Article
Computer Science, Interdisciplinary Applications
Ashkan Ayough, Behrooz Khorshidvand
Summary: This research addresses the worker-cell allocation and sequencing problems in mixed-model U-shaped assembly lines, considering the heterogeneity of workers' skills and uncertainty of task processing times. It proposes an efficient robust optimization model and demonstrates the superiority of the Lagrangian relaxation algorithm in large-scale instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Sajede Aminzadegan, Mohammad Tamannaei, Majid Fazeli
Summary: In the research, an integrated production and transportation scheduling problem is addressed, aiming to improve system performance and reduce overall costs by considering resource-dependent processing time and resource allocation. Experimental results show that the proposed Adaptive Genetic Algorithm performs better in optimality and efficiency.
APPLIED SOFT COMPUTING
(2021)
Article
Robotics
Hyungjoon Yang, Je-Hun Lee, Sang Hyun Lee, Seung Gi Lee, Hyung Rok Kim, Hyun-Jung Kim
Summary: The task assignment and worker balancing problem in assembly lines is crucial for maximizing productivity. This study focuses on a real automotive parts assembly line where multiple workers perform various tasks simultaneously in a workstation, with each worker's processing time varying. New positional constraints are introduced to ensure each worker's working space. The goal is to minimize cycle time, and a filtered beam search algorithm is proposed to efficiently solve large-scale instances.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Computer Science, Hardware & Architecture
George N. Rouskas, Chaitanya Bandikatla
Summary: We revisit the classical spectrum allocation problem in optical network design and make three contributions. Firstly, we propose a decomposition method for some SA problem instances that allows for independent solutions without losing optimality. Secondly, we prove the optimality property of the well-known first-fit heuristic algorithm. Finally, we leverage this property to develop a recursive and parallel algorithm that efficiently finds an optimal solution.
JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING
(2022)
Article
Multidisciplinary Sciences
Xiangyan Liu, Jianhong Zheng, Meng Zhang, Yang Li, Rui Wang, Yun He
Summary: The paper introduces a novel method for cellular D2D-MEC system, which achieves task offloading, resource allocation, and improved execution efficiency with low latency.
SCIENTIFIC REPORTS
(2021)
Article
Computer Science, Interdisciplinary Applications
Aslihan Karas, Feristah Ozcelik
Summary: This study introduces the Assembly Line Worker Assignment and Rebalancing Problem (ALWARBP), aiming to minimize variability in cycle time and workstation assignments by reallocating tasks and workers after disruptions occur. Both methods successfully obtained optimal solutions in small instances, while the proposed ABC algorithm showed better performance in terms of solution value and computation time in large test instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Management
S. Ehsan Hashemi-Petroodi, Simon Thevenin, Sergey Kovalev, Alexandre Dolgui
Summary: This study investigates the impact of model-dependent task assignment, workforce reconfiguration, and equipment duplication on mixed-model assembly lines. The results show that model-dependent task assignment can significantly reduce equipment costs and the number of workers.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Operations Research & Management Science
Arda Turkgenci, Huseyin Guden, Mehmet Gulsen
Summary: Project scheduling is crucial for many companies, and this study deals with the implementation of a project scheduling routine for a make-to-order machinery manufacturer, referred to as a Rich Project Scheduling Problem. The research employs two techniques to address complexity, calculating the latest start time for activities and breaking down the problem into manageable pieces, resulting in high-quality solutions for real-life problems.
OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Adalberto Sato Michels, Alysson M. Costa
Summary: Some solutions reported in a recent paper are infeasible, potentially undermining the conclusion that the best results were obtained for 75% of the 320 test instances for the ALWABP-2. This note explores the contributions of the paper, identifies infeasible solutions, and points out potential inconsistencies in the employed heuristic.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Engineering, Marine
Shuang Tang, Sudong Xu, Jianwen Gao, Mengdi Ma, Peng Liao
Summary: This article studies the evacuation strategy of container vessels in continuous terminals and analyzes the impact of service priority on the terminal by establishing a model and solving it with a genetic algorithm. The results show that using the square of handled container volume is more conducive to ensuring the shipping period of large vessels.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Lili Wang, Zhe Zhang, Yong Yin
Summary: This paper focuses on the order acceptance and scheduling problem in the divisional seru production system, which can achieve responsiveness, flexibility, and efficiency. A nonlinear integer programming model is established, and a bi-level nested heuristic algorithm is designed. Computational experiments show that the proposed algorithm outperforms the bi-level genetic algorithm in terms of objective value and running time, achieving better results and higher efficiency for divisional seru order acceptance and scheduling problems.
APPLIED SOFT COMPUTING
(2023)
Review
Chemistry, Analytical
Muhammad Ayoub Kamal, Hafiz Wahab Raza, Muhammad Mansoor Alam, Mazliham Mohd Su'ud, Aznida binti Abu Bakar Sajak
Summary: 5G communication technology aims to provide higher data rates, user experience, and lower power consumption, with its multi-layer model impacting interference management and resource allocation studies. One key challenge in resource allocation is mitigating network interference for improved service quality.
Article
Biology
Sylvie Estrela, Alicia Sanchez-Gorostiaga, Jean C. C. Vila, Alvaro Sanchez
Summary: The study found that while the family-level community composition can generally be predicted using the null, naturally additive model, there are systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance. Pairs of more similar nutrients tend to be more additive than pairs of dissimilar nutrients, and sugar-acid communities are generally more similar to sugar communities than acid communities, possibly due to family-level asymmetries in nutrient benefits. Overall, the study suggests that regularities in how nutrients interact may help predict community responses to dietary changes.
Article
Computer Science, Information Systems
Jianzhang Zheng, Xuan Tang, Xian Wei, Hao Shen, Lijun Zhao
Summary: The study focuses on the channel assignment in hybrid NOMA systems, treating it as a deep reinforcement learning task to improve environmental adaptability and reduce time complexity. Simulation results demonstrate that the proposed method outperforms conventional methods in terms of sum rate and spectral efficiency.
IEEE WIRELESS COMMUNICATIONS LETTERS
(2021)
Article
Engineering, Industrial
Nicolas P. Campana, Manuel Iori, Mayron Cesar O. Moreira
Summary: This study proposes new algorithms for the assembly line balancing problem with hierarchical worker assignment, aiming to minimize total cost while satisfying cycle time and precedence constraints. The effectiveness of the algorithms is demonstrated through extensive computational experiments on benchmark instances.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Manufacturing
Sampsa Vili Antero Laakso, Esko Niemi
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2016)
Article
Engineering, Manufacturing
Sampsa Vili Antero Laakso, Esko Niemi
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2016)
Article
Engineering, Marine
Henri Alfred Tokola, Esko Niemi, Heikki Remes
JOURNAL OF SHIP PRODUCTION AND DESIGN
(2016)
Article
Computer Science, Interdisciplinary Applications
Sampsa V. A. Laakso, Esko Niemi
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2017)
Article
Computer Science, Interdisciplinary Applications
Henri Tokola, Esko Niemi, Pekka Kyrenius
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2017)
Article
Engineering, Industrial
Jaakko Peltokorpi, Esko Niemi
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2019)
Article
Engineering, Multidisciplinary
Henri Tokola, Lauri Ahlroth, Esko Niemi
ENGINEERING OPTIMIZATION
(2014)
Article
Engineering, Industrial
Jaakko Peltokorpi, Henri Tokola, Esko Niemi
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2015)
Article
Engineering, Manufacturing
Sampsa V. A. Laakso, Mikko Hokka, Esko Niemi, Veli-Tapani Kuokkala
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2013)
Article
Automation & Control Systems
Rizwan Ullah, Jan Sher Akmal, Sampsa V. A. Laakso, Esko Niemi
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2020)
Article
Automation & Control Systems
Rizwan Ullah, Junhe Lian, Jan Akmal, Jiaojiao Wu, Esko Niemi
Summary: A finite element-based thermomechanical modeling approach is developed to predict the mesoscale melt pool behavior and part-scale properties for AlSi10Mg alloy. The Goldak heat source model is used for melt pool prediction, and a parametric approach is proposed to determine the necessary parameters. The study also investigates the correlation between mesh size, initial temperature, and residual stresses on the part-scale.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Jaakko Peltokorpi, Lauri Isojarvi, Kai Hakkinen, Esko Niemi
Summary: The study proposes a QR code-based order monitoring system to address uncertainty in the supply chains of principal manufacturers. The results show that the system is practical and promising in real-world applications, but faces challenges in technical integration and subcontractor adaptation.
Proceedings Paper
Engineering, Industrial
Henri Tokola, Christoph Groeger, Eeva Jarvenpaa, Esko Niemi
FACTORIES OF THE FUTURE IN THE DIGITAL ENVIRONMENT
(2016)
Proceedings Paper
Automation & Control Systems
Henri Tokola, Esko Niemi
Article
Engineering, Industrial
Henri Tokola, Eeva Jarvenpaa, Tapio Salonen, Minna Lanz, Mikko Koho, Esko Niemi
MANAGEMENT AND PRODUCTION ENGINEERING REVIEW
(2015)
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)