This Sherlock Ohms posting is a great example of the danger of assuming. He asked for 10 feet of cable, he was given a length of cable. But he didn't check to make sure he actually received 10 feet of cable.
Trust, but Verify. This example belongs in a collection of wise tales and parables handed to each new measurement apprentice. When it comes to measurements, folks should not be offended when their data is double-checked but instead remind the receiver to re-check their measurements and calculations. Imagine how much unnecessary effort and research was avoided by checking the initial value...
I'm not too sure how you get around this one. One company I consult for has work instructions AND a check list AND employee training AND there are still errors made relative to measurements. I will say this, we use a software package called MiniTab to perform Six Sigma calculations. With this software package, it is fairly easy to discover measurement errors. We always try to run a sample size of at least 30 pieces PER shift. Sometimes when we are checking against critical-to-quality specifications, we collect samples every hour for analysis. Another important factor, we always measure and calculate for gage R&R and factor that into analyzing the final data.
Many years ago a VP of engineering I knew had a sign on his office wall: "Measure twice, cut once." I memorized that one, and it's been helpful for avoiding mistakes like this one. Of course, it's easier to observe this rule when it's just you doing the measuring both times. I like the "Trust, but verify" maxim. That maxim completes the first one.
The problem came from assuming that the directions had been accurately followed. I had a similar problem when a new tech grabbed a stack of incomplete circuit boards from a stack and then was challenging me that my design was no good because the boards didn't work. I wound up posting a general memo that "designs will not perform as required unless they are built as designed." The lab manager challenged me as to what it was about, and I explained to him that it meant that the circuit boards would not work correctly unless all of the parts were installed. He agreed that was a correct assertion, and cautioned that tech to only use circuit boards that had passed the final inspection. The non-calibrated boards seldom met the requirements, and the incomplete boards never met them.
William: Your story really touches a raw nerve with me. I have lost count of how many times the "New Guy" finds errors where none exist merely because he wanted to impress somebody higher up with just how much he knows. Not all new guys, but a significant number.
@Tool_maker: That's true -- but then again, sometimes the "new guy" finds problems where no one else does, simply because all the "old guys" are so accustomed to looking at the same old problems that they no longer even recognize them as problems, but "just the way things are." Sometimes experience can be just as blinding as ignorance.
Dave: I said the new guy finds problems that do not exist, not that he finds problems which have been overlooked. For example: on parts in a car frame the only dimensions that mean anything are the areas where a robot will weld and hole locations where something else will bolt into place. The rest is just transition from point to point and unless there is an interference with something else, it is in the wind and an design engineer probably signed off on the variance when the part was tooled. Many times material has been added to improve strength. The part may be on thousands of vehicles without a problem.
Then a new quality guy comes in and rejects a delivery because an absolutely meaningless dimension is out of spec. I know every drawing should be updated in a timely fashion, but that often does not happen in the real world. One engineer at a truck manufacturer told me it cost more to change the drawing than to grant an order-order deviance. So it was only after our customer was in a "line-down" situation that someone in engineering straightened the situation out by issuing a "permanent deviance authorization. (And before anyone gripes about American made autos, this was on a Toyota.)
I am not saying this is always the case, but most times when get rejections on a part which was tooled in the 60's and has been in contiuous reorder on a variety of new models, we find there is a new guy involved. But then again the new guys often keep us dinosaurs on our toes, so it is all good.
A few years ago I was a "new guy" in a research group, and I did find a serious problem. Of course, being aware of how departmental politics worked, I was careful in handling my discovery. What I did was ask my associate, the scientist that I was supporting, what the significance of the one parameter that we were measuring meant. At first his comment was that it really did not mean very much, but then two days later he asked about how certain I was that my measurements were correct. I described my procedure and he was satisfied with the accuracy. The following Monday I was asked to join a meeting where our manager explained that my associate had noticed a problem with some of our original assumptions, (made prior to my joining the group), and we needed to make some fundamnetal changes in our research direction. It was very clear to me that this was due to my questioning about that parameter. The people that I was working with knew what had happened, and I gained a lot more respect from them after that.
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.