Toward Smart Manufacturing Using Decision Analytics

被引:0
|
作者
Brodsky, Alexander [1 ]
Krishnamoorthy, Mohan [1 ]
Menasce, Daniel A. [1 ]
Shao, Guodong [2 ]
Rachuri, Sudarsan [2 ]
机构
[1] George Mason Univ, Dept Comp Sci, Fairfax, VA 22030 USA
[2] NIST, Syst Integrat Div, Gaithersburg, MD 20899 USA
关键词
smart manufacturing; decision support; decision guidance; optimization; data analytics; HETEROGENEOUS ACTIVE AGENTS; OPTIMIZATION PROBLEMS; ALGORITHMS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is focused on decision analytics for smart manufacturing. We consider temporal manufacturing processes with stochastic throughput and inventories. We demonstrate the use of the recently proposed concept of the decision guidance analytics language to perform monitoring, analysis, planning, and execution tasks. To support these tasks we define the structure of and develop modular reusable process component models, which represent data, decision/control variables, computation of functions, constraints, and uncertainty. The tasks are then implemented by posing declarative queries of the decision guidance analytics language for data manipulation, what-if prediction analysis, decision optimization, and machine learning.
引用
收藏
页码:967 / 977
页数:11
相关论文
共 50 条
  • [31] Smart Manufacturing with Prescriptive Analytics A review of the current status and future work
    Vater, Johannes
    Harscheidt, Lars
    Knoll, Alois
    PROCEEDINGS OF 2019 8TH INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY AND MANAGEMENT (ICITM 2019), 2019, : 224 - 228
  • [32] Enriching analytics models with domain knowledge for smart manufacturing data analysis
    Zhang, Heng
    Roy, Utpal
    Lee, Yung-Tsun Tina
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2020, 58 (20) : 6399 - 6415
  • [33] INVESTIGATING GREY-BOX MODELING FOR PREDICTIVE ANALYTICS IN SMART MANUFACTURING
    Yang, Zhuo
    Eddy, Douglas
    Krishnamurty, Sundar
    Grosse, Ian
    Denno, Peter
    Lu, Yan
    Witherell, Paul
    PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2017, VOL 2B, 2017,
  • [34] Smart data analytics for identifying dynamic bottlenecks in flexible manufacturing systems
    Klenner, Ferdinand
    Lenze, David
    Schwarzer, Samuel
    Deuse, Jochen
    Friedrich, Tilman
    AT-AUTOMATISIERUNGSTECHNIK, 2016, 64 (07) : 540 - 554
  • [35] Machine Learning for Predictive and Prescriptive Analytics of Operational Data in Smart Manufacturing
    Lepenioti, Katerina
    Pertselakis, Minas
    Bousdekis, Alexandros
    Louca, Andreas
    Lampathaki, Fenareti
    Apostolou, Dimitris
    Mentzas, Gregoris
    Anastasiou, Stathis
    ADVANCED INFORMATION SYSTEMS ENGINEERING WORKSHOPS, 2020, 382 : 5 - 16
  • [36] Toward Standardization in Biotechnology Platforms to Support Smart Manufacturing
    Lin-Gibson, Sheng
    Srinivasan, Vijay
    SMART AND SUSTAINABLE MANUFACTURING SYSTEMS, 2020, 4 (03): : 250 - 253
  • [37] Toward smart manufacturing systems incorporating reconfiguration issues
    Garbie I.H.
    Garbie A.I.
    International Journal of Industrial and Systems Engineering, 2024, 46 (01) : 1 - 33
  • [38] Toward privacy-aware federated analytics of cohorts for smart mobility
    Gjoreski, Martin
    Laporte, Matias
    Langheinrich, Marc
    FRONTIERS IN COMPUTER SCIENCE, 2022, 4
  • [39] INTEGRATING DATA ANALYTICS AND SIMULATION METHODS TO SUPPORT MANUFACTURING DECISION MAKING
    Kibira, Deogratias
    Hatim, Qais
    Kumara, Soundar
    Shao, Guodong
    2015 WINTER SIMULATION CONFERENCE (WSC), 2015, : 2100 - 2111
  • [40] Data Analytics and Machine Learning for Smart Decision Making in Automotive Sector
    Ahaggach, Hamid
    ENTERPRISE DESIGN, OPERATIONS, AND COMPUTING: EDOC 2022 WORKSHOPS, IDAMS 2022, SOEA4EE 2022, TEAR 2022, 2023, 466 : 357 - 363