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A quick comparison

Characteristic Single-Run Comparative Optimization Knowledge extraction
Number of simulations One or more Two or more Many Many
Objective Assess scenario Compare alternatives Find optimum Find insights
Complexity Low Medium High Very high

Individual analysis

i
A single simulation is sufficient to answer the question. Used to understand the current situation or a specific scenario.
What will the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
be in this production line?
What will be the plant loss in station X?
Which operation step is the bottleneck?

Comparative analysis

i
Two or more simulations are run to compare different scenarios (e.g. a baseline against one or more experiments).
How much will the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
increase/decrease in this production line if the
  • Availability
  • MTTR
  • Cycle time
  • Process time
  • Turnaround time
  • Discard %
  • Discard settings
in
  • Station
  • Buffer
  • Conveyor segment
X changes to Y?
How much will the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
increase/decrease in this production line if the
  • Order point
  • MOQ
changes to Y?
Which line configuration leads to the highest
  • ROI
  • ROR
  • Productivity
?
Which shift plan leads to the highest
  • ROI
  • ROR
  • Productivity
?
How many
  • Operators
  • Setting-up staff
  • Maintenance staff
  • Forklifts
  • AGVs
are needed for the production line so that they are not restrictive on
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
?
In which station will an X% increase/decrease of the
  • Availability
  • MTTR
  • Cycle time
  • Process time
  • Turnaround time
  • Discard %
  • Discard settings
increase/decrease the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
in the line the most?

Systematic Analysis & Optimization

i
Many experiments are run systematically to explore parameter effects, or optimization techniques are used to find the best solution.
Which logic for the
  • Robot
  • Transport system
  • Robot portal
  • AGV system
  • Storage
  • Operator
should be used to
  • Maximize
  • Optimize
  • Minimize
the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
the most?
Which is the optimal
  • Order point
  • MOQ
to
  • Maximize
  • Optimize
  • Minimize
the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
most?
How big should
  • Buffer
  • Warehouse
  • Warehouse incoming goods
  • Finished goods warehouse
be to reach a
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
of Y?
What is the optimal buffer placement (between which operation steps) and buffer size to
  • Maximize
  • Optimize
  • Minimize
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
?
Which improvement is increasing/decreasing the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
the most?
Which stock configuration of locked positions (to a specific part number) will increase/decrease the
  • OEE / OOE / TEEP
  • Throughput / h
  • Lead time
  • WIP (Work in progress)
the most (WITHOUT exceeding the maximum number of buffer places)?

Knowledge extraction

i
Using data from simulations to find patterns and insights that are not obvious.
Which batch size rules are important to
  • Maximize takt/h
  • Minimize lead time
  • Minimize PIA
?
Which sequence rules matter to
  • Maximize takt/h
  • Minimize lead time
  • Minimize PIA
?
What stock configuration rules are important to
  • Maximize takt/h
  • Minimize lead time
  • Minimize PIA
?