Electricity consumption forecasting and alarm application in the white goods sector

Electricity is the most widely used energy source in the white goods manufacturing sector, directly impacting production costs and sustainability. Accurate electricity forecasts are essential to ensure the security of electricity supply. The white goods sector is significant for both the Turkish and global economies, making efficiency in this sector highly important. Given Turkey's strong position in white goods production and its global impact, efficient management of energy consumption is critical for sustainability. Effective use of valuable resources like electricity is vital for reducing costs and mitigating environmental impacts. With digitalization, data can be collected from production processes and processed for better management. This study applied forecasting models based on the electricity consumption of machines used in a furnace operation of a white goods manufacturing company. By analyzing the electricity consumption data of a machine used in production over a certain period, future electricity consumption is forecasted, and cost estimates are made. Digitalization enables more effective management of critical factors such as energy consumption by facilitating data collection and analysis in production processes. Efficient use of important resources like electricity is crucial for cost control and sustainability. With digitalization, the energy consumption data of machines used in white goods production can be monitored and analyzed in real-time. This allows for forecasting future energy needs and taking appropriate measures. Additionally, automation and alert systems brought by digitalization help prevent energy waste and increase operational efficiency. This study aims to reveal the positive impacts of digitalization on energy management, making industrial processes smarter and more sustainable. Since electricity is a valuable and scarce resource, the study analyzes alternative forecasting models with high modeling success to form the basis for planned consumption and strategic decisions. Keywords: Electricity consumption, Prediction model, Data mining, Digitalization.