7.2 Critical Appraisal of the Methodology
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lowest possible total energy consumption value for the given production scenario. The optimal values determined for the idle and the standby optimization
parameter can be brought back to the setup of the simulation model and are
thus used to simulate the ideal switching behavior of machines in cases of
production interruptions.
Besides the optimization parameters for the non-productive states, an offset
parameter was added to the model to reduce occurring power peak loads. The
offset parameter causes a defined delay in the machine start of production
machines and this leads to the fact that the single energy consumption profiles
add up differently in specific points in time. The height of power peaks may
thus be reduced.
Those examples show that it is possible to integrate energy as a control
parameter for different scenarios of production optimization.
Q3. How can the profitability of the energy optimization methodology be
rated considering the various fields of application?
As the prototypical implementation as well as the practical validation have
shown, the simulation-based optimization methodology offers great potentials
for the energy-efficient design of production processes. The optimization of the
total energy consumption through a reduction of non-value adding but energy
consuming production times can be implemented immediately in every production without requiring high financial investments in advance. The approach
is not limited to a certain production scenario but can be applied to any production situation, starting from single machine optimizations to the energy
efficient design of the total production. For the calculation of the profitability, only the costs for the simulation model generation have to be opposed
to the cost saving potentials. The savings are calculated using the prices of
the current energy contract. The height of the optimization potentials that can
be realized vary depending on the production and its optimization state. Have
general rules and measures to save energy already been applied, the achievable
potential of the simulation-based optimization methodology will be evaluated
to be lower than in a production were no steps to improve the energy efficiency
have been taken so far.
To what extent should the periphery of a production system be included in the simulation-based optimization in order to obtain a quantifiable
statement about the energetic behavior of the entire system?
203
lowest possible total energy consumption value for the given production scenario. The optimal values determined for the idle and the standby optimization
parameter can be brought back to the setup of the simulation model and are
thus used to simulate the ideal switching behavior of machines in cases of
production interruptions.
Besides the optimization parameters for the non-productive states, an offset
parameter was added to the model to reduce occurring power peak loads. The
offset parameter causes a defined delay in the machine start of production
machines and this leads to the fact that the single energy consumption profiles
add up differently in specific points in time. The height of power peaks may
thus be reduced.
Those examples show that it is possible to integrate energy as a control
parameter for different scenarios of production optimization.
Q3. How can the profitability of the energy optimization methodology be
rated considering the various fields of application?
As the prototypical implementation as well as the practical validation have
shown, the simulation-based optimization methodology offers great potentials
for the energy-efficient design of production processes. The optimization of the
total energy consumption through a reduction of non-value adding but energy
consuming production times can be implemented immediately in every production without requiring high financial investments in advance. The approach
is not limited to a certain production scenario but can be applied to any production situation, starting from single machine optimizations to the energy
efficient design of the total production. For the calculation of the profitability, only the costs for the simulation model generation have to be opposed
to the cost saving potentials. The savings are calculated using the prices of
the current energy contract. The height of the optimization potentials that can
be realized vary depending on the production and its optimization state. Have
general rules and measures to save energy already been applied, the achievable
potential of the simulation-based optimization methodology will be evaluated
to be lower than in a production were no steps to improve the energy efficiency
have been taken so far.
To what extent should the periphery of a production system be included in the simulation-based optimization in order to obtain a quantifiable
statement about the energetic behavior of the entire system?