arXiv:2609.39738v1 Announce Type: new
Abstract: Learning to generate machining process plans and toolpaths from B-rep CAD requires coupling discrete operation decisions with continuous tool motion as...
By Xiaolei Zhou, Boyi Lin, Yuchao Feng, Jianwei Zheng
The article explores physics-informed and hybrid machine learning approaches for predicting bond quality and porosity in fused filament fabrication (FFF) parts. It examines three strategies—embedding physics constraints in the loss function, adding physics model outputs as inputs, and pre‑training with physics data—to enforce consistency with physical laws. Eight combinations of these strategies are tested, showing that integrating multiple approaches yields accurate predictions even with limited experimental data.
By Berkcan Kapusuzoglu, Sankaran Mahadevan
arXiv:2607. 07863v1 Announce Type: new Abstract: In physically dominated machining processes, experimental datasets are small, expensive, and material-specific; in this regime, data curation, evaluation design, and the form of physics integration can matter as much as the learning algorithm.
By Sarah Grewe, J\"org Frochte
The paper introduces a cooperative neural network framework for partially inverse designing high‑performance concrete (HPC) mixes. It combines an imputation model with a surrogate strength predictor and is trained cooperatively, enabling it to produce valid, performance‑consistent mix designs in a single forward pass without retraining for different constraints. Compared to baseline methods, the approach achieves higher strength consistency (R² 0.84–0.89) and reduces mean squared error by 42–60%.
By Agung Nugraha, Heungjun Im, Jihwan Lee
arXiv:2606. 11605v1 Announce Type: cross Abstract: Predicting process-property relationships in manufacturing is often challenged by high experimental costs and the limited interpretability of complex 'black-box' models.
By Ge Song, Kiarash Naghavi Khanghah, Anandkumar Patel, Rajiv Malhotra, Hongyi Xu
arXiv:2609.07046v1 Announce Type: new
Abstract: AI has revolutionized various engineering domains, but its impact on semiconductor device design and defect discovery is still limited, due to limited...
By Hiu Yung Wong