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 5. 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 2022-05-01 to 2026-05-01.)
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 wafer18
Improved basic elements detection algorithm for bridge engineering design drawings based on YOLOv517
CNN–NSDBO–EWTOPSIS: A hybrid multi-objective optimization approach for concrete mixture proportion design problem12
Finite-element analysis case retrieval based on an ontology semantic tree12
Hybrid machine learning approach for accurate and expeditious 3D scanning to enhance rapid prototyping reliability in orthotics using RSM-RSMOGA-MOGANN12
Creation-as-transmission: a cognitive-based framework for cultural heritage learning through AI collaborative creation9
Managing combinatorial design challenges using flexibility and pathfinding algorithms9
Convolutional autoencoder for on-demand parametric inverse design of local resonator geometry in wind turbine metastructure targeting vibration control9
A semi-supervised anomaly detection approach for detecting mechanical failures9
Developing a data analytics toolbox for data-driven product planning: a review and survey methodology8
Sampling balanced high-quality data to train an automatic mesh generator7
Measuring ideation effectiveness in bioinspired design7
Enhancing TRIZ through environment-based design methodology supported by a large language model7
Analyzing problem framing in design teams: a systems mapping approach7
ChatGPT as an inventor: eliciting the strengths and weaknesses of current large language models against humans in engineering design7
Graph models for engineering design: Model encoding, and fidelity evaluation based on dataset and other sources of knowledge6
Comparative analysis of machine learning algorithms for predicting standard time in a manufacturing environment6
Design of an intelligent simulator ANN and ANFIS model in the prediction of milling performance (QCE) of alloy 2017A6
Towards the conceptual design of ML-enhanced products: the UX value framework and the CoMLUX design process6
Exploring the impact of set-based concurrent engineering through multi-agent system simulation6
Remaining useful life prediction methods of equipment components based on deep learning for sustainable manufacturing: a literature review5
The effects of generative AI model type and visual stimuli type on design creativity5
Optimal configurations of Minimally Intelligent additive manufacturing machines for Makerspace production environments5
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