Furnace Temperature Curve Model Based on Particle Swarm Optimization

In this paper, based on the process parameter distribution of industrial automation equipment, an optimization control model is proposed, which adopts advanced numerical methods to adjust the parameters, and introduces the particle swarm optimization algorithm to finely control the process parameters in multiple regions. Experimental results show that the optimization algorithm can effectively improve the accuracy of equipment parameter adjustment, so as to ensure the stability of production process and product quality. This method is not only applicable to traditional industrial automation control systems, but also plays an important role in the field of intelligent manufacturing. Future research can further expand the model to adapt to more complex industrial scenarios, and provide theoretical basis and technical support for the formulation of multi-dimensional control strategies.