This study aims to instantly measure environmental factors such as temperature, humidity and air quality and optimize the efficiency of the heating system used in the bag closing process based on these data. With the Proportional-Integral-Derivative (PID) control algorithm, it can provide energy efficiency and increase product bagging quality by dynamically adjusting the performance of the heating system according to environmental conditions. In traditional bag closing systems, heating methods that are insensitive to environmental variables lead to unnecessary energy consumption and high costs. A system optimized according to environmental factors will reduce costs by increasing energy efficiency. Providing consistent heating in different environmental conditions increases bag closing quality and ensures that products are safer and have a longer life. Thus, errors and quality reductions in the packaging process of products can be minimized. Changes in ambient temperature, humidity and air quality can create significant challenges for traditional systems. This project overcomes these challenges with the system’s ability to adapt to environmental conditions. A system that is sensitive to environmental factors and saves energy offers a more environmentally friendly and sustainable production process. This will be an important step especially for green production and sustainability policies. The ability of PID controlled systems to adapt to environmental variables offers an important innovation in terms of the integration of machine learning and automation technologies into production processes. Thanks to this system, it has been possible to close the bags at the ideal temperature by providing fast and precise temperature control with the algorithm.