Electricity Consumption Forecasting and Digital Energy Management in the White Goods Manufacturing Sector
Year: 2025
Type: conference-paper
Abstract: Electricity is the most widely used type of energy in the production sector. It has a direct impact on the cost of electrical energy and sustainability in production processes. In order to ensure electricity supply security, accurate forecasting methods must be applied. With the integration of digitalization into the production sector, data collected from production is analyzed and more effective decision-making processes are supported. In this study, estimation models were developed based on the electricity consumption of machines used in the oven business of a white goods manufacturing company. By taking the electrical energy data consumed by a machine in a certain time interval, different estimation methods were applied and energy consumption for the next period was estimated. In this way, cost calculations were made and energy management processes were improved. Digitalization in the manufacturing sector increases efficiency while also reducing costs. Analyzing data collected from machines on digital platforms helps businesses manage and optimize their production processes more effectively. Planning energy use with accurate estimates provides businesses with both sustainability and cost advantages. Digitalization also offers opportunities such as monitoring machine performance, detecting faults in advance, and developing planned maintenance strategies. As a result, digitalization plays a critical role in sustainability and competitive advantage by ensuring effective management of electrical energy in the manufacturing sector. In this study, since electrical energy is a scarce and valuable resource, alternative forecasting models with high modeling success were analyzed to support planned consumption and strategic decision processes.
Authors: Ayse Irem Kilitci, Irem Duzdar
Institution: Düzce Üniversitesi
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7104048625
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