Artificial intelligence’s main draw is its ability to extract complex pattern from a date sample. A sufficient data set will explain how quality is affected by process parameters changes. A data column should include the representation of a quality result. The parameters should be either controllable or non-controllable. They key row-wise data requirement should ensure its data represents it process and how such interactions will affect future quality. Continued availabilty of consistent data is a key component for success.
Key Takeaways:
- There should be requirements to regulate artificial intelligence in manufacturing.
- The data requirements for artificial intelligence should inform the machine on how to perform a task.
- The data available to artificial intelligence should be updated and improved.
“It’s important to note that data might not contain a full representation of how quality is measured in the factory.”
