Big data analytics for operations management in engineer-to -order manufacturing

被引：16
|
作者：
Kozjek, Dominik [1 ]
Vrabic, Rok [1 ]
Rihtarsic, Borut [2 ]
Butala, Peter [1 ]
机构：
[1] Univ Ljubljana, Fac Mech Engn, Askerceva 6, Ljubljana 1000, Slovenia
[2] Litostroj Power Doo, Litostrojska Cesta 50, Ljubljana 1000, Slovenia
来源：
51ST CIRP CONFERENCE ON MANUFACTURING SYSTEMS | 2018年 / 72卷
关键词：
Engineer-to-order manufacturing; Operations management; Data analytics; Industrial data; Data mining; Big data; SYSTEMS; FUTURE;
D O I：
10.1016/j.procir.2018.03.098
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Manufacturing data offers big potential for improving management of manufacturing operations. The paper addresses an approach to data analytics in engineer-to -order (ETO) manufacturing systems where the product quality and due-date reliability play a key role in management decision making. The objective of the research is to investigate manufacturing data which are collected by a manufacturing execution system (MES) during operations in an ETO enterprise and to develop tools for supporting scheduling of operations. The developed tools can be used for simulation of production and forecasting of potential resource overloads. 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 51st CIRP Conference on Manufacturing Systems.
引用
收藏
页码：209 / 214
页数：6
相关论文
共 50 条
  • [31] Data analytics for crop management: a big data view
    Chergui, Nabila
    Kechadi, Mohand Tahar
    [J]. JOURNAL OF BIG DATA, 2022, 9 (01)
  • [32] A big data analytics framework for scientific data management
    Fiore, Sandro
    Palazzo, Cosimo
    D'Anca, Alessandro
    Foster, Ian
    Williams, Dean N.
    Aloisio, Giovanni
    [J]. 2013 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, 2013,
  • [33] Data analytics for crop management: a big data view
    Nabila Chergui
    Mohand Tahar Kechadi
    [J]. Journal of Big Data, 9
  • [34] Big data analytics challenges to implementing the intelligent Industrial Internet of Things (IIoT) systems in sustainable manufacturing operations
    Qi, Quansong
    Xu, Zhiyong
    Rani, Pratibha
    [J]. TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2023, 190
  • [35] Improving Transport Management with Big Data Analytics
    Nagy, Albert
    Tick, Jozsef
    [J]. 2016 IEEE 14TH INTERNATIONAL SYMPOSIUM ON INTELLIGENT SYSTEMS AND INFORMATICS (SISY), 2016, : 199 - 203
  • [36] Big data analytics for network and service management
    Diao, Yixin
    Zincir-Heywood, A. Nur
    [J]. INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, 2017, 27 (04)
  • [37] Big Data Analytics for Supply Chain Management
    Leveling, Jens
    Edelbrock, Matthias
    Otto, Boris
    [J]. 2014 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM), 2014, : 918 - 922
  • [38] Big data analytics in production and distribution management
    Yin, Yunqiang
    Chu, Feng
    Dolgui, Alexandre
    Cheng, T. C. E.
    Zhou, M. C.
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2022, 60 (22) : 6682 - 6690
  • [39] Big Data Analytics Concepts and Management Techniques
    Elarabi, Tarek
    Sharma, Bhanu
    Pahwa, Karan
    Deep, Vishal
    [J]. 2016 INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT), VOL 2, 2016, : 234 - 239
  • [40] Big Data Analytics and Management Forecasting Behavior
    Goh, Beng Wee
    Li, Na
    Ranasinghe, Tharindra
    [J]. ACCOUNTING HORIZONS, 2024, 38 (03) : 59 - 76
12345