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
Engineering, Manufacturing
Nilesh Ashok Kharat, Ankit Agarwal, Tyler Grimm, Laine Mears
Summary: This research proposes a novel complex stochastic toolpath strategy to reduce surface error in the machining of free-form components. Compared to conventional machining strategies, this approach allows for continuous variation of chip load, force, and direction, avoiding conditions of high cutting loads and heat accumulation. Initial testing shows that stochastic toolpaths are longer but can reduce cutting time and result in lower scallop height, thereby improving surface condition.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2023)
Article
Engineering, Manufacturing
Minglong Guo, Zhaocheng Wei, Minjie Wang, Jia Wang, Shengxian Liu
Summary: This study establishes a milling force prediction model for freeform surface five-axis machining, taking into account mesoscopic size effects, and proposes a new form of dislocation density correction. Experimental results show that the calculated shear stress can comprehensively reflect cutting dynamic characteristics and successfully consider size effects.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2021)
Article
Engineering, Manufacturing
Ankit Agarwal, K. A. Desai
Summary: This article presents a novel approach to optimize geometric tolerances (flatness and cylindricity) by manipulating the rigidity among finishing and roughing cutting sequences during end milling of thin-walled components. The proposed approach combines mechanistic force model, finite element (FE) analysis-based workpiece deflection model, and particle swarm optimization (PSO) technique to determine optimal disposition of material along the length of component. The outcomes of the proposed algorithm are validated by conducting a set of end milling experiments for thin-walled components having different configurations.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2021)
Article
Engineering, Electrical & Electronic
Xuefeng Yang, Xulin Cai, Wenan Yang, Youpeng You
Summary: A contour parallel tool path generation method for pocket machining is developed based on sound field synthesis theory. The method extracts the simplified medial axis tree of the pocket and obtains the final tool path through sound field synthesis. Experimental results demonstrate that the tool path obtained by the novel method has advantages in improving machining quality and efficiency.
Article
Engineering, Manufacturing
Angelos Marinakis, Emmanouela Dandouti, Aristomenis Antoniadis
Summary: Involute gears are crucial in industry for their ability to provide flexible and accurate rotary motion. Gear shaping is a common gear cutting process used to manufacture various types of gears. Accurate prediction of cutting forces is essential as it impacts tool life and wear. This study developed a simulation model to simulate the involved kinematics and provide accurate results, which were validated by comparing produced gear flanks and measured cutting forces.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2022)
Article
Engineering, Manufacturing
Kazuki Kaneko, Jun Shimizu, Keiichi Shirase
Summary: A new method for analyzing workpiece elastic deformation during end milling is proposed. This method can be easily combined with a voxel-based milling simulation to predict cutting force and machining error. By discretely representing the workpiece using voxels connected by beam elements, the proposed method avoids the time-consuming remeshing required by the finite element method (FEM). Additionally, the stiffness matrix can be easily updated from a previous matrix, further reducing computation time.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2023)
Article
Engineering, Manufacturing
Lu Lei, Jiong Zhang, Xiaoqing Tian, Jiang Han, Hao Wang
Summary: This paper introduces a tool path optimization method for robotic surface machining using sampling-based motion planning algorithms. By considering the redundant degrees-of-freedom of industrial robots, the tool motion for surface machining can be optimized, ensuring that the tool-tip position strictly follows the tool path curve within certain constraints. The algorithm, based on the open motion planning library (OMPL), utilizes state-of-the-art sampling-based motion planners to generate an optimal path length for each joint of the robot.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2021)
Article
Chemistry, Physical
Ting-Hsun Lan, Yu-Feng Chen, Yen-Yun Wang, Mitch M. C. Chou
Summary: The study evaluated the feasibility of a new CAD/CAM material, NaCaPO4-blended zirconia, which showed improved densification and better marginal fit, making it a potential new material for dental restoration.
Article
Engineering, Manufacturing
Dong He, Yamin Li, Zhaoyu Li, Kai Tang
Summary: This paper presents a new method for planning the five-axis machining process of complex parts, utilizing curved intermediate surfaces influenced by the part's convex hull and generated with the geodesic distance field. The proposed method aims to improve the stiffness and stability of the workpiece during machining by alternating between roughing and finishing operations. Physical cutting experiments confirmed the advantages of this method.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2021)
Article
Mathematics
Cesar Garcia-Hernandez, Juan-Jose Garde-Barace, Juan-Jesus Valdivia-Sanchez, Pedro Ubieto-Artur, Jose-Antonio Bueno-Perez, Basilio Cano-Alvarez, Miguel-Angel Alcazar-Sanchez, Francisco Valdivia-Calvo, Ruben Ponz-Cuenca, Jose-Luis Huertas-Talon, Panagiotis Kyratsis
Summary: Trochoidal milling is a well-established machining strategy that can be applied to any type of material, but is usually associated with advanced materials. By adjusting the feed speed of the milling tool, the chip width can be kept constant, optimizing material usage and reducing tool wear.
Article
Dentistry, Oral Surgery & Medicine
Murali Srinivasan, Nicole Kalberer, Nicolas Fankhauser, Manuel Naharro, Sabrina Maniewicz, Frauke Mueller
Summary: This study aimed to evaluate and compare the differences between milled and 3D-printed complete removable dental prostheses. While both treatment modalities showed similar effectiveness, 3D-printed prostheses required more maintenance time and costs.
JOURNAL OF DENTISTRY
(2021)
Article
Dentistry, Oral Surgery & Medicine
Murali Srinivasan, Edward Chaoho Chien, Nicole Kalberer, Adrian Miguel Alambiaga Caravaca, Alicia Lopez-Castellano, Porawit Kamnoedboon, Salvatore Sauro, Mutlu Ozcan, Frauke Mueller, Daniel Wismeijer
Summary: The study quantitatively evaluated the elution of methylmethacrylate from CAD-CAM manufactured removable complete dentures using HPLC, finding significantly lower concentrations in 3D-printed RCDs compared to milled RCDs. Coating with an additional protective layer like Durecon or adopting an extended isopropanol wash cycle can further decrease the MMCs.
JOURNAL OF DENTISTRY
(2022)
Article
Computer Science, Artificial Intelligence
Lan Li, Fazhi He, Rubin Fan, Bo Fan, Xiaohu Yan
Summary: In this article, a hierarchical RL approach for 3D shape reconstruction is presented. The method utilizes macro actions and sub-agents to decompose the task into simplified sub-tasks. By using an augmented state space sub-agent, the training process is accelerated and parameter count reduced. Experimental results demonstrate the superior performance of this approach compared to other methods, as well as its high transferability among different classes of data.
INTEGRATED COMPUTER-AIDED ENGINEERING
(2023)
Article
Dentistry, Oral Surgery & Medicine
Passent Ellakany, Shaimaa M. Fouda, Maram A. AlGhamdi, Nourhan M. Aly
Summary: This study compared the color stability and surface roughness of 3-unit provisional fixed partial dentures fabricated by milling, conventional, and different 3D printing techniques. The results showed that the milled resin had the lowest surface roughness and color change, followed by the SLA printed resin. Therefore, SLA printed resins can be used as an alternative to milled resins in the fabrication of provisional FPDs to overcome the high expenses.
JOURNAL OF DENTISTRY
(2023)
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
Automation & Control Systems
Changqing Liu, Yingguang Li, Jingjing Li, Jiaqi Hua
Summary: This article proposes a meta-invariant feature space (MIFS) learning method for accurate tool wear prediction under cross conditions with large variations, by learning the nature law of data under different conditions through meta-learning.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Manufacturing
Yingguang Li, Changqing Liu, Ke Xu, Xiaozhong Hao, Shaochun Sui
Summary: The ability of research innovation is crucial in the rapidly changing era. This paper introduces a critical thinking framework based on seven questions, which helps engineering students to cultivate innovative thinking and develop their own ideas.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(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)