Day: December 12, 2008

Six Sigma and Simulation

Today, I stumbled over a blog article Six Sigma and Simulation Part 2 written by Jeff  Joines, who is an Associate  Professor in Textile Engineering at NCSU.   He identifies the areas he feels that Monte Carlo simulation can be used in each of the phases of the DMAIC process.

Define

*Estimate cost savings for each project by indicating variability instead of using single-point estimates; provide a more reliable estimation as well as a confidence level of achieving the estimated savings.

Analyze and Improve

*Design of Experiments (DOE) (Full, Fractional, Mixed, etc.) is the most common tool utilized that provides a base line to illustrate improvement when changes are made, as well identifying factors of interest to control or change.
*DFSS – If the product or process does not exist as is the case in a Design for Six Sigma, simulation models can be used to ascertain capability of a new process and product before implementation.
*Cost reduction of performing a DOE (i.e., raw material cost, cost of shutting down current process). You can determine the process capabilities and ascertain the potential improvements while minimizing time and expenditures.
*Multiple processes that feed one another. Transfer functions can be generated from a traditional DOE on each individual process but not the entire system. A simulation model can be used to combine each individual transfer function into determining the capability of the whole system as well as testing a wider range of values.

Control
*Simulation can also be used as a process control aid as the process is being implemented to determine potential problems.


I don’t know Jeff’s background and experience with Six Sigma, but he did a very nice job in both blogs explaining the Six Sigma methodologies. To read either posting in their entirety, visit Success in Simulation. I am looking forward to the third and final posting in the series.

Three Creatures of Finance and Risk

In a recent comment, I considered the role of speculators in the current volatility of oil prices (and, with the help of a savvy columnist, found them innocent of price manipulation).  At the time, I was under the impression that a speculator was the same kind of critter as a hedger or an arbitrageur.  Not so.  I have been corrected, and now realize these three creatures of the financial world are distinct individuals.  What lumps them together is risk and risk assessment.

While a speculator is someone who accepts a risk of loss in return for a possible reward, the hedger is a more conservative creature.  He or she–or, in the case of a business, it–makes an investment as insurance against loss.  A hedger calculates the value-at-risk in an investment in one market  and then makes a corresponding, opposite investment in a different market. The hedger swaps the probability of big win for the increased probability of a smaller win.

I, however, am a true fiscal chicken and 99 percent risk averse.  So I believe that if risk is what the speculator and the hedger have in common, what they should also have in common is some good operational risk software.   The same is true of the arbitrageur, whose modus operandi I will consider in my next column.