Optical component manufacturing is a complex process involving multiple processing stages.
It is considered a complex system of systems.
The slight performance failure in a small number of machines or steps will affect the final product’s quality. Industrial Internet of Things (IIoT) deployment in such manufacturing environments provides data related to the human, machine, and environment of the manufacturing system.
Machine learning techniques applied to the process data can produce a predictive model that takes intermediate measurements, sensor readings and operating parameters as the input and produce product quality and yield predictions as its output.
Further more, sensor data can be used to produce a predictive model capable of predicting machine wear and failure.
Reinforcement Learning algorithms are applied to IoT data to produce optimal decision making policies for maintenance and operation decisions.