With the rapid development of online shopping and prosperity of the e-commerce industry in recent years, traditional warehouses are struggling to cope with increasing order volumes.Accordingly, smart warehouses have gained considerable attention for their relatively high efficiency and productivity.In such warehouses, robots transport shelves to pi
This paper presents a framework to utilize multivariate time series data to automatically identify reoccurring events, e.g., resembling failure patterns in real-world manufacturing data by combining selected data mining techniques.The use case revolves around the auxiliary polymer manufacturing process of drying and feeding plastic granulate to ext
Amounts of historical data collected increase and business intelligence applicability with automatic forecasting of time series are in high demand.While no single time series modeling method is universal to all types Dining Table of dynamics, forecasting using an ensemble of several methods is often seen as a compromise.Instead of fixing ensemble d