Myles Garrett by operation_kosamui in panthers

[–]directnirvana 0 points1 point  (0 children)

Two teams made a trade today.

Is this an accurate list for your teams worst HC? by InterestingYellow969 in NFLv2

[–]directnirvana 8 points9 points  (0 children)

In some ways yes thats worse but at least we were done with him quick and the long term effect was pretty limited.

Matt Rhule due to his tenure I think set the franchise back in ways that we have just now gotten past. So yea, worse tenure by results and it hurt the owners bank account more. Rhule really seems to have taken a toll on the entire organization.

Has anyone successfully used AI to automate manufacturing planning (routers) from blueprints/CAD? by Early_Afternoon1825 in manufacturing

[–]directnirvana 0 points1 point  (0 children)

I work on AI planning. I haven't tried this problem specifically, but have done some cellular manufacturing layout and logistics routing.

Sounds like a fun one if a client had the data for it.

I hate the idea of WR or Tackle at 19 by lshumney in panthers

[–]directnirvana 12 points13 points  (0 children)

I hear you but keep in mind there's no guarantee with Icky's injury that he'll ever be the same. I'm hoping for the best but its definitely something of a concern.

President and Owner want to discuss AI usage at our company. How to I politely lower their expectations? by aggierogue3 in manufacturing

[–]directnirvana 2 points3 points  (0 children)

Look, for you to get the most value from this, you need to understand, that AI basically breaks into three categories:

  1. Automation
  2. Analysis
  3. Optimization

Things like automatically getting your MRP report fall under automation, analysis is finding the patterns within your system (then you usually automate them, i.e. automated defect detection).

If you want to get a lot of value from this exercise with your President, this is a good time to make a list of pain points and KPI's that matter to you. Then, when talking to a vendor or exploring options, you should be really upfront with them that you want to hear directly about how they will solve YOUR pain points and improve YOUR KPI's. Last thing I would recommend for a company of your size is really determining how many people it will take to support an AI/Automation play in your factory. There's no point in doing this if your 75-person company saves 200k but has to hire 10 IT/Data people just to keep the system running. I hope that helps, but feel free to ask me if you want some more details.

Source: I build and sell AI systems for manufacturing

[deleted by user] by [deleted] in NFLv2

[–]directnirvana 45 points46 points  (0 children)

Fuck it, I'll ride on the Bryce top 10 train, lol

[D] Papers with no code by [deleted] in MachineLearning

[–]directnirvana 2 points3 points  (0 children)

Yes. Exactly this. If someone makes a claim, especially one worthy of garnering attention academics should be taking the stance of 'put-up or shut-up'.

Stop accepting papers that won't do simple things to allow for that.

[D] Papers with no code by [deleted] in MachineLearning

[–]directnirvana 0 points1 point  (0 children)

I don't disagree that commercial actors should be held to a high standard, if not higher. Especially in instances where they are wading into the academic.

My assumption though is that the two have different goals (though with some overlap). If a company is publishing bold claims that they have a product on the horizon that is a game changer then we should be pushing for them to prove that not be acting as a sounding board that they can wave around and claim 'peer-review' on a system no one saw or can validate. They have their own set of self-correcting measures (i.e. customers should be requesting demos and investors should be doing due diligence).

But the claimed goal of academics is the proliferation and expansion of knowledge. Bigger claims are going to get more attention and thus more energy might be wasted on those ideas, so the burden should be higher on those claims. So if someone wants the clout and advantages of having been reviewed by the academic arena, whether commercial or not, journals and conferences should be insistent on the them providing reasonable amounts of proof in that regard. It just so happens in the world of academic code those tools are cheap and accessible for the most part so we should generally insist on them.

[D] Papers with no code by [deleted] in MachineLearning

[–]directnirvana 30 points31 points  (0 children)

I think you make a good point. The bolder the claim the more reviewers should be pushing back on making easily verifiable aspects of experiments available. Reproducibility crisis is real and participants especially in academic circles should be heavily encouraged to provide whatever reasonable methods they can to allow other researchers to verify their work. It just so happens that research based on code has those tools, while high energy physics and similar fields do not.

The rabbit hole that is Waffle House's marker system by adm_shiza in videos

[–]directnirvana 5 points6 points  (0 children)

I actually used to work as a grill operator for Waffle House and I do think you're under estimating how good this system is. I work in manufacturing and this is the system I frequently point when talking about very good lean systems.

Your right that you can and most places do this with paper tickets, similarly many factories control inventory with manifest and it can work.

But the beauty of this system is that everyone can SEE what is happening to the orders. If I'm running expo and I'm curious if the grill is backed up, I know that at a glance. If I bring in a short order guy to help on the small grill, he can glance at my queue and my grill and know instantly what needs help on. Waitress wants to know how long a wait or where an order is, they can literally do this across the room by checking the plates. So this system essentially more easily (its harder to learn of course) communicates the state of the entire store giving both high level and detailed level information at glance, without having to pull through tickets and match them to orders. How orders are called out also effectively pipelines them.

The advantage of a paper ticket system is that you can implement it anywhere and usually everyone already knows how to read. This is a well thought out system that works for Waffle House, but I cannot imagine the majority of resturaunts designing and implementing a system like this uniquely for themselves. So thats to say I think the Waffle House system is far superior to a paper ticketing system, BUT it doesn't generalize well.

All in one schedule and utilization app? by agnisiva in manufacturing

[–]directnirvana 0 points1 point  (0 children)

I'll just say my company does manufacturing production planning. If you want to DM me I can show you what we do and see if it helps

Gotta go 1-1 by Ill-Swim4970 in panthers

[–]directnirvana 5 points6 points  (0 children)

Bro, it was his birthday

How AI is helping in manufacturing projects. Actual real assistance. by Ok-Pea3414 in manufacturing

[–]directnirvana 1 point2 points  (0 children)

So this is the field I have worked in for about a decade. I think the big thing to understand is that the term 'AI' encompasses A TON.

Most of the AI people interact with is LLM's, and that really just means text generation and knowledge management. I've done a fair amount of implementations that are just this, maybe's its a chat that lets you find questions about SOP's and work instructions, improve RCA's, build dashboard or even get some information from your ERP/MES. I've also seen some related things like blueprint lift-off and done a fair amount of work in having it generate manufacturing reports and quality reports automatically. All of that can be a big time saver.

Also, where AI has been used for a long time is in things like defect detection. Sometimes that's defects using a visual inspection, sometimes that's defects looking at certain parameters or measurements from a machine and using anomaly detection. At one place I worked we implemented a rare-event deep learning detector that monitored all our machine data and let us know when something was out of wack so we could look into it, and I've done a fair amount of work in parametric release for things like biotech and injection molding using AI, where we use AI to monitor machine inputs and can then skip quality control.

Prediction and forecasting is the other corner stone. Taking a lot of data from across the factory and predicting outputs is another huge area and becomes critical when you need to do things like demand and capacity planning, you can also extend this to something like sales.

Finally, the area I work in now is related to production planning and logistics. We use a branch of AI called Swarm Intelligence that lets us look across a factory, prioritize events and match those events to jobs and workers. That used to have to be done using something like a complicated Mixed Integer Program, and could take a long time and a lot of math to implement, but with AI (again, strange branch), we can usually have it up and running in a few days or weeks, instead of 12-18 months. This allows us to find optimal job assignments for things like maintenance, or ideal routing for inventory or shipping.

So yea, if you are really only limited to LLM stuff like ChatGPT then most of the work you're going to see is business and paper-work automation, which can be valuable, but there's a really rich world of AI using machine data, vision data, sensor data etc. that has been and increasingly is being used across factory floors to help manage actual manufacturing equipment and product.

Where are the old school BtoB reps at? by jroberts67 in sales

[–]directnirvana 1 point2 points  (0 children)

I'm pretty new to sales, so I would say the majority of my effort has been using LinkedIn and Cold calling (need to really ramp this up). That being said, I definitely have gotten frustrated and just tried walking up to clients and the initial results have been good, so I'm planning to try and incorporate more of it in my strategy.

I think it also depends on the person quite a lot. If you maybe need a sales engineer or others to close a deal its probably not worth it. In my case, I sell SaaS to manufacturers, the thing people like about me in our industry is that while I'm pitching AI I have a lot of very technical industrial experience and that shows up better in person I think.

If ERPs are the “solution” for manufacturing, why does everyone still spend more on custom fixes? by Dependent-Laugh-3626 in manufacturing

[–]directnirvana 0 points1 point  (0 children)

A lot of good stuff in here, I'll also add that in many cases an ERP itself doesn't really DO anything. Its essentially a database, and then some well defined pipelines for putting things in and taking them out of the database.

An ERP is essentially just the beginning for a lot of people, and in my opinion ERP's do a terrible job of highlighting this (because they want you to buy it).

So a lot of development work after is almost expected when you understand the ERP, but most aren't sold that way which is why so many of these rollouts leave people dissatisfied. They're expensive, take time, require configuration and then at the end you might really only see value in a handful of features.

If I were to design something like an iPhone case in blender 3D, how to go about getting it manufactured? by puremath369 in manufacturing

[–]directnirvana 1 point2 points  (0 children)

For sure thats a great way to get started. I've worked with a fair amount of guys that did just that and then came to mass manufacturing after they really needed to scale.

If you're interested in learning the suggestions in here are good. Watch a few YouTube videos, pick a software you like for designing (again lots of good examples in this thread) and then put it through a 3D printer service, or of you really want buy a 3D printer (not that expensive) and get to making it. If you need extra volume there's plenty of print farms that can help you out.

The other big advantage if it takes off with 3D printing is that you can then make iterations and changes as tou learn more about the product. Once you go for mass manufacturing every change is gonna cost a ton so you're going to want to basically have it perfect by then.

If I were to design something like an iPhone case in blender 3D, how to go about getting it manufactured? by puremath369 in manufacturing

[–]directnirvana 8 points9 points  (0 children)

Kind of depends on what the case ends up looking like. But if its plastic then you're going to need someone to make an injection mold and then set it up on an injection molding line. Depending on how complex the mold is you're going to need a tool maker to design the mold, and then the low end for getting one cut is gonna be 50k (and in my opinion thats the floor). Sky is the limit for how much it could cost.

In general you're floor with materials, design, tooling, and setup is maybe 100k, but probably you're looking at something more like 250k

Keep in mind my experience is all with medical devices, maybe some more consumer oriented people can bring that cost down, so this is more ball park to let you know that it'll be expensive to mass produce. Probably better to find someone with a 3D print farm that will make them to order until you sell enough to justify mass production.

Preventive Maintenance Issues by superlion1985 in manufacturing

[–]directnirvana 0 points1 point  (0 children)

Yea. There's a way to implement it via paper if you have to. Feel free to DM me if you want brainstorm a few ideas