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by mediaman 1395 days ago
I'm a partner in a factory and I believe this is an incredibly important area, and the requirements are fairly different than normal "just put it on Confluence" workplaces, in a way that most tech people don't understand and usually completely miss the mark when they're doing product dev.

- Your team is out on the floor. Their hands have grease on them. Using tablets sounds great until you're trying to use it with a glove on it, or your hands are dirty, and it's hard to get grease off tablets. But they need the info out on the floor. Also, it can be noisy on the floor.

- The team tends to be very visual. They don't like tapping on computers a lot. Literacy ranges from pretty good to kinda OK. Sometimes they refuse to get (or wear) reading glasses for whatever personal reason.

- They're working on proprietary hardware, but technicians with the right knowledge are not nearby to come in and look at it. You really need to be able to see the issues visually. Sometimes even hear them. AR might be interesting here. (I spend $10k to fly a tech out for a few days to look at a machine. The bigger issue is that I lose $10k a day from one machine being down, and a tech might not be available to fly out for a week.)

- Predictive maintenance. The fancy sensors and whatnot mostly don't work. Tech people try it in a clean, quiet office and it works, and they can raise money on it from clueless VCs, so money keeps getting set on fire with smart AI machine learning magic motor sensor companies.

- Preventative maintenance. How to schedule, how to verify it was done, how to check whether it revealed an issue that needs a follow-up. Getting people to do it, and verify it was done, can be a challenge, but there are huge returns to preventative maintenance (for example: checking gearbox oil levels, verifying lubrication line function, checking valve temperatures.)

- Diagnosing machine problems. Using prior problem documentation helps team members see most likely issues. But many of these people don't really want to sort through a database of prior similar issues because they "know" what the problem is. How do you provide this information to them in a way that feels more approachable to them?

I could go on forever. Manufacturing is an interesting environment because downtime is usually hundreds to tens of thousands of dollars of hard cost per hour, depending on the operation, and they will spend quite a bit of money to stop it from going down, but culturally there's a vast gulf between the white collar SF tech bros and what actually happens in manufacturing plants, so innovation tends to be more limited.

3 comments

Predictive/preventive maintenance is actually a big thrust behind my current company, Dials.

HOAs, which we serve, are run by busy volunteers, yet expected to perform almost insane financial gymnastics, planning 30 years of major component replacement, e.g. common area roofs, piping, asphalt resurfacing. This involves (a) estimating each component's lifetime (total and remaining), (b) getting a cost estimate, and (c) coming up with a plan to spread paying for it out over however many years before it's needed, breaking that up between the units in the HOA, and collecting the funds, month after month.

People blame cultural issues ("people won't pay for maintenance") or "laziness" but the truth is, it's just too damn hard to do predictive/preventative without a very accurate inventory of what you have. You need to get all of this into a cloud environment, and then somehow expose it so that either internal staff or external vendors (more common) can see exactly what you have, bid on fixing it, and track status and work in a fine-grained way.

Our ultimate goal is doing the entire inventory automatically using computer vision (partner and I used to work in self-driving) and having enough data around that we can price and estimate everything accurately.

Nobody wants to pay for this as a standalone product so we just decided to build a payment collection product (for monthly dues), start with that, and build it up. It's going pretty well and we'd love to get more people on it. Email's in my profile in case you want to chat

Tracking stuff is hard. I wonder why QR codes won't work in this case, or something similar, or super basic otherwise / stickers or codes at first. Might be more annoying to generate and maintain them initially. CV could work really well to keep track of inspection steps as well, or to recommend what you should do next, and how to do it
We considered this, but it's another step. What I'm talking about is going to be hard and take a while, but feels like the "endgame" for how this is going to be done--automated, done with phones, no extra work.
This is really compelling!

How will you protect from incorrect estimates, insurance?

It sounds really interesting to work in a manufacturing plant for a year or two in order to empathize with the industry and learn how to blend in software in a way that actually solves problems like you describe. Or, generally, to penetrate areas where technology solutions don't apply obviously. I wonder how you'd set that kind of arrangement up. If you could design a company around displacing a few cofounders for a few years where the product research is hands on, on the ground, doing the job, I bet there are many people who would be interested in this type of setup. I agree the software industry does way too much "solve for ourselves first" type of product development and it's really discouraging.
On-site visits, or contract work on the shop floor should be a good way in. Alternatively pro-bono work, part time or longer.
I think a key point that people fail to remember or marketing just oversells, is that there is no silver bullet for all the problems, especially for an industry that has so much history, precedent and inertia. People want to try and solve (and from the other side, want perfect full solutions) all problems at once, whilst in reality small improvements in key areas are probably the 80/20 that is needed to bring business value. I think continuous feedback and good "translators" would be key for any product in those industries. Manufacturing people are busy and will tell you what the surface level pain point is, but they don't have the time or maybe don't have the idea fully thought out on what the underlying problem/goal is.

After typing up all that, I realise that most of this is applicable to every industry.

Spot on, many of these challenges are common across the board - from my father's plant to Pfizer and others I got the chance to work with. There is however a massive talent gap when it comes to high quality software / ML people in these industries as well. It's tough to get experts to generate quality data and 'recipes' for others to follow when their KPIs are not aligned. Maintenance and reliability don't seem to be sexy enough areas for management to invest in, especially if the value proposition is anecdotal at best. Would be great to chat about your approach for solving some of the above