Dynamic prediction for process control

摘要

Product data from a manufacturing process is analysed using techniques adapted from the study of chaos. Future values of a series of product data are predicted and an attractor structure is determined from the product data. This enables the manufacturing process to be monitored, controlled and analysed. Action can be taken to modify the manufacturing process using the results from the prediction and attractor structure to reduce costs and improve performance and efficiency.