Article
Green & Sustainable Science & Technology
Jiayao Liu, Linfeng Wang, Yunsheng Wang, Shipu Xu, Yong Liu
Summary: A digital twin system is a virtual system that provides a comprehensive description of a real physical system. It receives data from physical sensors and user input and provides feedback to the physical system. This emerging technology connects different objects through the Internet of Things and is in high demand in various industries, with research literature growing exponentially.
Article
Computer Science, Artificial Intelligence
Ankush Manocha, Yasir Afaq, Munish Bhatia
Summary: Since the development of smart healthcare services, different solutions, such as combining IoT, DT, FoT, CoT, and Blockchain, have been developed to increase patient's life expectancy by reducing healthcare cost. The proposed smart context-aware physical activity monitoring framework employs deep learning to analyze the physical movements of the elderly and detect irregular physical events in real time. Moreover, the framework ensures data security using advanced features of blockchain and demonstrates the effectiveness of DT in smart healthcare solutions. The proposed methodology's performance is evaluated in terms of event recognition, model training and testing, latency rate, and data processing cost.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Automation & Control Systems
Shaopeng Hu, Zhiwu Li
Summary: This paper addresses the problem of fault diagnosis and diagnosability enforcement of discrete event systems. By establishing a digital twin system as a special Petri net, the diagnosability of the original system is achieved, and necessary and sufficient conditions for diagnosability enforcement are provided.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Business
Meltem Kiygi-Calli, Marcel Weverbergh, Philip Hans Franses
Summary: This study examines the impact of advertising on a national call center's performance, forecasting the number of incoming calls and simulating service processes to show that advertising may lead to temporary overload and increased abandoned calls, affecting the center's efficiency.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Giovanni Lugaresi, Andrea Matta
Summary: Industry 4.0 has brought forth technologies that enable data-driven production planning and control. Digital twins, utilized for decision making based on the current state of manufacturing systems, depend on accurately representing the physical counterpart. Automating model generation through process mining can speed up the development of digital twins, but traditional techniques struggle with complex production environments. This paper proposes object-centric process mining and an algorithm for generating accurate digital models of manufacturing systems with complex material flows, and it has been successfully tested on real systems.
COMPUTERS IN INDUSTRY
(2023)
Article
Management
Rafael da Costa Jahara, Marcos Pereira Estellita Lins
Summary: This paper presents a multimethodology approach that combines qualitative and quantitative modeling to improve the performance of production processes in the prosthetics and orthotics industry. By using knowledge mapping and discrete-event simulation model, an alternative improvement scenario for orthotics manufacturing was developed and validated through effective intervention, resulting in increased production capacity and reduced manufacturing lead time.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Hongbin Qiu, Yong Chen, Huaxiang Zhang, Wenchao Yi, Yingde Li
Summary: Digital twin models combine physical simulation and data-driven simulation methods. This study develops an evolutionary digital twin workshop model by incorporating reinforcement learning, and verifies its effectiveness and performance.
APPLIED INTELLIGENCE
(2023)
Article
Public, Environmental & Occupational Health
Liau Zi Qiang Glen, Joel Yat Seng Wong, Wei Xuan Tay, Jiayi Weng, Gregory Cox, Andre Eu Jin Cheah
Summary: This study analyzes the correlation between the incidence rate of hand injuries and various major economic indicators in Singapore. The findings show that quarterly economic indicators from major economic industries can be used to predict the incidence of hand injuries with a 62.3% correlation. These findings are important for anticipating healthcare resource allocation to treat hand injuries.
JOURNAL OF OCCUPATIONAL MEDICINE AND TOXICOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Hao Wang, Tao Liu, Zhongyang Yu
Summary: This study aims to enhance the application efficiency of modern science and technology in farm operation, predict farm supply and demand using machine learning and blockchain technology, and contribute to the integrated management and sustainable development of enterprises.
Article
Computer Science, Artificial Intelligence
Navid Parvini, Mahsa Abdollahi, Sattar Seifollahi, Davood Ahmadian
Summary: Investigating different predictors for Bitcoin price forecasting, this study proposes a two-stage forecasting method and analyzes the profitability of the predictors through simulated trading experiments. The results show that Gold and Oil have the highest statistical accuracy in predicting Bitcoin returns, while S&P500 is the most profitable predictor.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Industrial
Haifan Jiang, Shengfeng Qin, Jianlin Fu, Jian Zhang, Guofu Ding
Summary: Digital twin is a virtual mirror of a physical world or system, serving as a key building block for smart factory and manufacturing under the Industry 4.0 paradigm. The key research question is how to effectively create a DT model during the design stage of a complex manufacturing system and make it usable throughout the system’s lifecycle. Modeling methods for rapidly creating a virtual model and the connection implementation mechanism between physical and virtual systems are crucial for achieving these goals.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Energy & Fuels
Chuantao Yao, Jian Wang, Hao Sun, Haiyang Chu, Tao Jin, Quanzhou Xiang
Summary: This study investigates the issue of fog computing in handling applications that require a lot of calculations in wireless IoT networks, while allocating computing and communication resources and maintaining QoS standards. The research proposes the deployment of NOMA for IoT networks to enable multiple devices to simultaneously transmit information to fog computing nodes (FNs) in a similar frequency range, optimizing resource allocation and transmission power while meeting QoS standards. The suggested architecture performs well in terms of throughput, delays, blackout likelihood, and power usage according to simulation outcomes.
Article
Automation & Control Systems
Andrew Eyring, Nathan Hoyt, Joe Tenny, Reuben Domike, Yuri Hovanski
Summary: With advancements in technology and smart manufacturing, the use of digital twins in factories and processes is becoming more common and useful. By combining discrete event simulation and live data, digital twins can provide more accurate predictions of future performance and issues, leading to smarter decision-making and implementation of solutions.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Shanshan Duan, Weidong Yang, Xuyu Wang, Shiwen Mao, Yuan Zhang
Summary: The proposed encoder-decoder model with attention mechanism accurately predicts the temperature of stored grain by extracting local and global features, combining meteorological factors for decoding and future temperature prediction. Results show that the model outperforms other schemes in forecasting grain temperature.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Management
Muhammed Ordu, Eren Demir, Chris Tofallis, Murat M. Gunal
Summary: The healthcare system in the UK is under increasing pressure, necessitating the need to optimize existing resources without additional funding. Detailed modeling is required to analyze demand and capacity shortages across all specialties and services, providing decision support tools for key stakeholders to make rational and realistic plans.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
Article
Engineering, Multidisciplinary
S. L. J. Millen, S. Ashworth, C. Farrell, A. Murphy
Summary: The study investigated the impact of heating rate on thermal damage predictions during lightning strikes through experimental and simulation analysis. It was found that using maximum heating rate extrapolation improved prediction accuracy, reducing errors in predicted severe damage area to within 8% of experimental values.
COMPOSITES PART B-ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Mahdi Damghani, Stephan Bolanos, Amandeep Chahar, Jason Matthews, Gary A. Atkinson, Adrian Murphy, Timothy Edwards
Summary: The study proposes a Variable Length Stepped Scarf (VLSS) scheme for highly loaded composite structures, which minimizes healthy material removal. Experimental and simulation investigations show that the VLSS scheme is comparable in restoring structural stiffness, but falls short in restoring static strength compared to other repair designs.
COMPOSITES PART B-ENGINEERING
(2022)
Article
Engineering, Industrial
Rao Fu, Patrick Curley, Colm Higgins, Zekai Murat Kilic, Dan Sun, Adrian Murphy, Yan Jin
Summary: This study introduces a novel concept of collaborative machining using dual PKMs to mill thin-walled parts with double-sided features, showing significantly improved static and dynamic performances of the workpiece. The double-sided synchronized milling strategy by dual collaborative PKMs achieved the best dimensional accuracy, surface quality, and double productivity compared to conventional single-sided machining.
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
(2022)
Article
Engineering, Civil
Damian Quinn, Adrian Murphy, Cara Harley, Trevor T. Robinson, Declan Nolan
Summary: This study systematically explores the performance changes of composite stiffened plates under low velocity impact and Compression After Impact loading, revealing that plate aspect ratio and boundary conditions have a significant impact on impact response and residual strength. The study demonstrates that increasing edge restraint for plates of different aspect ratios results in varying changes in residual strength.
THIN-WALLED STRUCTURES
(2022)
Article
Computer Science, Interdisciplinary Applications
Lauren McGarry, Joseph Butterfield, Adrian Murphy
Summary: There is a growing demand for industrial robots to perform high tolerance operations in line with Industry 4.0 requirements, especially in complex aerospace assembly. Existing standards lack specific guidance for determining robot accuracy, leading to researchers using customized methods for RBF determination. This study proposes a new approach that integrates metrology hardware and Design of Experiments to improve repeatability in establishing the RBF origin point.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Interdisciplinary Applications
T. Shannon, T. T. Robinson, A. Murphy, C. G. Armstrong
Summary: This paper presents the development of generalized Bezier components in the Moving Morphable Components optimization framework and discusses methods for enhancing component parameterization. By using control points and Bezier curves to represent structural components, the shape flexibility and parameterization compatibility with commercial CAD packages are achieved. The paper also includes methods for calculating analytical derivatives and numerical examples to demonstrate the integration of these structural components in the optimization framework.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2022)
Article
Computer Science, Interdisciplinary Applications
S. Li, J. Butterfield, A. Murphy
Summary: The aim of this work is to develop a self-adapting digital toolset for manufacturing planning that focuses on minimally constrained assembly line balancing. The approach involves determining the optimal number of workstations, cycle time, and task assignments through a bespoke genetic algorithm. The proposed algorithm consistently outperforms previous studies in terms of convergence time and solution quality, delivering detailed production plans for the simple assembly line balancing problem with minimal inputs.
JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING
(2023)
Article
Engineering, Civil
Mahdi Damghani, Rakib Ali Pir, Adrian Murphy, Mohammad Fotouhi
Summary: This study investigates the collapse behavior of laminates with cut-outs under shear loading, focusing on the influence of laminate shapes and hybridization on their post-buckling response. Experimental and numerical analysis show that a hybrid laminate design with shaped CFRP plies exhibits greater failure load and failure load to buckling load ratio compared to a pure CFRP design, despite having less CFRP material. However, the hybrid design has a slightly lower initial plate buckling load and endures more widespread shear damage of the matrix.
THIN-WALLED STRUCTURES
(2022)
Article
Materials Science, Composites
Xiaodong Xu, Scott L. J. Millen, Juhyeong Lee, Gasser Abdelal, Daniel Mitchard, Michael R. Wisnom, Adrian Murphy
Summary: Research on residual strength after lightning strike is increasing, but there are currently no standard test methods for measuring residual compressive strength. A systematic experimental study was conducted to evaluate modifications in specimen geometry and test jig design to induce specimen failure at the lightning damage region. Test set-up modifications were made considering the scale of the lightning damage. The Compression After Lightning (CAL) strength was significantly lower than the pristine CAI strength even at a relatively low peak current of 25 kA, indicating the need for careful modifications.
APPLIED COMPOSITE MATERIALS
(2023)
Article
Mechanics
Mahdi Damghani, John Saddler, Ethan Sammon, Gary A. Atkinson, Jason Matthews, Adrian Murphy
Summary: This paper investigates the effect of transverse impact loading on the in-plane shear behaviour of two laminate configurations. The results show that the use of glass plies in the laminate can reduce the damage caused by impact loading.
COMPOSITE STRUCTURES
(2023)
Article
Engineering, Civil
Mahdi Damghani, Jason Matthews, Adrian Murphy, Carol Featherston
Summary: The shape, thickness, and stacking sequence of a damage tolerant hybrid (GFRP-CFRP) composite laminate were optimized using the Optistruct solver. The optimized laminate was compared to a non-damage tolerant CFRP laminate and a traditionally optimized hybrid CFRP-GFRP laminate designed in a previous study. Experimental testing showed that the optimized hybrid laminate had higher pre-buckling stiffness but lower buckling and failure loads than predicted numerically. This can be attributed to geometric imperfections and stress concentration effects in the hybrid laminate design.
Article
Engineering, Aerospace
Scott Millen, Vipin Kumar, Adrian Murphy
Summary: This study examines the impact of carbon fiber composite specimen design parameters and electrical boundary conditions on the dissipation of current and the spread of damage. The distance to ground is found to be the controlling factor for current dissipation. Specimen dimensions and boundary conditions have an influence on current distribution and damage, but this influence can be limited by choosing an appropriate specimen size.
SAE INTERNATIONAL JOURNAL OF AEROSPACE
(2023)
Article
Engineering, Manufacturing
S. L. J. Millen, X. Xu, J. Lee, S. Mukhopadhyay, M. R. Wisnom, A. Murphy
Summary: This study proposes a novel integrated modelling framework to predict the residual compressive strength of carbon/epoxy composites after a lightning strike. The framework combines thermal-electric and thermo-mechanical models with Compression After Lightning Strike (CAL) analyses, taking into account both thermal and mechanical lightning strike damage. Experimental validation confirms the accuracy of the predicted lightning damage, which is then mapped to a compression model using python scripts.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Moustafa Faheem, Adrian Murphy, Vishal Sharma, Carlos Reano
Summary: This study investigates the relationship between performance, energy, and TCO in discrete event simulations for manufacturing factories. The findings suggest that high-resource edge devices are the most suitable hardware choice, achieving the best balance in terms of performance, energy efficiency, and TCO.
2022 IEEE INTL CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, BIG DATA & CLOUD COMPUTING, SUSTAINABLE COMPUTING & COMMUNICATIONS, SOCIAL COMPUTING & NETWORKING, ISPA/BDCLOUD/SOCIALCOM/SUSTAINCOM
(2022)
Proceedings Paper
Materials Science, Multidisciplinary
John McClelland, Adrian Murphy, Yan Jin, Saurav Goel
Summary: Drilling holes in CFRP assemblies is crucial in aerospace manufacturing, but tool wear remains a significant problem. This study proposes a new method to calculate the idealized number of abrasive contacts and conducts systematic experiments to investigate the influence of abrasive contacts on tool wear. The results reveal a consistent waterfall wear shape and show that wear is focused on the flank face. Furthermore, the study finds that tool wear increases with drilled depth and drilling contact time, independent of drilling speed and feed.
MATERIALS TODAY-PROCEEDINGS
(2022)
Article
Computer Science, Interdisciplinary Applications
Shenglin Wang, Jingqiong Zhang, Peng Wang, James Law, Radu Calinescu, Lyudmila Mihaylova
Summary: In Industry 5.0, Digital Twins provide flexibility and efficiency for smart manufacturing. Deep learning techniques are used to enhance the Digital Twin framework, enabling the detection and classification of human operators and robots during the manufacturing process. The framework shows promising results in accurately detecting and classifying actions of human operators and robots in various scenarios.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yi Liu, Junpeng Qiu, Jincheng Wang, Junhe Lian, Zeran Hou, Junying Min
Summary: In this study, a double-sided robotic roller forming process was developed to form ultrahigh strength steels to thin-walled profiles. Synchronized laser heating and iterative path compensation method were used to reduce forming forces and achieve high-precision forming.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zequn Zhang, Yuchen Ji, Dunbing Tang, Jie Chen, Changchun Liu
Summary: This paper proposes a digital twin system for human-robot collaboration (HRC) that overcomes the limitations of current methods and improves the overall performance. The system includes a human mesh recovery algorithm and uncertainty estimation to enhance the system's capabilities. Experimental results demonstrate the superiority of the proposed methods over baseline methods. The feasibility and effectiveness of the HRC system are validated through a case study involving component assembly.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Junmin Park, Taehoon Kim, Chengyan Gu, Yun Kang, Joono Cheong
Summary: This paper proposes a highly reliable and accurate collision estimator for robot manipulators in human-robot collaborative environments using the Bayesian approach. By assuming robot collisions as dynamic Markov processes, the estimator can integrate prior beliefs and measurements to produce current beliefs in a recursive form. The method achieves compelling performance in collision estimation with high accuracy and no false alarms.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Meng Wang, Kaixuan Chen, Panfeng Wang, Yimin Song, Tao Sun
Summary: In this study, a novel teleoperation machining mode and control strategy were proposed to improve efficiency and accuracy in small batch production of large casting parts. By using variable motion mapping and elastic compensation, constant cutting force was achieved, and the workpiece was protected by employing forbidden virtual fixtures and movement constraints on the slave robot.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhaoyu Li, Dong He, Xiangyu Li, Xiaoke Deng, Pengcheng Hu, Jiancheng Hao, Yue Hou, Hongyu Yu, Kai Tang
Summary: This paper presents a novel algorithm for planning a five-axis inspection path for arbitrary freeform surfaces. By converting the inspection path planning problem into a set-covering problem, the algorithm generates a near-minimum set of inspection paths that satisfy necessary constraints. Both computer simulation and physical inspection experiments confirm the effectiveness and advantages of the proposed method.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper introduces a novel framework based on deep reinforcement learning for generating machining process routes for designated parts. The framework utilizes graph representations of parts and employs convolutional graph neural networks for effective processing. Experimental results demonstrate the ability of the proposed method to generate efficient machining process routes and overcome limitations of traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Regina Kyung-Jin Lee, Hao Zheng, Yuqian Lu
Summary: Future manufacturing will witness a shift towards collaboration and compassion in human-robot relationships. To enable seamless knowledge transfer, a unified knowledge representation system that can be shared by humans and robots is essential. The Human-Robot Shared Assembly Taxonomy (HR-SAT) proposed in this study allows comprehensive assembly tasks to be represented as a knowledge graph that is understandable by both humans and robots. HR-SAT incorporates rich assembly information and has diverse applications in process planning, quality checking, and human-robot collaboration.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Jianhui He, Lefeng Gu, Guilin Yang, Yiyang Feng, Silu Chen, Zaojun Fang
Summary: This paper presents a new modular kinematic error model for collaborative robots and proposes a portable self-calibration device to improve their positioning accuracy.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hongwei Sun, Jixiang Yang, Han Ding
Summary: This paper proposes an asymmetrical FIR filter-based tool path smoothing algorithm to fully utilize the joint drive capability of robot manipulators. The algorithm considers the pose-dependent dynamics and constraints of the robot and improves motion efficiency by over 10% compared to traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Dongsheng Ge, Huan Zhao, Yiwei Wang, Dianxi Li, Xiangfei Li, Han Ding
Summary: This paper focuses on learning a stable force control policy from human demonstration during contact transients. Based on the analysis of human demonstration data, a novel human-inspired force control strategy called compliant dynamical system (CDS) is proposed. The effectiveness of the proposed method is validated through simulation and real-world experiments.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Xuepeng Huang, Zhenzhong Wang, Lucheng Li, Qi Luo
Summary: This study models the stiffness of a robot and modifies the tool influence function (TIF) with the Preston equation in order to achieve uniform surface quality in robotic bonnet polishing (RBP) of optical components. Experimental results validate the accuracy of the modified model.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Mario D. Fiore, Felix Allmendinger, Ciro Natale
Summary: This paper presents a constraint-based programming framework for task specification and motion optimization. The framework can handle constraints on robot joint and Cartesian coordinates, as well as time dependency. It also compares with existing methods and provides numerical support through illustrative examples and case studies.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yongxue Chen, Yaoan Lu, Ye Ding
Summary: This paper presents an optimization method for directly generating a six-degree-of-freedom toolpath for robotic flank milling. By optimizing the smoothness of the toolpath and the stiffness of the robot, the efficiency, accuracy, and finish of the machining are improved.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Chungang Zhuang, Haoyu Wang, Han Ding
Summary: This article proposes an end-to-end pipeline for synchronously regressing potential object poses from an unsegmented point cloud. It extracts point pair features and uses a voting architecture for instance feature extraction, along with a 3D heatmap for clustering votes and generating center seeds. An attention voting module is also employed to adaptively fuse point-wise features into instance-wise features. The network demonstrates robustness and improved performance in pose estimation.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
