Understanding Human-machine Collaborative Systems in Industrial Decision-making

被引:1
作者
Bhandari, K. [1 ]
Xin, Y. [1 ]
Ojanen, V [1 ]
机构
[1] LUT Univ, Dept Ind Engn & Management, Lappeenranta, Finland
来源
2021 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEE IEEM21) | 2021年
关键词
Human-Machine collaboration; Decision-making; Artificial Intelligence; Human intelligence; TASK ALLOCATION; WORK HUMAN; COOPERATION; COMMUNICATION; INTELLIGENCE; TRUST; AL;
D O I
10.1109/IEEM50564.2021.9673073
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The inclusion of Intelligent systems in industries has resulted in various opportunities as well as some unforeseen concerns. It has brought complexity in team dynamics, communication, and decision-making structure. Therefore, transforming the structure of the organizations into a collaborative space where both humans and intelligent machines work together as partners is challenging. This paper delves into these complexities elaborating on the impact of incorporating intelligent machines on decision-making and decision-makers. The paper explores the novel research area by the means of a systematic review of the literature in this field. The review process resulted in 37 carefully selected articles from Scopus and Web of Science databases. The results show the increasing number of publications in this interdisciplinary research area. As findings of the paper, four major concepts of human-machine collaborative systems in industrial decision-making have been derived, and applications within these conceptual areas are introduced in this paper. Finally, emerging, and potential future research are presented, as well as the essential areas to be paid attention to as managerial implications of the findings.
引用
收藏
页码:1402 / 1406
页数:5
相关论文
共 37 条
  • [1] Akata Z., 2020, COMPUTER
  • [2] A Guide for the Food Industry to Meet the Future Skills Requirements Emerging with Industry 4.0
    Akyazi, Tugce
    Goti, Aitor
    Oyarbide, Aitor
    Alberdi, Elisabete
    Bayon, Felix
    [J]. FOODS, 2020, 9 (04)
  • [3] Transforming the communication between citizens and government through AI-guided chatbots
    Androutsopoulou, Aggeliki
    Karacapilidis, Nikos
    Loukis, Euripidis
    Charalabidis, Yannis
    [J]. GOVERNMENT INFORMATION QUARTERLY, 2019, 36 (02) : 358 - 367
  • [4] [Anonymous], 2004, Keele University Technical Report No
  • [5] Bauer W., 2016, Leichtbauroboter in der manuellen Montage-einfach einfach anfangen
  • [6] Systematic review methodology in higher education
    Bearman, Margaret
    Smith, Calvin D.
    Carbone, Angela
    Slade, Susan
    Baik, Chi
    Hughes-Warrington, Marnie
    Neumann, David L.
    [J]. HIGHER EDUCATION RESEARCH & DEVELOPMENT, 2012, 31 (05) : 625 - 640
  • [7] Bradshaw J. M., 2014, HUMAN AGENT INTERACT
  • [8] Brynjolfsson E., 2017, HARVARD BUS REV, P1
  • [9] Cai H., 2010, P HUMAN FACTORS ERGO, V54, P2437
  • [10] Casini E, 2015, 2015 IEEE INTERNATIONAL MULTI-DISCIPLINARY CONFERENCE ON COGNITIVE METHODS IN SITUATION AWARENESS AND DECISION SUPPORT (COGSIMA), P200, DOI 10.1109/COGSIMA.2015.7108198