A state-of-the-art literature survey on artificial intelligence techniques for disassembly sequence planning

被引:3
|
作者
Chand, Mirothali [1 ]
Ravi, Chandrasekar [1 ]
机构
[1] Natl Inst Technol Puducherry, Dept Comp Sci & Engn, Karaikal, India
关键词
E-waste; Disassembly sequence planning; Artificial intelligence; Optimization; LEARNING-BASED OPTIMIZATION; DISCRETE BEES ALGORITHM; ELECTRONIC EQUIPMENT; GENETIC ALGORITHM; MAINTENANCE; GENERATION; PRODUCTS; DESIGN; INFORMATION; SEARCH;
D O I
10.1016/j.cirpj.2022.11.017
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In recent years, the utilization of artificial intelligence-based approaches has rapidly grown in the manu-facturing sectors. Disassembly sequence planning is an important combinatorial optimization problem that is gaining importance because of its significant role in the re-manufacturing sector and its ability to build a circular economy. An efficient disassembly process can reduce a product's ecological and economic impacts in the re-manufacturing industry. In this work, the state-of-the-art disassembly sequence planning methods are analyzed and explained in the point of disassembly objectives, disassembly attributes, and optimization techniques. This presentation also provides comparative inference of the functionality and limitation of various techniques used in disassembly sequence planning. A clear perspective on different optimization techniques is given which will be helpful for researchers to carry out their research in DSP for planning optimal disassembly sequences while satisfying various disassembly objectives and conditions.(c) 2022 CIRP.
引用
收藏
页码:292 / 310
页数:19
相关论文
共 50 条
  • [21] Artificial Intelligence Techniques for Cognitive Sensing in Future IoT: State-of-the-Art, Potentials, and Challenges
    Osifeko, Martins O.
    Hancke, Gerhard P.
    Abu-Mahfouz, Adnan M.
    [J]. JOURNAL OF SENSOR AND ACTUATOR NETWORKS, 2020, 9 (02)
  • [22] Artificial compound eye: a survey of the state-of-the-art
    Wu, Sidong
    Jiang, Tao
    Zhang, Gexiang
    Schoenemann, Brigitte
    Neri, Ferrante
    Zhu, Ming
    Bu, Chunguang
    Han, Jianda
    Kuhnert, Klaus-Dieter
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2017, 48 (04) : 573 - 603
  • [23] Artificial compound eye: a survey of the state-of-the-art
    Sidong Wu
    Tao Jiang
    Gexiang Zhang
    Brigitte Schoenemann
    Ferrante Neri
    Ming Zhu
    Chunguang Bu
    Jianda Han
    Klaus-Dieter Kuhnert
    [J]. Artificial Intelligence Review, 2017, 48 : 573 - 603
  • [24] Artificial intelligence in short term electric load forecasting: a state-of-the-art survey for the researcher
    Metaxiotis, K
    Kagiannas, A
    Askounis, D
    Psarras, J
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2003, 44 (09) : 1525 - 1534
  • [25] Artificial Intelligence in Software Requirements Engineering: State-of-the-Art
    Liu, Kaihua
    Reddivari, Sandeep
    Reddivari, Kalyan
    [J]. 2022 IEEE 23RD INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION FOR DATA SCIENCE (IRI 2022), 2022, : 106 - 111
  • [26] Review of State-of-the-Art in Deep Learning Artificial Intelligence
    Shakirov V.V.
    Solovyeva K.P.
    Dunin-Barkowski W.L.
    [J]. Optical Memory and Neural Networks, 2018, 27 (2) : 65 - 80
  • [27] A state-of-the-art review on artificial intelligence for Smart Buildings
    Panchalingam, Rav
    Chan, Ka C.
    [J]. INTELLIGENT BUILDINGS INTERNATIONAL, 2021, 13 (04) : 203 - 226
  • [28] A Survey on State-of-the-Art Drowsiness Detection Techniques
    Ramzan, Muhammad
    Khan, Hikmat Ullah
    Awan, Shahid Mahmood
    Ismail, Amina
    Ilyas, Mahwish
    Mahmood, Ahsan
    [J]. IEEE ACCESS, 2019, 7 : 61904 - 61919
  • [29] ARTIFICIAL-INTELLIGENCE FOR PROCESS ENGINEERING - STATE-OF-THE-ART
    MURATET, G
    BOURSEAU, P
    [J]. COMPUTERS & CHEMICAL ENGINEERING, 1993, 17 : S380 - S388
  • [30] Comment on “Artificial intelligence in gastroenterology: A state-of-the-art review”
    Thomas Bj?rsum-Meyer
    Anastasios Koulaouzidis
    Gunnar Baatrup
    [J]. World Journal of Gastroenterology, 2022, (16) : 1722 - 1724