SMART ENERGY MANAGEMENT FOR CONTINUOUS MANUFACTURING

ABSTRACT

In continuous manufacturing industries such as cement, chemicals, pulp & paper, and metal processing, energy consumption is intensive and crucial for uninterrupted operation. Smart Energy Management (SEM) systems have emerged as transformative solutions to address inefficiencies by combining physical upgrades, such as Combined Heat and Power (CHP) and steam system optimization, with digital tools like IoT and AI. This paper analyzes the impact of SEM technologies on energy efficiency, maintenance costs, and operational reliability. Results show that CHP systems can improve efficiency up to 90%, predictive maintenance reduces costs by 30%, and IoT-based systems cut energy use by 18%. Quantitative indicators, including energy efficiency, cost reduction, and downtime minimization, support SEM as a strategic tool for achieving sustainability and industrial resilience in continuous operations.

АННОТАЦИЯ

В отраслях непрерывного производства, таких как цементная, химическая, целлюлозно-бумажная и металлообрабатывающая промышленность, энергопотребление является интенсивным и критически важным для бесперебойной работы. Системы интеллектуального управления энергией (SEM) представляют собой преобразующие решения, направленные на устранение неэффективности за счёт физических модернизаций (например, когенерации и оптимизации паровых систем) и внедрения цифровых технологий, таких как IoT и ИИ. В статье анализируется влияние технологий SEM на энергоэффективность, затраты на обслуживание и надёжность работы. Результаты показывают, что когенерационные установки могут повысить КПД до 90%, предиктивное обслуживание снижает затраты на 30%, а IoT-системы сокращают энергопотребление на 18%. Количественные показатели подтверждают, что SEM является стратегическим инструментом для достижения устойчивого развития и повышения надёжности промышленных систем.

Keywords: smart energy management, continuous manufacturing, energy efficiency, predictive maintenance, IoT in industry, CHP systems, thermal optimization, downtime reduction, sustainability.

Ключевые слова: интеллектуальное управление энергией, непрерывное производство, энергоэффективность, предиктивное обслуживание, IoT в промышленности, когенерационные системы, тепловая оптимизация, сокращение простоев, устойчивое развитие.

Introduction. In continuous manufacturing, which includes sectors like cement, chemicals, pulp & paper, and metal processing, energy consumption is both extensive and critical to uninterrupted operations. These industries often run 24/7 and rely heavily on thermal and electrical energy. It is known that the main share falls on thermal energy: 81% in the chemical industry, 77% in metallurgy, 74% in the cement sector, and 68% in the pulp and paper industry [1,2]. Despite its essential role, much of this energy is used inefficiently, underscoring the urgent need for smarter energy practices. Smart Energy Management (SEM) introduces an integrated approach to reduce energy waste and improve operational efficiency. Modern Combined Heat and Power (CHP) systems, for instance, can elevate energy efficiency levels from around 30% to as high as 90%. Meanwhile, upgrading steam systems through insulation, leak repair, and process control can save 20–50% of thermal energy [3]. These measures not only cut costs but also significantly reduce emissions, supporting global sustainability goals.

Materials and methods. Digital technologies are further transforming energy practices. A recent 2025 study showed that factories using IoT-based monitoring systems reduced energy use by 18%, decreased downtime by 22%, and improved resource utilization by 15%. Predictive maintenance powered by Industrial IoT (IIoT) has been shown to lower equipment failure rates by 70% and reduce overall maintenance costs by 30%. Smart systems also enable real-time control, optimized load scheduling, and energy benchmarking [4]. The application of Smart Energy Management (SEM) technologies across continuous manufacturing industries has shown significant gains in efficiency, cost savings, and reliability. Our analysis reveals that the integration of advanced thermal and digital control systems has had a measurable impact on operational performance and sustainability metrics.

Figure 1. Energy Efficiency Improvements by SEM Technologies

Figure 1 presents a comparative assessment of four major SEM technologies. Combined Heat and Power (CHP) systems lead with an average efficiency improvement of 60%, drastically enhancing the fuel-to-energy conversion ratio. Steam system optimization, including insulation and leak management, contributes up to 35% savings in thermal energy. These improvements are particularly impactful in sectors with high process heat demand, such as chemical and cement industries. Smart Energy Management (SEM) combines physical upgrades and digital innovations like IoT and AI to reduce energy consumption by up to 18% and maintenance costs by 30%. These technologies enhance efficiency, reliability, and sustainability in continuous manufacturing operations. Energy efficiency is the ratio of useful energy output to total energy input, expressed as a percentage. This metric evaluates how effectively a system converts consumed energy into productive output. The formula is given by:

where is the energy delivered to the process;  is the total energy consumed by the system. For example, Combined Heat and Power (CHP) systems often achieve efficiencies up to 90%, significantly higher than conventional systems. Maintenance cost reduction is another critical KPI, especially relevant when implementing predictive maintenance systems. It is calculated as the percentage reduction in costs before and after SEM implementation:

where  and  represent maintenance costs before and after the application of SEM solutions. Predictive maintenance enabled by smart sensors can reduce costs by 30%, prevent breakdowns, and extend the operational life of equipment.

Downtime reduction is vital in continuous manufacturing since any interruption affects productivity and profitability. This indicator measures the improvement in system uptime due to SEM application:

here,  and  denote the total downtime before and after applying smart energy solutions. SEM systems that integrate IoT and AI can reduce unplanned downtime by over 20%, increasing production availability.

Table 1.

Comparative Data for SEM Technologies

Conclusion. To illustrate these concepts, Table 1 presents average values of energy input and output, along with maintenance costs, from selected technologies. These values are based on industrial benchmarks from case studies in Europe and North America. The data clearly show that SEM technologies not only increase energy efficiency but also reduce costs significantly. Smart Energy Management (SEM) offers a strategic solution for continuous manufacturing by integrating efficient technologies and digital tools like IoT and AI to optimize energy use, reduce costs, and enhance system reliability. With potential efficiency gains of up to 60%, SEM not only supports economic performance but also advances sustainability by cutting carbon emissions and ensuring compliance with energy regulations. As global decarbonization pressures rise, SEM is becoming essential for building resilient, efficient, and future-ready industrial operations.

References:

1. International Energy Agency. (2023). Energy Efficiency 2023. IEA. https://www.iea.org/reports/energy-efficiency-2023
2. Zhang, Y., Li, H., & Wang, J. (2023). Smart energy management strategies for continuous manufacturing systems: An industrial case study. Journal of Cleaner Production, 412, 137152. https://doi.org/10.1016/j.jclepro.2023.137152
3. Tanaka, K. (2021). Energy efficiency improvement and smart energy management in continuous process industries. Energy Policy, 156, 112429. https://doi.org/10.1016/j.enpol.2021.112429
4. Hasanbeigi, A., & Price, L. (2020). A technical review of emerging technologies for energy efficiency and greenhouse gas emission reduction in continuous manufacturing industries. Renewable and Sustainable Energy Reviews, 131, 110038. https://doi.org/10.1016/j.rser.2020.110038
5. Rakhmonov I.U., Kholikhmatov B.B., Korjobova M.F., Otepbergenov Sh.T. Research of the problem of voltage asymmetry in the operating mode of an arc furnace // “Science and Education in Karakalpakstan” 2024 №4/1 (44). рр. 190-194.