Demystifying Digital “X” – ICED Conference Paper

Posted Leave a commentPosted in CFMS, Chris Cox, DETI, Projects, Publications

The DMF lab recently (remotely) attended the International Conference of Engineering Design (ICED) 2021 to present seven papers. One of these, authored by Chris Cox, Ben Hicks and James Gopsill, investigates the new language surrounding the paradigm shift towards digital engineering. This presentation was shown at ICED 2021 as part of the “Digital Twins” panel, […]

Revisiting prototyping in 2020: A snapshot of practice in UK Design Companies

Posted Leave a commentPosted in Announcements, Digital-Physical Twinning, Prototwinning, Publications, Seamless Digital Physical Prototyping

Prototyping is an indispensable activity in the product development process but what does prototyping practice in industry look like? In this video we take a ‘snapshot’ of prototyping practice from 5 companies to see how practice has evolved and understand what the characteristics of industrial practices are. This work was presented at the International Conference […]

Comparison of digitisation methods: photogrammetry and structured light scanning

Posted Leave a commentPosted in Non-Identical Digital Twins, Prototwinning, Publications, Seamless Digital Physical Prototyping

What are the differences in performance and usability of digitisation techniques?  In this video we compare two such methods; photogrammetry and structured light scanning. For more details please see the full paper on the link here https://www.cambridge.org/core/journals/proceedings-of-the-design-society/article/comparison-of-structured-light-scanning-and-photogrammetry-for-the-digitisation-of-physical-prototypes/66038D84EF1A45F22F601B899EFC0D25. This work was presented at the International Conference of Engineering Design (ICED) 2021. 

Capturing Perceptions of Shape and Form using Machine Learning @ ICED21

Posted Leave a commentPosted in Publications

The Design Manufacturing Futures Lab has published and presented a paper entitled “Capturing Mathematical and Human Perceptions of Shape and Form through Machine Learning” that extends the groups knowledge, capability and understanding of how ML could be applied to support Engineering Design. This was published and presented at the International Conference on Engineering Design 2021 (ICED21)