Article
Engineering, Manufacturing
Benjamin C. Stump, Brian T. Gibson, Jay T. Reynolds, Charles C. Wade, Michael C. Borish, Peter L. Wang
Summary: As powder bed fusion (PBF) additive manufacturing (AM) progresses, system configurations are shifting towards unconventional configurations to increase throughput. The inclusion of multiple heat sources increases the complexity of control schemes and load balancing becomes crucial. This paper introduces high-performing load balancing methods for multi-beam systems of any complexity, enabling on-the-fly load balancing in case of beam failures and improving system robustness.
ADDITIVE MANUFACTURING
(2023)
Article
Engineering, Multidisciplinary
Martin Bihr, Gregoire Allaire, Xavier Betbeder-Lauque, Beniamin Bogosel, Felipe Bordeu, Julie Querois
Summary: This paper focuses on shape and topology optimization of parts and supports in the context of metal powder bed additive manufacturing. The process complexity is simplified using the inherent strain model, which allows for computationally efficient optimization. Three optimization criteria are proposed to minimize defects caused by additive manufacturing, and a compliance constraint is included to ensure the final performance of the part. The numerical results are validated through experimental testing and are used to calibrate the inherent strain model.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Inno Lorren Desir Makanda, Maolin Yang, Haoliang Shi, Wei Guo, Pingyu Jiang
Summary: Additive manufacturing (AM) systems are shifting towards network-based models to coordinate manufacturing resources from multiple enterprises for product orders. While AM technologies offer freedom in creating complex parts, challenges in production planning must be addressed for increased productivity. This study proposes heuristic algorithms to solve production planning and part-to-printer assignment issues in AM systems, demonstrating high-performance results in reducing production costs and time.
Article
Chemistry, Analytical
Osama Abdulhameed, Syed Hammad Mian, Khaja Moiduddin, Abdulrahman Al-Ahmari, Naveed Ahmed, Mohamed K. Aboudaif
Summary: Additive manufacturing is a technique used for producing 3D objects layer by layer, and it is gaining traction in various industries. However, part quality and build time are obstacles for mass production. This research proposes a new method for multi-part additive manufacturing that improves quality and reduces build time.
Article
Engineering, Multidisciplinary
Hongjia Lu, Linwei He, Matthew Gilbert, Filippo Gilardi, Jun Ye
Summary: Additive manufacturing (AM) has rapidly developed and offers the potential to fabricate structurally optimized components. The use of truss topology optimization methods has been effective in identifying optimal forms for highly design free components. However, geometric complexity and overhanging elements often require support structures when using traditional 3-axis AM machines. To eliminate the need for support structures, multi-axis AM machines with 5 or more axes can be used. A novel process-aware truss layout optimization strategy tailored for multi-axis AM machines is proposed in this study, which combines curved printing surface identification with truss layout and geometry optimization. The proposed strategies aim to achieve highly material-efficient structures and fully self-supporting structures with minimal material consumption. The effectiveness of the approach is demonstrated through several examples, showing that fully self-supporting optimized structures can be identified without sacrificing structural performance.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2024)
Article
Engineering, Manufacturing
Isaac M. Nault, Gehn D. Ferguson, Aaron T. Nardi
Summary: A 3D deposition model and tool path optimization algorithm are developed for cold spray additive manufacturing, allowing for the manufacture of arbitrary convex deposit shapes. The model is calibrated and the optimization scheme is evaluated through experiments.
ADDITIVE MANUFACTURING
(2021)
Article
Computer Science, Interdisciplinary Applications
Cunfu Wang, Xiaoping Qian
Summary: The paper proposes a simultaneous optimization method for part and support in additive manufacturing. A pseudo heat conduction problem is solved to simulate heat transfer between the part and support. The proposed formulation allows control of surface slope and the ability to obtain self-supported enclosed voids and removable external supports.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Manufacturing
Markellos Ntagios, Habib Nassar, Ravinder Dahiya
Summary: The new 3D printer developed in this study combines Fused Filament Fabrication and Direct Ink Write technologies, allowing the printing of multiple materials simultaneously. It expands the range of printable materials and enables the mixing and printing of multi-part materials, including complex ones like two-part rubbers. Experimental results demonstrate the printer's good control even at high printing speeds (up to 20 mm/s).
ADDITIVE MANUFACTURING
(2023)
Article
Chemistry, Multidisciplinary
Juan Carlos Pereira, Ramon Moreno, Christian Tenbrock, Arnold Herget, Thomas Wittich, Kelvin Hamilton
Summary: The HyProCell approach combines flexible additive manufacturing processes with precise subtractive machining processes, allowing for the production of new parts and the repair or improvement of existing parts. The research includes the design of pilot cell facilities, the development of a new modular architecture, and MES and data management methodologies for future improvements.
APPLIED SCIENCES-BASEL
(2021)
Article
Polymer Science
Brandon Jackson, Kamran Fouladi, Babak Eslami
Summary: This work focuses on finding the optimal printing conditions for a commercially available 3D printer and filament material. The study finds that the retraction speed plays a significant role in defining the ultimate tensile strength of the printed parts, while the number of walls has little effect on the strength.
Article
Engineering, Multidisciplinary
Weiming Wang, Fred van Keulen, Jun Wu
Summary: Additive manufacturing of metal parts often leads to distortion due to phase transformations and high temperature gradients. This paper proposes a computational framework that optimizes the fabrication sequence to minimize distortion in multi-axis additive manufacturing. By encoding the fabrication sequence using a continuous pseudo-time field and using gradient-based numerical optimization, the framework successfully reduces distortion by orders of magnitude compared to planar fabrication.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2023)
Article
Automation & Control Systems
Austen Thien, Christopher Saldana, Thomas Kurfess
Summary: This study investigates the impact of varying dwell time and input deposition power on wire arc additive manufacturing, concluding that lower input power and dwell time can significantly reduce production time.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Polymer Science
Claudio Tosto, Jacopo Tirillo, Fabrizio Sarasini, Claudia Sergi, Gianluca Cicala
Summary: Metal 3D-printed parts have important applications in various industries, but traditional manufacturing techniques are expensive. This study combines fused deposition modeling (FDM) with debinding-sintering processes to reduce costs. By optimizing printing parameters, the material density and mechanical performance of sintered stainless steel parts were improved.
Article
Computer Science, Interdisciplinary Applications
Jie Chen, Changyu Meng, Yi Gao, Yongming Liu
Summary: This paper proposes a novel multi-fidelity optimization framework by using convolutional neural networks for MF data aggregation and integrating it into a neural network-based optimization framework. The potential of this framework is demonstrated through numerical examples and engineering applications.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Energy & Fuels
Nimel Sworna Ross, M. Belsam Jeba Ananth, J. M. Jafferson, L. Rajeshkumar, M. Saravana Kumar
Summary: This study investigates the performance and effects of using vegetable oil as a coolant for machining aluminum alloy. The experimental results show that using minimal quantity lubrication can reduce the heat generated in the cutting zone, decrease surface roughness and temperature, and produce fine grains.
BIOMASS CONVERSION AND BIOREFINERY
(2022)
Review
Engineering, Industrial
Chao Liu, Pai Zheng, Xun Xu
Summary: This paper presents a systematic literature review on the digitalisation and servitisation of machine tools in the context of Industry 4.0. The review provides a comprehensive understanding of recent advancements in this field, including key technologies, methods, standards, architectures, and applications. Additionally, a novel conceptual framework called Cyber-Physical Machine Tool (CPMT) is proposed as a systematic approach to achieving digitalisation and servitisation of next-generation machine tools. The paper also discusses major research issues, challenges, and future research directions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Qiunan Meng, Xun Xu
Summary: In this paper, an incomplete covering rough set method based on object similarity is proposed to derive a cover for attribute reduction. Experimental results show that it outperforms compared rough set in factor selection accuracy and quote prediction with various proportions of missing data.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Zhenyang Gao, Guoying Dong, Yunlong Tang, Yaoyao Fiona Zhao
Summary: This article proposes a machine learning aided design method to generate conformal cooling systems that match the thickness distribution of the part, solving the temperature variance issue. By optimizing the design parameters, the proposed method achieves better temperature control and lower coolant pressure drop compared to conventional designs.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Engineering, Mechanical
Guoquan Chang, Yaohui Wang, Jian He, Yi Xiong
Summary: A generally applicable path planning method is proposed in this study to generate continuous toolpaths for fabricating cellular structures in CFRP-additive manufacturing. The method is based on graph theory and aims to minimize fiber cutting frequency, printing time, and total turning angle. The effectiveness of the method is validated through the fabrication of different types of composite cellular structures, showing a significant improvement compared to existing methods. The fiber cutting frequency, printing time, and total turning angle are reduced up to 88.7%, 52.6%, and 65.5%, respectively.
RAPID PROTOTYPING JOURNAL
(2023)
Article
Engineering, Industrial
Yi Xiong, Yunlong Tang, Samyeon Kim, David W. Rosen
Summary: Recent advancements in additive manufacturing have transformed it from a rapid prototyping tool to a viable production option. The relationships between human-machine in both cyber and physical spaces of additive manufacturing have become diverse and complex. Understanding these relationships in the context of human-cyber-physical systems is crucial for facilitating human-machine collaboration in additive manufacturing application scenarios.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Manufacturing
Tong Liu, Shangqin Yuan, Yaohui Wang, Yi Xiong, Jihong Zhu, Lu Lu, Yunlong Tang
Summary: Continuous fiber composite via additive manufacturing is an emerging field that combines design freedom and digital fabrication. Path planning for continuous fiber allows for tunable and lightweight performance. A wave projection function is proposed to control infill morphology and ratio based on a specific vector field, and mechanical stress field distribution is used to map infill ratio and path orientation. The path planning algorithm solves the traveling salesman problem to generate continuous fiber trajectories with minimized cutting points. The fabricated composite structure outperforms conventional Zig-Zag infill patterns with the same infill ratio. The proposed approach can also be integrated with topology optimized structures for concurrent optimization of infill fiber path and structural configuration.
ADDITIVE MANUFACTURING
(2023)
Article
Materials Science, Composites
Wenhao Li, Wuzhen Huang, Yi Xiong, Limin Zhou, Fei Gao, Jing Lin
Summary: This study investigates the failure mechanism and heat treatment effect of 3D-printed helicoidal composites using the helicoidal laminate stacking configuration found in the dactyl club in Homarus americanus. The results show that the helicoidal composites have higher flexural strength, flexural modulus, and absorbed energy compared to quasi-isotropic composites. Additionally, heat treatment enhances the flexural strength and modulus of the helicoidal specimens by promoting the formation of twisted cracks and inhibiting delamination failure.
COMPOSITES COMMUNICATIONS
(2023)
Article
Materials Science, Composites
Yuan-Fang Zhang, Honggeng Li, Chengyun Long, Yi Xiong, Qi Ge
Summary: The activation method of thermoresponsive materials plays a crucial role in the practical use of smart structures. This study proposes embedding a wavy heater into a thermoresponsive material matrix to create a composite structure with parametrically designed thermal activation behavior. A numerical model is developed to predict heat transfer and experimental validation is conducted. The results show that the wavy design reduces heating time by up to 82% compared to a flat design. Additionally, the stiffness tuning of thermoresponsive composite structures is demonstrated. This work facilitates the application of large-scale thermoresponsive composite structures in aerospace and architecture.
COMPOSITES COMMUNICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Jingchao Jiang
Summary: Thirty years after its development, additive manufacturing has become a mainstream manufacturing process, fabricating products layer-by-layer based on a 3D model. It allows for manufacturing complex parts and offers more design optimization possibilities compared to traditional techniques. Machine learning, a hot technology used in various fields, including medical diagnosis and image processing, is now being increasingly applied in the manufacturing industry, particularly additive manufacturing. This paper provides a comprehensive understanding of the current status of machine learning-enhanced additive manufacturing technologies and discusses future perspectives in a special issue organized by the International Journal of Computer Integrated Manufacturing.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Engineering, Manufacturing
Guoquan Zhang, Yaohui Wang, Ziwen Chen, Xuguang Xu, Ke Dong, Yi Xiong
Summary: The advancements in continuous fibre-reinforced polymer additive manufacturing (CFRP-AM) offer unprecedented opportunities for the development of high-performance composites with selective reinforcement. However, the current limitations in motion configuration hinder the exploration of non-planar fibre layouts. This study presents a novel CFRP-AM system that enables the fabrication of grid-stiffened shell structures with spatial features, improving compression strength and stiffness.
VIRTUAL AND PHYSICAL PROTOTYPING
(2023)
Article
Computer Science, Artificial Intelligence
Zhoumingju Jiang, Yongsheng Ma, Yi Xiong
Summary: This paper presents a bio-inspired generative design framework (BIGD) that automatically produces innovative designs by synthesizing a diverse range of natural designs using deep generative models. The researchers established a computational workflow for automated bio-inspired wing shape synthesis and successfully generated wings with superior lift performance based on biological domain knowledge.
ADVANCED ENGINEERING INFORMATICS
(2023)
Editorial Material
Computer Science, Interdisciplinary Applications
Jingchao Jiang, Bin Zou, Jikai Liu, David Rosen
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Engineering, Industrial
Ahmed Z. Naser, Fantahun Defersha, Xun Xu, Sheng Yang
Summary: This paper explores the feasibility of predictive Life Cycle Assessment (LCA) for Additive Manufacturing (AM) by proposing a data-driven framework that combines Machine Learning (ML) and LCA. The framework is demonstrated through a case study on the Fused Filament Fabrication (FFF) process, achieving high prediction accuracy and good generalizability.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Green & Sustainable Science & Technology
Kun Wang, Jun Cao, Jianhong Gao, Jing Zhao, Wei Jiang, Waqar Ahmad, Jingchao Jiang, Min Ling, Chengdu Liang, Jun Chen
Summary: In this study, a design strategy of inner-outer phosphorus (P) doped hollow spindle-like alpha-Fe2O3 nanoparticles (NPs) was introduced to improve the electroconductivity and buffering volume expansion of low-cost earth-abundant transition metal oxides (TMOs) used as anodes in Li-ion batteries. The results showed that the calcination temperature determined the P contents, and increasing temperature led to the emergence and disappearance of P-Fe3O4/Fe2O3 heterojunctions and the transition of hollow-to-solid structures, thus improving the electrochemical performances, electronic/ionic conductivity, and reaction kinetics. Notably, a 10 wt% P doped Fe2O3 (350 degrees C) anode exhibited remarkable rate capacity and cycle stability, indicating the potential of this design strategy to enhance the electrochemical performance of energy storage devices.
SUSTAINABLE MATERIALS AND TECHNOLOGIES
(2023)
Article
Engineering, Industrial
Kendrik Yan Hong Lim, Theresia Stefanny Yosal, Chun-Hsien Chen, Pai Zheng, Lihui Wang, Xun Xu
Summary: The increasing complexity of industrial systems requires more effective and intelligent maintenance approaches to address manufacturing defects. This paper introduces a cognitive digital twin system that leverages industrial knowledge graphs to support maintenance planning and operations. The system can manage interconnected systems, facilitate cross-domain analysis, and generate feasible solutions validated through simulation. It can also identify potential disruptions in new product designs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
