RobnAI: Empowering Robotic Design
through AI-Driven Optimization
The Greek SME I Know How partnered with AIRISE in the RobnAI experiment to enhance the design process of robotic components. With over two decades of experience and a strong focus on robotics and automation, I Know How aimed to incorporate AI technologies to produce more sustainable, cost-effective, and structurally optimized robotic products.
Key achievements:
AI Integration in Robotics: Successfully incorporated AI technologies into the design process of robotic components.
Enhanced Product Design: Improved sustainability, cost-efficiency, and structural optimization of robotic products.
Strategic Collaboration: Partnered with AIRISE through the RobnAI experiment, showcasing effective cross-organization cooperation.
Leverage of Expertise: Utilized over 20 years of experience in robotics and automation to drive innovation.
AI-driven optimization of robotic components
enhancing sustainability, cost-efficiency, and design automation
The company faced key challenges in optimizing the mechanical design of their robots, particularly in achieving sustainable production and lifecycle efficiency.
They identified that AI in product design was still underexplored in the industry, especially in developing robust solutions for manufacturing complexity, cost, and lifecycle considerations.
AIRISE supported I Know How by introducing topology optimization and geometry generation tools to integrate AI into their design workflows. Two robotic components were targeted: one from a logistics robot and one from a water magnetic crawler.
Tools like Blender (customised by AIMEN) and Fusion 360 were used to generate, simulate, and evaluate design alternatives. Engineers received training and were guided to integrate AI solutions seamlessly with manufacturability constraints in mind.
The RobnAI experiment led to significant advancements in robotic component design and manufacturing, resulting in the following key achievements:
- 50% mass reduction of components while maintaining structural integrity.
- 65% cost reduction in production of specific alternatives.
- Substantial design time savings by automating geometry generation.
- Simplified manufacturing and fewer production phases, improving customer satisfaction.
- Successful fulfilment of KPIs set at the project’s outset, including reduced complexity and faster production.
I Know How plans to continue using the AI tools provided through AIRISE, especially for complex parts and additive manufacturing. The experience has shaped their strategic goals, with further integration of generative design and AI-assisted engineering in future projects.
The team views the AIRISE collaboration as both “creative and informative,” empowering them to adopt innovations previously seen in larger companies.