AI EDAM-Artificial Intelligence for Engineering Design Analysis and Ma

Papers
(The TQCC of AI EDAM-Artificial Intelligence for Engineering Design Analysis and Ma is 6. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-07-01 to 2026-07-01.)
ArticleCitations
Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems25
Stacking ensemble learning based material removal rate prediction model for CMP process of semiconductor wafer25
Improved basic elements detection algorithm for bridge engineering design drawings based on YOLOv518
Finite-element analysis case retrieval based on an ontology semantic tree16
CNN–NSDBO–EWTOPSIS: A hybrid multi-objective optimization approach for concrete mixture proportion design problem12
Creation-as-transmission: a cognitive-based framework for cultural heritage learning through AI collaborative creation12
Hybrid machine learning approach for accurate and expeditious 3D scanning to enhance rapid prototyping reliability in orthotics using RSM-RSMOGA-MOGANN12
Convolutional autoencoder for on-demand parametric inverse design of local resonator geometry in wind turbine metastructure targeting vibration control10
Managing combinatorial design challenges using flexibility and pathfinding algorithms10
A semi-supervised anomaly detection approach for detecting mechanical failures10
Measuring ideation effectiveness in bioinspired design10
Sampling balanced high-quality data to train an automatic mesh generator9
Comparative analysis of machine learning algorithms for predicting standard time in a manufacturing environment9
Developing a data analytics toolbox for data-driven product planning: a review and survey methodology9
Design of an intelligent simulator ANN and ANFIS model in the prediction of milling performance (QCE) of alloy 2017A8
Exploring the impact of set-based concurrent engineering through multi-agent system simulation8
Analyzing problem framing in design teams: a systems mapping approach7
Enhancing TRIZ through environment-based design methodology supported by a large language model7
ChatGPT as an inventor: eliciting the strengths and weaknesses of current large language models against humans in engineering design7
Towards the conceptual design of ML-enhanced products: the UX value framework and the CoMLUX design process7
Remaining useful life prediction methods of equipment components based on deep learning for sustainable manufacturing: a literature review6
Automatic weld joint type recognition in intelligent welding using image features and machine learning algorithms6
Optimal configurations of Minimally Intelligent additive manufacturing machines for Makerspace production environments6
Graph models for engineering design: Model encoding, and fidelity evaluation based on dataset and other sources of knowledge6
The effects of generative AI model type and visual stimuli type on design creativity6
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