automated manufacturing optimization using AI
Description
Briotech is a world-class manufacturer of hypochlorous acid (HOCl)
and a pioneer of innovation for the creation of the world’s first geographically dispersed HOCl manufacturing networks, BrioWHISH® Systems (WHISH).
I worked on the WHISH for 7 months to develop an AI that predicts the outcome variable based on the machine's parameters. This is to solve a problem which will soon be explained in the following section.
Although I can't reveal full details of the proprietary deatils due to an NDA, disclosure of my contribution without revealing proprietary information has been permitted by the company.
The Problem
Because the manufacturing process of HOCl is a sophisticated task, a technician must be present to monitor the output variable of the solution, and make slight adjustments, if necessary. This was a big obstacle to Briotech's expansion.
The Solution
The solution was to automated this monitoring process with an AI. Under the guidance of a Google's AI architect, I designed and trained a supervised AI that predicts the output with a high accuracy.
Challenges
Ambiguity
Our task was simple; Briotech wants to develop an artificial intelligence that can aid their manufacturing process. With no additional instructions given, the project could go anywhere. To address this, I held weekly meetings with the management for progress reports, design proposals, and feedback. From this ambiguity, I learned the necessity of communication and thorough planning.
Scalability
With Briotech's vision to expand globally, my work had to be scalable.
Troubleshooting
AI
Communication
Our task was simple; Briotech wants to develop an artificial intelligence that can aid their manufacturing process. With no additional instructions given, the project could go anywhere. To address this, I held weekly meetings with the management for progress reports, design proposals, and feedback. From this ambiguity, I learned the necessity of communication and thorough planning.
Skills
