
The Machine Learning Opportunity in Manufacturing, Logistics - rbanffy
https://www.nextplatform.com/2018/02/01/machine-learning-opportunity-manufacturing-logistics/
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Bucephalus355
I don’t think people realize how big a trend in general manufacturing will be
in the future. The life cycle of the world can best be described as new
systems / software supporting new infrastructure / hardware.

We’ve had 40 years of massive improvements in software and code. There have
absolutely been hardware improvements in that time, but we haven’t seen the
levels of improvement we saw from 1920 to 1960 for example. The reason for
this is that software or hardware tends to dominate for 40 or so years,
followed by a reverse, where the new area takes advantages of the advances
laid down in the other. This dynamic tends to play out in other fields of a
soft science or liberal arts supporting a hard science.

Interestingly, the 40 year pattern tends to hold for national real estate as
well, where prices tend to shift back and forth between coastal areas and the
“inner US”.

All of this means that the mid-west, with its incredibly cheap real estate and
100+ year history of manufacturing won’t be the new Silicon Valley ever, but
it will be what it once was, a great place to be during a dominant era of
American manufacturing supported by advances in software. Probably will also
decline again at some point too though.

Also there are plenty of places in Ohio where you can get a 2500 square foot
100k house in a reasonable school district in a town of 200k+. Also means SF
and NY real estate likely to revert to what it was like in the 1970’s, a super
cheap albeit dangerous place to live.

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markdoubleyou
This article basically says that there's a trend of increasing interest. Well,
that's great--I'm sure there's plenty of interest from industrial firms. But
there's a lot of grunt work that needs to be done before anyone can hope to
make real money off ML in this space... industrial equipment is often ancient
and analog, standards are all over the place, and the talent pool isn't there.
GE learned this the hard way with Predix.

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king_magic
Yup. This is my day-to-day life. Yes, huge industrial firms might have a ton
of data... but it might be spread out over 5000 hard drives from 1995-present.
It's extremely hard for an outside AI/ML startup to target that type of space,
because they just don't have the data. Or the knowledge that lives in the head
of a 30+-year-engineer who knows everything about every piece of equipment
that has ever been used on a manufacturing floor.

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52-6F-62
Do you work directly for a manufacturing company/relevant company?

I wonder if this would be a better opportunity for an outside firm in a
longer-term contractual role, so that they both have some autonomy but also
access to the data. At least that way they come away with field-knowledge but
would obviously be restricted in terms of the proprietary data.

I don't know how real-world unrealistic I am being, but for instance:

\- Pitch the potential project, including its mass of limitations, but also
its end product / projects given x is possible, y is possible, z is possible,
etc

\- Present a contract that allows for years, potentially, and enough running
capital to hire a staff that can handle modeling the schema, collecting
arranging the data, interviewing the experts and quantifying their
understanding if necessary.

I mean, if there's a perceived and expected value out of doing it, surely
there could be some compromise like start with one sub-process and one type of
machine and go from there?

Do you imagine it should need to be holistic?

Or, maybe design a new machine?

For instance, at a major auto sub-manufacturer they are _extremely_ critical
and thorough with their quality controls. Currently, this is done 100%
manually. Parts (pre- and post-assembly) every N parts or H hours are pulled
off the line while the line runs, taken to the lab, welds tested, measurements
tested against calibrations, and in some cases chemical tests made to ensure
proper galvanization.

That data could be entered initially and measurement data accumulate pretty
rapidly.

I'm sure that process could be replaced for the most part using the AI/ML.

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whatever1
Yes let's do heuristics instead of first principle modeling and rigorous math
programming / control.

