Push-pull digital thread for digital transformation of manufacturing systems

被引:2
作者
Akay, Haluk [1 ,2 ]
Lee, Sang Hyun [3 ,4 ]
Kim, Sang -Gook [1 ]
机构
[1] MIT, Dept Mech Engn, Cambridge, MA 02139 USA
[2] KTH Royal Inst Technol, KTH Climate Act Ctr, Stockholm, Sweden
[3] Hyundai Motor Grp, Res & Dev Div, Gyeonggi, South Korea
[4] Sungkyunkwan Univ, Sch Mech Engn, Gyeonggi, South Korea
基金
美国国家科学基金会;
关键词
Manufacturing system; Decision making; Digital transformation; DESIGN;
D O I
10.1016/j.cirp.2023.03.023
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Current digitalized manufacturing systems do not yet achieve the goal of smart manufacturing: precise con-trol and agility under unexpected disruptions. Push-Pull Digital Thread is a solution concept to enable contex-tual data and knowledge exchange across operational and functional units in a manufacturing enterprise. The extraction of decision reasoning and functional information can be facilitated by Large Language Models proc-essing information obtained from a decision maker at the point of decision. This concept shows a potential to address critical limitations in previous endeavours for smart manufacturing systems by building a semanti-cally searchable and sharable knowledgebase in manufacturing systems and beyond.& COPY; 2023 CIRP. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:401 / 404
页数:4
相关论文
共 15 条
  • [1] Semantic data management for the development and continuous reconfiguration of smart products and systems
    Abramovici, Michael
    Goebel, Jens Christian
    Dang, Hoang Bao
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2016, 65 (01) : 185 - 188
  • [2] Akay H, 2021, P INT C AXIOMATIC DE, V1174
  • [3] Akay H, 2021, P AM SOC MECH ENG ID, P85390
  • [4] Reading functional requirements using machine learning-based language processing
    Akay, Haluk
    Kim, Sang-Gook
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2021, 70 (01) : 139 - 142
  • [5] [Anonymous], 2017, MIT Sloan Management Review
  • [6] Bernstein William Z, 2018, Int J Prod Lifecycle Manag, V10, P326, DOI 10.1504/IJPLM.2017.090328
  • [7] Bonnaud S, 2019, IND 4 0 COGNITIVE MA
  • [8] Adaptive Cognitive Manufacturing System (ACMS) - a new paradigm
    ElMaraghy, Hoda
    ElMaraghy, Waguih
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2022, 60 (24) : 7436 - 7449
  • [9] Semantic Virtual Factory supporting interoperable modelling and evaluation of production systems
    Kadar, Botond
    Terkaj, Walter
    Sacco, Marco
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2013, 62 (01) : 443 - 446
  • [10] AI for design: Virtual design assistant
    Kim, Sang-Gook
    Yoon, Sang Min
    Yang, Maria
    Choi, Jungwoo
    Akay, Haluk
    Burnell, Edward
    [J]. CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2019, 68 (01) : 141 - 144