Several years ago I bought a brand-new Lexus (cost a bundle!). From the day I drove it out of the dealership, it had a severe hesitation when I stepped on the gas. I brought it in with the complaint, and was told that yes, they knew there was a problem, and that it was caused by the transmission-control software. They would replace the software and it should be OK.
They replaced the software and the hesitation was somewhat mitigated, but it didn’t go away. Since then they’re replaced the software at least twice more, and the car still hesitates. Now, when I bring the car in for a routine oil change and mention the problem to the service manager, all I get is a shrug accompanied by a “what can I do?” expression. I don’t know if the monkeys are in the engineering department (because they CAN’T figure out how to fix the problem) or in the Lexus administration (because they WON’T fix the problem). All I know is that I would not buy another Lexus. But at least I don’t get a runaway acceleration.
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.