Neural net predictive control in factories
A self-calibrating neural net predictive control unit for a certain type of factory machinery. Simulations have shown its potential to prevent accidents with humans and cut energy use by > 70 % vs state-of-the-art controllers, which prevents factory downtime and damage to products (Will tell you more in conversations, I'm currently filing for patent :)
Why this is huge:
The controller addresses issues at the top of users problem list, and brings the performance of old machines to the level of new ones without any other hardware change. There are 4 million machines in use, 400'000 being installed each year, growing at 6-8 % annually.
How we'll make money:
Each unit will cost Eleatec < $ 1 k (off-the-shelf parts) , can easily save users $ 100 k , and when priced at $ 5 k -including installation- should sell like hot cakes considering how annoying the issues it solves are, and how much hassle switching to new machinery would be. Eleatec will sell to large distributors for $ 3 k per unit (whose life the device will make easier as well). The goal is to have 0.8 % of machinery retro-fitted in five years, which means a $ 100 million revenue for Eleatec at contribution margins upwards of 66%.
Current state (6 months since raw idea, been working alone):
Why work with me:
I WORK LIKE THREE
Feel free to share or call anytime!
+4368110293749 email@example.com www.linkedin.com/in/alexandermarkhayes/