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 3. 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 2021-05-01 to 2025-05-01.)
ArticleCitations
Stacking ensemble learning based material removal rate prediction model for CMP process of semiconductor wafer17
Enabling multi-modal search for inspirational design stimuli using deep learning14
Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems14
Potentials and challenges of analyzing use phase data in product planning of manufacturing companies11
inML Kit: empowering the prototyping of ML-enhanced products by involving designers in the ML lifecycle11
Improved basic elements detection algorithm for bridge engineering design drawings based on YOLOv511
Gamification of design thinking: a way to enhance effectiveness of learning10
Finite-element analysis case retrieval based on an ontology semantic tree9
Towards comprehensive digital evaluation of low-carbon machining process planning9
Hybrid machine learning approach for accurate and expeditious 3D scanning to enhance rapid prototyping reliability in orthotics using RSM-RSMOGA-MOGANN8
Breaking up data-enabled design: expanding and scaling up for the clinical context8
A semi-supervised anomaly detection approach for detecting mechanical failures7
Adaptive hyperball Kriging method for efficient reliability analysis7
Artificial intelligence methods for improving the inventive design process, application in lattice structure case study7
Developing a data analytics toolbox for data-driven product planning: a review and survey methodology6
Assurance monitoring of learning-enabled cyber-physical systems using inductive conformal prediction based on distance learning6
Measuring ideation effectiveness in bioinspired design6
Evaluating the learning and performance characteristics of self-organizing systems with different task features5
ChatGPT as an inventor: eliciting the strengths and weaknesses of current large language models against humans in engineering design4
Comparative analysis of machine learning algorithms for predicting standard time in a manufacturing environment4
Data-enabled sketch search and retrieval for visual design stimuli generation4
Analyzing problem framing in design teams: a systems mapping approach4
A stochastic topology optimization algorithm for improved fluid dynamics systems4
Design of an intelligent simulator ANN and ANFIS model in the prediction of milling performance (QCE) of alloy 2017A4
Exploring the impact of set-based concurrent engineering through multi-agent system simulation4
Extenics enhanced axiomatic design procedure for AI applications4
Towards the conceptual design of ML-enhanced products: the UX value framework and the CoMLUX design process3
A hybrid particle swarm optimization and recurrent dynamic neural network for multi-performance optimization of hard turning operation3
Stone masonry design automation via reinforcement learning3
Optimal configurations of Minimally Intelligent additive manufacturing machines for Makerspace production environments3
Enhancing TRIZ through environment-based design methodology supported by a large language model3
AIE volume 35 issue 3 Cover and Front matter3
A method to explore strategies to communicate user experience through storyboards: an automotive design case study3
Remaining useful life prediction methods of equipment components based on deep learning for sustainable manufacturing: a literature review3
Graph models for engineering design: Model encoding, and fidelity evaluation based on dataset and other sources of knowledge3
Automatic weld joint type recognition in intelligent welding using image features and machine learning algorithms3
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