Many models are used to estimate the remaining useful life for a system or component. These models rely on data collection techniques to detect and record the occurrence of data patterns that are not typically observed during normal operations. These patterns are considered anomalies.
This use case focuses on the operation of an hypothetical industrial furnace. It uses synthetic temperature data that is generated using a software program to control the mix of normal data vs. anomalies. That data is then used to ensure that the detection model is working as expected.
Dell EMC created a scenario as a story that is simple to understand, yet its solution requires developing all the important components of a realistic data analytics project. That project spans systems on the edge and in a data center. The story uses the following assumptions: