Comments on: Predicting Process Variability

By: Combining Lean Six Sigma with Simulation Software | Pyzdek Institute

Combining Lean Six Sigma with Simulation Software | Pyzdek Institute — Fri, 08 Feb 2013 19:35:43 +0000

[...] is the opening line from a Predicting Process Variability blog. It is also, according to the blog, “the driving force behind most improvement [...]

By: Human Judgment Beats Simulation | Success in Simulation

Human Judgment Beats Simulation | Success in Simulation — Fri, 09 Jul 2010 13:27:43 +0000

[...] you haven’t read it, I’d suggest you pause now and read the blog on Predicting Process Variability. Did you pass the test? Don’t feel bad, almost no one does. My facility is much more complicated [...]

By: Rufaidah

Rufaidah — Fri, 19 Mar 2010 17:17:20 +0000

It is important to predict the variability in any project, simulation helps to do that

By: nurozge

nurozge — Mon, 06 Apr 2009 15:19:51 +0000

By using simulation we have an idea about process variability. I also agree that many complex systems can be modeled by using simulation easily (easier than the other methods).

On the other hand, simulation does not give us exact answers, it gives us estimates. Moreover, the number of replications, and/or run-lenght should be taken into account to conclude.

By: Fay

Fay — Mon, 30 Mar 2009 03:40:17 +0000

Simulation is an important tool to predicting process variability. Using simulated data to develop and study for data analysis is very beneficial. In mathematics area, people can gain insight about what happens when assumptions are needed to be proved by simulating models. And we should pay attention that simulated data related to process variability is a reasonable representation of what one would usually expect in the real world.

By: Fay

Fay — Mon, 30 Mar 2009 03:38:59 +0000

Simulation is a important tool to predicting process variability. Using simulated data to develop and study for data analysis is very beneficial. In mathematics area, people can gain insight about what happens when assumptions are needed to be proved by simulating models. And we should pay attention that simulated data related to process variability is a reasonable representation of what one would usually expect in the real world.

By: Success in Simulation » Blog Archive » Six Sigma and Simulation: Part 1

Sat, 06 Dec 2008 00:48:50 +0000

[...] rarely perform exactly as predicted” was the starting line for the blog Predicting Process Variability and is the driving force behind most improvement projects. As stated, variability is inherent in [...]

By: dsturrock

dsturrock — Mon, 03 Nov 2008 16:42:58 +0000

Answers to the questions.

In a system where every customer arrives exactly 60 seconds apart and every customer requires exactly 55 seconds of service, customers will never have to wait. The answer is zero because every customer will be done, 5 seconds before the next customer arrives.

In a system where customers arrive an average of 60 seconds apart and customers require an average of 55 seconds of service (both following exponential distributions), an average customer will wait about 10 minutes! If you do short simulation runs, you may see different answers, but if you do a statistically valid simulation run of a non-terminating system, you should be able to confirm this answer.