Smart Manufacturing with Prescriptive Analytics A review of the current status and future work

被引:0
作者
Vater, Johannes [1 ]
Harscheidt, Lars [1 ]
Knoll, Alois [2 ]
机构
[1] BMW Grp, Planning & Prod Electrified Powertrains, Munich, Germany
[2] Tech Univ Munich, Robot Artificial Intelligence & Real Time Syst, Munich, Germany
来源
PROCEEDINGS OF 2019 8TH INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY AND MANAGEMENT (ICITM 2019) | 2019年
关键词
industry; 4.0; smart manufacturing; data analytics; prescriptive analytics; prescriptive automation; internet of things; review; INDUSTRY; 4.0; FRAMEWORK; SYSTEMS; NETWORK;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Automotive industry faces challenges in manufacturing like increasingly individualized products with a short lead-time to market and higher quality. Additionally to that, new technologies, such as Internet of Things (IoT), big data, data analytics and cloud computing, are changing the production into the next generation of industry. To address these challenges intelligent manufacturing in combination with data analytics plays an important role. In this sense, the integration of prescriptive analytics in manufacturing may help industry to increase productiveness. This paper provides first a comprehensive review of key elements for prescriptive analytics in manufacturing. Furthermore, this paper highlights requirements for a prescriptive analytics based production control, so called prescriptive automation, and finally points out field of activities in this topic.
引用
收藏
页码:224 / 228
页数:5
相关论文
共 50 条
  • [41] Shop Floor Digital Twin in Smart Manufacturing: A Systematic Literature Review
    Corallo, Angelo
    Del Vecchio, Vito
    Lezzi, Marianna
    Morciano, Paola
    SUSTAINABILITY, 2021, 13 (23)
  • [42] Smart manufacturing maturity models and their applicability: a review
    Vance, David
    Jin, Mingzhou
    Price, Christopher
    Nimbalkar, Sachin U.
    Wenning, Thomas
    JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT, 2023, 34 (05) : 735 - 770
  • [43] A Comprehensive Review of Blockchain Technology-Enabled Smart Manufacturing: A Framework, Challenges and Future Research Directions
    Guo, Xin
    Zhang, Geng
    Zhang, Yingfeng
    SENSORS, 2023, 23 (01)
  • [44] A topic-based patent analytics approach for exploring technological trends in smart manufacturing
    Wang, Juite
    Hsu, Chih-Chi
    JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT, 2021, 32 (01) : 110 - 135
  • [45] Integrating BIM and AI for Smart Construction Management: Current Status and Future Directions
    Pan, Yue
    Zhang, Limao
    ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2023, 30 (02) : 1081 - 1110
  • [46] Augmented reality smart glasses in industrial assembly: Current status and future challenges
    Danielsson, Oscar
    Holm, Magnus
    Syberfeldt, Anna
    JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2020, 20
  • [47] Federated learning-empowered smart manufacturing and product lifecycle management: A review
    Leng, Jiewu
    Li, Rongjie
    Xie, Junxing
    Zhou, Xueliang
    Li, Xiang
    Liu, Qiang
    Chen, Xin
    Shen, Weiming
    Wang, Lihui
    ADVANCED ENGINEERING INFORMATICS, 2025, 65
  • [48] Pharmaceutical Product Liabilities: A Review of Current Status and Future Trends
    Boudes, Pol F.
    DRUG INFORMATION JOURNAL, 2009, 43 (03): : 253 - 261
  • [49] Systematic Literature Review on Visual Analytics of Predictive Maintenance in the Manufacturing Industry
    Cheng, Xiang
    Chaw, Jun Kit
    Goh, Kam Meng
    Ting, Tin Tin
    Sahrani, Shafrida
    Ahmad, Mohammad Nazir
    Kadir, Rabiah Abdul
    Ang, Mei Choo
    SENSORS, 2022, 22 (17)
  • [50] Anomaly detection in Smart-manufacturing era: A review
    Elia, Inaki
    Pagola, Miguel
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2025, 139