Autonomous decision making is the most progressive aspect of data-based decision making: Based on historical data and predictions of future events, autonomous agents execute actions on their own in order to serve predefined goals. In the ideal case, the production system acts autonomously and reacts immediately to any disturbances that occur. Compared to human decisions, opportunities can be better exploited and risks can be avoided more quickly.
Prescriptive Analytics forms the third and final stage of decision support in production engineering. In contrast to the first two stages, Descriptive (1) and Predictive (2) Analytics, not only are past events and probable future scenarios considered, but also measures are taken to continuously optimize the process. Through the continuous use of recurring simulations and forecasts, the decision-making accuracy of the agent is constantly improving.