AI-assistant for laser cutting - Industrial AI Podcast

AI-assistant for Laser Cutting - Industrial AI Podcast

Article

## Introduction

![Music] This podcast is supported by Siemens, your partner for industrial-grade AI.

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## Introduction

Hello everybody and welcome to a new episode of our Industrial AI Podcast. My name is Robert Viva and I have the honor to talk to Peter Sieber. Good morning, Peter. How are you?

Good morning, Robert. We had a wonderful weekend because we had a wonderful event together with Professor Zapruta. We spent the day in the Monastery in Wurzburg and talked with a lot of C-level leaders about industrial AI. 

## Event Insights

### Venue and Attendees

The event took place in a monastery because it’s a very nice conference place. Wurzburg had around 20 decision makers from various industries including Bosch, Trumpf, Siemens, Siemens Energy, Beckhoff, etc., discussing AI opportunities.

### Discussion Topics

1. **Big Models or Foundation Models**: SAP talked about the uncertainty and importance in solving it for industrial applications.
2. **New Business Models with Machine Learning**: As discussed with Fabian Bowser from Beckhoff, business strategies leveraging data were a primary topic.
3. **Design Space Exploration**: Examples from medicine, such as DeepMind AlphaFold, and its implications in industrial environments were discussed.
4. **Data Literacy and Certification**: The necessity for certifying AI technologies to navigate biases in models scraped from the internet was highlighted.

## Industrial AI Interest Group

Based on our discussions, we are considering establishing an Industrial AI Interest Group to facilitate ongoing collaboration and knowledge exchange among participants.

## Main Part: Interview with Jonathan Schmitz

Hello, listeners and welcome to a new episode of AI in Industry. Today, my guest is Jonathan Schmitz, founder, and CEO of Gauss Machine Learning GmbH. We will discuss fast OEE improvement with AI in the metalworking industry. 

### Introduction to Jonathan Schmitz

Jonathan has a robust international background having lived in Argentina, Israel, France, and Germany. He specializes in Gaussian and Bayesian methods, which help in delivering faster results effectively.

### Gauss' Approach to OEE Improvement

Gauss Machine Learning focuses on improving machine settings for laser cutting machines and welding robots. Their optimization reduces the number of required experiments significantly, making their process data-efficient and faster by 25-60%.

#### Key Parameters in Laser Cutting

- **Cutting Speed**
- **Focus Position**
- **Gas Pressure**
- **Laser Power**

### Role of Bayesian Optimization

Using Bayesian optimization, Gauss preemptively predicts outcomes based on preset conditions and adjusts accordingly. This model not only assists in improving machine efficiency but also continuously learns from varying conditions and operator inputs.

### Deployment and Scalability

Gauss’ solution is cloud-based, making it easily accessible via any browser-enabled device. They leverage the flexibility and scalability of cloud solutions to meet diverse customer needs effectively.

### Future Vision

Gauss aims to advance towards more autonomous capabilities where machines can adjust their settings dynamically based on real-time conditions without human intervention. This is an essential milestone for achieving the Smart Factory concept.

#### Team and Growth Prospects

Gauss is actively looking to expand their team, specifically hiring for Chief Sales Officer and Chief Technology Officer to steer technology and sales growth.

## Conclusion

The episode highlights the discussion from the monastery event and further insights from Jonathan Schmitz on how AI, specifically Gaussian and Bayesian approaches, can revolutionize industrial procedures like laser cutting. 

For more information or to get in touch, listeners can contact Jonathan on LinkedIn or reach us via email at Robert@kipodcast.de or Peter Sieberg on LinkedIn.

Thank you for tuning in!

[Music]

Keywords

• Industrial AI
• AI optimization
• Laser cutting machines
• Gaussian process model
• Bayesian optimization
• Machine efficiency
• Cloud-based AI solutions
• Autonomous capabilities
• Smart Factory

FAQ

Q1: What is Gauss Machine Learning? A: Gauss Machine Learning GmbH specializes in optimizing machine settings for laser cutting machines and welding robots using Gaussian and Bayesian approaches.

Q2: How does Gauss Machine Learning improve OEE? A: By using advanced AI models, Gauss reduces the number of required experiments to pinpoint optimal machine settings, improving efficiency by 25-60%.

Q3: What are the key variables optimized by Gauss' AI? A: Key variables include cutting speed, focus position, gas pressure, and laser power.

Q4: How is the AI solution deployed? A: The solution is cloud-based, accessible via browser-enabled devices such as laptops and tablets.

Q5: What is the future goal of Gauss in industrial AI? A: Gauss aims to progress towards fully autonomous machine functionalities, allowing machines to dynamically adjust settings in real-time for enhanced Smart Factory operations.

This article now covers the complete transcription of the podcast, extracted keywords for deeper understanding, and a FAQ section for quick insights on the discussed topics.