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Medium-sized can be in the $10 million per year range.

Let's take plastic injection molding since it's such a good example of a really broken industry (there are a small number of excessively competent injection molders and a vast legion of incompetent ones).

You're shooting a part every couple of seconds (or faster), and that injection molding machine has lots of knobs to dial in. Temperature of incoming plastic pellets, water content of incoming plastic pellets, dye feed rate, plastic feed rate, mixing chamber temperature, feed screw motor load, initial injection pressure, plateau injection pressure, release injection pressure, actual pressure inside the mold, time spent cooling--I can go on and on and on.

Most injection molding problems generally get solved one way: increase injection time. It's fairly straightforward to adjust, isn't likely to make things go wrong, and the people on the line don't get paid to experiment. They've got 100K parts to shoot in 72 hours, and an hour lost is a thousand or so parts they're going to get yelled at for. Better to dial the time up 10% and take 79 hours rather than experimenting for 7 hours and not shooting or waste a bunch of plastic.

Of course, if this is your only hammer, you can see where this is going. Every single time something goes wrong, that mold gets another 10% added to its cycle time. And it never goes the other way without "A Pronouncement From God, Himself(tm)". Eventually, your entire business is running at 50% productivity because all the molds are shooting so slow and you think you need to build another factory when what you need to do it fix your molding times.

Now, back to sensors--the problem is that nobody with incentive has a way to identify AT THE TIME IT CAN BE DEBUGGED that "something is going wrong". Someone on the line dialing up the injection time should cause an immediate dump of ALL the data on that machine (probably a week or more+) up to an engineer who can go through it looking for anomalies. Even better would be for the machine to flag to an engineer any "likely anomalies" (an increase in incoming plastic pellet water content should get flagged, for example) so that they can be corrected before they affect the injection process and cause failures/wastage.

This is, of course, all predicated on logging an enormous amount of data and being able to run an analysis against it in almost real-time.

Handling this data is non-trivial.




Thanks for this. A long-ago summer job was running those machines to make things like mirror rims and taillights. I still have a couple of the fantastic blobs produced when changing over from one job to another.

One of the things that struck me then is how much the line workers were treated like furniture, when many of them were quite sharp. They took such pride in getting things done well and at speed, in continually improving. I really wish I could put that kind of data in the hands of a couple of the people who trained me. Just an app on their phones. Spending 40+ hours/week on a machine means you really get to know it. I'd love to see how many of them would get great first-pass analysis and remediation.


I don't understand why such a system needs to look at every data point. Are the failures so rare that you can't get away with sampling?


Usually the cause that requires high sampling is vibration. But that can be condensed with FFT stuff easily.

Honestly from working in plastics and sensor design for 15 years it usually boils down to engineers not willing to let go of information because they envisage potential future issues. Its easier to imagine problems in a meeting than to imagine and deliver solutions upfront before the problem ever happens. Also, a lack of care for the economics of doing such sampling.

That's not to say there is an easy fix. These same people are the ultimate end customer who have the final word on such engineering environments.




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