Article
Engineering, Multidisciplinary
Eric Garner, Jun Wu, Amir A. Zadpoor
Summary: Recent advances in 3D printable micro-architected materials have opened up unprecedented possibilities for highly tailored orthopaedic implants. This study presents computational methods to synthesize patient-specific implants with heterogeneous micro-architecture, aiming to minimize the risks of load-induced interface fracture and post-operative bone remodelling. The optimized implant designs demonstrate significant improvements in bone remodelling and interface fracture risk compared to conventional solid implant designs.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Koji Shimoyama, Atsuki Komiya
Summary: This paper optimizes the design of a lattice-structured heat sink using topology optimization, aiming to maximize thermal performance and minimize material cost. The optimized designs show improved thermal performance compared to a reference fin-structured design.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Automation & Control Systems
Wadea Ameen, Abdulrahman Al-Ahmari, Muneer Khan Mohammed, Husam Kaid
Summary: Electron-beam melting (EBM) is an effective metal additive manufacturing method for producing complex and customized parts. However, challenges arise when dealing with overhang structures without support. This study focused on designing support structures that are easy to remove, consume less material, and do not affect part quality. Multi-objective optimization using a genetic algorithm was employed to minimize support volume and removal time while limiting deformation.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
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
Management
F. Tevhide Altekin, Yossi Bukchin
Summary: This paper addresses the production planning problem in multi-machine additive manufacturing (AM) systems by proposing a unified model that minimizes cost and makespan objectives while considering part and job assignments. Experimental results demonstrate that when identical machines are used, the trade-off between objectives is relatively small; however, when non-identical machines are used, considering both objectives simultaneously becomes important.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Engineering, Mechanical
Konstantin Kappe, Klaus Hoschke, Werner Riedel, Stefan Hiermaier
Summary: This paper presents a multi-objective optimization procedure for effectively designing gradient lattice structures under dynamic loading. The aim is to maximize energy absorption characteristics and achieve a lightweight design. Through considering design variables such as the relative density and density gradient, the peak crushing force reduction and maximized specific energy absorption are simultaneously optimized. A simplified beam-based finite element model is used to efficiently model and simulate the lattice structures. An artificial neural network is trained to predict energy absorbing characteristics and find optimal lattice structure configurations. The network is trained using a multi response adaptive sampling algorithm, allowing parallel simulation with automatically generated finite element models. A multi-objective genetic algorithm is then used to find optimal combinations of design parameters for lattice structures under different impact velocities and cell topologies.
INTERNATIONAL JOURNAL OF IMPACT ENGINEERING
(2024)
Article
Optics
Abhijit Sadhu, Anitesh Kumar Singh, Amit Kumar Das, Dilip Kumar Pratihar, Asimava Roy Choudhury
Summary: This study focuses on the energy and material saving in additive manufacturing. By using a fiber laser and specific techniques, optimized output responses including laser energy efficiency, powder deposition efficiency, and dilution were achieved. The deposited coating showed excellent microstructure and wear performance.
OPTICS AND LASER TECHNOLOGY
(2022)
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
Engineering, Manufacturing
Zhiping Wang, Yicha Zhang, Shujie Tan, Liping Ding, Alain Bernard
Summary: Support structures are crucial for additive manufacturing processes, with the number and position of support points directly impacting the performance and final printing quality. This paper proposes a method to determine support points, optimizing their distribution while ensuring manufacturability, particularly useful for complex structures in medical applications.
ADDITIVE MANUFACTURING
(2021)
Article
Optics
Lanyun Qin, Dongxu Zhao, Wei Wang, Guang Yang
Summary: In this paper, a defect identification and compensation method for laser deposition manufacturing (LDM) is proposed. By utilizing a high-speed laser profiler to collect surface point cloud data and applying various processing techniques, the geometric defects of the LDM part can be successfully detected and controlled, resulting in improved part quality.
OPTICS AND LASER TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Yupeng Han, Hu Peng, Changrong Mei, Lianglin Cao, Changshou Deng, Hui Wang, Zhijian Wu
Summary: This paper proposes a new multistrategy multiobjective differential evolutionary algorithm, RLMMDE, to solve the exploration and exploitation dilemma in multiobjective optimization problems (MOPs). The algorithm utilizes a multistrategy and multicrossover DE optimizer, an adaptive reference point activation mechanism based on RL, and a reference point adaptation method. Experimental results show that RLMMDE outperforms some advanced MOEAs on benchmark test suites and practical mixed-variable optimization problems.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Industrial
Qiao Wu, Naiming Xie, Shaoxiang Zheng, Alain Bernard
Summary: This paper studies cloud-based additive manufacturing, proposes a realistic online scheduling scenario, and constructs a mixed integer linear programming model to solve the 3D printing online scheduling problem. Simulation results show that the proposed algorithm can effectively solve this problem.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Nikolai Gerzen, Thorsten Mertins, Claus B. W. Pedersen
Summary: This paper presents a theoretical framework for constructing novel geometrical constraints in density-based topology optimization. The predefined geometrical dimensionality is enforced locally on the components of the optimized structures by using singular value decomposition of point clouds and relative density design variables. Numerical examples demonstrate the validity of the derived theoretical framework for geometric dimensionality control.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Engineering, Chemical
Wendi Xu, Xianpeng Wang, Qingxin Guo, Xiangman Song, Ren Zhao, Guodong Zhao, Yang Yang, Te Xu, Dakuo He
Summary: Single-objective to multi-objective/many-objective optimization is a new paradigm in evolutionary transfer optimization. Theoretical insights into this area are relatively rare, so we propose a study on the theoretical advances of multi-objective optimization based on a case study of a permutation flow shop scheduling problem.
Article
Materials Science, Multidisciplinary
Ziyad Smoqi, Joshua Toddy, Harold (Scott) Halliday, Jeffrey E. Shield, Prahalada Rao
Summary: The study demonstrates that preheating the substrate and depositing the coating at moderate energy density can reduce cracking, while localized laser-based preheating and moderate energy density can mitigate steep temperature gradients to prevent thermally induced cracking of the Stellite coating in the inter-dendritic regions.
MATERIALS & DESIGN
(2021)
Article
Engineering, Manufacturing
Ruimin Chen, Prahalada Rao, Yan Lu, Edward W. Reutzel, Hui Yang
Summary: Powder bed fusion additive manufacturing offers design flexibility for metal products, but controlling quality becomes challenging with complex designs. This study explores advanced imaging for improved quality control and introduces a novel generalized recurrence network for analyzing the interaction between design parameters and quality characteristics in thin-wall builds. The results demonstrate sensitivity of network features to build orientations, width, height, and contour space, providing insights for optimizing engineering design and enhancing build quality.
ADDITIVE MANUFACTURING
(2021)
Article
Engineering, Manufacturing
Reza Yavari, Richard Williams, Alex Riensche, Paul A. Hooper, Kevin D. Cole, Lars Jacquemetton, Harold (Scott) Halliday, Prahalada Krishna Rao
Summary: LPBF metal additive manufacturing has the potential to overcome traditional manufacturing barriers, but its use is limited by flaws. Predicting thermal history is crucial for flaw prevention.
ADDITIVE MANUFACTURING
(2021)
Review
Materials Science, Multidisciplinary
YubRaj Paudel, Deepesh Giri, Matthew W. Priddy, Christopher D. Barrett, Kaan Inal, Mark A. Tschopp, Hongjoo Rhee, Haitham El Kadiri
Summary: This paper reviews the existing approaches to incorporating twinning in crystal plasticity models, discusses their capabilities, addresses their limitations, and suggests prospective views to fill gaps. The incorporation of a new physics-based twin nucleation criterion in crystal plasticity models holds groundbreaking potential for substantial progress in the field of computational material science.
Review
Materials Science, Biomaterials
Samuel Gerdes, Srikanthan Ramesh, Azadeh Mostafavi, Ali Tamayol, Iris Rivero, Prahalada Rao
Summary: Biological additive manufacturing (Bio-AM) is a promising method for fabricating biological scaffolds with nano- to microscale resolutions and biomimetic architectures beneficial to tissue engineering applications. However, flaws introduced during fabrication can affect mechanical properties and lead to unpredictable biological responses from cells interacting with the defective scaffolds.
ACS BIOMATERIALS SCIENCE & ENGINEERING
(2021)
Article
Materials Science, Multidisciplinary
Reza Yavari, Ziyad Smoqi, Alex Riensche, Ben Bevans, Humaun Kobir, Heimdall Mendoza, Hyeyun Song, Kevin Cole, Prahalada Rao
Summary: The graph theory approach can predict flaw formation in LPBF based on the thermal history trends within a fraction of build time with accurate results, providing rapid guidance for part design and processing parameter selection.
MATERIALS & DESIGN
(2021)
Article
Thermodynamics
Kevin D. Cole, Alex Riensche, Prahalada K. Rao
Summary: This work introduces a method for solving the heat equation using the spectral graph method, which is applicable to temperature defined at discrete points and described by a graph. The method utilizes eigenvectors and eigenvalues to solve the heat equation on the graph, eliminating the need for computationally intensive procedures in the finite element method. The method is extended to include boundary heat loss and physics-based edge weights, and a discrete Green's function is introduced for solutions under various heating conditions. The accuracy of the method is validated through comparison with analytical solutions and finite difference solutions.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2022)
Article
Nanoscience & Nanotechnology
Joseph Messina, Renjie Luo, Ke Xu, Guanghong Lu, Huiqiu Deng, Mark A. Tschopp, Fei Gao
Summary: Magnesium alloys have advantages in applications due to their high strength-to-weight ratio, but properties like corrosion resistance, formability, and creep are still concerns, especially in magnesium-aluminum alloys. This study quantifies aluminum segregation energetics at grain boundaries using atomistic simulations, showing that the segregation of aluminum is influenced by grain boundary structure and the local atomic environment, which has broad implications for grain boundary science and engineering.
SCRIPTA MATERIALIA
(2021)
Article
Materials Science, Multidisciplinary
R. Yavari, A. Riensche, E. Tekerek, L. Jacquemetton, H. Halliday, M. Vandever, A. Tenequer, V Perumal, A. Kontsos, Z. Smoqi, K. Cole, P. Rao
Summary: The research aims to develop a strategy for real-time monitoring of defect formation in metal parts, exploring flaw formation mechanisms in LPBF manufacturing and the application of digital twin methods.
MATERIALS & DESIGN
(2021)
Article
Materials Science, Multidisciplinary
Ziyad Smoqi, Benjamin D. Bevans, Aniruddha Gaikwad, James Craig, Alan Abul-Haj, Brent Roeder, Bill Macy, Jeffrey E. Shield, Prahalada Rao
Summary: The objective of this study is to reduce flaw formation in powder and laser-based additive manufacturing process by controlling the meltpool temperature through closed-loop control. The results demonstrate that parts built under closed-loop control have reduced porosity variation and consistent microstructure compared to parts built under open-loop conditions.
MATERIALS & DESIGN
(2022)
Article
Engineering, Manufacturing
Andre Ramalho, Telmo G. Santos, Ben Bevans, Ziyad Smoqi, Prahalad Rao, J. P. Oliveira
Summary: This study aims to investigate the effects of different contaminations on the acoustic spectrum of WAAM and lay the foundations for a microphone-based acoustic sensing approach for monitoring the quality of WAAM-fabricated parts. By analyzing the acoustic signals, the location of flaw formation can be accurately identified.
ADDITIVE MANUFACTURING
(2022)
Article
Business
Mahdi Fathi, Mohammad Marufuzzaman, Randy K. Buchanan, Christina H. Rinaudo, Kayla M. Houte, Linkan Bian
Summary: Society 5.0 is an advanced society based on big data, artificial intelligence, sensors, and robots to improve various aspects of life in a smart city. This article focuses on the role of sensors in Society 5.0 and proposes a competitive sensor network model that considers the service price and location on a secured grid area. A bi-level nonlinear program is developed to maximize revenue and social benefits while minimizing wait time and damage cost. The model is validated through an illustrative example.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Review
Computer Science, Information Systems
Somayeh Bakhtiari Ramezani, Logan Cummins, Brad Killen, Richard Carley, Amin Amirlatifi, Shahram Rahimi, Maria Seale, Linkan Bian
Summary: Early detection and timely maintenance scheduling can minimize risk and improve the lifespan, reliability, and availability of a system. Two main data-driven approaches, direct calculation and indirect analysis, are used to determine the Remaining Useful Life (RUL) in predictive maintenance. This study reviews the state-of-the-art data-driven methods for RUL prediction, discussing their capabilities, scalability, performance, weaknesses, current challenges, and future directions.
Article
Automation & Control Systems
Seyyed Hadi Seifi, Aref Yadollahi, Wenmeng Tian, Haley Doude, Vincent H. Hammond, Linkan Bian
Summary: The study focuses on evaluating fatigue performance directly from the process signature of laser-based additive manufacturing processes, proposing a novel two-phase modeling methodology. In Phase (I), a convolutional neural network is used to detect the relative size of defects, while Phase (II) incorporates defect characteristics to build a fatigue-life prediction model. Estimating defect characteristics from the in situ thermal history facilitates the fatigue predicting process.
ADVANCED INTELLIGENT SYSTEMS
(2021)
Article
Engineering, Manufacturing
Roozbeh (Ross) Salary, Jack P. Lombardi, Darshana L. Weerawarne, Prahalada Rao, Mark D. Poliks
Summary: Aerosol jet printing is a high-resolution additive manufacturing technique for electronic devices, but the process is unstable and requires a physics-based model for control.
JOURNAL OF MICRO AND NANO-MANUFACTURING
(2021)