Article
Engineering, Industrial
Yuanjun Laili, Fei Ye, Yongjing Wang, Lin Zhang
Summary: This paper discusses the use of a probability matrix to represent uncertain interference and proposes a multi-threshold planning scheme to generate optimal disassembly sequence plans. The research demonstrates that this approach is effective in handling disassembly problems under complex end-of-life conditions.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Engineering, Industrial
Yongjing Wang, Feiying Lan, Jiayi Liu, Jun Huang, Shizhong Su, Chunqian Ji, Duc Truong Pham, Wenjun Xu, Quan Liu, Zude Zhou
Summary: Remanufacturing involves rebuilding a product using a combination of reused, repaired, and new parts, with disassembly as a key and labor-intensive process. Robotic disassembly is an attractive alternative but still requires manual planning due to the complexity of end-of-life products. The proposed method in this paper allows machines to plan disassembly by generating and manipulating specific matrices, providing a flexible and effective approach for dealing with complex mechanical structures.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Review
Automation & Control Systems
Xiwang Guo, MengChu Zhou, Abdullah Abusorrah, Fahad Alsokhiry, Khaled Sedraoui
Summary: It is crucial to efficiently disassemble obsolete products to avoid environmental pollution and maximize economic benefits. This paper surveys the state of the art of disassembly sequence planning, aiming to provide guidance for researchers and decision makers in optimal planning solutions. The progress in disassembly sequencing planning is discussed in various aspects, stimulating further engagement in research and development in the Industry 4.0 era.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Automation & Control Systems
Yuanjun Laili, Xiang Li, Yongjing Wang, Lei Ren, Xiaokang Wang
Summary: The key step in remanufacturing is disassembling the returned product, but challenges arise due to uncertainties in the condition of the cores. This research focuses on developing flexible sequencing of robotic disassembly with online recovery by incorporating backup actions. Through modeling the time and success rate of backup actions, a dual-objective optimization model for robotic disassembly sequence planning is established using a dual-selection multiobjective evolutionary algorithm.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Mechanical
Hao-yu Liao, Yuhao Chen, Boyi Hu, Sara Behdad
Summary: This study proposes an optimization framework for planning disassembly sequences under uncertainty, considering human-robot collaboration. The framework combines disassembly cost, safety, and complexity to identify the optimal disassembly path and allocate operations between human and robot.
JOURNAL OF MECHANICAL DESIGN
(2023)
Article
Computer Science, Artificial Intelligence
Yicong Gao, Shanhe Lou, Hao Zheng, Jianrong Tan
Summary: Selective disassembly is a method for removing target components from End-of-Life (EOL) products for reuse, recycling, and remanufacturing. However, the process is often affected by unpredictable factors, making it difficult to determine a feasible disassembly sequence. In this paper, a data-driven method is proposed to address uncertainty in selective disassembly planning, where disassemblability is considered as the degree of difficulty in removing components under uncertainty. The method predicts the turning time of disassemblability and determines the best selective disassembly sequence with a tradeoff between the number of operations and feasibility.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Computer Science, Interdisciplinary Applications
Fei Ye, James Perrett, Lin Zhang, Yuanjun Laili, Yongjing Wang
Summary: Robotic disassembly sequence planning (DSP) is a research area focused on achieving autonomous disassembly with high efficiency and low cost in remanufacturing and recycling applications. Uncertain interference conditions and a lack of tools to handle them are observed challenges in the field. To address this, the paper proposes a new DSP method called fuzzy disassembly sequence planning (FDSP) that can adapt to uncertain interference conditions.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Robotics
Xikun Zhao, Congbo Li, Ying Tang, Jiabin Cui
Summary: This letter addresses the challenge of structure uncertainty of end-of-life products by proposing a new disassembly sequence planning method using deep Q-network and a multi-level selective disassembly hybrid graph model. The proposed method outperforms NSGA-II and ABC algorithms in minimizing disassembly time and maximizing disassembly profit through extensive comparative experiments.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Computer Science, Information Systems
Hongyu Liu, Linsheng Zhang
Summary: This paper introduces a method for partial disassembly sequence planning, which effectively addresses uncertainties in the actual disassembly process. By formulating success rates of disassembly operations to model an expected profit-based disassembly sequence planning, and introducing different neighborhood structures to improve disassembly solutions, the approach proves its superiority and effectiveness through case studies and comparison with existing metaheuristics.
Review
Engineering, Industrial
S. K. Ong, M. M. L. Chang, A. Y. C. Nee
Summary: Disassembly sequence planning (DSP) is a challenging research area that has attracted significant attention from researchers worldwide. New solutions are continuously proposed to tackle the complexities of disassembling products, with advancements in computing and introduction of new concepts like virtual reality. Survey papers in the past 12 years have focused on product representation models, sequencing algorithms, and methodology validation in DSP research.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Soran Parsa, Mozafar Saadat
Summary: The research proposes a disassembly planning method based on human-robot collaboration, utilizing human flexibility and robot precision to handle complex disassembly tasks and improve process efficiency. Components are targeted based on remanufacturability parameters, and optimization is done using a mathematical model and genetic algorithm.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Computer Science, Interdisciplinary Applications
Natalia Hartono, F. Javier Ramirez, D. T. Pham
Summary: Remanufacturing is crucial for a circular economy as it helps reduce landfill waste and preserve natural resources, benefiting the environment. This study proposes a model for planning the sequence of steps for robotic disassembly, using the Bees Algorithm to optimize profitability, energy savings, and greenhouse gas emission reductions.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Software Engineering
Arun Rehal, Dibakar Sen
Summary: This paper presents a scheme for efficient disassembly sequence planning based on part accessibility. It introduces the concept of shell structures for analyzing the accessibility of parts and explores their applications in maintenance planning and end-of-life processing. A grid-based method is proposed for constructing the shell structure. The results demonstrate the effectiveness of the proposed methods in assessing accessibility and updating shell structures.
COMPUTER-AIDED DESIGN
(2023)
Article
Engineering, Electrical & Electronic
Zongze Li, Shuai Wang, Shiyao Zhang, Miaowen Wen, Kejiang Ye, Yik-Chung Wu, Derrick Wing Kwan Ng
Summary: This article proposes a robust V2X motion planning policy that adapts between competitive driving under a low communication delay and conservative driving under a high communication delay. It guarantees small communication delays at key waypoints via power control. Simulation results show that the proposed driving policy achieves the smallest collision ratio compared with other benchmark policies.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Engineering, Industrial
Wenli Peng, Gilles Merckx, Aadhaar Chaturvedi, Philippe Chevalier
Summary: This paper investigates the impact of information sharing on OEMs' motivations towards joint purchasing agreements and consumer surplus. The study finds that a joint purchasing agreement is preferred by OEMs and beneficial to consumers when product substitutability is low, technology level uncertainty is moderate, or cost savings through joint purchasing are high.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Leif P. Berg, Sara Behdad, Judy M. Vance, Deborah Thurston
JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING
(2015)
Article
Engineering, Mechanical
Sara Behdad, Leif P. Berg, Deborah Thurston, Judy Vance
JOURNAL OF MECHANICAL DESIGN
(2014)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Leif P. Berg, Sara Behdad, Judy M. Vance, Deborah Thurston
PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE 2012, VOL 2, PTS A AND B
(2012)
Proceedings Paper
Engineering, Industrial
Sara Behdad, Leif P. Berg, Deborah Thurston, Judy Vance
PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE 2012, VOL 3, PTS A AND B
(2012)