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5 Development of a Simulation-based Methodology …
Simulation Module
Machine Component (1 … n)
Production Flow Component
Energy Component
operational
machine state
energy
state
Production Process Parameters
Setup times
Production/Cycle Times
MTTR/MTTF
Operational state restrictions
…
Planning Parameters
Production orders
Shift models
Quantities
Working schedules
…
Energy consumption parameters
> Mathematical functions
> Value tables/ table functions
> Energy state values
DES material flow
Machine process logic
Production Flow Parameters
Product data
Resource Assignment
Maintenance cycles
Waiting times
Quantities
…
SD energy flow
Objective
Functions
Optimization
Module
Optimization Constraints
Optimization Parameter
Idle Optimizer
Standby Optimizer
Offset Parameter
Feasible Parameter
Configurations
Unfeasible Parameter
Configurations
Best Feasible Parameter
Configuration
retrieve simulation results
run simulation model
Figure 5.22 Conceptual model for the simulation-based optimization of energy efficiency
To find the optimal solution, the simulation model is run a defined number
of iterations. For every iteration the set of parameters is varied, the produced
simulation results, not all of them improving or feasible, provide a trajectory to
the best solution. Is a parameter set complying with all constraints and restrictions,
it is counted as a feasible solution. All feasible solutions are then looked through
for the best parameter set, guaranteeing the most efficient production set up for
the simulation model. The optimization experiment thus provides the best possible
values for the decision variables in regard to a selected objective function. This
results in the conceptual model for the simulation-based optimization shown in
Figure 5.22.
Following, the software selection as well as a prototypical implementation
will be described, using a production scenario that has slightly been adapted for