Strict Quality Requirements Research Articles

Next-Gen AI Quality Checks: Redefining Data Integrity in Automated Workflows

There is a growing need for strong methods to guarantee the accuracy and reliability of data due to the widespread use of next-generation AI in automated processes. This research delves into new approaches to rethink AI system quality checks, with a focus on context-aware, adaptable, and dynamic validation. Modern artificial intelligence ecosystems are notoriously difficult for traditional data integrity frameworks to manage due to the sheer volume and variety of data streams and continuous learning paradigms used therein. A proactive and scalable quality assurance methodology is proposed by this study by combining state-of-the-art methods including feedback loops, explainable AI, and anomaly detection. Research shows that using these methods greatly improves AI-driven processes in terms of accuracy and dependability while decreasing the likelihood of bias, mistakes, and inefficiencies. Findings from this research highlight the need of continuously improving quality assurance procedures for sustaining credibility and efficiency in the age of intelligent automation. This paper delves into the changing landscape of quality assurance in AI-driven processes, with a focus on how automated workflows must prioritise data integrity. With their reliance on varied, high-volume information and complicated algorithms, next-generation AI systems are dynamic and complex, making traditional quality checks inadequate. In order to guarantee strong data integrity, this study suggests a new AI quality assurance system that combines adaptive mistake detection, predictive analytics, and sophisticated validation techniques. The framework reimagines quality standards in AI operations by using state-of-the-art technologies such as blockchain for traceability and federated learning for decentralised validation. There are noticeable gains in efficiency, accuracy of decisions, and reduction of errors in empirical assessments. The results highlight the need to reconsider quality standards in order to build trustworthy and reliable AI ecosystems, which will allow for their ethical and scalable implementation. Organisations striving to align AI systems with strict quality and integrity requirements in increasingly automated settings might look to our work as a benchmark.

Characterisation of defects following MicroCT sampling inspection of specimens produced by electron beam powder bed fusion

ABSTRACT With the maturation of metal additive manufacturing (AM) technologies, and the evolution of the machine capabilities, the discussions in literature are pivoting towards reliability and quality of the components produced. There is still much concern amongst stakeholders in the medical, aerospace and automotive industries about whether metal AM parts will meet many of the strict quality requirements. Following a Systems-V approach to quality assurance verification, this work focused on the characterisation of defects detected by µCT sampling scans of Ti-6Al-4V specimens produced via electron beam powder bed fusion (EB-PBF). Pore characteristics were classified by volume, surface area, diameter, compactness, sphericity, spatial distribution and orientation. From a statistical analysis of these attributes, a covariance matrix was established that revealed defect dependencies important to consider for manufacturing quality components in EB-PBF. Due to the sampling method employed, the results were combined with machine process parameters to predict the expected levels of porosity for the entire specimens with good agreement. Thus, this work provides evidence in support of quality verification by µCT sampling methods.

Taking pleasure in distinction: Unlocking specialty coffee preference

Specialty coffee, comprising a tenth of the global coffee trade, is distinguished by its strict quality requirements and traceable origins. The diverse flavor profiles of specialty coffee raise demands on providers to serve individual taste preferences. Prior research has not sufficiently explored how to predict customer preferences for specific flavor profiles or how these preferences influence behavioral intentions such as revisiting or recommending a café. This study hypothesized that customer involvement, the extrinsic factors of coffee experience, and culinary risk-taking would predict flavor preference, which would in turn affect behavioral intentions. In an experiment involving 47 participants, individuals tasted and evaluated two espresso flavor profiles in a counterbalanced order. Results showed that taking pleasure in buying coffee, an aspect of involvement, significantly predicted preference for a distinctly acidic single-origin flavor profile over a more conventional blend. However, factors such as interest in involvement, sensory and service quality aspects of the café experience, and culinary risk-taking in coffee consumption were not significant predictors of coffee preference. Furthermore, there was no significant relationship between coffee preference and the intention to revisit or recommend the establishment, though individual evaluations of each coffee were predictive of these behavioral intentions. These results refine the existing theory linking specialty coffee consumption and consumer behavior, particularly highlighting the role of acidity in flavor preferences. They also confirm the link between the sensory experience of tasting specialty coffee and subsequent behavioral intentions, applicable across diverse flavor profiles.

ВЛИЯНИЕ КИСЛОРОДСОДЕРЖАЩИХ СОЕДИНЕНИЙ НА ОСНОВНЫЕ ЭКСПЛУАТАЦИОННЫЕ СВОЙСТВА ДИЗЕЛЬНЫХ ФРАКЦИЙ

A complex analysis of the latest world research has revealed the tendency of using oxygen-containing compounds as promoters of the fuel combustion process capable to reduce harmful emissions, to identify the need of improving the environmental properties of diesel fuels associated with stricter quality requirements. Due to the significant growth of the diesel car park both in the world and in Russia in particular, the increase in emissions of nitrogen oxides has become an urgent problem and an important task is to find ways to solve it. The following research objects were selected for experiments: straight-run oil fractions with boiling points 180-240°C and 240-290°C. As oxygen-containing additives, it was proposed to inject the following oxygenates belonging to different classes of compounds: isopropyl alcohol, ethylcarbitol, methyl carbonate. The concentration of the oxygenate additive varied in the ratio from 1 to 5% in order to find the optimal balance between the cost-effectiveness and effectiveness of its action. Mixtures of diesel fractions with oxygen-containing additives in various concentrations have been studied in order to improve operational and environmental characteristics: kinematic viscosity, flash point in a closed crucible and low-temperature properties such as: freezing point, turbidity point and limit filterability point of diesel fuel have been measured. It was revealed that the oxygen atom in the composition of the oxygenate groups of the introduced additives made it possible to produce a more complete combustion of fuel, respectively, to reduce the amount of harmful emissions in the form of unburned hydrocarbons into the environment. Indirectly, it was possible to show that oxygenate mixtures with diesel fractions contributed to reduce emissions, thereby increasing the environmental performance of exhaust gases. The optimal ones are proposed.

Thermal Measurements Based on Image Processing for <i>In Situ</i> Monitoring of 3D Fused Filament Fabrication (FFF)

Nowadays new applications based on the 3D printing technique demand increasingly strict product quality requirements. The in-situ monitoring of variables associated with the manufacturing process through the application of different techniques could help to evaluate the process and ultimately to ensure product quality. In this regard, the acquisition and evaluation of variables and indexes derived from thermographic analysis during the process are key for an early defect detection and can contribute to quality estimation. In this work, a new methodology is proposed for the monitoring and analysis of the additive manufacturing process based on the processing of thermographic images from an LWIR (Long Wave Infrared) camera. The methodology and the suitability of the variables and indexes extracted during the monitoring of the manufacturing process are discussed for the case of a 3D fused filament fabrication of polymers.

STRATEGI PENGEMBANGAN USAHATANI JAGUNG (Zea Mays L.) DI KABUPATEN KARO, SUMATERA UTARA

Corn (zea mays) is one of the potential food crops aimed at improving the national economy. The increase made in corn production through the suppression of corn imports by the government so that the land for corn development can be utilized. Karo Regency is a corn production center in North Sumatra that has the potential to develop corn farming with a land area of 107,241 ha with a production of 715,940 tons. The purpose of this study was to analyze the corn farming development strategy and the internal and external constraints faced in corn farming activities. The research method used is descriptive method and data collection techniques are carried out using observation, interviews and questionnaires. There are two sub-districts as samples, namely Simpang Empat and Barusjahe Districts. The analysis technique used is descriptive and SWOT analysis. The results of the study indicate that the development strategies that can be carried out in corn farming in Karo Regency are (a) increasing the bargaining power of farmers in the context of industry/traders that impose strict quality requirements; (b) increase productivity to prepare for competition from imported corn products; (c) planning for weather variations to improve the quality of corn produced by farmers; (d) increase the knowledge and capacity of farmers in the context of controlling pests and diseases in maize; (e) reduce corn production costs to reduce fluctuations in production, quality, and price

Правовые основы ответственности производителей лекарственных средств

The author compares the concepts of ‘”circulation of medicines” and “pharmaceutical activity”. The main content of the text is an analysis of the responsibility of manufacturers for damage caused to the health of citizens by substandard, falsified medicines. The relevance lies in the fact that now, during the pandemic, special attention is being paid to new medicines. Due to the fact that they are a special type of product, they are subject to strict requirements for quality, safety and effectiveness, compliance with which also falls on manufacturers of medicines, which once again underlines the need for clearly defined responsibility of manufacturers of medicines. In conclusion, the author suggests possible changes in the legislation on the responsibility of the manufacturer of medicines.

Design of Online Detection System of Boiler Water Quality Based on STM32

Industrial boilers have strict requirements for water quality. It is necessary to adjust water treatment measures and regular blowdown according to the monitoring of phosphate and soluble silica content in boiler water to avoid boiler scaling, corrosion, and deterioration of steam quality, and prevent major accidents. The traditional boiler water quality detection technology has a strong lag and long detection time, which cannot meet real-time online detection. Aiming at the requirement of detection of phosphate radical and soluble silica content in boiler water quality, a portable and low-cost online detection system of boiler water quality based on STM32 was studied. The pump valve flow path is constructed with a syringe pump equipped with a syringe and a distribution valve, LED and silicon photocell are used for the light source and detector of the system respectively, and the photoelectric detection part is composed of a designed Z-shaped flow cell, which reduces the experimental cost; Design a data acquisition circuit based on STM32 microcontroller and a 16-bit high-precision analogy-to-digital converter, as well as a constant-current drive circuit for driving LED light sources, to improve the stability and high precision of the automatic measuring instrument. The system test results show that the boiler water quality online detection system based on STM32 can accurately detect the phosphate and soluble silica concentrations in boiler water quality.

Energy- and Quality-Aware Task Offloading for WebVR Service in Terminal-Aided Mobile Edge Network

Web virtual reality (WebVR) is gaining increasing attention as interactive VR experiences become more prevalent. The high energy consumption and strict quality requirements are still significant challenges for its application in the mobile edge network. In this context, content caching and task offloading are promising solutions to save the energy of WebVR. This paper proposes a hybrid decentralized offloading architecture in which the MEC server and multiple terminals jointly participate in the caching and processing of WebVR tasks. In this framework, the graph convolutional network and unsupervised clustering algorithm are jointly applied to process the WebVR service feature graph to achieve FoV-level content caching. Moreover, WebVR users with idle computing resources assist neighboring users with performing tasks. On this basis, we propose a distributed low-bound-based alternative direction method of multiplier (LADMM) algorithm to optimize the offloading mode and the allocation of tasks and computing power resources to minimize system energy consumption. The proposed offloading mode can lower energy consumption while maintaining a good balance between delay performance and resource utilization.

IMPROVEMENT OF THE MODE OF OPERATION OF BIOLOGICAL WASTEWATER TREATMENT FACILITIES

Despite the strict requirements for wastewater quality, intensive pollution and accumulation of industrial pollution, potentially hazardous substances, continues in the places of wastewater discharge. Therefore, the aim of the study is to improve the operation of biological wastewater treatment plants to ensure compliance with environmental requirements. To achieve this goal, the features of wastewater treatment are analyzed and it is found that the treatment process depends on the concentration of activated sludge, the amount of air and the properties of the wastewater entering the treatment. With this in mind, it is proposed to adjust the ratio of "sewage active sludge air" to ensure compliance with environmental requirements. Factors influencing the cleaning process are also identified. Such factors are the consumption of wastewater coming for treatment, oxygen saturation of the mixture of activated sludge and wastewater, the quantity and quality of activated sludge fed into the aeration tank. In addition, the peculiarities of the processes occurring in different parts of the buildings are taken into account, and it is proposed to divide the cleaning process into two stages. The first stage takes place in the first corridor of the aeration tank (regenerator), where the activated sludge enters for regeneration. The second stage covers the second or third corridors of the aeration tank and the secondary settling tank, where the wastewater is first mixed with activated sludge, then the mixture is discharged to the secondary settling tank. An experimental study of the cleaning process was carried out, as a result of which the necessary data for the mathematical description of the processes were obtained. After processing the experimental data, regression equations were obtained that describe the purification processes in the system "aeration tank-displacer - secondary settling tank", namely the change in the concentration of activated sludge at the outlet of the regenerator and the change in the concentration of contaminants in the purified water. The adequacy of the equations was checked according to Fisher's test. It was found that the equations are adequate to real processes within the accepted conditions and assumptions. Analytical solutions of the obtained equations allow to analyze the course of purification processes at different stages, to determine the influence of factors on the process. A procedure for the use of equations is proposed, which allows without additional experiments to choose the mode of operation of biological treatment facilities, which will ensure compliance with environmental requirements.

Indoor Air Radon Concentration in Premises of Public Companies and Workplaces in Latvia.

Considering the multitudes of people who spend their time working indoors in public premises and workplaces, it is worth knowing what their level of exposure is to natural radioactive radon gas, the second most widespread and dangerous carcinogen for lung cancer development after cigarette smoking. This state-level study covered most of the territory of Latvia and conducted 941 radon measurements with Radtrack2, placed for 4–6 months in the premises of public companies, educational institutions, medical care institutions, etc. The study found that 94.7% of samples did not exceed the national permissible limit (200 Bq/m3), the level at which preventive measures should be initiated. The median value of average specific radioactivity of radon in these premises was 48 Bq/m3 (Q1 and Q3 being 27 and 85 Bq/m3), which is below the average of the European region. Slightly higher concentrations were observed in well-insulated premises with plastic windows and poorer air exchange, mostly in schools (59 (36, 109) Bq/m3) and kindergartens (48 (32, 79) Bq/m3). Industrial workplaces had surprisingly low radon levels (28 (16, 55) Bq/m3) due to strict requirements for air quality and proper ventilation. Public premises and workplaces in Latvia mostly have low radon concentrations in the air, but more attention should be paid to adequate ventilation and air exchange.

Port Community Systems: Accelerating the Transition of Seaports toward the Physical Internet—The Portuguese Case

Supply chains are complex systems that have grown in dimension and spread worldwide. In supply chains, physical and information flows have strict service quality requirements, namely transparency conditions and traceability. Seaports, connecting land and maritime transport, are special components of supply chains where multiple players interact with different perspectives, and conflicting goals may arise. Port community authorities invest in electronic platforms to foster communication and integration with the companies that interact with the seaport, guiding the digitization of the seaport business. In main European and world ports, the Port Community System (PCS) is the platform that supports the creation of a network composed of shipping agents, shippers, freight forwarders, transporters, terminals, logistics platforms, and public entities. PCS focuses on service level, partner networks, maritime services, freight services, logistical services, and advanced port services. These features have an impact on seaport operations, which affects supply chain performance. Digitization within the scope of the PCSs has fostered the development of horizontal collaboration between seaport community partners. The Physical Internet (PI) is an innovative concept that seeks new logistics solutions requiring integration and interoperability between partners in the supply chain, including maritime and land transport. This paper focuses on (i) the evolution guidelines of PCSs and (ii) on the PCS Business Factors that can drive the supply chain into a significant improvement in performance. A survey was sent to a sample of Portuguese supply chain experts regarding the causal relationship between PCS Business Factors and supply chain performance in the next 10 to 20 years. From the data collected, recent services evolving at PCS are promoting a mindset change aligned to the implementation of a Physical Internet. Establishing a Physical Internal in Portuguese seaports could take decades, but it will support the transition to a new phase of PCS, accelerating the transition from Isolated Supply Chains (I-SCs) to Open Supply Chains (O-SCs), thus improving supply chain performance.

Challenges of the green supply chain management in the pharmaceutical industry

Green supply chain management has gained significant interest in recent years; however, we still have limited understanding of specific characteristics of different industries. The aim of this paper is to characterize the pharmaceutical supply chains from an environmental perspective. Our methodology provides a novel contribution to the literature describing green supply chain management, since no detailed analysis of the environmental aspects of the pharmaceutical industry has been carried out this way. Our results can inform pharmaceutical businesses and policymakers about the limiting factors of green supply chain management in the pharmaceutical sector and provide insights to overcome hindrances and to design new tools. By looking at the supply chains of the pharmaceutical sector, we demonstrate that the potentials of green supply chain management may be limited by several factors. First, the relationship between pharmaceutical substance suppliers and medicinal product manufacturers is characterized by long-term partnerships and strong interdependence. Second, interviews suggest that consumers neither have environmental expectations towards medicinal products, nor act in an environmentally conscious manner regarding the disposal of medicinal products. Third, our findings on actual environmental measures implemented by companies suggests that the specific characteristics of pharmaceutical supply chains, such as strict quality and health requirements, impose severe limitations on the greening of supply chains. This study builds on the analysis of the international literature, through which it presents the issues of green supply chains in the pharmaceutical industry. Our research can be useful to national and international readers as well.

Offshore fresh groundwater in coastal unconsolidated sediment systems as a potential fresh water source in the 21st century

Coastal areas worldwide are often densely populated and host regional agricultural and industrial hubs. Strict water quality requirements for agricultural, industrial and domestic use are regularly not satisfied by surface waters in coastal areas and consequently lead to over-exploitation of local fresh groundwater resources. Additional pressure by both climate change and population growth further intensifies the upcoming water stress and raise the urgency to search for new fresh water sources. In recent years, offshore fresh groundwater (OFG) reserves have been identified as such a potential water source. In this study, we quantify, for the first time, the global volume of OFG in unconsolidated coastal aquifers using numerical groundwater models. Our results confirm previously reported widespread presence of OFG along the global coastline. Furthermore, we find that these reserves are likely non-renewable resources mostly deposited during glacial periods when sea levels were substantially lower compared to current sea level. We estimate the total OFG volume in unconsolidated coastal aquifers to be approximately 1.06 ± 0.2 million km3, which is roughly three times more than estimated previously and about 10% of all terrestrial fresh groundwater. With extensive active and inactive offshore oil pumping present in areas of large OFG reserves, they could be considered for temporary fresh groundwater exploration as part of a transition to sustainable water use in coastal areas on the long run.

Stochastic shelf-scale modeling framework for the freezing stage in freeze-drying processes

Freezing and freeze-drying processes are commonly used to improve the stability and thus shelf life of pharmaceutical formulations. Despite strict product quality requirements, batch heterogeneity is widely observed in frozen products, thus potentially causing process failure. Such heterogeneity is the result of the stochasticity of ice nucleation and the variability in heat transfer among vials, which lead to unique freezing histories of individual vials.We present for the first time a modeling framework for large-scale freezing processes of vials on a shelf and publish an open source implementation in the form of a python package on pypi. The model is based on first principles and couples heat transfer with ice nucleation kinetics, thus enabling studies on batch heterogeneity. Ice nucleation is assumed to be an inhomogeneous Poisson process and it is simulated using a Monte Carlo approach. We applied the model to understand the individual pathways leading to batch heterogeneity. Our simulations revealed a novel mechanism how ice nucleation leads to heterogeneity based on thermal interaction among vials. We investigated the effect of various cooling protocols, namely shelf-ramped cooling, holding steps and controlled nucleation, on the nucleation and solidification behavior across the shelf. We found that under rather general conditions holding schemes lead to similar solidification times, as in the case of controlled nucleation, thus identifying a potential pathway for freezing process optimization.

Environmental benefit gain from exporting: Evidence from Vietnam

AbstractLarge‐scale trade reforms in developing countries over the past decades, while boosting economic growth, have raised concerns about deteriorating environmental quality. This paper examines whether participating in export markets affects a firm's energy and emission intensity. Using Vietnamese manufacturing firm‐level data over the period 2009–2014, this study finds that upon entering into the export markets, firms reduce their energy intensity by 27%. Furthermore, along with this energy efficiency gain, there is a decrease in emission intensity by roughly 31%–32%. Moreover, these reductions persist in subsequent periods. A possible mechanism for this is that strict requirements for product quality from buyers in high‐income regions drive firms to use higher‐quality inputs and/or invest in cleaner technology.

Partitioning and Translocation of Dry Matter and Nitrogen During Grain Filling in Spring Barley Varieties and Their Roles in Determining Malting Quality.

To meet the strict requirements for the malting quality of both grain size and protein content for malting barley, a better understanding of the partitioning and remobilization of dry matter (DM) and nitrogen (N) from individual vegetative organs during grain filling may contribute to adjusting a balance in both quality parameters to satisfy the malting criteria of the brewing industry. A 2-year experiment that included 23 spring malting barley varieties was carried out to determine the DM and N partitioning in different organs at anthesis and maturity and to estimate their remobilization to grains. In contrast to the genetic variation of the 23 barley varieties, year effect was the most important single factor influencing the DM and N accumulation at pre-anthesis, and the DM and N translocation from their reserves at pre-anthesis. Post-anthesis assimilates accounted for 71–94% of the total grain yield among the barley varieties in 2014 and 53–81% in 2015. In contrast, the N reserved in vegetative tissues at anthesis contributed to barley grain N from 67% in the variety Union to 91% in the variety Marthe in 2014, and 71% in the variety Grace to 97% in the variety Shakira in 2015. The results concluded that photosynthetically derived assimilates at post-anthesis played an important role in determining grain size, whereas N reserves at pre-anthesis and N remobilization at post-anthesis probably determined the grain protein content of the malting barley. To achieve a high quality of malting barley grains in both grain size and protein content simultaneously, balancing photosynthetic assimilates at post-anthesis and N reserves at pre-anthesis and N remobilization should be considered as strategies for the combination of the selection of spring malting barley varieties together with agronomic N management.

An update and beyond: key landscapes for conservation land cover and change monitoring, thematic and validation datasets for the African, Caribbean and Pacific regions

Abstract. Natural resources are increasingly threatened in the world. Threats to biodiversity and human well-being pose enormous challenges in many vulnerable areas. Effective monitoring and protection of sites with strategic conservation importance require timely monitoring, with a particular focus on certain land cover classes that are especially vulnerable. Larger ecological zones and wildlife corridors also warrant monitoring, as these areas are subject to an even higher degree of pressure and habitat loss as they are not “protected” compared to protected areas (national parks, nature reserves, etc.). To address such a need, a satellite-imagery-based monitoring workflow was developed to cover at-risk areas. The first phase of the programme covered a total area of 560 442 km2 in sub-Saharan Africa. In this update, we remapped some of the areas using the latest satellite images available, and in addition we included some new areas to be mapped. Thus, in this version we have updated and mapped an additional 852 025 km2 in the Caribbean, African and Pacific regions, involving up to 32 land cover classes. Medium- to high-spatial-resolution satellite imagery was used to generate dense time series data, from which the thematic land cover maps were derived. Each map and change map was fully verified and validated by an independent team to meet our strict data quality requirements. The independent validation datasets for each key landscape for conservation (KLC) are also described and presented here (all datasets presented are available at https://doi.org/10.1594/PANGAEA.931968; Szantoi et al., 2021a).

An Approach to Detect White Spots during Pre-Turning of DA718 Components

The increasing demand for high-performance components is leading to a greater use of advanced alloys such as DA718, which is, e.g., used in engine parts due to its high-temperature strength. The strict quality requirements pose major challenges for the machining of engine components for aircrafts. Quality deviations along the value chain can lead to high costs due to rework and, in the worst case, rejections in order to prevent material failure within a safety-critical environment. These deviations include, e.g., an increased surface roughness, deviations in the shape tolerances as well as increased internal stresses or surface deformations. Material defects are an additional reason to reject the manufactured components. These are usually inspected only at the end of the value chain and—due to measurement limitations—only if they occur close to the surface of the workpiece. Ultrasonic testing is used in order to detect defects near the surface of the raw part. For the evaluation of the finished part, etching and optical inspection of the surface is used. However, defects inside the components cannot be detected in this way. If material defects are located in areas subjected to intense load changes and high temperatures, the components have to be rejected since engine parts require a high level of fatigue strength. Such rejects constitute a significant economic risk, as a large part of the added value has already been completed and a significant amount of machine time has been invested. Thus, an identification of material defects in an earlier stage of the manufacturing process is required. In this paper, fundamental investigations on machining artificially generated material defects in a micro-milling process and the signal analysis during the pre-turning of turbine disks made of nickel-based materials like DA718 will be presented. Based on force measurements, characteristic signals were identified that could indicate material defects during the turning process.

Автоматизированная установка для охлаждения молока при использовании естественного хладоносителя

In the chain from milk production to the sale of dairy products, the process of ensuring the required temperature is the main one. Moreover, to cool the milk, the tempera-ture of the cooling agent should be above milk freezing. Taking into account the fact that the process of cooling and storing milk in a chilled form imposes strict requirements for reliability and quality of management on farms, compressor refrigeration units have been used in recent years despite high energy consumption. Theanalysis of technical solu-tions in this direction by the example of farms of the Altai and Novosibirsk Regions showed that during the greatest boom of the livestock industry, film-tray, spray-cooling tow-er, and pipe and tank installations using natural cooling agents were widely used. Taking into account the climatic features of the area when choosing water cooling units as an intermediate coolant made it possible to significantly reduce energy consumption for milk cooling especially in winter. However, the complexity of controlling the process of preparing the intermediate coolant with unpredictable environmental parameters did not allow for high reliability and quality of manual control. A device for cooling the in-termediate coolant with the main -natural cold in winter with an automatic direct-acting regulator that provides the required operating mode of the cooling unit is proposed. The variants of automatic device operation both when the outdoor air temperature decreases and increases are con-sidered. An automated installation for cooling the interme-diate coolant with natural cold may be recommended both for cattle farms and processing enterprises