How Machine Learning can help SMEs to maximize the value of operational data

Data generated by manufacturing or process operations, especially time series data, is very rich in information that can provide actionable insights on the current and future health of the production systems and the products they create. As companies start to digitize their industrial operations, they are learning that they are rich in operational data but poor in the ability to analyze such massive amounts of it. As a result, much of this data goes underutilized as traditional approaches such as regression models, statistical process control (SPC) and optimization have limitations to effectively leverage multivariate trends and uncover new insights for improving operations. A key source of insights in time series data comes from multivariate trends, also called patterns, which are often reviewed forensically to understand past system behavior. Such patterns are often hard to describe and cannot be easily captured by traditional analytics approaches.