...Mutahar Safdar; Jiarui Xie; Andrei Mircea; Yaoyao Fiona Zhao Data-driven research in Additive Manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature to emerge. The knowledge in these works consists of AM and Artificial Intelligence (AI...

... artificial intelligence human–computer interfaces/interactions Physical human–robot interaction (pHRI) aims to integrate robotic systems with human cognitive abilities to perform tasks that exceed the capabilities of either entity alone [ 1 ]. Two critical aspects must be considered: (1) ensuring...

...@outlook.com Artificial Intelligence Manufacturing Automation Journal of Computing and Information Science in Engineering. Received July 18, 2024; Accepted manuscript posted March 18, 2025. doi:10.1115/1.4068235 Copyright © 2025 by ASME; reuse license CC-BY 4.0 Accepted Manuscript Not Copyedited...

... Corresponding author. Email: sarabehdad@ufl.edu 19 04 2024 27 01 2025 07 02 2025 12 03 2025 human motion prediction gated recurrent unit Bayesian neural network long short-term memory human–robot collaboration disassembly remanufacturing artificial intelligence...

... collaboration (HRC) artificial intelligence machine learning for engineering applications National Science Foundation 10.13039/100000001 2026276 Human–robot collaboration (HRC) is a rapidly growing area of research and application. It plays an important role in various sectors, including...

...@g.clemson.edu Email: shazarika@parc.com Email: rrai@clemson.edu 13 12 2023 09 02 2025 12 02 2025 07 03 2025 artificial intelligence machine learning for engineering applications physics-based simulations process modeling for engineering applications In the heart...

... and Artificial Intelligence (ECAI) , Pitesti, Romania , June 27–29 , IEEE , pp. 1 – 6 . [15] Hu , Y. , Wu , X. , Zheng , G. , and Liu , X. , 2019 , “ Object Detection of UAV for Anti-UAV Based on Improved Yolo V3 ,” 2019 Chinese Control Conference (CCC), IEEE , pp. 8386 – 8390...

... network sparse voxel representation manufacturing feature recognition computer-aided process planning (CAPP) artificial intelligence cybermanufacturing manufacturing automation National Science Foundation 10.13039/100000001 2229260 Automatic manufacturing feature recognition...

... , A. , and Li , A. , 2020 , “ Orthogonal Gradient Descent for Continual Learning ,” International Conference on Artificial Intelligence and Statistics (AISTATS) , Palermo, Sicily, Italy , Aug. 26–28 , PMLR, pp. 3762 – 3773 . [31] Yoon , J. , Kim , S. , Yang , E. , and Hwang , S. J...

... for simulating, analyzing, and controlling their operation in real-time [ 12 , 13 ]. There has been a rapid increase in the usage of digital twins in industries, concurrent with advancements in machine learning, artificial intelligence, cloud computing, and data analytics [ 14 ]. Different industries...

.... In the final stage, latent needs are identified using an LLM on a provided criteria, and finally a report is generated from the identified latent needs. requirements elicitation large Language models artificial intelligence LLM agents computer-aided design Requirement elicitation (RE) sits...

...@asu.edu Email: Farhad.Ameri@asu.edu 23 04 2024 03 12 2024 08 12 2024 10 01 2025 artificial intelligence big data and analytics cybermanufacturing data-driven engineering knowledge engineering machine learning for engineering applications manufacturing automation...

... manufacturing. In recent years, with the rise of smart manufacturing and the Industry 4.0 paradigm, LFAM has been increasingly incorporating intelligent and automated technologies. Machine learning and artificial intelligence are now being utilized to refine the printing process and enhance the efficiency...

... artificial intelligence knowledge engineering Inspirational stimuli have been widely shown to support designers during the early stage design process by serving as a catalyst for creativity and innovation [ 1 – 3 ]. Among the various methods employed to elicit such stimuli, the use of design...

.... , Lee , Y. T. , Li , Y. , Lundberg , S. , and Nori , H. , 2023 , “ Sparks of Artificial General Intelligence: Early Experiments With GPT-4 ,” arXiv Preprint arXiv:2303.12712. [4] Barbhuiya , R. K.. , 2023 , “ Introduction to Artificial Intelligence: Current Developments...

..., focusing on concept generation and detailed modeling. By comparing outcomes from artificial intelligence (AI)-assisted groups to those without AI assistance, our research reveals that AI significantly broadens concept generation diversity but also introduces bias for existing popular designs. Additionally...

... bJy. CAoSmMpEut. Inf. Sci. Eng. Table 1 Table Caption List Comparative MAPE Performance of Sequence Modeling Techniques in Tire Health Prediction Accepted Manuscript Not Copyedited 24 Advanced Computing Infrastructure Artificial Intelligence Big Data and Analytics Data-Driven engineering...

... model variational graph autoencoder artificial intelligence Graphical Abstract Figure 05 04 2024 16 07 2024 27 07 2024 15 11 2024 1 Corresponding author. Email: hongyi.3.xu@uconn.edu Email: zihan.5.wang@uconn.edu Email: kiarash.naghavi_khanghah...

... context-aware design assistance artificial intelligence data-driven engineering machine learning for engineering applications Material selection plays an important role in the conceptual design phase of engineering projects. The choice of materials directly impacts the overall performance...

... , X. , Xu , H. , Zhang , Y. , Zhu , X. , Yin , H. , and Zheng , Y. , 2022 , “ DeepThermal: Combustion Optimization for Thermal Power Generating Units Using Offline Reinforcement Learning ,” Proceedings of the 36th AAAI Conference on Artificial Intelligence , Virtual , Feb. 22...