Journal of Computing and Information Science in Engineering
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EISSN:1944-7078|ISSN:1530-98270|Disc:The Journal of Computing and Information Science in Engineering publishes archival research results and advanced technical applications|Priority:4|Publisher:American Society of Mechanical Engineers|
Recent Submissions
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Integrating Graph Retrieval-Augmented Generation With Large Language Models for Supplier Discovery
(The American Society of Mechanical Engineers (ASME), 2025)As supply chain complexity and dynamism challenge traditional management approaches, integrating large language models (LLMs) and knowledge graphs (KGs) emerges as a promising method for advancing supply chain analytics. ... -
Design Knowledge as Attention Emphasizer in Large Language Model-Based Sentiment Analysis
(The American Society of Mechanical Engineers (ASME), 2024)Aspect-based sentiment analysis (ABSA) enables a systematic identification of user opinions on particular aspects, thus improving the idea creation process in the initial stages of a product/service design. Large language ... -
Evaluating Large Language Models for Material Selection
(The American Society of Mechanical Engineers (ASME), 2024)Material selection is a crucial step in conceptual design due to its significant impact on the functionality, aesthetics, manufacturability, and sustainability impact of the final product. This study investigates the use ... -
Experimental Investigation Using Robust Deep VMD-ICA and 1D-CNN for Condition Monitoring of Roller Element Bearing
(The American Society of Mechanical Engineers (ASME), 2024)A rotor-bearing system experiences numerous vibrations during the operation that frequently degrade performance and endanger operational safety. Roller-bearing failure has significant consequences, leading to downtime or ... -
A Modified Simulated Annealing-Based Method for Hybrid Lattice Support Structure Design in LPBF Additive Manufacturing
(The American Society of Mechanical Engineers (ASME), 2024)When designed effectively, support structures play a critical role in quickly dissipating heat and mitigate part distortion without driving up excessive costs within the additive manufacturing metals technique of Laser ... -
MODAL-DRN-BL: A Framework for Modal Analysis Based on Dilated Residual Broad Learning Networks
(The American Society of Mechanical Engineers (ASME), 2025)Each object has unique inherent frequencies and vibration modes, which are known as modal parameters. The modal analysis aims to study the free vibration characteristics of an object under an external force action. In modal ... -
Elicitron: A Large Language Model Agent-Based Simulation Framework for Design Requirements Elicitation
(The American Society of Mechanical Engineers (ASME), 2025)Requirement elicitation, a critical, yet time-consuming and challenging step in product development, often fails to capture the full spectrum of user needs. This may lead to products that fall short of user expectations. ... -
Transformer-Based Offline Printing Strategy Design for Large Format Additive Manufacturing
(The American Society of Mechanical Engineers (ASME), 2025)In the realm of large format additive manufacturing (LFAM), determining an effective printing strategy before actual printing involves predicting temperature behaviors and controlling layer time, which has consistently ... -
Offline Reinforcement Learning for Adaptive Control in Manufacturing Processes: A Press Hardening Case Study
(The American Society of Mechanical Engineers (ASME), 2024)This paper explores the application of offline reinforcement learning in batch manufacturing, with a specific focus on press hardening processes. Offline reinforcement learning presents a viable alternative to traditional ... -
A Global Feature Reused Network for Defect Detection in Steel Images
(The American Society of Mechanical Engineers (ASME), 2024)Accurate detection of surface defects for steel is essential to improve surface quality and service life. Deep learning (DL) used in steel surface defect detection can solve the problems of low efficiency and poor accuracy ... -
Data-Driven Digital Twins for Real-Time Machine Monitoring: A Case Study on a Rotating Machine
(The American Society of Mechanical Engineers (ASME), 2025)In this work, we present a framework for data-driven digital twins for real-time machine monitoring. Data-driven digital twins are gaining prominence in a variety of industrial applications owing to their ability to capture ... -
Haptic Interaction Methods for Freehand Contour Generation on a Refreshable Pin Display
(The American Society of Mechanical Engineers (ASME), 2025)Emerging surface haptic display technology holds promise for enhancing manual interactions such as contour drawing, a task that requires simultaneous generation and sensing for accurate control of the emerging shape. ... -
Manufacturing Feature Recognition With a Sparse Voxel-Based Convolutional Neural Network
(The American Society of Mechanical Engineers (ASME), 2025)Automated manufacturing feature recognition is a crucial link between computer-aided design and manufacturing, facilitating process selection and other downstream tasks in computer-aided process planning. While various ... -
Mixed Finite Element Formulation in Nonlinear Geometrical Analysis of Space Trusses and Application to Trusses With Member Length Imperfection
(The American Society of Mechanical Engineers (ASME), 2024)Space trusses usually have a significant number of elements. As a result, it is inevitable that some elements have imperfections. In this study, the authors proposed a mixed finite element method for nonlinear geometrical ... -
Epsilon-Greedy Thompson Sampling to Bayesian Optimization
(The American Society of Mechanical Engineers (ASME), 2024)Bayesian optimization (BO) has become a powerful tool for solving simulation-based engineering optimization problems thanks to its ability to integrate physical and mathematical understandings, consider uncertainty, and ... -
Optimizing Robotic Manipulation With Decision-RWKV: A Recurrent Sequence Modeling Approach for Lifelong Learning
(The American Society of Mechanical Engineers (ASME), 2025)Models based on the transformer architecture have seen widespread application across fields such as natural language processing (NLP), computer vision, and robotics, with large language models (LLMs) like ChatGPT revolutionizing ... -
Do Large Language Models Produce Diverse Design Concepts? A Comparative Study with Human-Crowdsourced Solutions
(The American Society of Mechanical Engineers (ASME), 2024)Access to large amounts of diverse design solutions can support designers during the early stage of the design process. In this article, we explored the efficacy of large language models (LLMs) in producing diverse design ... -
A Framework of Real-Time Knowledge Capture and Formalization for Model-Based Design With Spoken Annotation and Design Operations
(The American Society of Mechanical Engineers (ASME), 2024)Capturing knowledge without an extra burden on engineers is one of the most challenging issues in the engineering domain. This study proposes a framework of real-time knowledge capture and systematic formalization for the ... -
Calibration of RAFM Micromechanical Model for Creep Using Bayesian Optimization for Functional Output
(The American Society of Mechanical Engineers (ASME), 2025)A Bayesian optimization procedure is presented for calibrating a multimechanism micromechanical model for creep to experimental data of F82H steel. Reduced activation ferritic martensitic (RAFM) steels based on Fe(8–9)%Cr ... -
DesignQA: A Multimodal Benchmark for Evaluating Large Language Models’ Understanding of Engineering Documentation
(The American Society of Mechanical Engineers (ASME), 2024)This research introduces DesignQA, a novel benchmark aimed at evaluating the proficiency of multimodal large language models (MLLMs) in comprehending and applying engineering requirements in technical documentation. Developed ...