Increase In Operating Costs Research Articles

A probabilistic model-based approach to assess and minimize scaling in geothermal plants

Geothermal installations often face operational challenges related to scaling which can lead to loss in production, downtime, and an increase in operational costs. To accurately assess and minimize the risks associated with scaling, it is crucial to understand the interplay between geothermal brine composition, operating conditions, and pipe materials. The accuracy of scaling predictive models can be impacted by uncertainties in the brine composition, stemming from sub-optimal sampling of geothermal fluid, inhibitor addition, or measurement imprecision. These uncertainties can be further increased for fluid at extreme conditions especially high salinity and temperature. This paper describes a comprehensive method to determine operational control strategies to minimize the scaling considering brine composition uncertainties. The proposed modelling framework to demonstrate the optimization under uncertainty workflow consists of a multiphase flow solver coupled with a geochemistry model and an uncertainty quantification workflow to locally estimate the probability of precipitation potential, including its impact on the hydraulic efficiency of the geothermal plant by increasing the roughness and/or decreasing the diameter of the casings and pipelines. For plant operation optimization, a robust control problem is formulated with scenarios which are generated based on uncertainties in brine composition using an exhaustive search method. The modelling and optimization workflow was demonstrated in a geothermal case study dealing with barite and celestite scaling in a heat exchanger. The results showed the additional insights in the potential impact of brine composition uncertainties (aleatoric uncertainties) in scaling potential and precipitation location. Comparing the outcome of optimization problem for the deterministic and fluid composition uncertainties, a change of up to 2.5% in the temperature control settings was observed to achieve the optimal coefficient of performance.

Risks and sustainability of outdoor ski resorts in China under climate changes

Global warming is jeopardizing the artificial snow making conditions, shortening outdoor ski resorts opening days and increasing operation cost, severely threatening the sustainability of outdoor ski industry. The sustainability of 772 outdoor ski resorts in China under RCP 4.5 climate scenarios in 2030 s and 2050 s had been analyzed. (1) The skiing sports developed prominently during 1996 to 2023 and will boom in China in the coming decades. (2) Accelerated global warming is the main threat to the sustainability of outdoor ski resorts of China. However, snowfall isn’t a critical influencing factor in the coming decades. (3) The outdoor ski resorts in south China are facing the most threats and are the most unsustainable resorts. We proposed a nexus of Government-Operator-Skier adaptation framework for adapting climate change threats and advocating the temporal small-scale ski resorts are more adaptive as their high water and energy efficiencies for saving water and electricity resources.

Sensitivity Analysis of North Surabaya Hospital Investment Feasibility

The aim of this research is to analyze the feasibility of investing in North Surabaya Hospital, Bulak District, Surabaya City with the parameters Net Present Value, Internal Rate of Return, Benefit Cost Ratio (BCR) and Payback Period. This research focuses on the North Surabaya Hospital which was built by the Surabaya City Government Health Service with a budget for 2026. The research instruments used were interview guidelines and observation sheets, with data collection procedures via location with related parties in the construction of the hospital, site observation, as well as documentation that includes primary and secondary data. Based on investment analysis of North Surabaya Hospital and evaluation of sensitivity to operational costs and potential income, the conclusion obtained is: Alternative 1 is feasible because it produces an NPV value of Rp. 211,014,227,005, IRR of 9.85%, BCR of 1.23 and PP of 7.69 years, but will be sensitive to the point that it is not feasible if there is an increase in hospital operational costs above 2.05% or a decrease in hospital service levy rates above 1.39% . Alternative 2 is not feasible because it produces an NPV value of Rp. 28,416,192,984, IRR of 6.57%, BCR of 1.14 and PP of 8.34 years, but it will be sensitive and feasible if there is a decrease in hospital operational costs above 7.73% or an increase in hospital service levy rates above 5.59%. Alternative 3 is not feasible because it produces an NPV value of Rp. 66,444,241,124, IRR of 7.30%, BCR of 1.16 and PP of 8.20 years, but it will be sensitive and feasible if there is a decrease in hospital operational costs above 5.7% or an increase in hospital service levy rates above 4.08%. Alternative 4 is feasible because it produces an NPV value of Rp. 166,294,504,181, IRR of 9.26%, BCR of 1.20 and PP of 7.70 years, but it will be sensitive to the point of being unfeasible if there is an increase in hospital operational costs above 0.15% or a decrease in hospital service levy rates above 0.10%.

Analysis the MCA method as a basis decision making value engineering in determining choice of clean water house connection to the house

Non-Revenue Water (NRW) or Loss of Water is a term for water that has been produced but does not reach consumers. In Indonesia, NRW is also often referred to as Unbilled Water or ATR. Non-renewable water loss (NRW) is a known quantity that cannot be accounted for but can be monitored.The effects of NRW are increasing operation costs, water leaks, and impaired performance of PDAM. The purpose of this research is to analyze the MCA method as a basis for decision-making value engineering in determining the choice of clean water house connection to the house. The single case study is water treatment in Manado, North Sulawesi. The result of the research is that the new design is a lockable valve, ferrule pursuit fan push-fit elbow has a higher MCA value at 3. The research result is valuable for the government, stakeholders in water treatment, and academicians.

Outcomes of Endoscopic Transcanal Same Sitting Bilateral Myringoplasty: An Observational Study in a Tertiary Care Center

INTRODUCTION The trend of same sitting bilateral myringoplasty has been sparkling the Otolaryngologists interest to go either microscopically or endoscopically as per the surgeon’s skill and comfort as unilateral myringoplasty would lead to considerable increase in operation cost, time and discomfort to the patient. MATERIAL AND METHODS This prospective, observational study was held in the Department of Otorhinolaryngology and Head and Neck Surgery (ORL-HNS), Universal College of Medical Sciences-Teaching Hospital (UCMS-TH). There were 30 patients with age range of 8-50 years. All cases were done under general as well as local anesthesia. Tragal cartilage and the temporalis fascia graft were used as a graft material. Graft uptake results were assessed after 12 weeks and the intraoperative and postoperative complications were observed. RESULTS 12 (40%) were male and 18 (60%) female. 15 (50%) patients had temporalis fascia graft and other 15 (50%) patients had tragal cartilage graft. 1 patient in each (fascia/cartilage) had a residual peroration in the subsequent operated side. The graft uptake success rate was 96.7% in both the temporalis fascia graft and the tragal cartilage graft myringoplasties with statistically significant association between type of graft and outcome (p=0.976. There were no significant complications observed during the 3 months follow up except the discomfort due to the bilateral mastoid dressing. CONCLUSION It is a safe, minimally invasive, and satisfactory procedure with a favourable and similar graft uptake success rate with the advantages of cost reduction, single anesthesia exposure, a low rate of postoperative complications and better cosmesis.

Peningkatan Efisiensi Produksi Pakan dan Keselamatan Kerja di Kelompok Ternak 99 Farm Melalui Implementasi Mesin Pencacah Rumput Hemat Energi

The 99 Farm Livestock Group faces challenges in increasing feed production efficiency and occupational safety and health (OHS). These challenges are caused by the use of inefficient and unergonomic grass chopping machines, which pose risks to livestock farmers' safety and increase operational costs. This community service program aims to address these issues by introducing energy-efficient grass chopping machines designed with ergonomic and OHS aspects in mind. This study examines the impact of implementing this technology on livestock farmers' operational efficiency and welfare. The results show a significant increase in the efficiency of the grass chopping process, reduced operational costs, and improved working conditions for livestock farmers. The implementation of this technology is also expected to be an example for other livestock farmers to implement more sustainable and safe practices.

The Impact of E-commerce Development on Regional Economy, Household Income, and Population Mobility: An Empirical Study Based on Zhejiang Province from 2000 to 2021

This study explores the impact of e-commerce development on regional economic growth, household income, and population mobility in Zhejiang Province from 2000 to 2021. Using a dynamic panel data model, the paper analyzes the influence of e-commerce, measured by Taobao Villages, on economic performance and migration patterns across counties. The results reveal a significant negative correlation between e-commerce development and economic growth, suggesting that in the short term, the increase in operational costs may outweigh the benefits. However, e-commerce significantly enhances the income of both urban and rural residents and indirectly influences population mobility by attracting labor back to small and medium-sized cities and rural areas. This study provides critical insights for policymakers in balancing the economic impacts of e-commerce and addressing population dynamics.

A Qualitative Analysis of the Socio-cultural Barriers to Intra-African Trade: Evidence from Nigerian Exporters

This study qualitatively analyzed the sociocultural barriers to intra-African trade, focusing on challenges faced by African businesses in cross-border markets, their impacts, and mitigation strategies. An exploratory case study design was adopted, using purposive and snowball sampling to select participants. Primary data were obtained through in-depth interviews with 10 members of the Association of Nigerian Exporters (ANE). Reflexivity and participant validation ensured research credibility, while Braun and Clarke’s reflexive thematic analysis framework guided data analysis, with thematic maps aiding interpretation. The findings identified five key sociocultural barriers substantially inhibiting intra-African trade: cultural complexity, corruption and bureaucratic obstacles, trust gaps, unhealthy rivalries, and business network challenges. These barriers contribute to miscommunication, failed negotiations, weakened consumer demand, failed partnerships, and increased operational costs for intra-African trade. These findings underscored that sociocultural factors play a pivotal role in shaping the success or failure of intra-African trade, highlighting the need for targeted strategies to address these barriers. In particular, they emphasized that cultural complexity hampers communication and negotiations, while corruption and bureaucratic obstacles erode trust and create inefficiencies. Trust gaps weaken partnerships, unhealthy rivalries hinder collaboration, and business network challenges limit market access and increase operational costs. Tackling these issues is crucial for improving trade efficiency and fostering stronger economic integration across the African continent.

Impact of Geopolitical and Bilateral Trade Frictions on Global Supply Chain Resilience: Strategies for Multinational Corporations

In the context of the growing interconnectivity of the global economy, the resilience of global supply chains (GSCs) is increasingly contingent upon a range of external factors, including geopolitical developments and the implementation of bilateral trade policies. This study examines the vulnerabilities faced by GSCs in recent years, particularly the challenges they have shown in responding to geopolitical events and bilateral trade frictions. Taking the United Kingdom’s exit from the European Union and the trade war between the United States and China as examples, this study analyzes the significant impacts of these events on GSCs, including issues such as increased operating costs and structural reorganization. This study also proposes strategies for multinational corporations to cope with the complex international environment, such as supply chain diversification and localization of production. It is found that enhancing supply chain resilience is crucial to cope with geopolitical risks and safeguard business continuity, which helps to improve their market competitiveness and ability to cope with unexpected events.

Decision Making by Trade-In Programs in the E-Commerce Supply Chain, Considering Cash Rebate Strategies and Platform Services

As the consumer market becomes more saturated, the e-commerce supply chain (E-SC) has introduced the trade-in program in an attempt to drive consumption. This paper considers the strategy of the E-SC to provide cash rebates for consumers participating in the trade-in program and incorporates the e-commerce platform’s trade-in service efforts into the E-SC’s decision-making system. Depending on who provides the cash rebate, we construct four decision-making models of the E-SC, i.e., the no-cash-rebate model, the manufacturer model, the platform model, and the cooperative model, where both the manufacturer and the platform jointly provide the cash rebate. We show that the platform model reduces the trade-in service level, but the manufacturer model increases the trade-in service level. In addition, since the cash rebate increases operation costs, the sale price of products is inevitably improved. Furthermore, the platform model raises product demand, but the manufacturer model lowers product demand. The cooperative model proves effective in enhancing demand only when the manufacturer contributes a minor share of the cash rebate and the trade-in service is less efficient. Cash rebates can increase the E-SC’s profits, but the degree of this increase becomes smaller as the cash rebates increase. The manufacturer and the platform always want to exploit each other’s cash rebate strategies. Consumer surplus and social welfare are highest in the platform model and lowest in the manufacturer model. Taking into account the profits, consumer surplus, and social welfare, the platform model is the most conducive to E-SC system operations.

Problematika Ekonomi dalam Dakwah

Islamic boarding schools are religious educational institutions that have an important role in shaping the character and morals of Indonesian society. However, in recent years, the rising cost of education has become one of the main challenges that hinder access for students, especially for underprivileged families. This study aims to analyze the impact of rising education costs on student access in Islamic boarding schools and identify solutions to overcome these problems. This study uses a qualitative approach with an analytical descriptive method. Data was collected through in-depth interviews with Islamic boarding school leaders, ustaz, students, and parents of students, as well as direct observation at several Islamic boarding schools. Documentation studies are also carried out to obtain information about cost management policies and programs run by pesantren. The results of the study show that the increase in operational costs of Islamic boarding schools, especially for infrastructure and modernization of education, is the main factor affecting the increase in education costs. In addition, family economic factors, the shift in social values from spiritualism to materialism, and the lack of government support have also worsened students' access to Islamic boarding schools. However, Islamic boarding schools are trying to find solutions by implementing zakat and infaq-based scholarship programs, as well as collaborating with philanthropic institutions. Some Islamic boarding schools also develop independent business units to support operations without burdening students. This study concludes that efficient management of education costs and innovation in education programs are essential to keep pesantren inclusive. Thus, pesantren can continue to be a pillar in da'wah and affordable Islamic education, as well as support the development of a better society.

Pemodelan Sistem Pemilihan Tempat POI Terdekat di Wilayah Klaten Kota Menggunakan Metode Dijkstra oleh PT. Telkom Klaten

The Point of Interest (POI) represents a specific geographic location defined by its coordinates, including longitude and latitude, and holds value as a site of interest or utility. Examples of POIs include tourist attractions, hotels, restaurants, ATMs, pharmacies, health centers, retail shops, gas stations, and other categories integral to modern navigation systems. PT. Telkom Klaten has faced increased demands to conduct POI surveys efficiently, driven by advancements in technology that call for faster and more streamlined processes. A primary challenge in these surveys is the selection of an optimal route that minimizes time, costs, and fuel consumption, given that the company currently relies on manual input in Google Maps to determine distance and travel time. This manual approach may hinder survey efficiency and increase operational costs. To address this, an application employing the Dijkstra algorithm was developed to determine the shortest route effectively. The Dijkstra algorithm, known for selecting edges with minimal weight to connect sequential nodes, requires defined origin and destination points, thereby generating the most efficient route between them. This study applies the Dijkstra algorithm to optimize survey routes by modeling them as graph-based routes, aiming to identify the shortest and most efficient paths between multiple POI locations. The findings indicate that the Dijkstra algorithm significantly reduces travel distance and time, thereby achieving notable savings in fuel and operational time for POI surveys.

Ladder electrodialysis: Efficient up-concentration of lithium ion and its mechanisms behind

The development of lithium extraction technology from salt lakes has seen significant demand in recent years, driven by the surge in energy storage needs for lithium-ion batteries used in electric vehicles and renewable power plants. Currently, evaporation technologies such as Mechanical Vapor Recompression (MVR) and Multi-Effect Distillation (MED) are commonly employed to concentrate lithium chloride for subsequent lithium carbonate precipitation. However, these evaporation methods limit lithium yield and increase capital and operational costs, particularly in high latitude areas. Pressure-driven membrane processes like reverse osmosis are hindered by concentration polarization and cannot significantly increase lithium chloride concentration. This study proposes a new membrane stack configuration with a laddered compartment design, termed Ladder Electrodialysis (LED), which addresses the concentration polarization issue and achieves a lithium salt (LiCl) concentration of 16.39 % (196 g·L−1). Economic analysis shows that the energy consumption is only 0.42 kWh per kilogram of LiCl. Ladder electrodialysis is a novel salt concentration technology, with applications in brine valorization or disposal.

Effects of the use of acetone as co-solvent on the financial viability of bio-crude production by hydrothermal liquefaction of CO2 captured by microalgae

Hydrothermal Liquefaction (HTL) is a promising technology to produce biocrude from microalgal biomass that has captured gaseous CO2. However, several problems of this technology must still be solved to make it economically and technically feasible. One of the main problems in the financial viability of the HTL process is the low yield obtained when only water is used as a solvent, with results close to or lower than 30 wt%. This, in turn, increases the production cost to over 120 USD/BBL. In recent years, some authors have focused their efforts on increasing biocrude production through the extensive use of organic solvents, without considering the effects on economic viability. The present work evaluated the financial effect of using acetone as an organic co-solvent, finding that high acetone contents increased operating costs of the process, mainly due to losses in its handling and recovery. On the contrary, very low acetone contents had very little effect on the biocrude yield. It was possible to establish that concentrations close to 5 wt% of acetone, mixed with water, resulted in a yield of about 60 wt% and a production cost of 50 USD/BBL of biocrude, with an energetic densification of 30.25 MJ/kg and 8.60∘ API, classifying it as heavy crude, which makes it necessary to include refining processes for heteroatom removal. Chemical characterization of biocrude revealed a high content of nitrogenous compounds (23.6 wt%) and oxygenated compounds (10.7 wt%), which have to be removed for the subsequent production of commercial liquid fuels. It is concluded that the use of a water-acetone mixture allows for obtaining positive operating profits, which helps to the high capital costs involved in this type of technology, making it more financially comparable with the conventional petroleum industry.

A Solution to Reduce the Impact of Patients' No-Show Behavior on Hospital Operating Costs: Artificial Intelligence-Based Appointment System.

Patient no-show behavior is a critical factor complicating hospital resource optimization and causing waste. The inefficiency caused by patients' no-shows and the resulting increased operating costs negatively affect the hospitals' financial structure and service quality. For this reason, health managers must make accurate predictions about whether patients will attend an appointment and plan the appointment system within the framework of these predictions. This research aims to optimize the hospital appointment system by making accurate predictions regarding the no-show behavior of the patients, based on recorded data. An artificial intelligence-based appointment system has been developed according to patients' demographics and past behavior patterns. The forecast results and realized performance results were compared. The artificial intelligence we have developed continuously improves appointment assignments by learning from past and current data. According to the findings, the artificial intelligence-based appointment system increased the rate of patients attending appointments by 10% per month. Likewise, the hospital capacity utilization rate increased by 6%. Findings from the study confirmed that no-show risks could be managed in the appointment process through artificial intelligence. This artificial intelligence-based design for appointment systems significantly decreases hospital costs and improves service quality performance.

Trade facilitation, market size, and supply chain efficiency of Taiwan semiconductor companies.

In an environment marked by global economic volatility and geopolitical uncertainties, the stability of Taiwan's supply chain takes on heightened importance, particularly given Taiwan's crucial role in the global semiconductor supply chain. In recent years, semiconductor companies in Taiwan have faced increasing inventory pressures, which will reduce their competitiveness and increase operational costs over the long term. Although previous studies have explored the influence of trade facilitation on macroeconomic and trade efficiencies, its specific impacts on the semiconductor industry have been less frequently addressed. This study integrates corporate inventory, trade facilitation, and geopolitical factors within a unified analytical framework to construct a model that explores mediating and moderating effects. This study conducted regression analysis on data from 52 Taiwan-listed integrated circuit companies from 2014 to 2022. Contrary to traditional findings that trade facilitation decreases inventory in other industries, it predominantly fosters inventory accumulation within Taiwan's semiconductor sector by expanding market size, thereby affecting supply chain efficiency. Moreover, geopolitical factors were found to intensify the effects of trade facilitation on corporate inventory. Elevated geopolitical risks lead to greater inventory accumulation, which ultimately threatens long-term competitiveness and diminishes the semiconductor industry's advantage in Taiwan, further influencing supply chain efficiency. Consequently, this study recommends that to more accurately forecast market size, semiconductor companies in Taiwan are encouraged to expand their manufacturing investments in Chinese mainland. Additionally, the prudent handling of cross-strait relations by the Taiwan authorities is an important strategy to mitigate geopolitical risks affecting the semiconductor supply chain.

Environmental and socio-economic evaluation of a groundwater bioremediation technology using social Cost-Benefit Analysis: Application to an in-situ metal(loid) precipitation case study

Bioremediation can be an alternative or complementary approach to conventional soil and water treatment technologies. Determining the environmental and socio-economic impacts of bioremediation is important but rarely addressed. This work presents a comprehensive sustainability assessment for a specific groundwater bioremediation case study based on In-situ Metal(loid) Precipitation (ISMP) by conducting a social Cost-Benefit Analysis (CBA) using two different approaches: environmental Life Cycle Costing (eLCC) and Impact Pathway Approach (IPA). Externalities are calculated in two ways: i) using Environmental Prices (EP) to monetize Life Cycle Assessment (LCA) results and metal(loid)s removed at field scale, and ii) following the IPA steps to determine the social costs avoided by removing arsenic contamination at full scale. The results show that, in the baseline scenario, the project is not socio-economically viable in both cases as the Net Present Value (NPV) is −129,512.61 € and − 415,185,140 € respectively. Sensitivity and scenario analyses are performed to identify the key parameters and actions needed to reach a positive NPV. For instance, increasing the amount of water treated per year to 90 m3 and assuming a 20 % increase in operation costs and a 60 % increase in construction costs can make the project socio-economically viable at the field scale, while a reduction in the social discount rate from a 4 % to a 2 % can lead to a positive NPV at the full scale. The approaches proposed in this work may be useful for practitioners and policymakers when evaluating the environmental and socio-economic impacts of bioremediation technologies at different scales and regions, as well as human health impacts caused by contaminants at the current legal limits.

Damping optimization of a fully viscoelastic structure with enforced mass reduction

Current damping methods employed in industry, such as Constrained Layer Damping (CLD), all require the introduction of additional mass and a secondary material to the structure. In transportation industries, this weight addition is often correlated with an increase in operational costs. Additionally, in applications with large temperature changes, such as in space, the secondary material introduces an additional source of stress during thermal expansion and contraction. This work presents a methodology to significantly improve the damping performance of a fully viscoelastic, single material structure while also enforcing a mass reduction. The work expands upon the modal strain energy (MSE) method to calculate the damping performance of a fully viscoelastic structure and develops a novel weighting scheme to make the optimization more robust. The methodology is then implemented on a technology demonstration thermoplastic lunar rover. This implementation demonstrates the ability to optimize a fully viscoelastic structure to significantly improve the damping performance while also achieving a large decrease in mass. The implementation also demonstrates the robustness of the weighting scheme as it allows the natural frequencies to shift between iterations. The skin thickness of the rover’s base panel was optimized. After optimization, the base panel of the rover achieved a 20% damping improvement for Mode 1 with a 9% mass reduction. The skin thickness of the full rover was optimized and achieved a 15% damping improvement for Mode 2 with an 11% mass reduction.

EETS: An energy-efficient task scheduler in cloud computing based on improved DQN algorithm

The huge energy consumption of data centers in cloud computing leads to increased operating costs and high carbon emissions to the environment. Deep Reinforcement Learning (DRL) technology combines of deep learning and reinforcement learning, which has an obvious advantage in solving complex task scheduling problems. Deep Q Network(DQN)-based task scheduling has been employed for objective optimization. However, training the DQN algorithm may result in value overestimation, which can negatively impact the learning effectiveness. The replay buffer technique, while increasing sample utilization, does not distinguish between sample importance, resulting in limited utilization of valuable samples. This study proposes an enhanced task scheduling algorithm based on the DQN framework, which utilizes a more optimized Dueling-network architecture as well as Double DQN strategy to alleviate the overestimation bias and address the shortcomings of DQN. It also incorporates a prioritized experience replay technique to achieve importance sampling of experience data, which overcomes the problem of low utilization due to uniform sampling from replay memory. Based on these improved techniques, we developed an energy-efficient task scheduling algorithm called EETS (Energy-Efficient Task Scheduling). This algorithm automatically learns the optimal scheduling policy from historical data while interacting with the environment. Experimental results demonstrate that EETS exhibits faster convergence rates and higher rewards compared to both DQN and DDQN. In scheduling performance, EETS outperforms other baseline algorithms in key metrics, including energy consumption, average task response time, and average machine working time. Particularly, it has a significant advantage when handling large batches of tasks.

EXPERIMENTAL STUDIES OF THE STAND OF THE AUTOMATED MILKING UNIT WASHING SYSTEM WITH AIR INJECTORS AND A PHOTO SENSOR FOR DETERMINING THE CONTAMINATION LEVEL

One of the key indicators of the quality of milk used for further processing is the level of bacterial contamination. This parameter directly depends on the sanitary and hygienic maintenance of milking equipment, the speed of milk cooling and the influence of other external factors. During milking, milk passes through various elements of the system, such as milking machines, milk pipes, milk collectors, individual and group meters, etc. These elements can become sources of bacterial contamination. To improve the quality of milk, it is recommended to increase the efficiency of washing milking units, which includes extending the duration of washing. However, this leads to an increase in operational costs (water, detergents, electricity, etc.) and, accordingly, the cost of dairy products. Over time, deposits of an alkaline and acidic nature are formed on the inner surfaces of the milk ducts, which differ in composition, properties and strength of adhesion to the surface. This contamination leads to bacterial contamination of milk, which reduces its quality and shelf life [1]. To improve the quality of washing, it was proposed to use an injector that periodically supplies air to the milk line. This creates significant fluctuations in vacuum pressure, which, in turn, causes controlled hydraulic shocks. This process should be managed by automated milking equipment systems. The quality of the flushing system is difficult to assess and control without special sensors and devices for measuring the contamination of the milk duct [2]. The purpose of the study is to conduct experimental tests of the operating modes of the air injector of the milk duct washing system and determine its optimal parameters. It is also planned to develop equipment for automatic detection of contamination of the milk duct during washing. In experimental studies, the dependences between the rate of pressure change and the level of cleanliness of the milk duct, as well as between the working vacuum pressure, the volume flow of air through the injector, the duration of air intake and the duration of the pause were found. In order to achieve a compromise, which consists in minimizing the rate of pressure change at the maximum level of cleanliness of the milk duct, the optimal parameters of the injector operating modes were determined. The expediency of using the developed equipment for automatic control of contamination of the milk duct during washing is shown. The dependence of the thickness of the layer of milk moving in the glass tube on the resistance of the photoresistor, which is affected by the light partially absorbed by the milk, is also established.