Identification and Design of Industry 4.0 Opportunities in Manufacturing: Examples from Mature Industries to Laboratory Level Systems

被引:9
|
作者
Menezes, Brenno C. [1 ]
Kelly, Jeffrey D. [2 ]
Leal, Adriano G. [1 ]
机构
[1] Ctr Informat Automat & Mobil, Inst Technol Res, BR-05508901 Sao Paulo, SP, Brazil
[2] Ind Algorithms Ltd, Toronto, ON M1P 4C3, Canada
来源
IFAC PAPERSONLINE | 2019年 / 52卷 / 13期
基金
巴西圣保罗研究基金会;
关键词
Industry; 4.0; Smart manufacturing systems; High-end sensing; Advanced analytics;
D O I
10.1016/j.ifacol.2019.11.581
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Considering the nascent application of advanced technologies in industry within the context of the new industrial revolution, we propose a methodology for identification and design (ID) of smart operations in manufacturing. The ID study considers the elements of the Industry 4.0 (14) such as autonomous robots, advanced analytics, systems integration, high-end sensing, big data, internet of things, cloud computing and human-machine interactions. Toward achievable I4-based production, the proposed IDoI4 (ID-of-I4) approach integrates 14 fundamental elements regarding a) modelling and solution algorithms (MSA), b) information and communication technologies (ICT), c) high-performance computing (HPC), and d) mechatronics (MEC). These four groups of the 14 elements are examined in the industrial cases covering from mature industries to laboratory level systems to determine their current technological states and gaps into the 14 stage. The examples highlighted are crushed-ore stockpile level control in the mining field, resin bed cleaning timetabling in water demineralisation treatment, compositional data-driven real-time optimisation of hydrocarbon streams and diverse 14 basics in the next generation of biorefineries. In the main example, supported by a high-end sensing apparatus to measure crushed-ore stockpile levels in real-time (live inventory as a controlled variable by a target), a hybrid dynamic control prescribes (every 4 minutes) discrete positions and time-slots of the shuttle-conveyor tripper car mechatronics that creates the stockpiles. From such IDoI4 methodology, a table on the MSA, ICT, HPC and MEC ground bases summarises how such technologies are integrated to the industrial examples considering research, development and deployment in stable, demanded and highly demanded stages of the technologies into the 14 mandate. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码:2494 / 2500
页数:7
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    [J]. 52ND CIRP CONFERENCE ON MANUFACTURING SYSTEMS (CMS), 2019, 81 : 1016 - 1021
  • [2] Are Industry 4.0 technologies enablers of lean? Evidence from manufacturing industries
    Narula, Sanjiv
    Puppala, Harish
    Kumar, Anil
    Luthra, Sunil
    Dwivedy, Maheshwar
    Prakash, Surya
    Talwar, Vishal
    [J]. INTERNATIONAL JOURNAL OF LEAN SIX SIGMA, 2023, 14 (01) : 115 - 138
  • [3] The implementation of Industry 4.0 in manufacturing: from lean manufacturing to product design
    Huang, Zhuoyu
    Jowers, Casey
    Kent, Damon
    Dehghan-Manshadi, Ali
    Dargusch, Matthew S.
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2022, 121 (5-6): : 3351 - 3367
  • [4] The implementation of Industry 4.0 in manufacturing: from lean manufacturing to product design
    Zhuoyu Huang
    Casey Jowers
    Damon Kent
    Ali Dehghan-Manshadi
    Matthew S. Dargusch
    [J]. The International Journal of Advanced Manufacturing Technology, 2022, 121 : 3351 - 3367
  • [5] Design and management of digital manufacturing and assembly systems in the Industry 4.0 era
    Cohen, Yuval
    Faccio, Maurizio
    Pilati, Francesco
    Yao, Xifan
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2019, 105 (09): : 3565 - 3577
  • [6] Design and management of digital manufacturing and assembly systems in the Industry 4.0 era
    Yuval Cohen
    Maurizio Faccio
    Francesco Pilati
    Xifan Yao
    [J]. The International Journal of Advanced Manufacturing Technology, 2019, 105 : 3565 - 3577
  • [7] An IoT based industry 4.0 architecture for integration of design and manufacturing systems
    Anbalagan, Arivazhagan
    Moreno-Garcia, Carlos Francisco
    [J]. MATERIALS TODAY-PROCEEDINGS, 2021, 46 : 7135 - 7142
  • [8] A Perspective on Industry 4.0: From Challenges to Opportunities in Production Systems
    Khan, Ateeq
    Turowski, Klaus
    [J]. IOTBD: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS AND BIG DATA, 2016, : 441 - 448
  • [9] Integrated Decision Process to Design Manufacturing Systems towards Industry 4.0
    El Abdellaoui, Mahdi El Alaoui
    Grimaud, Frederic
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    Delorme, Xavier
    [J]. IFAC PAPERSONLINE, 2019, 52 (13): : 1373 - 1378
  • [10] The impact of Industry 4.0 on the reconciliation of dynamic capabilities: evidence from the European manufacturing industries
    Felsberger, Andreas
    Qaiser, Fahham Hasan
    Choudhary, Alok
    Reiner, Gerald
    [J]. PRODUCTION PLANNING & CONTROL, 2022, 33 (2-3) : 277 - 300