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4 State of the Art
of such optimization algorithms. By using different modeling accuracies, the
mathematical models of the operating states are combined to depict the complete consumption profile of a production machine. Thus, the optimal solution
improving energy efficiency in a production system can be determined.
• Studies in the field of simulation-based modeling of the energy demand in
production systems (intersection II in Figure 4.1) primarily focus on the consideration of resource consumption based on physically measured operating
states, which are expected to be constant over a defined period of time. The
energy consumption of resources is assumed to be status based and presented as part of discrete event simulation approaches. Furthermore, some
hybrid simulation approaches can be found. The hybrid simulation is here
used to merge the DES techniques for material flow simulations with the continuous approach for energy flow simulation to depict the complex interactions
between the material flow and the energy demand.
• Studies on simulation-based optimization in the context of production systems
(intersection III in Figure 4.1) combine simulation techniques with optimization methods to find the best input variable values from among all possibilities
without manually evaluating each possibility of a complex large-scale problem.
As the simulation-based optimization is well studied and has already been described in section 2.3, publications in this intersection are not considered in this
literature review due to the missing focus on energy related topics.
• Simulation-based optimization of energy efficiency in production (intersection
IV in Figure 4.1) requires the combination of discrete or hybrid simulation
approaches with integrated optimization possibilities in order to achieve an
improvement of measures in the relevant field of action. Modeling the diversity
of energy flows in the context of the whole production system together with
an integrated evaluation system can constitute a decisional support system for
production planning and control in order to achieve an optimum use of energy
in production systems.
The aforementioned intersections I and II as well as the convergence of all three
concepts (intersection IV) provide the focus of this literature review.
4 State of the Art
of such optimization algorithms. By using different modeling accuracies, the
mathematical models of the operating states are combined to depict the complete consumption profile of a production machine. Thus, the optimal solution
improving energy efficiency in a production system can be determined.
• Studies in the field of simulation-based modeling of the energy demand in
production systems (intersection II in Figure 4.1) primarily focus on the consideration of resource consumption based on physically measured operating
states, which are expected to be constant over a defined period of time. The
energy consumption of resources is assumed to be status based and presented as part of discrete event simulation approaches. Furthermore, some
hybrid simulation approaches can be found. The hybrid simulation is here
used to merge the DES techniques for material flow simulations with the continuous approach for energy flow simulation to depict the complex interactions
between the material flow and the energy demand.
• Studies on simulation-based optimization in the context of production systems
(intersection III in Figure 4.1) combine simulation techniques with optimization methods to find the best input variable values from among all possibilities
without manually evaluating each possibility of a complex large-scale problem.
As the simulation-based optimization is well studied and has already been described in section 2.3, publications in this intersection are not considered in this
literature review due to the missing focus on energy related topics.
• Simulation-based optimization of energy efficiency in production (intersection
IV in Figure 4.1) requires the combination of discrete or hybrid simulation
approaches with integrated optimization possibilities in order to achieve an
improvement of measures in the relevant field of action. Modeling the diversity
of energy flows in the context of the whole production system together with
an integrated evaluation system can constitute a decisional support system for
production planning and control in order to achieve an optimum use of energy
in production systems.
The aforementioned intersections I and II as well as the convergence of all three
concepts (intersection IV) provide the focus of this literature review.