Article
Energy & Fuels
Liu Zhang, Kaitian Zhang, Zhong Zheng, Yi Chai, Xiaoyuan Lian, Kai Zhang, Zhaojun Xu, Sujun Chen
Summary: This research proposes an integrated scheduling model that allows for flexible interaction between oxygen distribution and steelmaking-continuous casting. By considering the probability information of demand uncertainty, the model shows superior performance in cost reduction and uncertainty risk compared to recent methods.
Article
Energy & Fuels
Sheng-Long Jiang, Gongzhuang Peng, I. David L. Bogle, Zhong Zheng
Summary: The study developed an optimal oxygen distribution strategy considering uncertain demands and proposed a two-stage robust optimization model to address the balance issue in energy management. The results show that the model is well adapted to solving industrial cases under uncertainty.
Article
Computer Science, Information Systems
Haiping Ma, Haoyu Wei, Ye Tian, Ran Cheng, Xingyi Zhang
Summary: Constrained multi-objective optimization problems are challenging to handle due to the complexities of objectives and constraints. To address this issue, a multi-stage evolutionary algorithm is proposed in this paper, which gradually adds constraints and sorts their handling priority based on their impact on the Pareto front. Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art algorithms in dealing with complex constraint problems.
INFORMATION SCIENCES
(2021)
Article
Operations Research & Management Science
Hongming Zhou, Sufen Wang, Faqun Qi, Shun Gao
Summary: This paper describes an optimal preventive maintenance policy and optimization method for operation parameters of a production line consisting of multiple execution units. By establishing the relationship between the reliability and operating parameters of the execution unit, as well as the relationship between the operating parameters and maintenance cost, the objective of minimizing maintenance cost and maintaining effective operating speed is achieved through a heuristic algorithm to derive the optimal parameters. Finally, a numerical example and simulation experiments are presented to validate the effectiveness of the proposed method.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Management
Marc Goerigk, Stefan Lendl, Lasse Wulf
Summary: This study focuses on two-stage robust optimization problems as games between a decision maker and an adversary. By adding an extra adversary stage, the study extends the problem into min-max-min-max problems, advancing from two-stage settings towards more general multi-stage problems. The study specifically examines budgeted uncertainty sets and explores both continuous and discrete cases.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Shan Ren, Lichun Shi, Yang Liu, Weihua Cai, Yingfeng Zhang
Summary: This study proposes a personalized maintenance approach (POMA-CP) to improve the accuracy and applicability of maintenance schemes for industrial products by establishing a refined maintenance model. The approach includes a multi-level case library, dynamic equipment portrait model, and case-pushing mechanism. Through this approach, active pushing of the best similar cases and automatic generation of service schemes can be achieved, resulting in higher accuracy and applicability for maintenance schemes.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Green & Sustainable Science & Technology
Gaurav Shukla, Jeng Shiun Lim, Nitin Dutt Chaturvedi
Summary: Pipelines are efficient and secure for transporting various products, but uncertainties in parameters can reduce the efficiency of gas allocation networks. This paper proposes a two-stage stochastic programming approach to deal with discrete uncertainties and lower investment costs.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Information Systems
Ebenezer Fiifi Emire Atta Mills, Siegfried Kafui Anyomi
Summary: This paper proposes a hybrid two-stage robustness approach for portfolio construction that evaluates the efficiency of candidate stocks using a dynamic slack-based measure data envelopment analysis model and determines optimal weights using a robust mean-variance-Entropic Value-at-Risk model. The method reduces computational complexity, increases robustness, and provides a comprehensive evaluation of stocks under different financial decisions.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Social Sciences, Interdisciplinary
Chunliu Zhou, Shan Ye, Hongjun Wang, Jianhua Cao, Zhenhua Gao
Summary: This paper proposes the use of mass customization thinking to improve the efficiency of maintenance activities for complex equipment. By dividing the product/service into mandatory and optional modules, multiple optional maintenance service solutions can be formed, and configuration optimization is used to find the most satisfied maintenance solution.
Article
Computer Science, Artificial Intelligence
Zhen Wang, Qianwang Deng, Like Zhang, Haiqiu Li, Fengyuan Li
Summary: This paper proposes a collaborative optimization problem of spare parts production and worker arrangement driven by O&M. An improved Non-dominated Sorting Genetic Algorithm-II (INSGA-II) is used to solve the mixed integer programming model, which considers the production of spare parts and the limited number of workers. Extensive experiments validate the effectiveness of INSGA-II.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Shenyinying Tu, Andreas Wachter, Ermin Wei
Summary: This paper proposes a scalable decomposition approach for solving the AC-OPF problem, utilizing a small amount of communication between the master and subnetworks, as well as a smoothing technique and barrier problem formulation to achieve fast solutions. The framework allows for parallel processing of subnetworks and has convergence guarantees, with the ability to solve instances with over 11 million buses.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Mechanics
Sergey Shevtsov, Igor Zhilyaev, Shun-Hsyung Chang, Jiing-Kae Wu, Natalia Snezhina, Jyun-Ping Huang
Summary: The technology of polymer composites production based on vacuum infusion has gained popularity for its simplicity and low cost equipment. However, industrial use requires extensive trial tests to ensure stable quality, prompting the need for computer modeling systems to accurately describe the dynamic infusion process. The use of phase field equations and postprocessing software modules have been shown to improve accuracy in determining resin front shape and dry spot localization, ensuring repeatability and quality in manufacturing composite parts.
COMPOSITE STRUCTURES
(2021)
Article
Computer Science, Artificial Intelligence
Jun Liu, Yanmin Liu, Huayao Han, Xianzi Zhang, Xiaoli Shu, Fei Chen
Summary: In this paper, a two-stage maintenance and multi-strategy selection algorithm for multi-objective particle swarm optimization (TMMOPSO) is proposed, which enhances the global exploration and local exploitation abilities of the population. By using hyper-cone domain and aggregation, the algorithm adaptively selects the global best and updates the personal best. Additionally, the algorithm perturbs excellent particles and uses a two-stage maintenance strategy for the external archive, improving the solution quality and convergence speed of the population. Experimental results show that TMMOPSO outperforms other comparison algorithms on most benchmark problems.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Energy & Fuels
Ke Li, Fan Yang, Lupan Wang, Yi Yan, Haiyang Wang, Chenghui Zhang
Summary: This paper proposes a two-stage stochastic optimization approach based on scenario analysis for the efficient operation of multi-energy microgrids. By fitting forecast errors using mixed distribution and conditional distribution, and reducing scenarios using an improved K-means clustering algorithm, the approach can flexibly deal with uncertainty in MEMG operations.
Article
Engineering, Industrial
Yilan Shen, Xi Zhang, Leyuan Shi
Summary: In this study, the interaction between production scheduling and maintenance in a hybrid production system is considered. A model is formulated by introducing stochastic and workload ratio degradation, and the actual job completion time and maintenance costs can be determined based on the degradation status of each machine. An opportunistic maintenance strategy and an adaptive random-key genetic algorithm are proposed and validated through numerical studies.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Business
Huatao Peng, Yuming Chang, Yang Liu
Summary: This study finds that serial entrepreneurs who take more risks tend to have higher entrepreneurial performance, based on an analysis of 588 listed serial entrepreneurial companies in China. The influence of risk preference on performance is strengthened for serial entrepreneurs with relevant industry experience, but weakened for those with rich entrepreneurial experience.
ASIA PACIFIC BUSINESS REVIEW
(2023)
Article
Engineering, Industrial
Wei Qin, Zilong Zhuang, Yanning Sun, Yang Liu, Miying Yang
Summary: This study investigates a push-pull based available-to-promise (ATP) problem and proposes a dynamic resource reservation policy to maximize the total profit. A corresponding push-pull based stochastic ATP model is established with known independent demand distributions. Simulation experiments reveal the impact of key factors and provide theoretical guidance and implementation methods for companies to maximize overall profits.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Wenke Wang, Kang Li, Yang Liu, Jiayao Lian, Shu Hong
Summary: The Tibetan area of Sichuan Province serves as a green shelter for national ecological security, and the development of green agriculture is crucial for protecting the environment. By utilizing a system dynamics model, this paper examines the impact of population and investment policies on agricultural economic benefits. The simulation results show that population policy and investment policy have significant effects on improving agricultural economic benefits. Furthermore, green policies play a critical role in enhancing the ecological benefits of agriculture. The paper concludes with specific recommendations for government investment, ecological environment protection, and agricultural market promotion. It is expected that this system dynamics model and suggestions will contribute to the green development of agriculture not only in the Sichuan Tibetan area but also in other regions.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Energy & Fuels
Shuaiyin Ma, Wei Ding, Yang Liu, Shan Ren, Haidong Yang
Summary: This study proposes a sustainable smart manufacturing strategy based on information management systems for energy-intensive industries (EIIs) by considering both digital twin and big data technologies. The integration of digital twin and big data enables key technologies for data acquisition, prediction, mining, and real-time control. Two case studies demonstrate the effectiveness of the strategy, achieving energy saving and cost reduction goals, and reducing environmental protection costs.
Article
Green & Sustainable Science & Technology
Abhishek Mojumder, Amol Singh, Ashwani Kumar, Yang Liu
Summary: This study aims to identify and analyze the critical barriers to green procurement adoption in the Indian construction sector and develop solutions. Through questionnaire surveys and data analysis, the study identifies the impact and criticality of the barriers, and then uses the fuzzy best-worst method to determine the most significant barriers and propose solutions for Indian construction companies and the government.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Xizhao Zhang, Xu Hao, Yang Liu, Rui Wu, Xiaonian Shan, Shunxi Li
Summary: Reducing carbon emissions from trucks is crucial for achieving the carbon peak in road freight. This study analyzes the total greenhouse gas emissions of China's road freight under different scenarios and predicts the truck population from 2021 to 2035. The results show that a combination of clean trucks and low carbon energy transition can effectively reduce emissions and achieve the carbon peak.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Xing Bao, Wei Wei, Yang Liu
Summary: This research examines the challenges faced by a ventilator remanufacturer during the COVID-19 pandemic and provides insights to improve remanufacturing performance. Mathematical models and numerical studies are used to analyze the behavior of the remanufacturing process and derive optimal lead times.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Green & Sustainable Science & Technology
Cejun Cao, Yuting Xie, Yang Liu, Jiahui Liu, Fanshun Zhang
Summary: A safe and effective medical waste transport network is crucial for controlling the COVID-19 pandemic and slowing down the spread of the virus. This paper focuses on a two-phase COVID-19 medical waste transport with multi-type vehicle selection, sustainability, and infection probability. Through a mixed-integer programming model, the study aims to minimize infection risks, environmental risks, and maximize economic benefits. The results highlight the importance of considering sustainable objectives and infection probability in designing a COVID-19 medical waste transport network.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Jin Wang, Yang Liu, Shan Ren, Chuang Wang, Shuaiyin Ma
Summary: This paper proposes a real-time digital twin flexible job shop scheduling method with edge computing to address the issue of abnormal disturbances in production. It presents an overall framework for real-time scheduling and utilizes an improved Hungarian algorithm to obtain the optimal result. The method effectively deals with unexpected disruptions in the production process.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Engineering, Civil
Wenke Wang, Xinlin Guo, Yang Liu, Aomei Tang, Qin Yang
Summary: This study constructed a conceptual model of unsafe behaviors in UAV flight based on the Swiss cheese model and investigated the influence mechanism of these behaviors using social network analysis. The findings showed that unreasonable safety management structure and weak supervision were major factors contributing to unsafe UAV flight. It is recommended to eliminate critical unsafe behaviors in UAV supervision to improve flight safety.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Environmental Studies
Md. Bokhtiar Hasan, Md. Sumon Ali, Gazi Salah Uddin, Masnun Al Mahi, Yang Liu, Donghyun Park
Summary: The sustainability of Bangladesh's recent economic progress depends on how it addresses environmental challenges. The study finds that increasing renewable energy consumption significantly boosts economic growth and improves environmental quality, while non-renewable energy consumption worsens environmental deterioration. Additionally, the policy measures in Bangladesh have limited effectiveness in reducing pollution.
Article
Computer Science, Interdisciplinary Applications
Fengyi Lu, Guanghui Zhou, Chao Zhang, Yang Liu, Fengtian Chang, Zhongdong Xiao
Summary: This paper proposes a novel multi-pass parametric optimization method based on deep reinforcement learning (DRL) to improve energy efficiency. By allowing parameters to vary, and transforming the model into a Markov Decision Process, the proposed method significantly improves material removal rate and specific cutting energy while meeting deformation tolerance, which substantiates the benefits of the energy-efficient parametric optimization.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Interdisciplinary Applications
Shan Ren, Lichun Shi, Yang Liu, Weihua Cai, Yingfeng Zhang
Summary: This study proposes a personalized maintenance approach (POMA-CP) to improve the accuracy and applicability of maintenance schemes for industrial products by establishing a refined maintenance model. The approach includes a multi-level case library, dynamic equipment portrait model, and case-pushing mechanism. Through this approach, active pushing of the best similar cases and automatic generation of service schemes can be achieved, resulting in higher accuracy and applicability for maintenance schemes.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Green & Sustainable Science & Technology
Qianyun Wen, Axel Lindfors, Yang Liu
Summary: This study explores a new method to generate semi-dynamic multi-criteria decision-making results through scenario analysis. Applied to the case of residential heating in Denmark, the results show that solar heating is the preferred alternative, while the oil boiler performs the worst. This study highlights the importance of considering potential changes in alternative performance and decision-makers' value perceptions.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Green & Sustainable Science & Technology
Zhichao Wang, Yang Liu, Zhenhong Lin, Han Hao, Shunxi Li
Summary: Arranging appropriate charging infrastructure in advance is crucial in decarbonising heavy freight through electrification. This study conducted a techno-economic comparison of charging modes for battery heavy-duty vehicles, analysing their profitability and performance advantages.
JOURNAL OF CLEANER PRODUCTION
(2023)
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)
