Considering AI? Understand what data you need at the outset - DataProphet

At the core of today's state-of-the-art Artificial Intelligence (AI) algorithms is the ability to learn patterns from a sample of data. In the manufacturing context, an example of such a pattern might be the ways in which a set of parameters contained in that data, which are related to a process in a factory, vary together. When considering using AI, it is important to understand what the data requirements are. The general answer as to what constitutes the "right" data for AI-enabled process optimisation, is the set of data that is sufficient to describe how changes to a process's parameters affect quality. The bulk of process data can generally be represented as a table, or a collection of tables, comprising columns (parameters) and rows (production examples, representing, say, one production batch per row).