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Embedding detailed robot energy optimization into high-level scheduling

Alberto Vergnano, Carl Thorstensson, Bengt Lennartson, Petter Falkman, Marcello Pellicciari, Chengyin Yuan, Stephan Biller, Francesco Leali

Year
2010
Citations
38

Abstract

Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modelled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system is presented. It shows that there exists a possibility for a significant reduction of the energy consumption, in comparison to state-of-the-art scheduling approaches.

Keywords

Energy consumptionScheduling (production processes)Integer programmingComputer scienceEmbeddingParameterized complexityMathematical optimizationJob shop schedulingRobotNonlinear programming

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