• DocumentCode
    580897
  • Title

    Modeling green factory physics — An analytical approach

  • Author

    Prabhu, Vittaldas V. ; Jeon, Hyun Woo ; Taisch, Marco

  • Author_Institution
    Marcus Dept. of Ind. & Manuf. Eng., Pennsylvania State Univ., University Park, PA, USA
  • fYear
    2012
  • fDate
    20-24 Aug. 2012
  • Firstpage
    46
  • Lastpage
    51
  • Abstract
    There is a need for energy-aware models of manufacturing systems that link the physics of energy consumption at the individual machine-level to the energy consumption at the factory-level. Such energy-aware models would enable analysis of green factory designs, especially for evaluating alternatives during early design stages. This paper proposes to leverage existing analytical models based on queuing theory to include energy control for waste reduction. Specifically we propose analytical models for single server and serial production lines by extending the basic M/M/1 model with energy control policy for managing idle time power consumption. These analytical models can be readily used to estimate reduction in energy waste for different production and power parameters. Simulation experiments are used to test the robustness of the analytical models by using exponential, normal, hyper-exponential and hypo-exponential distributions. Results show that the energy consumption estimated by the analytical models differ less than 10%, indicating that the proposed models are reasonably robust.
  • Keywords
    design for environment; energy conservation; exponential distribution; manufacturing systems; normal distribution; queueing theory; waste reduction; M/M/1 queuing model; analytical approach; energy consumption physics; energy control policy; energy waste reduction estimation; factory-level; green factory designs; green factory physics modeling; hyperexponential distribution; hypoexponential distribution; idle time power consumption management; machine-level; manufacturing system energy-aware models; normal distribution; power parameters; production lines; production parameters; Analytical models; Energy consumption; Manufacturing systems; Robustness; Servers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering (CASE), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • ISSN
    2161-8070
  • Print_ISBN
    978-1-4673-0429-0
  • Type

    conf

  • DOI
    10.1109/CoASE.2012.6386361
  • Filename
    6386361