Automating the Design for Additive Manufacture Process with AI
Lead Participant:
BATCHW LIMITED
Abstract
Our project focuses on revolutionising the design process for additive manufacturing (AM) through the integration of artificial intelligence (AI) technology. Batch.Works, a leading Design and Additive Manufacture business, will collaborate with Lancaster University's School of Engineering to put together a feasibility study and roadmap for the development of AI-driven design methodologies
Batch.Works is a rapidly growing company that specialises in innovative circular manufacturing practices in the UK. However, their design process for AM is currently manual and time-intensive, involving trial and error across different software platforms and physical prototypes. This hinders their scalability and ability to meet the increasing demand for their services.
In collaboration with Lancaster University, renowned for its expertise in Additive Manufacturing Innovation, we will identify and test opportunities to leverage cutting-edge AI technologies to transform the AM design landscape. Our focus areas include data-driven decision-making and design optimisation, targeting the core challenges faced by Batch.Works.
Through data-driven decision-making, we will monitor and analyse the existing design workflow to identify opportunities for automation and optimisation. By implementing AI-based support systems, we aim to minimise manual tweaking, reduce trial and error, and enhance overall product quality. This will result in improved efficiency, reduced costs, and enhanced competitiveness for Batch.Works.
The design phase is critical for Batch.Works, harnessing AI will be key to streamlining and enhancing this process. By developing AI-driven plugins and tools, we will provide real-time feedback on the suitability of designs for additive production. This will significantly reduce the number of design iterations required, allowing designers to focus more on creativity and accelerating the design-to-production timeline.
In addition to driving productivity gains, our project will also prioritise sustainability in the manufacturing industry. Batch.Works' commitment to circular manufacturing practices aligns perfectly with our goals. By leveraging AI to optimise the creative design process, we will also reduce material waste, energy consumption, and environmental impact.
Our project will provide Lancaster with the opportunity to broaden their research into AI for AM technology and build strong bonds with a new industry partner. Batch.Works will have built a roadmap for integrating AI into their design development, enabling them to meet the growing demands of their production capacity. By combining their expertise with cutting-edge AI technologies, Batch.Works will gain a competitive advantage, unlock new opportunities, and become a leader in the additive manufacturing industry.
Batch.Works is a rapidly growing company that specialises in innovative circular manufacturing practices in the UK. However, their design process for AM is currently manual and time-intensive, involving trial and error across different software platforms and physical prototypes. This hinders their scalability and ability to meet the increasing demand for their services.
In collaboration with Lancaster University, renowned for its expertise in Additive Manufacturing Innovation, we will identify and test opportunities to leverage cutting-edge AI technologies to transform the AM design landscape. Our focus areas include data-driven decision-making and design optimisation, targeting the core challenges faced by Batch.Works.
Through data-driven decision-making, we will monitor and analyse the existing design workflow to identify opportunities for automation and optimisation. By implementing AI-based support systems, we aim to minimise manual tweaking, reduce trial and error, and enhance overall product quality. This will result in improved efficiency, reduced costs, and enhanced competitiveness for Batch.Works.
The design phase is critical for Batch.Works, harnessing AI will be key to streamlining and enhancing this process. By developing AI-driven plugins and tools, we will provide real-time feedback on the suitability of designs for additive production. This will significantly reduce the number of design iterations required, allowing designers to focus more on creativity and accelerating the design-to-production timeline.
In addition to driving productivity gains, our project will also prioritise sustainability in the manufacturing industry. Batch.Works' commitment to circular manufacturing practices aligns perfectly with our goals. By leveraging AI to optimise the creative design process, we will also reduce material waste, energy consumption, and environmental impact.
Our project will provide Lancaster with the opportunity to broaden their research into AI for AM technology and build strong bonds with a new industry partner. Batch.Works will have built a roadmap for integrating AI into their design development, enabling them to meet the growing demands of their production capacity. By combining their expertise with cutting-edge AI technologies, Batch.Works will gain a competitive advantage, unlock new opportunities, and become a leader in the additive manufacturing industry.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| BATCHW LIMITED | £29,006 | £ 29,006 |
Participant |
||
| LANCASTER UNIVERSITY | £14,976 | £ 14,976 |
People |
ORCID iD |
| Milo Mcloughlin-Greening (Project Manager) |