Thanks, Tool_maker, for that input. It sounds like either SPC software needs to be adapted a lot to individual industries and/or specific manufacturers, which may take too much time and cost in engineer hours, or that users might benefit from industry-specific packages, kind of like what's emerging in industrial robotics. I know from covering machine vision that the first is sometimes simply not done for the reasons given (although the "too much" may be due to perception or procrastination), and that the second has not been successful because the technology is used so differently by each end user.
Ann. I am sure every phase of manufacturing comes complete with its own set of problems unique to that area. I work in the stamping industry and maybe it has more variables than other areas, but rarely do SPC parameters written for maching operations serve any purpose other than to frustrate stampers.
The problem in this case involved the grain produced in the raw steel when it was produced in a rolling mill. When you form the material with the grain it reacts one way and when formed across the grain it reacts another. The parts in question were round so the forming went in every direction possible. As a result points checked 90 degrees apart would have a wide variance, with one on the low side of the tolerance and the other on the high side. Both within tolerance, but with a wide enough difference that when subjected to the SPC procedure the resulting formulation flagged an out of control process that would yield bad parts.
Our eventual solution was to only check parts in a restrained condition similar to that in which they would eventually mount onto the earth mover. The biggest problem we encountered was convincing the customer QC head that his methods developed in machining raw stock and castings, were worthless when working with stampings.
There are many cases where sensors have been mounted in stamping dies to monitor and grade parts before they even exit the tool, but sometimes I think "hands on" is the only way possible to properly evaluate the product.
On re-reading Tool_maker's story I realized that not only was that inspection process flawed, but it apparently left out information that only a human could supply. I wonder whether the automatic SPC process could be adjusted with the correct information, or whether it would always take a human's explanation. In other words, can we really automate everything in QC?
Good point, Ann. While I see many economic metrics that are similar to the early 1980s, I agree that our distribution of wealth and the distribution of opportunity has changed dramatically from 30 years ago. That means fewer good jobs as a percentage of what is out there, particularly for young people.
Rob, I see your parallel with the early 80s, but so much has changed since then, including way more people and a shift to lower-paying service jobs that I don't think there are nearly enough good, mortgage-paying jobs for all of us, younger or older, in manufacturing. Or did you mean something different?
I'm still optimistic, Ann. We're seeing a lot of innovation now. This time reminds me of the early 80s. We were roaring in high tech innovation while unemployment was still very high. Eventually the innovation created jobs, which created more jobs.
Once we get more jobs, the 20-something post-grad kids will move out of their parents' home and drive housing growth.
Thanks for that summary, Rob. That's really too bad--heartening news on one hand about a really important trend, and not so happy news about the employment scene (and the ongoing mortgage scandal fallout).
Yes, given the advances in mnaufacturing, we would actually be in pretty good economic shape is we still had a housing industry and we weren't in the middle of massive layoffs of city and state workers.
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.