Preliminary understanding of Simulation of Manufacturing System

1. Simulation of Manufacturing System
Deepa Abin, PCCoE
deepa.abin@pccoepune.org

2. Simulation
Simulation can be used to understand underlying mechanisms
that control the behaviour of a system
 predict the future behaviour of a system
 can determine what one can do to influence that future
behaviour
Simulation model is a surrogate to actually experiment with a
manufacturing system, that is generally infeasible.
Crucial check points for Simulation Model :
- whether the model is valid
- the model to be credible or not

3. Use of Simulation in Manufacturing
Process
 Level of details with availability of input data, knowledge
about working of various system components and interaction
with each other is vital.
 In non existent systems, data may not be sufficient, system
knowledge may be based on assumptions and experts opinion.
 Simulation can be used to evaluate and compare effectiveness
of various aspects and for suggestion of various
improvements.
 Debugging and fine tuning can be beneficial.
Scope of simulation is very crucial and customer should be
ideally involved throughout simulation study to help design the
model effectively.

4. Manufacturing Process
Manufacturing
Steps through which the raw materials are transformed into a
final product is the process of Manufacturing
 Product design
 Material specification
 Material modification through processes for refined product
Application Areas
 can be used to quantify system performance
 to predict the performance of an existing or planned system
 to compare alternative solutions for a particular design
problem

5. System Randomness
It is important to model system randomness correctly and also to
design and analyse simulation experiments in a proper manner.
Some sources of randomness in simulated manufacturing
systems:
 Arrivals of orders/parts/ raw materials
 Processing, assembly or inspection times
 Machine times to failure
 Machine repair times
 Loading/unloading times
 Setup times
Appropriate probability distribution needs to be used to model
each source of randomness.

6. Simulation Run in Manufacturing Systems
 Most of the cases in simulation of manufacturing systems uses
long run or steady state behaviour of the system.
 Independent runs using different random numbers for each run
can be used for each system design.
 As empty or idle state is the beginning point of such
simulation systems hence deviation from normal behaviour is
observed and hence warmup period data is used.
 Length of each simulation run, number of independent
simulation runs and length of the warmup period are crucial.
Therefore warm up period followed by steady state is used to
estimate desired performance measure.

7. References
 S. Andradóttir, K. J. Healy, D. H. Withers and B. L. Nelson,
Proceedings of the 1997 Winter Simulation Conference
 Frank L. Severance, “System Modeling and Simulation a
Introduction”, Severance, John Wiley & Sons Ltd, ISBN 9812-
53-175-0.
 Averill M Law, “Simulation Modeling and Analysis”, McGraw
Hill Education, ISBN-13: 978-0-07- 066733-4.