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International Journal of Economic, Technology and Social Sciences (Injects)International Journal of Economic, Technology and Social Sciences (Injects)This paper described the design of a fuzzy logic-based temperature control system for Paint Protection Film (PPF) installation workshop spaces. PPF installation requires optimal temperature conditions (20-27°C) to ensure proper adhesion, but workshop environments often experience temperature fluctuations that compromise installation quality. The research method uses computational simulation with a modified Mamdani fuzzy logic approach, incorporating more aggressive membership functions, adaptive aggression factors, and integral control. Simulation was conducted with a setpoint of 20°C, initial temperature of 30°C, and duration of 30 minutes. Results show the system successfully achieved a steady-state error of 1.491°C, overshoot of 45.14%, and settling time of 30.0 minutes, meeting validation criteria with steady-state error < 1.5°C. The system maintained temperature within the manufacturer-recommended range for PPF installation. The research concludes that modified fuzzy logic control strategies effectively enhance system performance for specific PPF workshop applications. The main contribution is the development of a control system tailored to the specific requirements of PPF workshop environments, filling a research gap in intelligent control system applications for this context.
The research successfully designed and simulated a fuzzy logic-based temperature control system optimized for PPF installation workshop spaces.The system effectively controlled room temperature from 30°C to a 20°C setpoint within 30 minutes, achieving a steady-state error of 1.This study contributes a modified fuzzy logic control strategy tailored to the unique requirements of PPF workshop environments, addressing a gap in existing research.
Further research should investigate the integration of humidity control within the fuzzy logic system to create a more comprehensive environmental control solution for PPF workshops, as humidity significantly impacts film adhesion. Additionally, exploring the implementation of this system with real-time data from actual workshop environments, including variations in worker activity and sunlight exposure, would validate its performance under realistic conditions. Finally, a comparative study evaluating the energy efficiency of this fuzzy logic-based system against other control methods, such as PID control and conventional HVAC systems, could provide valuable insights for optimizing energy consumption and reducing operational costs in PPF installation facilities. These investigations, building upon the current research, will contribute to a more robust and practical solution for maintaining optimal environmental conditions in PPF workshops, ultimately enhancing the quality and efficiency of the installation process.
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