Article
Computer Science, Artificial Intelligence
Yuanzhe Deng, Matthew Mueller, Chris Rogers, Alison Olechowski
Summary: The emerging multi-user CAD systems have the potential for collaborative learning, leading to the proposal of a MUCAD collaborative learning framework. This framework interprets user actions from MUCAD software and observes differences in CAD behavior among different user types.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Engineering, Biomedical
Daofeng Wang, Lin Han, Gaoxiang Xu, Wupeng Zhang, Hua Li, Cheng Xu, Huanyu Li, Jitian Li, Hao Zhang, Jiantao Li
Summary: This study designed a new method using 3D printing and CAD for bone biomechanical study and verified the accuracy of osteotomy. This method is expected to achieve homogeneity and standardization of osteotomy in bone biomechanical study.
INTERNATIONAL JOURNAL OF BIOPRINTING
(2022)
Article
Computer Science, Interdisciplinary Applications
P. Perez, J. A. Serrano, M. E. Martin, P. Daza, G. Huertas, A. Yufera
Summary: A computer program is developed for the system design of biosensors applied to monitoring cell culture dynamics. The program allows for the confident obtaining of system information through electrical stimulation, accurately predicting the output frequency and amplitude ranges of the voltage response. Deep insight information on cell size, number, and time-division can be extracted from comparing with real cell culture assays in the future.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Review
Computer Science, Interdisciplinary Applications
Monika Dyavenahalli Shivegowda, Pawinee Boonyasopon, Sanjay Mavinkere Rangappa, Suchart Siengchin
Summary: Computer-aided design and manufacturing have become the most common trend, with designers using CAD to generate design concepts and engineers using CAM to produce goods. These two technologies are merged into unified CAD/CAM systems, which allow for easy management of the design and production process.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2022)
Article
Health Care Sciences & Services
Paolo Scolozzi, Francesco Michelini, Claude Crottaz, Alexandre Perez
Summary: Computer-aided design and computer-aided manufacturing (CAD/CAM) techniques have proven to be valuable in dental implant surgery, improving the success rate and patient satisfaction while ensuring implant parallelism. This study analyzed the clinical and radiological data of thirteen edentulous patients treated using CAD/CAM techniques, showing successful outcomes.
JOURNAL OF PERSONALIZED MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Song Wang
Summary: Computer-aided CAD system is crucial in urban planning and heritage conservation. It can effectively identify existing CAD models and facilitate their reuse, leading to shorter development cycles, lower costs, and improved efficiency. This paper introduces the concept of computer learning algorithm and proposes a model of naive Bayesian algorithm to emphasize the significance of urban cultural heritage as a carrier of human history and culture.
Review
Biotechnology & Applied Microbiology
Aurelio Salerno, Paolo A. Netti
Summary: The review discusses the recent scientific literature on AM fabrication of drug delivery scaffolds for TE, focusing on bioactive molecule loading into 3D porous scaffolds and their release effects on cell fate and tissue growth. strategies such as bioprinting were reviewed to achieve passive and stimuli-responsive drug delivery scaffolds for TE and cancer precision medicine. The integration of AM, microfluidic, and soft lithography is highlighted for enhancing 3D porous scaffold bioactivation towards functional bioengineered tissues and organs.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2021)
Article
Engineering, Multidisciplinary
Yingjun Wang, Mi Xiao, Zhaohui Xia, Peigen Li, Liang Gao
Summary: This paper proposes a novel design mode, called human-aided design (HAD), to replace conventional computer-aided design (CAD). In HAD, computers can automatically complete product design using a new isogeometric topology optimization (ITO), while humans assist in making slight modifications. An embedded domain ITO is introduced for designing complex models with irregular domains, and editable geometric models of optimized results can be generated automatically. Experimental results on three different examples demonstrate the potential of the HAD mode to deliver high-quality optimized models, suggesting it as a revolutionary technology to transform the current design mode.
Article
Computer Science, Interdisciplinary Applications
Tahir Abbas Jauhar, Soonhung Han, Soonjo Kwon
Summary: This study analyzed different CAD applications in terms of their abilities to import and export neutral models with identification information. It was found that heterogeneous CAx environments have issues with missing identification information when neutral models are re-imported, leading to associativity problems.
JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING
(2021)
Article
Chemistry, Analytical
Chen-Yang Zhao, Chi-Fai Cheung, Wen-Peng Fu
Summary: The paper presents an investigation into cutting strategy for the optimization of machining parameters in ultra-precision machining of polar microstructures used for optical precision measurement. Critical machining parameters affecting surface generation and quality were studied through cutting simulations and experiments. The study includes theoretical modeling, image processing, and an experimental investigation of cutting tool geometry, depth of cut, and groove spacing on polar microstructures.
Article
Engineering, Manufacturing
M. L. Guo, Z. C. Wei, H. Gao, Z. H. Zhang, J. Jiang
Summary: With the increasing demands on machining accuracy and quality for precision copper electrode in product molds, this paper deeply analyzes the distribution type and formation mechanism of burrs based on the geometric features of the electrode. The influence of cutting-edge geometry on the lateral dimension of burrs is investigated and a new left-handed fillet milling cutter is designed. Experimental results show that the new cutter and process can greatly reduce the size of burrs and achieve almost burr-free machining, increasing the service life and meeting the actual machining needs.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2023)
Article
Chemistry, Multidisciplinary
Fenfang Zeng, Shaoting Liu, Feng Yang, Yisen Xu, Guofu Zhou, Jifeng Xuan
Summary: Computer Aided Design (CAD) is a set of techniques that automate the designing and drafting of 2D and 3D models using computer programs. The quality of CAD software is crucial in ensuring the reliability of the designed models. Software testing is an important way to detect defects in CAD software development. This paper proposes an approach, PriorCadTest, to learn and prioritize test cases for CAD software, and evaluates its effectiveness on a real-world CAD project.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Physical
Chao-Min Huang, Anjelica Kucinic, Joshua A. Johnson, Hai-Jun Su, Carlos E. Castro
Summary: Recent studies have shown that integrating molecular dynamics-based computer-aided engineering with computer-aided design allows for the rapid construction of large three-dimensional DNA assemblies with control over their geometry, mechanics, and dynamics, expanding the scope of structural complexity and design capabilities for DNA assemblies.
Article
Business
Angelo Corallo, Mariangela Lazoi, Gabriele Papadia, Claudio Pascarelli
Summary: This article explores the integration of existing systems with virtual reality as a supporting tool for product and process design in industrial companies. The study conducted with oil and gas manufacturing companies reveals that virtual reality technology has proven to be reliable for CAD, CAE, and CAM data immersive visualization, resulting in improved design and limited negative impacts related to errors during manufacturing phase.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Automation & Control Systems
Lai Hu, Zhenggang Chen, Yaolong Chen
Summary: This study measures the accuracy of closed impeller machining machines in aerospace, particularly focusing on a cradle type five-axis machining center. The research focuses on the difficulties in measuring the accuracy of cradle-type five-axis machining centers and proposes solutions to improve accuracy. Laser interferometer is used to measure the straightness of X, Y, Z, and the positioning accuracy of X, Y, Z, B, and C axes. The importance of temperature sensor in improving measurement accuracy is highlighted through comparative analysis.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Engineering, Manufacturing
Jiaqi Hua, Yingguang Li, Wenping Mou, Changqing Liu
Summary: A novel cutting tool wear prediction method based on continual learning is proposed in this paper, which can accurately predict tool wear under varying cutting conditions and have strong adaptability.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2022)
Article
Chemistry, Multidisciplinary
Shuting Liu, Yingguang Li, Qiangqiang Liu, Ke Xu, Jing Zhou, Yingxiang Shen, Zijian Yang, Xiaozhong Hao
Summary: Manipulation of heat distribution in thermal functional materials has been a long-term goal, with various methods developed but facing challenges such as external equipment dependency and limited thermal resolution. A computed thermal patterning method introduced tomography principles to achieve dynamic thermal manipulation without external heaters or cables, solving thermal diffusion issues and demonstrating great potential in diverse applications.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Materials Science, Composites
Jing Zhou, Yingguang Li, Zexin Zhu, Eyan Xu, Shengping Li, Shaochun Sui
Summary: For the first time, a method has been proposed to make highly reflective CFRP laminates perfectly absorptive by introducing ultra-thin and flexible metallic resonance structures, leading to rapid energy-efficient heating. Experimental results show that the cured CFRP laminates using this method exhibit comparable or even higher mechanical properties than autoclave processed counterparts.
COMPOSITES SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Tianchi Deng, Yingguang Li, Xu Liu, Lihui Wang
Summary: This research aims to achieve manufacturing data sharing based on federated learning, utilizing scattered data for machine learning while protecting data privacy. An enterprise-oriented framework is proposed to find FL participants with similar data resources, and an FL model is developed for machining parameter planning in aircraft structural parts.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Materials Science, Composites
Wenzheng Xue, Yingguang Li, Jing Zhou, Tao Yang, Xiaozhong Hao, Youyi Wen
Summary: This paper presents the development of a wireless self-heating tooling with good durability and low thermal mass using microwave technology. By employing electromagnetic resonators, efficient and rapid microwave heating of the metallic panel was achieved. Experimental results showed that the composite laminates cured by the self-heating tooling exhibited comparable quality and performance, while reducing energy consumption by 81.5%.
APPLIED COMPOSITE MATERIALS
(2023)
Article
Chemistry, Physical
Di Li, Jing Zhou, Yingguang Li, Wenzheng Xue, Zexin Zhu, Youyi Wen
Summary: Recently, the interest in thermal manipulation in carbon materials using microwave heating has increased. Microwave heating has advantages such as non-contact heating, fast temperature response, and low energy consumption. However, the lack of effective control methods on electromagnetic properties has made it challenging to achieve real-time thermal manipulation. In this study, we propose a solution by using tunable electromagnetic resonators, allowing pixel-controlled microwave heating in carbon materials. The experimental results show that the microwave absorbance and heating rate can be tuned, suggesting potential applications in customized materials processing, thermal display, deicing, and defrosting.
Article
Engineering, Industrial
Yingguang Li, Ke Xu, Shixin Wang, James Gao, Paul Maropoulos
Summary: This paper introduces a new thermal control method using digital image based programming to accurately control temperature distribution in advanced heat treatment processes. The method efficiently estimates required heat sources and controls temperature distribution in a step-wise numerical manner. Simulation and real heating tests validate the method for microwave curing of composites, showing excellent temperature uniformity and consistency compared to existing technologies.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Xu Liu, Yingguang Li, Yinghao Cheng, Yu Cai
Summary: Establishing accurate dynamic models for ball-screw drives is crucial for improving motion control precision. However, due to nonlinear factors such as position-dependent dynamics and friction disturbance, accurately modeling these drives is challenging. To overcome this, a sparse identification method is proposed, representing the drives as discrete-time linear parameter-varying systems and using dictionary function libraries. By constructing the system model and implementing stepwise sparse regression, an accurate and linearizable dynamic model can be identified.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Interdisciplinary Applications
Xu Liu, Yingguang Li, Lu Chen, Gengxiang Chen, Boya Zhao
Summary: This paper proposes a method called Multiple Source Partial Knowledge Transfer (MSPKT) to address the global shift and local discrepancy problems in multi-source learning. It introduces the TSK fuzzy system as the basic learner to represent partial knowledge effectively. A transferability measurement of partial knowledge is designed to support transfer learning with multiple source domains. The effectiveness of the proposed method is validated using a synthetic dataset and two manufacturing system datasets.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Mechanics
Qinglu Meng, Yingguang Li, Xu Liu, Gengxiang Chen, Xiaozhong Hao
Summary: This paper proposes a novel physics informed neural operator (PINO) framework that can solve parametric coupled PDEs unsupervised and accelerate the training process significantly by enforcing global constraints on the field outputs. Experiments demonstrate the notable superiority of the proposed method under both deterministic and parametric settings.
COMPOSITE STRUCTURES
(2023)
Article
Computer Science, Artificial Intelligence
Lu Chen, Yingguang Li, Gengxiang Chen, Xu Liu, Changqing Liu
Summary: This paper proposes a Physics-Guided High-Value (PGHV) data sampling method to reduce the required experiments for data-driven stability prediction. The optimal experimental parameter set is determined by maximizing the dataset value, and the experimental labelled dataset is constructed by performing cutting experiments under the sampled experimental parameters. The stability prediction model can then be obtained by the data-driven modelling method with the experimental labelled dataset. Experimental verification shows that the proposed method can reduce the number of experiments by more than 60% compared to the existing sampling methods.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Engineering, Industrial
Ke Xu, Yingguang Li, Guanguan Cao, Shuting Liu
Summary: This paper proposes an image-based optimization scheme to control the temperature field in thermosetting composite curing process. A grayscale image is generated to encode a nominal temperature field, and an adaptive thresholding algorithm is developed to regularize the temperature field, reducing cure-induced distortion. Experimental results show a noticeable reduction in distortion distribution, with a decrease of 25-50% in average distortion using the optimized temperature field.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Gengxiang Chen, Yingguang Li, Xu Liu, Charyar Mehdi-Souzani, Qinglu Meng, Jing Zhou, Xiaozhong Hao
Summary: This paper proposes a physics-guided neural operator to directly predict the high-dimensional temperature history from the given cure cycle. By integrating domain knowledge into a time-resolution independent parameterised neural network, the mapping between cure cycles to temperature histories can be learned using a limited number of labelled data. Detailed experiments show that the proposed model can accurately predict the temperature histories and provide better process optimisation results.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Manufacturing
Qiang-Qiang Liu, Shu-Ting Liu, Ying-Guang Li, Xu Liu, Xiao-Zhong Hao
Summary: This paper proposes a non-contact, full-field monitoring method based on deep learning to predict the internal temperature field of composite parts in real time. It achieves high accuracy and feasibility.
ADVANCES IN MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Jiaqi Hua, Yingguang Li, Changqing Liu, Peng Wan, Xu Liu
Summary: This article proposes a kind of PINN with weighted losses (PNNN-WLs) by uncertainty evaluation for accurate and stable prediction of manufacturing systems. The proposed approach improves the prediction accuracy and stability over existing methods by quantifying the variance of prediction errors and establishing an improved PINN framework.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
