3D Printing Innovation</h2>In Hall 15 of Shenzhen World, TCT Shenzhen organizers are preparing to host over 250 exhibitors spanning the entire value chain of additive manufacturing, including hardware, materials, software, services, and end-use applications. While the full list of exhibitors has not been disclosed yet, here’s a glimpse of what will be on show.<h3>Hardware</h3>Under the theme “Drive the New Wave of 3D Printing Innovation”, the event will showcase the latest 3D printing equipment, including metal, polymer, ceramic, and sand mold printing technologies. Among the leading exhibitors in the hardware space are Avimetal, ELEGOO, Formlabs, Makera, Creality, lingxi, eufyMake, Xhorse, MINGPIN, Douchuan 3D, WSX, GUANGSU.<h3>Materials</h3>In the materials segment, exhibitors including Zhongyuan, Honggang Petrochemical, Royal, Global Laser Box, and HISUN will display a wide variety of 3D printing consumables, from consumer polymers and engineering composites, to industrial metal powders and technical ceramics.  <h3>Software and Services</h3>On the software and services side, TCT Shenzhen will welcome a host of innovative exhibitors, including specialists in CAD modeling, topology optimization, digital twin technology, process simulation, slicing, and digital manufacturing services. While the exhaustive list of exhibitors has not yet been released, visitors can expect to see key players in the software and services space, including GENI, HOME-LINK, Pliith, Demute Intelligence, FLOW 3D, ZHUJIN, and pancolour. <h3>Applications</h3>Of course, no trade show would be complete without a focus on end-use applications that demonstrate the versatility of 3D printing technologies and the capacity of the value chain components exhibited. Various applications will be on show, including consumer products, consumer electronics, luxury goods like jewelry, tooling and molds, new energy vehicles, dental and medical devices, and low-altitude economy systems. Notably, TCT Shenzhen 2026 will highlight AI-enabled 3D printing applications, especially related to the use of AI for 3D printing design and manufacturing workflow efficiency. On this front, several AI innovators will be present, including Tripo AI, Meshy, DreamTech, Hi3D, Deemos, QUWAN, and SeaMe. <h2>Seven Highlights at TCT Shenzhen 2026</h2>In addition to the main exhibition hall, TCT Shenzhen also invites visitors to participate in a range of discussions, networking events, and interactive experiences, all geared towards driving AM innovation and creating valuable connections. Here are the seven key highlights to look forward to:<ol><li>80+ Sessions on Industry Trends</li></ol>Over the course of the three-day trade show, there will be over 80 sessions covering the 3D printing industry’s latest developments and biggest trends. These sessions comprise industry forums, technical presentations, product launches, maker activities, and networking opportunities. Topics to be covered include medical and dental applications, consumer products, thermal management, the low-altitude economy, and global market expansion. <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789757540451-1789757540451.jpeg" width="624" height="390" class="fr-fic fr-dii" />Source: TCT Shenzhen<ol><li>3D Genius Hub</li></ol>After previous successful editions, the 3D Genius Hub is back again for TCT Shenzhen 2026. With a dedicated space for innovation, discussions, and maker culture, the 3D Genius Hub emphasizes 3D printing’s role as a creative technology, enabling new ideas to come to life. As TCT Shenzhen says: “Rather than simply viewing products on the show floor, visitors can discover new ideas around future products, innovative design and digital manufacturing.” As part of the 3D Genius Hub, the organizers are also connecting with INNO100 Global Innovation Flagship Store to showcase new 3D printing projects—including popular Kickstarters—from around the world.<ol><li>Business Matchmaking</li></ol>Networking is an integral part of industry events and to support this side of TCT Shenzhen, organizers have set up a Business Matchmaking program that facilitates face-to-face meetings between exhibitors, buyers, distributors, agents, and end users from Southeast Asia, Japan, South Korea, and beyond. As part of this program, matches are strategically made based on specific business requirements that are collected ahead of the event by TCT Shenzhen.<ol><li>AI + 3D Printing Intelligent Manufacturing Forum</li></ol>In this topical forum, a number of AI experts and companies will come together to discuss how AI is impacting the 3D printing industry, with a particular focus on how AI tools, such as Tripo AI and Hi3D, can aid in the development of new products through generative design. The forum will also cover AI’s role in optimizing production processes and increasing manufacturing efficiency, showing how the technology can lead to new commercial opportunities. <ol><li>Hackaday Program</li></ol>Hackaday, the global open-source hardware platform, will be making its first appearance in China as part of a TCT Shenzhen program. The collaborative program will consist of a hackathon, maker project showcases, and a DIY activity that will invite participants to make their own electronic badges. This interactive segment of TCT Shenzhen is open to all visitors, including those without professional AM experience, and aims to drive connection and innovation through hands-on making.<ol><li>3D Printing Footwear Summit</li></ol>TCT Shenzhen will be hosting the second edition of the China 3D Printing Footwear Summit this October. As the name suggests, this summit will be focused on 3D printed footwear, which is one of the most visible and fastest growing consumer AM application areas. From sandals to performance athletic shoes, 3D printing is transforming how designers and manufacturers approach shoe development. To discuss this transformation, footwear brands, equipment and materials companies, and segment experts will come together to talk about the current state and future of footwear 3D printing.<ol><li>The 3D Printing Farm Ecosystem Summit</li></ol>Last but certainly not least in TCT Shenzhen’s event round-up is the 3D Printing Farm Ecosystem Summit. This event will showcase one of the region’s particular strengths: the establishment of large-scale 3D print farms, capable of massive production volumes. The 3D Printing Farm Ecosystem Summit will bring together experts in the field to look at what’s behind the rise in these production sites (i.e., advances in desktop 3D printing, AI, cross-border e-commerce), as well as discuss print farm operations, supply-chain collaboration, and more. <h2>Visitor Information &amp; Directions</h2>As TCT Shenzhen organizers make their final preparations, visitors are welcome to <a href="https://en.tctasia.cn/tctshenzhen.shtml">pre-register for the upcoming event</a>. (Note that registration for visitors is free until October 13, 2026.) As we said, the event will be held over three days, from October 14 to 16, 2026, at the Shenzhen World Exhibition &amp; Convention Center.  <img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789757540465-1789757540465.jpeg" width="517" height="442" class="fr-fic fr-dii" />Source: TCT ShenzhenThe venue is accessible by public transit, and TCT Shenzhen has provided the following directions:Getting to the venue by metro:Line 12 → Guozhan North Station, Exit D; approximately 15 minutes on foot or 5 minutes by bike to Hall 15. Or, Line 20 → Guozhan Station, Exit D; approximately 15 minutes on foot or 5 minutes by bike to Hall 15.Getting to the venue from Shenzhen North Railway Station:Take Line 5 from Shenzhen North Station to Lingzhi Station, transfer to Line 12 and get off at Guozhan North Station, Exit D. Hall 15 is approximately a 15-minute walk from the station. Total journey time is around 1.5 hours.Getting to the venue from Shenzhen Bao'an International Airport:Grab a taxi (approximately 25 minutes) or take the metro line 11 from Airport Station to Airport North Station, transfer to Line 20 and get off at Guozhan Station, Exit D. Walk approximately 15 minutes to Hall 15. Total journey time is around 45 minutes.<a href="https://en.tctasia.cn/tctshenzhen.shtml" target="_blank" rel="noopener noreferrer">For additional information about the event, check out the TCT Shenzhen event page.</a><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789760027466-TCT%232.png" style="width:100%px" class="fr-fic fr-dib" />

With just one month before the South Asian 3D printing trade show, we look at the events and showcases visitors will be able to take part in.

What Not to Miss at TCT Shenzhen 2026

<h2 id="isPasted">What Is Lean Manufacturing? </h2>Lean manufacturing takes the old saying 'waste not, want not' and applies it as a blueprint for smarter, more efficient production. Toyota pioneered this approach in the 1950s, and today, businesses across the world use it to streamline their processes and cut waste. The goal is simple: eliminate anything that doesn’t add value to the final product. <h2>What Are the Key Principles of Lean Manufacturing? </h2>Lean manufacturing is based on five main principles that help companies improve production while reducing waste. Let’s break them down: <h3>Identify Value </h3>The first step in lean manufacturing is figuring out what customers actually want. What makes a product useful to them? Is it durability, speed, or cost? Anything that doesn’t contribute to said value is considered waste and should be reduced or, even better, removed. The goal is to make sure every step in production is helping to deliver what really matters. <h3>Map the Value Stream </h3>Once you know what’s valuable, the next step is to look at the entire production process and pinpoint where waste happens. This is called value stream mapping. It helps flag delays, unnecessary steps, and anything else that slows things down. Once these areas of waste are identified, it's time to start trimming the fat.  <h3>Create Flow </h3>Next up is breaking down each part of the process to make sure everything moves smoothly, with parts and materials transitioning easily from one step to the next without delays. This can involve training employees, adjusting production workflows, and incorporating automation like robotics and AI to improve efficiency. <h3>Establish Pull </h3>Instead of making large batches based on predictions, lean manufacturing uses a pull system—producing only when there’s actual demand. This prevents overproduction, reduces excess inventory, and keeps production responsive. A pull-based approach means companies manufacture what’s needed, when it’s needed, avoiding wasted materials and unnecessary costs. <h3>Seek Perfection </h3>Lean isn’t a quick fix—it’s a mindset of constant improvement. Businesses should keep looking at how they are doing things, listening to employee feedback, and making small changes to get even better results.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789378221965-1789378221965.png" class="fr-fic fr-dib" /><h2 id="isPasted">What Are the Benefits of Lean Manufacturing? </h2><ul><li>Lean manufacturing makes businesses more flexible, efficient, and responsive to customer demands. </li><li>Flexibility: Lean keeps production adaptable, so businesses can react quickly to market changes. </li><li>Efficiency: Simpler processes move products through production faster with less waste. </li><li>Quality: Regularly fine-tuning production leads to fewer defects, more consistent results, and better products overall. </li><li>Cost savings: Less waste means less money, with lower costs across the board. </li><li>Sustainability: A manufacturing approach that uses only what’s needed results in a smaller environmental footprint. </li></ul><h2>What Are the Main Types of Waste in Lean Manufacturing? </h2>Lean manufacturing points to eight areas where waste tends to build up. <ul><li>Overproduction: Making more than needed. </li><li>Waiting time: Delays between production steps. </li><li>Unnecessary motion: Extra movement that doesn’t add value. </li><li>Excess inventory: Storing more materials or products than necessary. </li><li>Defects: Errors that require fixing or scrapping. </li><li>Over-processing: Doing extra work that isn’t required. </li><li>Unutilised talent: Failing to make the most of employees’ skills. </li><li>Transportation waste: Moving products and materials more than necessary. </li></ul><h2>How Does Lean Manufacturing Work? </h2>Lean manufacturing works by analysing workflows and cutting waste at every step. Using strategies like just-in-time production, standardisation, and automation, lean keeps operations running as smoothly as possible. Different industries and technologies tailor the application of lean principles to meet each specific need. <h4>Lean by Technology </h4>The tools and techniques used for lean manufacturing also vary: injection moulding is ideal for large-scale lean manufacturing, while CNC machining and 3D printing enable rapid prototyping and small-batch production. <ul><li><a rel="noopener" href="https://www.protolabs.com/en-gb/services/injection-moulding/" target="_blank">Injection moulding</a>: Great for high-volume production, injection moulding produces consistent parts quickly while keeping material waste low. </li><li><a rel="noopener" href="https://www.protolabs.com/en-gb/services/cnc-machining/" target="_blank">CNC machining</a>: Reduces waste by automating precision cutting, eliminating human error, and optimising material use. </li><li><a rel="noopener" href="https://www.protolabs.com/en-gb/services/3d-printing/" target="_blank">3D printing</a>: Supports lean through rapid iteration, allowing companies to refine designs without mass production waste. </li><li><a rel="noopener" href="https://www.hubs.com/sheet-metal-fabrication" target="_blank">Sheet metal fabrication</a>: Helps manufacturers produce only what’s needed by using lean-friendly, on-demand production methods. </li></ul><h2>What Are the Biggest Challenges of Implementing Lean Manufacturing? </h2>Switching to lean manufacturing isn’t always easy. It requires companies to rethink the way they work, which can take time and effort. <ul><li>Resistance to change: Employees and managers may be hesitant. </li><li>Upfront costs: Training and restructuring require investment. </li><li>Complexity: Large operations can be harder to streamline. </li><li>Balancing efficiency and flexibility: Lean should improve workflow without becoming too rigid. Process for process’s sake isn’t helpful.  </li></ul><h2>How Has Lean Manufacturing Changed Over Time? </h2>Lean manufacturing has come a long way since the 1950s. Quickly expanding beyond the Toyota factory floor, it was widely adopted across industries such as aerospace, medical devices, and consumer electronics. Companies have refined lean practices using new tools like Six Sigma, automation, and real-time data monitoring to make operations even more efficient. The biggest evolution in lean manufacturing has been the introduction and integration of new digital technologies. Automation, robotics, AI-driven analytics, and predictive maintenance now allow manufacturers to optimise workflows, reduce human error, and cut lead times.  The rise of on-demand manufacturing platforms, like Protolabs, has also transformed lean manufacturing. Founded in 1999, Protolabs pioneered online manufacturing, allowing companies to rapidly prototype and produce parts with minimal waste. Today, Protolabs also offers instant access to a highly vetted global network of manufacturing partners, further expanding capacity while speeding up workflows. <h2>How Does on-Demand Manufacturing Support Lean Principles? </h2>On-demand manufacturing is one of most effective tools in the lean utility belt. Producing only what’s needed, when it’s needed, helps businesses avoid overproduction, lower costs, and stay flexible. <ul><li><a rel="noopener" href="https://www.protolabs.com/en-gb/resources/blog/the-theory-advantages-and-disadvantages-of-just-in-time-manufacturing/" target="_blank">Just-in-time production</a>: Reduces excess inventory.<a rel="noreferrer noopener" href="https://www.protolabs.com/en-gb/resources/blog/the-theory-advantages-and-disadvantages-of-just-in-time-manufacturing/" target="_blank"> </a> </li><li><a rel="noopener" href="https://www.protolabs.com/en-gb/services/rapid-prototyping/" target="_blank">Rapid prototyping</a>: Allows fast design iterations. </li><li><a rel="noopener" href="https://www.protolabs.com/en-gb/resources/insight/supply-chain-management/" target="_blank">Optimised supply chains</a>: Uses <a rel="noopener" href="https://www.protolabs.com/en-gb/resources/blog/lean-manufacturing-in-the-age-of-digital/" target="_blank">digital manufacturing</a> and AI to match production with real demand. </li></ul>As an on-demand manufacturing platform, Protolabs unlocks a variety of lean principles for engineers. With automated quoting, digital workflows, and rapid production, we help companies adopt a leaner, more streamlined manufacturing process.<a rel="noreferrer noopener" href="https://www.protolabs.com/en-gb/why-protolabs/" target="_blank"> </a> <h2 id="isPasted">FAQs About Lean Manufacturing </h2><h3>How is lean different from Six Sigma?  </h3>Lean manufacturing focuses on eliminating waste and streamlining production so that every step adds value. Six Sigma, on the other hand, is mostly about reducing variation and defects to improve product quality. Many businesses combine both—lean to optimise workflows and Six Sigma to enhance precision and consistency.<h3>What are the 5 M's of lean manufacturing?  </h3>The 5 M’s refer to manpower, machines, materials, methods, and measurement. These are key factors to evaluate when trying to identify possible areas of waste. <h3>Can lean be applied to low-volume production?  </h3>Yes, lean works for both mass production and lower-volume custom manufacturing by stepping up efficiency at every level.<h3> How does lean manufacturing impact supply chains? </h3>It reduces excess inventory, improves supplier coordination, and boosts overall efficiency in the supply chain. <h3> What are some real-world examples of lean manufacturing?  </h3>Toyota revolutionised manufacturing with its just-in-time system, Amazon applies a lean, automated approach in its fulfilment centres, and Protolabs brings lean to digital manufacturing, enabling fast, on-demand production. <h2 id="isPasted">Get a Quote for Lean Manufacturing </h2>Protolabs helps companies apply lean manufacturing principles with digital production. <ul><li>Rapid prototyping with CNC machining and 3D printing. </li><li>Low-volume production to reduce waste and costs. </li><li>Rapid injection moulding for lean, high-efficiency part production. </li><li>Automated workflows for fast, efficient manufacturing. </li></ul>Make manufacturing leaner, faster, and more efficient. <a rel="noopener" href="https://www.protolabs.com/en-gb/ecom/get-a-quote/?lang=en-GB&amp;getaquote=true" target="_blank">Upload your designs</a> to get a free, instant quote.

Lean manufacturing focuses on creating more value with less waste. Pioneered by Toyota in the 1950s, this approach helps businesses streamline processes, improve efficiency, and eliminate activities that don't add value to the final product.

What are the Key Principles of Lean Manufacturing?

<a href="https://cdfam.com/pasteur-labs-nyc25/" target="_blank" rel="noopener noreferrer">Alexander Lavin of Pasteur Labs</a> spent his New York presentation at CDFAM on simulation intelligence, and stopped partway through to name the thing underneath it: the data interfaces problem in digital engineering.<blockquote>If you think you don’t have this data problem, you just haven’t run into it yet.— Alexander Lavin, Pasteur Labs, CDFAM NYC 2025</blockquote><iframe width="640" height="360" src="https://www.youtube.com/embed/SfypDDqn0qY?&amp;t=986s&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">                   </iframe>Pasteur hit it early, four years before that talk, and ended up building a data engineering pipeline for its own machine learning staff before it could build much else on top.That is the shape of it across four years of CDFAM presentations. Many of the talks that look like they are about AI turn out, once you get past the demo, to be about data: where it came from, what format it arrived in, and whether it carries the information the problem actually depends on.A 2022 article opened on the gap between text-to-image progress and 3D engineering, and landed on the reason: “the same volume of open data does not exist for 3D objects in quite the same way.” Four years later, the three answers taking shape are common formats, synthetic data, and fields.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789403099289-3MF+ISO+Banner+150+X.jpg" style="width:100%px" class="fr-fic fr-dib" /><h2> </h2><h2>Formats are the Plumbing</h2>Geometry has to move between tools before anything else can happen, and the format it moves in decides what survives the trip. The STL problem is the familiar version: a lattice or a TPMS structure described by a short mathematical function becomes an enormous pile of triangles the moment it is tessellated, and the design freedom is then capped by triangle count.The <a href="https://3mf.io/" target="_blank" rel="noopener noreferrer">3MF Consortium</a>’s Volumetric and Implicit Extension attacks this by letting a file carry spatial functions — a stack of images, a mathematical function, or both — so material properties and geometry travel as the thing itself. Jan Orend, who contributes to the specification on behalf of EOS, framed the stakes plainly in a <a href="https://cdfam.com/3mf-consortium-volumetric-and-implicit-extension-release/" target="_blank">CDFAM interview</a>: the consortium exists to solve “the interoperability challenges that are holding back the industry.”That matters more now than it did when the extension was released. Every agentic workflow demonstrated assumes tools can call each other and hand over geometry without losing what makes it meaningful. Wesley Essink of Siemens showed the receiving end, exporting the same implicit model out as volumetric data, mesh, B-rep, beams or slice data depending on where it was headed next.<h2>Synthetic data, because the real stuff is expensive and wrong</h2>The bottleneck Francis Bitonti of <a href="https://www.lexset.ai" target="_blank" rel="noopener noreferrer">Lexset </a>described in 2023 has aged well. Collect images, send them to a third party for annotation, wait, run quality assurance, send them back with feedback, repeat. Hundreds of people touching your data, biases and fatigue baked into the labels, security exposure, and a cycle his customers measured in months.<blockquote>Before working with us this process can take about six months, and we’ve even had some customers say this takes a year to go and collect these data sets.— Francis Bitonti, Lexset, CDFAM NYC 2023</blockquote><iframe width="640" height="360" src="https://www.youtube.com/embed/RANHS_7PpE4?&amp;t=296s&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">          </iframe>His conclusion was that crowdsourcing does not scale with model size, and that simulation and synthetic data are where the field goes next. It went there. Verena Vogler of McNeel Europe described teams using Grasshopper to generate training sets as a matter of course. Wasil Rezk of BeyondMath showed models trained on self-generated data grounded in first principles rather than on a customer’s simulation archive, reporting predictions within a few percent of full CFD while needing an order of magnitude less data, and more to the point, generalising to geometries the model had never seen.The economic argument is the one that lands with manufacturers. Training data you generate is training data you do not have to buy, annotate, or wait a year for.<h2>Fields, where words run out</h2>The most interesting shift is in what counts as data in the first place.Mike Frei of ARENA-AI opened his Barcelona talk on human intuition — how we know by looking how heavy something is, learned across thousands of small physical feedbacks. Then he put up a band-pass filter, a structure used in RF constantly, and demonstrated how the electromagnetic wave propagates through it.<blockquote>Probably few of you would know. Even fewer people actually have an intuition of how to change the structure to have it do something different.— Mike Frei, ARENA-AI, CDFAM Barcelona 2026 · <a href="https://www.youtube.com/watch?v=Dd80tO-pZzM&amp;t=160s" target="_blank" rel="noopener noreferrer">watch</a></blockquote><iframe width="640" height="360" src="https://www.youtube.com/embed/Dd80tO-pZzM?&amp;t=160s&amp;wmode=opaque&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">        </iframe>An 8mm square, one layer, and the simulation still takes minutes. A modern system might be twenty layers and half a metre across. There is no vocabulary that compresses this usefully, because the thing being described is a continuous field, and language is the wrong container for it. His group’s answer is two models: a forward model that takes geometry and materials and characterises the electromagnetic behaviour, and an inverse model that runs the other way.The same logic shows up in geometry tools. Essink’s demonstration of field-driven design treats a parameter as something that varies through space rather than as a number — lattice parameters, fillet radii, shell thicknesses, all under spatial control.<blockquote>This is really where we can take data and map it to the geometry, because a lot of the data that we work with is either volumetric or planar.— Wesley Essink, Siemens Digital Industries Software, CDFAM Barcelona 2026</blockquote>The inputs he listed are instructive: CAD features, simulation output, raw point clouds, a CSV with a scalar at every point, image data. Any of it can drive geometry once geometry accepts fields as an input. Luminary’s <a href="https://cdfam.com/luminary/" target="_blank">case for physics AI as a strategic advantage</a> rests on the same foundation — the value sits in the field data, and in being able to compute over it fast enough to stay in the loop.<img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789403334890-Coreform+A+range+of+analyses+run+with+IGA.jpeg" style="width:100%px" class="fr-fic fr-dib" /><h2>What this adds up to</h2>Formats decide what can move. Synthetic data decides what can be learned. Fields decide what can be expressed at all. The AI tooling is the visible layer, and it rests on those three.Which is the same thing people at CDFAM were discussing<a href="https://cdfam.com/the-need-for-data-for-ai-generated-engineering/" target="_blank"> in 2022</a>, before there was much to demonstrate: more than geometry, this needs design intent and validation.<hr />Hear it from the people building itSearch the <a href="https://cdfam.com/presentation-index/" target="_blank" rel="noopener noreferrer">CDFAM presentation index</a>, with transcripts of every recorded presentation in the series. Search by speaker, company or topic, or search what was actually said to find the moment itself. Every result links to the exact second of the recording.

The data problem

The Data Foundation for Engineering with AI

Across four years of <a href="https://cdfam.com/" target="_blank" rel="noopener noreferrer">CDFAM Computational Design Symposium</a> talks, AI agents have gone from a research curiosity to something structural engineers run in Slack. The record of how fast that happened is sitting in the transcripts.<table><tbody><tr><td>Event</td><td>Talks referencing AI agents</td></tr><tr><td>NYC 2023</td><td>2</td></tr><tr><td>Berlin 2024</td><td>1</td></tr><tr><td>NYC 2024</td><td>3</td></tr><tr><td>Amsterdam 2025</td><td>2</td></tr><tr><td>NYC 2025</td><td>6</td></tr><tr><td>Barcelona 2026</td><td>14</td></tr><tr><td>Washington DC 2026</td><td>4 of 6, so far</td></tr></tbody></table><a href="https://cdfam.com/cd-dc-26/" target="_blank" rel="noopener noreferrer">Washington DC</a> recordings are still incomplete. Four of the first six talks released mention agents.The word arrived before the capability. In 2023, when Chris McComb of Carnegie Mellon described agents to a <a href="https://cdfam.com/nyc/" target="_blank" rel="noopener noreferrer">CDFAM audience in New York</a>, he was reporting an experiment rather than a product. His group had run human design teams against hybrid ones, and the hybrid teams were missing half their people.<blockquote>We had some human teams, we had some hybrid teams where we ripped out half of the people and replaced them with AI agents.Chris McComb, Carnegie Mellon University, CDFAM NYC 2023</blockquote><iframe width="640" height="360" src="https://www.youtube.com/embed/72yVB9_PNJE?&amp;t=868s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">              </iframe>The finding was that the hybrid teams held up, and that they held up because communication went up rather than down. People took on what McComb called the role of an AI handler, translating between the model and the task so the agents could stay useful members of the team. Two years later that description reads less like a laboratory result and more like a job.<h2>The Turn</h2>What changed between 2023 and now was not the idea but the plumbing. By the Amsterdam symposium in 2025, Andrew Sartorelli of Synera was describing an agentic layer sitting on top of automated workflows that already existed, wired into the systems a manufacturer actually keeps its knowledge in: product lifecycle management, simulation data management, requirements tracking. The agents were not being asked to invent engineering. They were being given access to it.<iframe width="640" height="360" src="https://www.youtube.com/embed/RfBTGqdDsRg?&amp;t=328s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">             </iframe>That is the pattern that repeats across every discipline in the year since. The interesting work is rarely the model. It is the harness.<h2>Aerospace</h2>Ryan McClelland's generatively designed spacecraft parts at NASA Goddard were already familiar to the CDFAM audience by 2024, but the agent question he raised was about assembly rather than geometry. Once individual evolved components exist, they can be combined into larger systems either by code or by agents, until an automated electronic box is something you specify rather than something you draw. The unit of design moves up a level.<iframe width="640" height="360" src="https://www.youtube.com/embed/DV_DVw0UIF0?&amp;t=1257s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">           </iframe><h2>Automotive</h2>The most concrete automotive account came from SEAT in <a href="https://cdfam.com/bcn/" target="_blank" rel="noopener noreferrer">Barcelona in 2026</a>. A year of automation work on body-in-white development had already cut development time from two hours to five minutes in one case, and from forty-two hours to one in another, before agents entered the picture at all.What they showed next was a multi-agent system for sheet metal manufacturability. An engineer uploads a CAD component into a chat window and a supervisor orchestrates the agents beneath it: one extracting geometry such as wall thicknesses and blank size, another running forming simulation, others handling cost and carbon once sourcing data is supplied.<blockquote>There's a supervisor which is calling and orchestrating all the agents underneath.Tilman Steininger, Synera, CDFAM Barcelona 2026</blockquote>The output is not a verdict but a location. If a component cannot be made, the system returns images showing where the problem is, and the engineer goes back into CATIA to resolve it. That loop, rather than any individual model, is the product.<h2>Architecture</h2>Architecture and structural engineering produced the year's most concrete demonstrations, possibly because the work is so heavily gated by specialist availability. At CD/DC in Washington, Sergey Pigach of CORE studio showed an agentic system his firm runs on AWS and interacts with through Slack. Ask it, in a sentence, for a concrete column stack and footing for a five-storey residential building in New York and let it make the remaining assumptions, and it calls the same tools the firm's engineers use, renders the column and writes a design summary.<iframe width="640" height="360" src="https://www.youtube.com/embed/TqKjZU0UfT0?&amp;t=189s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">         </iframe>His framing of why it works is the sharpest line anyone offered on the subject.<blockquote>It's not a domain expertise problem. It's really an unhobbling problem.Sergey Pigach, CORE studio | Thornton Tomasetti, CDFAM Washington DC 2026</blockquote>Frontier models, on his evidence, are already competent at engineering work. What they lack is a way to reach the tools. Pigach also noted something easy to overlook: the agent lives in Slack deliberately, because putting it in a shared space where people already work changes the relationship compared with sitting down in front of a chatbot.Matthew Goldsberry and Junling Zhuang of HDR gave the practitioner's counterweight at NYC 2025, opening by locating themselves precisely: from the trenches of trying to use these tools in an architecture firm. Their term for it, form jamming, describes assembling AI coding tools and image generation into something usable per project, and their conclusion was that the framework matters more than any finished pipeline.<iframe width="640" height="360" src="https://www.youtube.com/embed/fv6yCKngCe0?&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">       </iframe>At Barcelona, Augmenta described full automation of mechanical, electrical and plumbing design as fully agentic, compressing MEP work from weeks to days, while noting plainly that there is a long way still to go.<iframe width="640" height="360" src="https://www.youtube.com/embed/tmgj-DoGXHQ?&amp;t=784s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">      </iframe><h2>Industrial design</h2>The consumer-facing end of the field has been slower to use the word and quicker to build the constraints agents will eventually need. Ruben Verhack of Datameister put the problem precisely at Amsterdam in 2025. Industrial design is governed by hard points: fixed locations, dimensions and rules that cannot move without major consequence, whether that is where a car's engine and occupants sit or where the batteries and cooling zones fall in a consumer device.<blockquote>You don't want to be creative on these things.Ruben Verhack, Datameister, CDFAM Amsterdam 2025</blockquote><iframe width="640" height="360" src="https://www.youtube.com/embed/zoSI979fcjw?&amp;t=165s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">     </iframe>General-purpose visual AI generates from the surface inward, he argued, while design works from the inside out, and the last twenty percent is always where it breaks. His team's answer was to constrain generation to geometry already known to be manufacturable, so an exterior can be explored freely around components that are fixed. Laurence Cook of Generative Engineering made a parallel case at Barcelona for splitting a simulation pipeline apart, so stress, impact displacement and manufacturing cost can be explored alongside a designer working in the language of form.<iframe width="640" height="360" src="https://www.youtube.com/embed/-RjobfZM634?&amp;t=757s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">    </iframe><h2>What has to exist underneath</h2>The most structural claim came from Intact Solutions at CD/DC. Today's tools, they argued, give you a co-pilot sitting inside an application. What replaces it is a set of agents standing in for domain and subject-matter experts, talking to each other, over what has to be a robust callable physics infrastructure underneath. Without that layer there is nothing for an agent to call, and the demonstration collapses into text generation about engineering rather than engineering.<iframe width="640" height="360" src="https://www.youtube.com/embed/cwEyKEsIIQ0?&amp;t=513s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">   </iframe>That is also why the sceptical voices this year have been so precise. SimScale's Andrew Acuff opened his CD/DC talk by renaming it: the programme said agentic workflows were reshaping simulation-driven product development, and he told the room he preferred accelerating, because the iterative loop between design and simulation is worth keeping. What he wanted gone was the waiting.<iframe width="640" height="360" src="https://www.youtube.com/embed/Mr3H905ePsg?&amp;t=55s&amp;wmode=opaque&amp;rel=0&amp;enablejsapi=1&amp;origin=https://www.wevolver.com" frameborder="0" class="fr-draggable">  </iframe>Read across four years, that is the actual shape of the change. Not the arrival of autonomous design, which nobody credible is claiming, but the steady disappearance of the queue.<h2>Hear it from the people building it</h2>Every talk quoted here is in the CDFAM presentation index, along with transcripts of every other recorded presentation from the symposium series. Search by speaker, company or topic, or search what was said to find the moment itself. Every result links to the exact second of the recording.<a href="https://cdfam.com/presentation-index/" target="_blank">Explore the CDFAM presentation index</a><img src="https://s3-us-west-1.amazonaws.com/wevolver-project-images/froala%2F1789145485842-SearchforspecifictermsatCDFAM-ezgif.com-video-to-gif-converter.gif" style="width:100%px" class="fr-fic fr-dib" />

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