Congratulations to Dr Mohamed Gomaa et al for the publication of their journal paper investigating the thermal properties of 3D printed cob. This paper has resulted from the feasibility study funded by Connected Everything and led by Dr Wassim Jabi (Cardiff University).
SLS sensing system
Following his feasibility study funding, Phillip Stanley-Marbell (Cambridge) has created a new sensing system for a Selective Laser Sintering machine. This #Github link gives a really nice overview of the work: https://github.com/physical-computation/Sesame
Connected Everything: Shared Learning Workshop, 13 February 2019
On Wednesday 13 February, researchers awarded funding via Connected Everything came together to present and discuss their experiences in a Shared Learning Workshop. The Workshop had three sessions; presentations from the feasibility study teams outlining their projects’ outcomes or progress to date, presentations from the Early Career Researchers who have been on placements and … Continue reading Connected Everything: Shared Learning Workshop, 13 February 2019
Automatic Fault Detection for Selective Laser Melting Using Semi-Supervised Machine Learning
The team behind the “Towards additive manufacturing process control using semi-supervised learning” feasibility study have just released a pre-print of the outcomes of their project. Click on the following link to read the paper "Automatic Fault Detection for Selective Laser Melting Using Semi-Supervised Machine Learning". https://www.preprints.org/manuscript/201809.0346/v1
