TY - GEN
T1 - Modeling green factory physics - An analytical approach
AU - Prabhu, Vittaldas V.
AU - Jeon, Hyun Woo
AU - Taisch, Marco
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84872511706&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84872511706&partnerID=8YFLogxK
U2 - 10.1109/CoASE.2012.6386361
DO - 10.1109/CoASE.2012.6386361
M3 - Conference contribution
AN - SCOPUS:84872511706
SN - 9781467304283
T3 - IEEE International Conference on Automation Science and Engineering
SP - 46
EP - 51
BT - 2012 IEEE International Conference on Automation Science and Engineering
T2 - 2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012
Y2 - 20 August 2012 through 24 August 2012
ER -