78
4 State of the Art
steps characterized by parameters. Additionally, they implemented control functionalities based on finite state machine (FSM) control algorithms that have been
translated into C# and thus integrated into the simulator. The energetic states of
the machines have been modeled and integrated the same way. Thus, the energy
behavior can be run in the simulator together with the mechanical behavior and
the control functionality. Cataldo, Taisch, and Stahl validate their approach
through a simulation study with a serial production line made of four machines.
They prove that their method allows engineers to analyze the simulated production
line and to evaluate the efficiency of the simulated layout.
The above-mentioned approaches focus on the consideration of energy consumption based on measured operating states, describing them as constant over a
fixed period of time. DES approaches do often not provide a sufficient accuracy
for the modeling of highly dynamic production processes. To get a more detailed description of dynamic processes, hybrid simulation models are named as a
possible solution in literature [SP2014, p. 111]. The hybrid simulation merges
the DES techniques for material flow simulations with a continuous approach for
energy flow simulation to model the complex interactions between the material
flow and the energy demand. As the topic of hybrid simulation is quite new in
the context of production simulation, only four publications have been identified
for this literature review.
As a part of the “SimEnergy” research project, Peter and Wenzel develop
an approach focusing on bidirectional interactions between discrete event production models and continuous energy models [PW2015]. Using a communication
platform, the discrete event simulation tool for modeling the material flow is
connected with the continuous simulator to depict the energy aspects. The platform allows for the parametrization of the material and the energy flow model.
Having a separate plug-in, the data exchange as well as the synchronization time
are being controlled. Peter and Wenzel validate their approach using a practical
example from the automotive industry sector. Executing several simulation runs,
the influence of different shut-off temperatures on the output quantity is examined. It is shown that the interaction between production processes and energy
flows through coupled simulation models can be analyzed and evaluated. Peter
and Wenzel criticize that adjustments in production control to reduce energy
consumption are only implemented in real industry cases, as long as they do not
have a negative influence on output quantity [PW2015, p. 543].
Schmidt and Pawletta follow a research approach to describe hybrid production models in a purely discrete event simulation environment [SP2014].
Unlike Peter and Wenzel in their research, the combined consideration of the
event discrete and the continuous modeling aspects is not realized through the
4 State of the Art
steps characterized by parameters. Additionally, they implemented control functionalities based on finite state machine (FSM) control algorithms that have been
translated into C# and thus integrated into the simulator. The energetic states of
the machines have been modeled and integrated the same way. Thus, the energy
behavior can be run in the simulator together with the mechanical behavior and
the control functionality. Cataldo, Taisch, and Stahl validate their approach
through a simulation study with a serial production line made of four machines.
They prove that their method allows engineers to analyze the simulated production
line and to evaluate the efficiency of the simulated layout.
The above-mentioned approaches focus on the consideration of energy consumption based on measured operating states, describing them as constant over a
fixed period of time. DES approaches do often not provide a sufficient accuracy
for the modeling of highly dynamic production processes. To get a more detailed description of dynamic processes, hybrid simulation models are named as a
possible solution in literature [SP2014, p. 111]. The hybrid simulation merges
the DES techniques for material flow simulations with a continuous approach for
energy flow simulation to model the complex interactions between the material
flow and the energy demand. As the topic of hybrid simulation is quite new in
the context of production simulation, only four publications have been identified
for this literature review.
As a part of the “SimEnergy” research project, Peter and Wenzel develop
an approach focusing on bidirectional interactions between discrete event production models and continuous energy models [PW2015]. Using a communication
platform, the discrete event simulation tool for modeling the material flow is
connected with the continuous simulator to depict the energy aspects. The platform allows for the parametrization of the material and the energy flow model.
Having a separate plug-in, the data exchange as well as the synchronization time
are being controlled. Peter and Wenzel validate their approach using a practical
example from the automotive industry sector. Executing several simulation runs,
the influence of different shut-off temperatures on the output quantity is examined. It is shown that the interaction between production processes and energy
flows through coupled simulation models can be analyzed and evaluated. Peter
and Wenzel criticize that adjustments in production control to reduce energy
consumption are only implemented in real industry cases, as long as they do not
have a negative influence on output quantity [PW2015, p. 543].
Schmidt and Pawletta follow a research approach to describe hybrid production models in a purely discrete event simulation environment [SP2014].
Unlike Peter and Wenzel in their research, the combined consideration of the
event discrete and the continuous modeling aspects is not realized through the