IMPROVING ENERGY EFFICIENCY IN GRAIN GRINDING PROCESSES THROUGH MOISTURE CONTROL AND PROCESS AUTOMATION

УДК 664.7.047

Abstract

This paper investigates energy efficiency improvement in grain grinding processes with a focus on moisture control and process automation, using a flour milling enterprise as a case study. Special attention is paid to energy-intensive operations such as grain grinding and the processing of intermediate products, which account for the major share of electricity consumption in flour mills. The current state of electrical energy consumption in milling equipment is analyzed, and standard values of specific electricity consumption per ton of flour are reviewed. The study examines the influence of grain milling properties, particularly moisture content, on energy distribution and consumption across technological systems. The results show that grain moisture level has a significant impact on electricity consumption during grinding, and a reduction in specific energy consumption is observed when optimal moisture conditions are maintained. However, the analysis also reveals the absence of modern measurement and control devices for real-time monitoring of moisture during the conditioning process. To optimize production processes and reduce energy consumption, the implementation of an automated monitoring and control system for grain conditioning is proposed. The recommended system includes grain moisture sensors, grain flow measurement devices, a microprocessor-based control unit, and an automated water supply control module. Theoretical and experimental assessments indicate that stabilization of grain moisture through automation can reduce electricity consumption by approximately 2–3%. The proposed approach contributes to improved energy efficiency, rational resource utilization, and enhanced economic performance of flour milling enterprises.

Аннотация

В данной статье исследуется повышение энергоэффективности процессов измельчения зерна с акцентом на контроль влажности и автоматизацию процесса на примере мукомольного предприятия. Особое внимание уделяется таким энергоемким операциям, как измельчение зерна и переработка полуфабрикатов, на которые приходится основная доля потребления электроэнергии на мукомольных заводах. Анализируется текущее состояние потребления электроэнергии на мукомольном оборудовании и пересматриваются нормативные значения удельного расхода электроэнергии на тонну муки. В исследовании изучается влияние свойств помола зерна, в частности, содержания влаги, на распределение и потребление энергии в технологических системах. Результаты показывают, что уровень влажности зерна оказывает существенное влияние на потребление электроэнергии во время помола, и при поддержании оптимальных условий влажности наблюдается снижение удельного энергопотребления. Однако анализ также выявил отсутствие современных измерительных и контрольных устройств для мониторинга влажности в режиме реального времени в процессе кондиционирования. Для оптимизации производственных процессов и снижения энергопотребления предлагается внедрение автоматизированной системы мониторинга и управления процессом кондиционирования зерна. Рекомендуемая система включает датчики влажности зерна, устройства для измерения расхода зерна, микропроцессорный блок управления и модуль автоматического управления подачей воды. Теоретические и экспериментальные оценки показывают, что стабилизация влажности зерна с помощью автоматизации может снизить потребление электроэнергии примерно на 2-3%. Предлагаемый подход способствует повышению энергоэффективности, рациональному использованию ресурсов и повышению экономических показателей мукомольных предприятий.

Ключевые слова: измельчение зерна, энергоэффективность, контроль влажности, автоматизация процесса, потребление электроэнергии, мукомольный завод, удельный расход энергии.

Keywords: grain grinding, energy efficiency, moisture control, process automation, electricity consumption, flour milling, specific energy consumption.

Introduction

The continuous rise in global energy demand and the corresponding increase in electricity costs have intensified the need for energy-efficient technologies across all sectors of industry. Among these, the grain-processing and flour-milling industries are recognized as some of the most energy-intensive within the agro-industrial complex. In these operations, a significant portion of electrical energy—ranging from 60% to 75%—is consumed by grinding and classification systems, which involve the repeated crushing, sifting, and pneumatic transportation of grain and intermediate products. Therefore, improving the energy efficiency of these processes is a crucial factor in reducing production costs and enhancing the competitiveness of flour-milling enterprises.

In Uzbekistan, the milling sector plays a vital socio-economic role, providing the population with staple food products such as flour and semolina. According to national industry data, over 5 million tons of grain are processed annually across hundreds of milling facilities. However, the majority of these enterprises operate with outdated equipment and low automation levels, leading to high energy losses and inconsistent product quality. For example, energy audits conducted by the Tashkent State Technical University and Tashkent Agrarian University have shown that the specific electricity consumption per ton of flour in Uzbekistan’s mills is 1.5–2 times higher than in comparable European facilities. This discrepancy is largely attributed to inefficient energy use, inadequate process monitoring, and the lack of adaptive control systems for moisture conditioning and material feed [4, 9–11].

Moisture control represents a particularly critical aspect of the milling process. The mechanical resistance of grain to grinding strongly depends on its water content: excessively dry kernels cause excessive friction and increased electricity consumption, while overly moist grains can cause clogging, uneven particle sizes, and reduced throughput. Consequently, maintaining an optimal moisture level during the conditioning stage—known as otvolazhivanie (hydration and tempering)—is essential to achieving both energy efficiency and high product quality [3, 17–20].

Despite the importance of this process, many flour mills in Central Asia, including “GALLA-ALTEG,” rely on outdated conditioning systems with limited measurement and feedback capabilities. Operators must manually regulate water addition based on approximate empirical assessments, which results in fluctuating moisture content and inefficient energy utilization. This manual approach not only reduces process stability but also prevents consistent quality control across production batches [10, 11, 18, 19].

In light of these challenges, the modernization of conditioning and grinding systems through automation and digital control technologies has become an essential priority. The integration of microprocessor-based controllers, moisture sensors, and data-driven feedback systems allows continuous monitoring and optimization of process parameters. Recent developments in industrial automation, particularly under the “Industry 4.0” framework, provide new opportunities for creating intelligent systems capable of adaptive self-regulation and predictive maintenance [6, 7].

The objective of this research is to analyze the specific energy consumption patterns of the “GALLA-ALTEG” flour mill and to develop a comprehensive model for improving energy efficiency through moisture control automation. The study also aims to determine the relationship between grain humidity levels and energy expenditure, as well as to evaluate the potential energy savings achievable through intelligent process regulation. The research findings contribute to the broader field of sustainable grain processing by offering practical solutions for integrating energy management and automation in industrial-scale milling operations.

The question of energy efficiency in grain milling has been the focus of extensive research across both international and regional contexts. Flour-milling plants consume large amounts of electricity, mainly in mechanical grinding, pneumatic conveying, and sifting operations. The modernization of these systems through moisture control and automation has thus become a central priority for improving operational performance and reducing costs.

Studies conducted by the U.S. Department of Energy and European milling associations have shown that energy use in flour production ranges between 45–100 kWh per ton of product, depending on plant configuration, transport type, and level of automation [1].

One of the earliest comprehensive studies on energy optimization in milling was conducted by Galitsky, Worrell, and Ruth (2003), who analyzed the corn wet-milling industry and identified process integration, motor control, and air management as key drivers of energy savings of up to 20%[1].

In recent years, Tchoffo Houdji et al. (2022) conducted experiments on small-scale corn mills and demonstrated that controlling induction motor speeds through variable frequency drives (VFDs) significantly improves grinding efficiency while reducing total power use (Energy Efficiency, 2022). These results emphasize that the control of motor torque and speed directly affects flour granularity and energy output [2].

The physical structure of wheat grain — composed of bran, aleurone layers, and starchy endosperm — exhibits strong dependence on moisture content during grinding. Conditioning or tempering softens the outer bran layers, facilitates separation, and reduces mechanical resistance during milling.

According to Dziki (2023), hydrothermal treatment of wheat at controlled temperatures (15–20 °C) and moisture levels (14–15%) enhances the efficiency of grinding and leads to lower energy consumption per unit of flour output [3]. The hydration process causes partial swelling and loosening of endosperm structures, allowing smoother passage through the rollers.

However, over-moistening the grain can cause adhesion between kernel layers and hinder the separation of endosperm and bran. Thus, a narrow moisture control window is crucial.

In the context of Uzbekistan and Central Asia, Kalandarov and Mukimov (2021) developed and tested automated grain-humidity control devices for flour mills. Their experiments demonstrated that real-time feedback systems integrating moisture sensors, flow meters, and microprocessor-based controllers can ensure uniform hydration, reducing energy use by 2–3% while maintaining consistent flour quality [4, 10, 11].

Similarly, Kalandarov and Ubaydullayeva (2023) proposed a digital control architecture using adaptive algorithms for continuous monitoring of grain moisture during the tempering process [5]. Their research emphasized the integration of smart sensors and industrial communication networks to minimize manual intervention in flour-milling operations.

The implementation of automation technologies in grain processing has evolved substantially with the advent of Industry 4.0 frameworks. Grassi et al. (2020) presented an Industrial Internet of Things (IIoT)–based control system for milling processes using Near-Infrared (NIR) spectroscopy to monitor moisture and temperature in real-time [6]. Their work demonstrated how integrating electric drive supervision with digital twins can enhance process stability and energy utilization.

Recent designs such as the Automated Flour Recirculation and Dust-Free Grinding Mechanism developed by Baluprithviraj et al. (2024) show how modern engineering solutions can simultaneously improve worker safety, environmental cleanliness, and energy performance [7].

These innovations underline the transition from simple mechanized control to intelligent, data-driven systems capable of predictive regulation.

In regional studies, Bazaluk et al. (2022) examined energy-saving approaches in post-harvest grain cleaning systems, reporting up to 18% energy reduction with the use of automated control schemes[8].

Their findings are in line with local research in Uzbekistan by Mukimov & Kalandarov (2021), who confirmed that adaptive control of water dosing and tempering time significantly improves energy balance and flour output quality.

Despite these advancements, several research gaps remain evident:

• Many existing systems rely on static control algorithms that do not dynamically adapt to fluctuating input conditions such as grain type, initial moisture, and temperature.
• Few studies address the coupled relationship between energy consumption and grain conditioning, treating them as separate processes rather than interdependent systems.
• In Central Asian contexts, particularly Uzbekistan, the practical implementation of automated energy-management frameworks is still limited due to equipment costs, outdated control systems, and lack of digital infrastructure.

The reviewed literature highlights that energy efficiency in grain grinding depends on three interlinked parameters: grain moisture control, motor power regulation, and automation integration. While developed countries have made notable progress in applying IIoT and sensor-based solutions, developing economies are still in the transitional phase. Therefore, comprehensive studies combining hydrothermal conditioning dynamics with automated process control are needed to bridge this technological gap and achieve sustainable production efficiency in the milling industry.

Materials and methods

The research was conducted at the “GALLA-ALTEG” Joint-Stock Company, a flour-milling plant located in Tashkent, Republic of Uzbekistan. The enterprise operates two parallel production lines, each with a daily processing capacity of 200 tons of wheat, producing high-grade and first-grade flour. The plant is equipped with a conventional roller-mill system and employs pneumatic transport for internal material transfer. The total installed electrical capacity of the plant is approximately 400 kW, with the grinding section accounting for nearly 70% of total power consumption.

The study focused on analyzing the energy distribution and specific energy consumption (SEC) within various technological subsystems of the mill, including: Grain cleaning and preparation, Breaking (coarse grinding) systems, Reduction and sifting systems, Pneumatic transport, Auxiliary drives and aspiration systems.

The analysis also included the conditioning section (otvolazhivanie), where grain moisture is adjusted prior to grinding. This section was of particular interest due to its significant influence on milling energy efficiency.

Energy consumption data were collected using digital power analyzers (model: Metrel MI 2892 Energy Master), capable of measuring voltage, current, and power factor with 0.2% accuracy. The devices were installed on primary feed lines supplying each subsystem [1, 8].

To measure grain moisture content, a capacitive grain moisture meter (Pfeuffer HE 50, Germany) was employed, calibrated within the 8–20% range. Temperature and humidity during conditioning were monitored by HOBO MX1101 environmental sensors [15, 16].

For automation experiments, an experimental microprocessor-based control unit was assembled using an Arduino Mega 2560 board connected to digital flow meters, solenoid valves, and temperature-humidity sensors (DHT22). The system provided continuous real-time monitoring of the conditioning process, controlling water addition through a pulse-width modulated (PWM) valve actuator.

The study consisted of two main experimental stages:

Baseline Energy Audit: In the first stage, energy consumption was measured for all mill systems operating under standard (manual) control conditions. The data were collected over 10 consecutive working days to establish baseline averages for each subsystem.

Automated Conditioning Experiment: In the second stage, the automated moisture control system was implemented in the conditioning unit. The system regulated water addition automatically based on sensor readings of incoming and outgoing grain moisture [4, 5, 10]. Energy consumption was monitored under identical operational loads, allowing for direct comparison between manual and automated conditions.

The specific energy consumption (SEC) for each technological subsystem was determined using the following equation:

where:

— average power of subsystem i (kW),

 — operation time (h),

— processed grain mass (t).

The total specific energy consumption of the plant was then obtained as the sum of the individual subsystem consumptions:

Comparative analysis between manual and automated operation modes was performed using the relative energy saving coefficient (η), calculated as:

All measurements were repeated three times to ensure reproducibility. Data were processed using OriginPro 2023b and MATLAB R2022a software for statistical evaluation and graphical visualization. Mean values, standard deviations, and correlation coefficients between grain moisture and energy consumption were calculated.

Regression analysis was used to model the relationship between moisture level (X, %) and energy demand (Y, kWh/t) [3, 8]. The dependence was found to be nonlinear and approximated by a second-degree polynomial:

This model allowed the estimation of the optimal moisture range that minimizes energy consumption while maintaining flour yield and quality.

To validate the proposed automation system, results were compared with published benchmarks from international studies such as those by Dziki (2023) and Bazaluk et al. (2022), as well as domestic works by Kalandarov and Mukimov (2021).

The comparison confirmed that automated humidity regulation under Uzbek milling conditions yielded comparable energy savings to those achieved in modern European facilities—approximately 2–3% reduction in SEC, depending on grain type and ambient humidity.

Results and discussion

The results of the experimental analysis conducted at “GALLA-ALTEG” reveal distinct patterns of electrical energy consumption across the milling process. The findings confirm that the grinding, sifting, and pneumatic transport systems remain the most energy-intensive stages, accounting for approximately 70 % of total electricity use. The automation of moisture conditioning contributed to a measurable reduction in total energy consumption and improved uniformity of flour quality.

Table 1 presents the baseline distribution of electrical energy among major technological subsystems during standard (manual) operation.

Table 1. Distribution of Energy Consumption in the Mill

Interpretation: Grinding and sieving stages jointly consume more than 40 % of total energy, confirming that material-reduction systems are the main energy sink. Idle energy accounts for roughly one-quarter of total demand, indicating substantial potential for energy recovery through motor control and automation.

4.2. Specific Energy Consumption Standards

Table 2 compares typical specific energy consumption (SEC) values for different milling configurations. The data illustrate the impact of transport type (mechanical vs pneumatic) on overall electricity use.

Table 2. Approximate SEC for Flour-Milling Plants

Interpretation: Pneumatic conveying increases SEC by 25–40 % compared with mechanical transport because of higher airflow resistance and frictional losses. Speed control of blower motors and optimized pipeline routing are thus essential for reducing specific energy consumption.

4.3. Energy Distribution under Industrial Conditions

A detailed energy audit was performed at the GALLA-ALTEG plant operating at 200 t day⁻¹ per line. Table 3 summarizes the relative power consumption of each subsystem.

Table 3. Energy Distribution in the Mill (200 t day⁻¹)

Figure 1. Energy Distribution in the Mill

Interpretation: Grinding and breaking together consume nearly 47.5 % of total electricity, while pneumatic transport accounts for 12 %. Auxiliary drives (10 %) and aspiration systems (<1 %) show relatively small contributions. This distribution emphasizes the importance of targeting the grinding line for energy-saving interventions.

4.4. Energy Distribution within the Breaking Systems

To refine energy diagnostics, each of the six breaking systems was analyzed separately (Table 4).

Table 4. Energy Distribution across Breaking Systems

Interpretation:

The first three systems together account for more than 15 % of total plant energy. Their optimization—through balanced feed rates, uniform grain size, and roller pressure control—offers the greatest immediate savings.

4.5. Energy Distribution in Intermediate Grinding Systems

Table 5 illustrates energy consumption for the regrinding of intermediate (semolina and dunst) products

Table 5. Energy Distribution for Intermediate Product Grinding

Interpretation: Energy distribution across regrinding systems demonstrates diminishing consumption from C-1 to C-9, consistent with the gradual size reduction of material. Entoleators consume nearly 5 % due to high rotor speeds, but their role in improving product hygiene justifies this expenditure. Nonetheless, motor speed optimization could reduce their load by 10–12 %.

An analysis of energy distribution indicates that improving production efficiency and conserving all types of resources represent the most critical directions for enterprise development. Along with an increase in production output, the reduction of the energy intensity of the production process becomes an increasingly important task [1, 8, 17].

In the field of energy conservation, the primary strategic focus of the joint-stock company GALLA-ALTEG is cooperation with scientific institutions aimed at implementing advanced high-efficiency technologies and realizing innovative energy-saving projects [4, 15, 16]. The analysis shows that more than 13 types of equipment are employed in the production of high-grade flour at the enterprise. The total installed power capacity reaches approximately 95–100%, while the actual operating load is about 75–80%. Specific electricity consumption is one of the key indicators characterizing the technological properties of grain [3, 12, 13, 20]. The results of this study demonstrate that specific electricity consumption is determined by the structural and mechanical properties of the grain and is strongly influenced by the organization of the grinding process as well as the hydrothermal conditioning (tempering) stage.

An examination of electricity consumption distribution reveals that up to 90% of total energy usage is associated with the production process itself, whereas transmission losses account for approximately 9–10%. Therefore, priority measures should be directed toward reducing energy consumption and improving energy efficiency within the production process.

To further decrease electricity demand in flour-milling plants, it is necessary to conduct in-depth research and continuous development of modern milling technologies in order to achieve high efficiency, compactness, economic feasibility, and ease of maintenance. At the same time, particular attention must be paid to monitoring and optimizing the hydrothermal conditioning process. In this context, the implementation of automation systems is one of the most urgent production tasks. The increasing use of sensors and software solutions replaces manual control by mill operators and ensures stable operation as well as continuous quality control in flour production.

Conclusion

In the flour-milling industry, the most energy-intensive stages are grain cleaning, grain grinding, and the processing of intermediate products. Optimization of these processes requires effective management of the entire production system. To address this challenge, the implementation of an integrated automated system is recommended, comprising the following key components: (1) a measurement device for monitoring grain moisture during the conditioning (tempering) process; (2) a grain flow rate sensor; (3) a microprocessor-based unit for process monitoring and control; and (4) a water supply control unit. Such a system enables automated regulation of grain moistening using high-precision measuring instruments and sensors. Theoretical calculations show that the application of this technology makes it possible to stabilize grain moisture levels, resulting in a reduction in energy consumption by approximately 2–3%.

The implementation of an automated grain conditioning control system contributes to the rational use of resources, improves the efficiency of production processes, and reduces overall energy costs [4–7, 10, 11]. As a result, the competitiveness of the enterprise is enhanced, and profitability increases due to more effective satisfaction of market demand for flour products. Grinding of grain and intermediate products remains the primary source of energy consumption in flour-milling operations. Addressing this issue requires precise regulation of the grain conditioning system. For this purpose, the use of an integrated automated system is recommended, consisting of a grain moisture measurement unit, a grain flow measurement unit, a microprocessor-based monitoring and control device, and a water control and regulation unit. The integration of these components forms a comprehensive automatic monitoring and control system that enables automated grain moistening based on high-accuracy grain moisture meters and grain and water flow sensors. Overall, the proposed system allows stabilization of the output grain moisture, which in turn leads to a reduction in electricity consumption by 2–3%. The adoption of automation-based grain conditioning management ensures rational grain utilization, enhances production efficiency, and improves energy-saving performance in flour milling. Moreover, rational distribution of electrical energy contributes to a reduction in energy intensity and supports sustainable growth of the enterprise’s gross output.

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