# Lukas M. Ziegler

Lukas M. Ziegler creates content about industrial automation and manufacturing technology, including robotics, CNC machining, AI, and digital production systems.

- Profile: https://b2binfluencer.marketing/creators/lukas-m-ziegler/
- LinkedIn: https://www.linkedin.com/in/zieglerr
- LinkedIn followers: 268,789
- YouTube: https://www.youtube.com/channel/UCrGmmssx0mOFU6o8MhOAeDw
- Topics: artificial-intelligence, physical-ai, industrial-automation, robotics
- Based on 12 dated posts, latest 2026-10-07

## Summary

Most useful for technical explainers on industrial automation, robotics, CNC, and digital production for engineering audiences.

- Best for: This fits automation suppliers selling CNC-integrated robot cells for aerospace and energy parts.
- Not for: This does not fit warehouse robotics, logistics audiences, or short product videos without technical specifics.
- Check first: Ask for audience data, newsletter figures, and recent sponsored placement results.

### Takeaways

- A digital thread is only as good as its weakest handoff.
- Machine-tool language should stay in charge of the robot.
- Measure automation in minutes, microns and square metres.

## Main ideas

- **A digital thread is only as good as its weakest handoff**: Ziegler tests connected manufacturing not by how well a fully integrated showcase runs, but by how much value the chain delivers in mixed environments, because real factories combine vendors. They walk through a production chain step by step, identify which company supplies each layer, then point to the handoffs where information falls out. That matters in aerospace, where parts are specified to microns and grams and every production step must be documented for certification.
- **Machine-tool language should stay in charge of the robot**: Ziegler favors robots that fit how machinists already work, rather than adding a separate world of controllers, programming languages and specialists. When the robot's kinematics run inside the CNC, the arm is path-controlled rather than point-to-point, and people who already know G-code can program it as they do the machine.
- **Explain the result and the catch, including who does the work**: Ziegler routinely asks what the limitation is and who is responsible for each part of the delivery. That is both a priority and a method: a capability becomes understandable when the operating model, partners and deployment conditions are on the table. A post that skips them makes a capability claim, not an explanation.
- **Measure automation in minutes, microns and square metres**: Ziegler favors production metrics and physical constraints over general claims. Their framing, credited to a Siemens robotics expert, is that large workpieces usually push buyers toward very large, expensive and inflexible machine tools, while a robotics approach quickly hits accuracy and stability limits. The useful territory lies between those two, and what matters is what changes on the floor.
- **AI and simulation are production tools, not separate subjects**: AI runs through these posts as a layer in a manufacturing chain: design, programming, machine health and adaptive orchestration. Simulation gets the same treatment—as a way to de-risk a physical process or make an invisible one tangible and discussable. Ziegler's range extends beyond factory equipment, but the argument stays the same when the setting changes.

## Work to read

- [A faster route to machining large parts](https://www.linkedin.com/posts/zieglerr_siemenspartner-sponsored-activity-7510656946123800576-qiMI)
- [Programming a robot with G-code](https://www.linkedin.com/posts/zieglerr_siemenspartner-sponsored-activity-7501194848020955136-uo-R)
- [An AI-designed aerospace part and its digital thread](https://www.linkedin.com/posts/zieglerr_siemenspartner-sponsored-activity-7513506662956302336-vMwq)
- [Physical AI on a production floor](https://www.linkedin.com/posts/zieglerr_sponsored-siemenspartner-siehm-activity-7463117636357238784-eJbV)
- [Using simulation to make acoustics tangible](https://www.linkedin.com/posts/zieglerr_siemenspartner-sponsored-activity-7485229425362362368-_Hy_)

## Brand relationships

- **Siemens Industry** (sponsor)
- **Weekly robotics newsletter (ziegler.substack.com)** (owned_business)

## Partnerships

Every partnership example in the posts is a Siemens-sponsored post. Ziegler visits a Siemens plant, trade-show booth, or technology demonstration, films and interviews the people running it, then publishes a LinkedIn write-up that credits Siemens, links to a Siemens page or ticket offer, and points readers to the weekly robotics newsletter at ziegler.substack.com. The subject matter is technical and specific — machine-tool robots, digital-thread manufacturing, acoustic simulation, physical AI on production floors — and each post carries a sponsorship disclosure. The posts show no published rate card, media kit, audience breakdown, or official sponsorship inquiry route. Ask for pricing, turnaround, exclusivity, and deliverables beyond a post.

## Alternatives

- Leo Vieira: Choose Vieira for a campaign about enterprise digital-manufacturing priorities, not for explaining a machine-tool cell to engineers. In a Hannover Messe reflection, the post connects Physical AI to an earlier warehouse-inventory drone project and notes recurring client interest in MES and OEE. A shorter post about the Brazilian pavilion sets the event in a digital-manufacturing context. The material is a better fit for a business-level transformation story than a detailed demonstration of CNC-integrated robotics.
- Cristian M.: Choose Cristian M. for a campaign showing software engineers how industrial automation, robotics, and simulation can connect through .NET. The project overview describes C# tools for EtherNet/IP, ROS, simulation, and digital twins. In a digital-twin experiment, an ONNX walking policy trained in MuJoCo runs in PhysX through Gemelli Studio; the post notes that matching the policy’s conventions took work. This integration example is more useful than a product overview when buyers need to assess developer access and interoperability.
- Ozgur Tohumcu: Choose Tohumcu for a campaign seeking an executive-level view of industrial AI and supply-chain transformation across sectors. The Japan and Nagoya takeaways discuss product priorities, software-defined vehicle architecture, compute constraints, and AI-partner decisions. Separately, the VivaTech post reports a panel discussion on AI in industrial supply chains and gives cost-reduction and forecast-accuracy figures. Together, the posts offer a strategic narrative, not a technical account of how a robot cell works.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/