[AT] Statistics In Tractor Manufacturing Was Bicycle Program

Jim Thomson macowboy at comcast.net
Sun Sep 15 05:41:24 PDT 2019


I have used statistics for the past 25 years or so in a manufacturing setting. I would bet the farm that if a good root cause investigation took place on this model from NH, one of the results you would probably find that every component or system was designed without the interactions with other systems taken into consideration. For example, I led a investigation for a class III medical device that was under FDA recall notification for a major global medical device manufacture. The device was a defibrillator which is considered a life sustaining device. The device was failing its IPX5 water ingress test and devices  were shorting out in the field. To sum things up, the R&D designers put the design on paper, threw it over the wall to manufacturing. As the individual processes of components varied over time, there was a tolerance stack up issue which caused the cases not to seal correctly. If, the variability of the individual components were modeled using a Monte Carlo simulation which takes this into account, the problem would have been addressed before it was released to the public. Toyota does this with their cars on all their systems. This is why they are so reliable but even they miss things once in a while. On the antique tractor side of things, they were designed with generous tolerances and overbuilt for what they had to do. That is why they are still around after many years of use. The John Deere G is a perfect example of a over built tractor designed to last.

Jim Thomson
Rehoboth, MA   


> On September 14, 2019 at 11:26 AM James Peck <jamesgpeck at hotmail.com> wrote:
> 
> 
> Some years ago I did participate in an academic Statistical Quality Control course. Much of the course involved the Weibull Distribution. If I remember correctly, the Weibull Curve predicted the lifespan of a manufactured assembly such as a tractor.  It appears to be a gift from the mathematicians.
> 
> https://en.wikipedia.org/wiki/Weibull_distribution
> 
> The same distribution probably predicts that Cecil’s New Holland money pit will continue to be so and will suffer an early demise.
> 
> [Stephen Offiler] I never took a whole semester of Statistics.  Instead, we had a course called Engineering Experimentation, which was heavy on experiment design and statistical data analysis.  That gave me a very good appreciation for the practical application of statistics.   Out in the real world, on-the-job training programs in quality control principles in manufacturing (Deming, Juran, Lean Six Sigma) continued to solidify the practical applications.
> 
> [Cecil Bearden] Steve: I nearly flunked statistics I only passed because I was a graduating senior.  However, I did flunk Rocks & Clods 2124 and had to find another 4 hours to graduate.   Then 35 years later I retire as a Geotechnical engineer designing foundations. !!!  
> 
> [Stephen Offiler] I'm not sure if that is an interesting statistic, or simply predictable statistically.  All you just said is that a bell-curve distribution for 2-year degrees overlaps a bell-curve distribution for 4-year degrees.   
> 
> [ James Peck] The interesting statistic is that some technical 2 year programs have higher starting incomes than many 4 year degree programs. People who complete such a program can later take a 2+2 program to get a four year degree if they choose.
> 
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