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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 ther

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.

king_magic 9y ago
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.
- 52-6F-62 9y ago
  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.
- contingencies 9y ago
  I would be keen to have a chat. I come from a software architecture background myself, but we are working on a distributed network of local food manufacturing robotic service locations - http://infinite-food.com/ http://infinite-food.com/ - and a central industrial facility for ingredient inflow, Q/A, etc. On the latter in particular I'd be keen to pick your brain for insights as there is a whole world of machinery out there, it's not cheap, any insights in to data could be useful and we've already hired ML expertise and begun to apply it to manufacturing logistics. Send me an email if you are happy to have a chat, email in profile.

king_magic 9y ago

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.

52-6F-62 9y ago
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.
contingencies 9y ago
I would be keen to have a chat. I come from a software architecture background myself, but we are working on a distributed network of local food manufacturing robotic service locations - http://infinite-food.com/ http://infinite-food.com/ - and a central industrial facility for ingredient inflow, Q/A, etc. On the latter in particular I'd be keen to pick your brain for insights as there is a whole world of machinery out there, it's not cheap, any insights in to data could be useful and we've already hired ML expertise and begun to apply it to manufacturing logistics. Send me an email if you are happy to have a chat, email in profile.