Detailed Integrated Simulation of a PID Controller and an Automated Production Management System

Abstract

This paper investigates the application of a classical Proportional–Integral–Derivative (PID) controller augmented with an adaptive supervisory mechanism for managing production and inventory systems under variable demand and time-delay conditions. Unlike traditional process control, industrial production and inventory operate on macroscopic time scales (hours to days), where delays and stochastic disturbances significantly affect system stability. A simulation-based study is conducted to evaluate the performance of the proposed PID + supervisor framework in comparison with a fixed-gain PID controller. Results demonstrate that the adaptive scheme significantly reduces inventory oscillations, overshoot, and root-mean-square error while smoothing production rates. The approach is computationally efficient and can be readily integrated into existing manufacturing execution systems, providing a robust and practical solution for real-time production–inventory regulation.