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.

Modeling green factory physics — An analytical approach

TAISCH, MARCO
2012-01-01

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.
2012
9781467304306
Energy efficiency
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/709142
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