SIMUL8 is the simulation tool of choice for the World’s largest and innovative manufacturing
organizations, including Ford, General Motors, Siemens, Cameron and Kroger. Our vast manufacturing
user base and experience with manufacturing users means we understand what is important
for manufacturing engineers and the key stake holders involved with process improvement.
Let’s look at an example. This simulation is set within an Assembly
Line where multiple families of electric motors are produced. The purpose of this simulation
is to see how we can increase the throughput of our current production line based on the
production schedules feeding the line. As the model runs, you'll see different colored
balls; these represent various products moving through the line. Time is shown on the clock
and the number of finished goods is represented by the throughput number on screen.
Let’s look at some of the inputs feeding the line.
For the purpose of this simulation, we will change the production schedules and view the
impact of increasing the demand. You can also change other variables using this interface,
such as the processing times for the machines based on the product type. You can also control
the changeover times for the different machines based on the product type in the system. Other
inputs to the simulation are the line operators currently working within the system and responsible
for specific areas. Let's run the simulation to the end and check
out some of the results for the four week period.
Moving the speed bar to full shows how fast you can get access to those all-important results.
Now it’s Friday, week four, we can see the throughput of the system is 619 finished goods off the line.
To examine some of my results, the simulation is pre-populated with various
KPIs. These are the important KPIs I want to report on. The types of measures available
to analyze are things like: units per hour, average time in the system, resource utilization
including operators, and utilization of equipment.
So this brings us onto some 'what if' analysis.
I want to change the input schedule to increase the demand for products.
Previously the system was using production schedule 1,
now we’ll switch to production schedule 2.
By running the simulation again I can now test out these new scenarios and compare KPI’s.
Feeding in extra work increased throughput to 817 finished goods.
The simulation shows you instantly where your bottlenecks exist and it’s clear in this simulation that we
have a large bottleneck before the winding stations.
Let's do some more 'what-if' analysis.
An increase in demand means your system is
going to struggle so the obvious thing to change here is the number of winding cells.
Let’s select these and create additional winding machines.
The simulation will now run with double the capacity.
Interestingly, by increasing the capacity we have in fact reduced the throughput.
There could be a number of different reasons for this happening.
If I look at my KPI dashboard in the Results Manager, I can see that the
winders are nearly 100% utilized. What would happen if we changed the number of winders?
We will recruit another member of staff on that shift to see.
The throughput has now increased to 839; however we have shifted a bottleneck to the oven area.
So did we actually require the extra winding machines? These could have cost around $1M
per machine – potentially a large investment.
Let's take them out.
This is an example of cost avoidance, and strategically placing resources within your system.
We have managed to maintain the throughput level, so actually we didn't need those extra
winding machines! We could have bought them and spent 3 million dollars but by using this
simulation we can see we don’t need to.
By using this simulation we are able to make
the most cost effective decision to drive the throughput of our Assembly line and that
decision was to employ an additional member of staff at our Winding area.
This is just one major benefit about testing your 'what-if' scenarios within simulation
before implementation in your real life system.
That was a simple introduction on how you might use a manufacturing simulation to quickly
experiment with different scenarios; allowing for data-backed decisions.
Check out more of our videos for further introductions or contact us if you would like to see something
more complex or specific to your own application. Speak to us and learn why so many process
improvers in manufacturing choose SIMUL8 for rapid accurate system modelling.