Article
Chemistry, Multidisciplinary
Jeng-Dao Lee, Chen-Huan Chang, En-Shuo Cheng, Chia-Chen Kuo, Chia-Ying Hsieh
Summary: The development of an intelligent robotic palletizer system has significantly improved the efficiency and safety of stacking operations, providing real-time monitoring and stack inspection to ensure stacking correctness and personnel safety.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Industrial
Muhammet Ceyhan Sahin, Mustafa Kemal Tural
Summary: To stay competitive and adapt to the Industry 4.0 revolution, manufacturing companies are incorporating robots in their assembly processes to replace human workers. This study focuses on the impact of robots on cycle time in stochastic assembly lines with human-robot collaboration. The research proposes formulations and conducts computational studies to explore the stochastic assembly line balancing problem and evaluate the effects of robots on cycle times.
FLEXIBLE SERVICES AND MANUFACTURING JOURNAL
(2023)
Review
Computer Science, Artificial Intelligence
Parames Chutima
Summary: This review paper addresses the development and generalization of the research on the robotic assembly line balancing problem (RALBP) over time. The RALBP is classified and divided based on the types of layouts and the 4 M (Man, Machine, Material, and Method) concept. The main contributions of different articles are summarized chronologically in a table, and the research contribution precedence diagram illustrates the sequential order and linkage relationship among studies. Future research directions are pinpointed and discussed based on the findings of the review.
JOURNAL OF INTELLIGENT MANUFACTURING
(2022)
Review
Robotics
Bin Wei, Dan Zhang
Summary: The paper summarizes the main dynamic balancing methods of robotic mechanisms, presenting most of the methods while discussing the advantages and disadvantages of each. The goal is to provide an informative overview for future research in dynamic balancing of robotic mechanisms.
Article
Construction & Building Technology
Jiangpeng Shu, Wenhao Li, Yifan Gao
Summary: This research presents a trajectory planning approach for robotic assembly of lightweight structures for COVID-19 healthcare facilities. The approach developed an algorithm that refined the RRT* algorithm to enable collision avoidance. Testing revealed satisfactory performance in collision-avoiding and trajectory-smoothing, with time and labor savings compared to traditional methods.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Construction & Building Technology
Thikra Dawood, Emad Elwakil, Hector Mayol Novoa, Jose Fernando Garate Delgado
Summary: This study presents a novel framework for assessing water main condition index, utilizing a hybrid technique of intelligent systems to enhance evaluation efficiency and accuracy. The research demonstrates the effectiveness of the framework in evaluating water piping system conditions, promoting urban and environmental sustainability.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Engineering, Industrial
Weikai Wang, Xian Chen
Summary: In this paper, a condition-based imperfect maintenance model based on piecewise deterministic Markov process (PDMP) is constructed. The degradation of the system includes two types: natural degradation and random shocks. The impulse optimal control theory of PDMP is used to determine the optimal maintenance strategy. A numerical study dealing with component coating maintenance problem is presented, along with sensitivity analyses on the influences of discount factor, observation interval and maintenance cost.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Automation & Control Systems
Kai Meng, Qiuhua Tang, Zikai Zhang
Summary: This paper investigates the assembly line balancing problem with preventive maintenance scenarios, and proposes a robust approach to solve the uncertain processing time. A mixed-integer optimization model and an improved algorithm are developed to solve this problem. Experimental results demonstrate the necessity of considering preventive maintenance scenarios.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Engineering, Industrial
Marcel Albus, Marco F. Huber
Summary: The successful operation of an assembly line requires balancing work among resources and stations to minimize costs, known as the Assembly Line Balancing Problem (ALBP). Most research focuses on new production facilities without pre-existing resources, known as a greenfield approach. However, reconfigurable production due to market demands imposes new constraints on the ALBP.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Paraskevi Th. Zacharia, Elias K. Xidias, Andreas C. Nearchou
Summary: This article discusses the assembly line balancing problem in production lines with collaborative robots. Collaborative robots have the potential to improve automation, productivity, accuracy, and flexibility in manufacturing. The article explores the use of a problem-specific metaheuristic to solve this complex problem under uncertainty.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
Article
Automation & Control Systems
Daniel Sanchez-Martinez, Carlos A. Jara, Francisco Gomez-Donoso
Summary: Nowadays, there are many industrial processes that involve tedious and repetitive tasks, often with dangerous materials or machinery. This paper presents an automatic and innovative collaborative robotic system that can handle the demoulding task in toy doll manufacturing. The system uses a vision-based algorithm and a custom gripper integrated into a UR10e robot to detect and extract the pieces from the mold.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Computer Science, Interdisciplinary Applications
Jingang Jiang, Liang Yao, Zhiyuan Huang, Guang Yu, Lihui Wang, Zhuming Bi
Summary: This review examines the challenges faced by assembly robots in performing precise assembly tasks, with a particular focus on peg-in-hole assemblies. It explores various search strategies to improve positioning accuracy and discusses the integration of multiple sensor data in search strategies. The review concludes by discussing future research directions for automated assembly search strategies.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2022)
Article
Construction & Building Technology
Anja Kunic, Roberto Naboni, Aljaz Kramberger, Christian Schlette
Summary: The field of architecture is increasingly turning to wood as a sustainable solution for new buildings while reducing carbon emissions. Research in Robotic Timber Construction (RTC) has rapidly evolved to focus on improving production efficiency through automated assembly, aided by human-robot collaboration. This paper presents an original workflow for automated design and assembly of reversible timber structures, enhancing the material life cycle of wood and its carbon store.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Computer Science, Artificial Intelligence
Zixiang Li, Mukund Nilakantan Janardhanan, S. G. Ponnambalam
Summary: This study investigates the cost-oriented robotic assembly line balancing problem, including purchasing cost and setup time optimization, by developing a mixed-integer linear programming model. The proposed IMABC algorithm introduces new employed bee phase and scout phase to enhance exploration and exploitation.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Automation & Control Systems
Bo-Rui Chen, Chun-Fei Hsu, Tsu-Tian Lee
Summary: This study proposes an intelligent balancing control system for unicycle robots, addressing the nonlinear and underactuated behavior through fuzzy control approach. The system comprises three controllers that enable the robot to maintain balance while moving at a desired speed. Additionally, a trajectory tracking control system is proposed for bicycle robots, achieving high accuracy trajectory tracking.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Fangyu Chen, Yongchang Wei, Hongchang Ji, Gangyan Xu
Summary: This paper introduces a dual-layer network analytical framework for evaluating standard systems in construction safety management and validates its effectiveness through a case study. The research findings suggest that key standards often encompass a wider array of risks, providing suggestions for revising construction standards.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Minghao Li, Qiubing Ren, Mingchao Li, Ting Kong, Heng Li, Huijing Tian, Shiyuan Liu
Summary: This study proposes a method using digital twin technology to construct a collision early warning system for marine piling. The system utilizes a five-dimensional model and four independently maintainable development modules to maximize its effectiveness. The pile positioning algorithm and collision early warning algorithm are capable of providing warnings for complex pile groups.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Seokhyun Ryu, Sungjoo Lee
Summary: This study proposes the use of patent information to develop a robust technology tree and applies it to the furniture manufacturing process. Through methods such as clustering analysis, semantic analysis, and association-rule mining, technological attributes and their relationships are extracted and analyzed. This approach provides meaningful information to improve the understanding of a target technology and supports research and development planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Shuai Ma, Kechen Song, Menghui Niu, Hongkun Tian, Yanyan Wang, Yunhui Yan
Summary: This paper proposes a feature-based domain disentanglement and randomization (FDDR) framework to improve the generalization of deep models in unseen datasets. The framework successfully addresses the appearance difference issue between training and test images by decomposing the defect image into domain-invariant structural features and domain-specific style features. It also utilizes randomly generated samples for training to further expand the training sample.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Fang Xu, Tianyu Zhou, Hengxu You, Jing Du
Summary: This study explores the impact of AR-based egocentric perspectives on indoor wayfinding performance. The results reveal that participants using the egocentric perspective demonstrate improved efficiency, reduced cognitive load, and enhanced spatial awareness in indoor navigation tasks.
ADVANCED ENGINEERING INFORMATICS
(2024)
Review
Computer Science, Artificial Intelligence
Yujie Lu, Shuo Wang, Sensen Fan, Jiahui Lu, Peixian Li, Pingbo Tang
Summary: Image-based 3D reconstruction plays a crucial role in civil engineering by bridging the gap between physical objects and as-built models. This study provides a comprehensive summary of the field over the past decade, highlighting its interdisciplinary nature and integration of various technologies such as photogrammetry, 3D point cloud analysis, semantic segmentation, and deep learning. The proposed 3D reconstruction knowledge framework outlines the essential elements, use phases, and reconstruction scales, and identifies eight future research directions. This review is valuable for scholars interested in the current state and future trends of image-based 3D reconstruction in civil engineering, particularly in relation to deep learning methods.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper presents a novel framework for segmenting intersecting machining features using deep reinforcement learning. The framework enhances the effectiveness of intersecting machining feature segmentation by leveraging the robust feature representation, decision-making, and automatic learning capabilities of deep reinforcement learning. Experimental results demonstrate that the proposed approach successfully addresses some existing challenges faced by several state-of-the-art methods in intersecting machining feature segmentation.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Chao Zhao, Weiming Shen
Summary: This paper proposes a semantic-discriminative augmentation-driven network for imbalanced domain generalization fault diagnosis, which enhances the model's generalization capabilities through synthesizing reliable samples and optimizing representations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ching-Chih Chang, Teng-Wen Chang, Hsin-Yi Huang, Shih-Ting Tsai
Summary: Ideation is the process of generating ideas through exploring visual and semantic stimuli for creative problem-solving. This process often requires changes in user goals and insights. Using pre-designed content and semantic-visual concepts for ideation can introduce uncertainty. An adaptive workflow is proposed in this study that involves extracting and summarizing semantic-visual features, using clusters of adapted information for multi-label classification, and constructing a design exploration model with visualization and exploration.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Zhen Wang, Shusheng Zhang, Hang Zhang, Yajun Zhang, Jiachen Liang, Rui Huang, Bo Huang
Summary: This research proposes a novel approach for machining feature process planning using graph convolutional neural networks. By representing part information with attribute graphs and constructing a learning model, the proposed method achieves higher accuracy and resolves current limitations in machining feature process planning.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hong-Wei Xu, Wei Qin, Jin-Hua Hu, Yan-Ning Sun, You -Long Lv, Jie Zhang
Summary: Wafer fabrication is a complex manufacturing system, where understanding the correlation between parameters is crucial for identifying the cause of wafer defects. This study proposes a Copula network deconvolution-based framework for separating direct correlations, which involves constructing a complex network correlation diagram and designing a nonlinear correlation metric model. The proposed method enables explainable fault detection by identifying direct correlations.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yida Hong, Wenqiang Li, Chuanxiao Li, Hai Xiang, Sitong Ling
Summary: An adaptive push method based on feature transfer is proposed to address sparsity and cold start issues in product intelligent design. By constructing a collaborative filtering algorithm model and transforming the rating model, the method successfully alleviates data sparsity and cold start problems.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Hairui Fang, Jialin An, Bo Sun, Dongsheng Chen, Jingyu Bai, Han Liu, Jiawei Xiang, Wenjie Bai, Dong Wang, Siyuan Fan, Chuanfei Hu, Fir Dunkin, Yingjie Wu
Summary: This work proposes a model for real-time fault diagnosis and distance localization on edge computing devices, achieving lightweight design and high accuracy in complex environments. It also demonstrates a high frame rate on edge computing devices, providing a novel solution for industrial practice.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Yujun Jiao, Xukai Zhai, Luyajing Peng, Junkai Liu, Yang Liang, Zhishuai Yin
Summary: This paper proposes a digital twin-based motion forecasting framework that predicts the future trajectories of workers on construction sites, accurately predicting workers' motions in potential risk scenarios.
ADVANCED ENGINEERING INFORMATICS
(2024)
Article
Computer Science, Artificial Intelligence
Ling-Zhe Zhang, Xiang-Dong Huang, Yan-Kai Wang, Jia-Lin Qiao, Shao-Xu Song, Jian-Min Wang
Summary: Time-series DBMSs based on the LSM-tree have been widely applied in various scenarios. The characteristics of time-series data workload pose challenges to efficient queries. To address issues like query latency and inaccurate range, we propose a novel compaction algorithm called Time-Tiered Compaction.
ADVANCED ENGINEERING INFORMATICS
(2024)
