The aim of this study is to suggest a reliable low cost smart system for automating the heat treatment process. This system will reduce human direct interaction. The Fuzzy-PI control algorithm combined with ON/OFF algorithm was designed to automate the whole system operations. The overall automated furnace system includes control unit, algorithm, sensor and drive circuit was simulated in MATLAB/Simulink, tested for different heat treatment techniques. Normalizing and annealing heat treatments were performed on AISI1040 steel using a traditional method as well the embedded system with Fuzzy-PI control. The results show that the suggested Fuzzy-PI control algorithm and whole furnace system can reproduce any desired and arbitrary heat treatment technique curve with minimum error. Heat treatments resulted in significant changes in microstructure and hardness of the AISI1040 steel under investigation. In addition, there is no significant differing between the microstructure and hardness of AISI1040 steel after traditional and automated heat treatment processes. Where the hardness after traditional normalizing heat treatment was 234 HV, while it was 232 HV after automated normalizing heat treatment system. This confirms that the proposed automatic control system for heat treatment processes is reliable and useful in reducing the cost and time spent in these processes.

这项研究的目的是提出一种可靠的低成本智能系统，以使热处理过程自动化。该系统将减少人与人之间的直接互动。模糊PI控制算法与开/关算法相结合，旨在使整个系统运行自动化。整个自动化炉系统包括控制单元，算法，传感器和驱动电路，均在MATLAB / Simulink中进行了仿真，并针对不同的热处理技术进行了测试。使用传统方法对AISI1040钢以及带有Fuzzy-PI控制的嵌入式系统进行正火和退火热处理。结果表明，所提出的Fuzzy-PI控制算法和整个熔炉系统可以以最小的误差再现任何期望的任意热处理技术曲线。热处理导致所研究的AISI1040钢的组织和硬度发生了显着变化。此外，经过传统的和自动的热处理工艺后，AISI1040钢的组织和硬度之间没有显着差异。传统的正火热处理后的硬度为234 HV，而自动正火热处理系统的硬度为232 HV。这证实了所提出的用于热处理工艺的自动控制系统是可靠的并且在减少这些工艺中花费的成本和时间方面是有用的。传统的正火热处理后的硬度为234 HV，而自动正火热处理系统的硬度为232 HV。这证实了所提出的用于热处理工艺的自动控制系统是可靠的并且在减少这些工艺中花费的成本和时间方面是有用的。传统的正火热处理后的硬度为234 HV，而自动正火热处理系统的硬度为232 HV。这证实了所提出的用于热处理工艺的自动控制系统是可靠的并且在减少这些工艺中花费的成本和时间方面是有用的。