"Quality" is a misleading word. In manufacturing, Quality is conformance to specifications. So if your design specification is junk, you can make "quality" junk. And Defect does not equal Defective. "Defective" may mean 1 or 2 Major Defects, or possibly 4 or more Minor Defects.
Quality is also "in the mind of the beholder". I remember the story of a driver who was willing to wait 2 weeks for parts for his Mercedes - "a fine piece of automotive engineering", but complained that getting parts for his Dodge would take 2 days = "piece of junk".
I agree that engineers may be hampered by the limits set by upper management. I wonder who decided that the Pontiac Fiero, which I thought was supposed to be the Pontiac Corvette, would have a 4 cylinder engine. We called it "All show, no go".
Chuck, given what you said, it is interesting to note that the differences in overall quality that I have seen are miniscule. The Consume Reports methodology is tailored to their own measurement systems. I have in the past picked products (not including cars) that were not high in their estimation, but that worked great for me and others who had them.
I prefer those measures that track actual reported defects over time. In those, as I mentioned, the probablity of experiencing a defect with any of the automobiles offered today is much lower than it was ten or twenty years ago. In addition, the difference in manufacturers rates of defects were close to zero.
I like a well laid out system as much as anyone else. On the other hand, for consumer level products, it is the results that count. Just listen to Car Talk on NPR. Most of the people who call in have foreign made cars that are older. They have problems. A car won't last forever without a lot of work. I know, I started out with small English sports cars made in the 1960's. Fun, stylish and incredibly unreliable. We often said that those parts we had the most trouble with were designed by the junior engineers. There were other parts that would last forever.
@Chuck -- in a nutshell "Those manufacturers, the Center says, tend to think in terms of systems, rather than individual parts." Wow, does this hit it right on the head. I've been teaching Systems Thinking to undergraduate future technical managers since 2000. The idea of "parts make systems" rather than "systems are comprised of parts" is something that takes quite a while to transform in our students. Not knocking 12-years of elementary and secondary school, but they too often take a bottom-up approach when it comes to teaching concepts -- picking up seemingly random concepts that are only integrated in the much higher grades, if at all. In my own experience, I didn't get the value of algebra, geometry, trig, and calculus until I took Differential Equations and applied it in my Physics and Engineering Mechanics courses.
One of the memes I use in my Systems courses is "Start from Scratch rather than Patch" -- bolting on components makes a product "multi-functional" but it does not make it "inter-functional". When each of the component parts is integrated into the design with an awareness of the other parts, the concept of "elegance" is allowed to emerge...
This post offers a pretty insightful look into the psyche of how auto makers come at creating a culture around product development. The thing that stood out to me is the whole Japanese focus on looking at engineering from a systems standpoint. Not a new concept, certainly, but definitely one we are hearing spades about as products, be it cars or aircraft, get more complex.
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.