Repair Costs Research Articles

Time-Driven, Activity-Based Cost Analysis of Pars Plana Vitrectomy in Rhegmatogenous Retinal Detachment at a Large Academic Center.

Purpose: To perform a time-driven, activity-based cost analysis of retinal detachment (RD) surgery and compare it with reimbursement rates. Methods: This economic analysis at a single academic institution used time-driven, activity-based costing methodology to determine the cost of rhegmatogenous RD repair with primary pars plana vitrectomy. A process flow map was created to highlight each surgical case's operative episodes, including clinical follow-ups. Time logs were obtained from the electronic health record for each operative phase and clinical follow-up. The overhead and anesthesia costs were collected from the institution's cost accounting system. The direct material and personnel costs were obtained from internal financial data. Results: Seventy-six cases that met the inclusion criteria were included in the cost analysis study. The time-driven, activity-based cost of RD was $6247.17, and the reimbursement was $5442.91. Therefore, each procedure had a net negative loss of $804.26. To break even, the average operation time would need to be reduced from the determined average of 90.49 minutes to 64.90 minutes. Conclusions: This study found that Medicare underestimates the true cost of RD surgery. Changes in referral patterns may be motivated by reimbursement rates lower than the cost of the procedure, which could ultimately affect patient access to care.

A LSTM algorithm-driven deep learning approach to estimating repair and maintenance costs of apartment buildings

PurposeThis study proposes a deep learning algorithm-based model to predict the repair and maintenance costs of apartment buildings, by collecting repair and maintenance cost data that were incurred in an actual apartment complex. More specifically, a long short-term memory (LSTM) algorithm was adopted to develop the prediction model, while the robustness of the model was verified by recurrent neural networks (RNN) and gated recurrent units (GRU) models.Design/methodology/approachRepair and maintenance cost data incurred in actual apartment complexes is collected, along with various input variables, such as repair and maintenance timing (calendar year), usage types, building ages, temperature, precipitation, wind speed, humidity and solar radiation. Then, the LSTM algorithm is employed to predict the costs, while two other learning models (RNN and GRU) are taught to validate the robustness of the LSTM model based on R-squared values, mean absolute errors and root mean square errors.FindingsThe LSTM model’s learning is more accurate and reliable to predict repair and maintenance costs of apartment complex, compared to the RNN and GRU models’ learning performance. The proposed model provides a valuable tool that can contribute to mitigating financial management risks and reducing losses in forthcoming apartment construction projects.Originality/valueGathering a real-world high-quality data set of apartment’s repair and maintenance costs, this study provides a highly reliable prediction model that can respond to various scenarios to help apartment complex managers plan resources more efficiently, and manage the budget required for repair and maintenance more effectively.

Smart retrofitting for office buildings: Comparison of decision-making criteria between developing and developed regions

Given the constantly evolving nature of modern infrastructure, retrofitting existing buildings with state-of-the-art smart technologies presents a pivotal opportunity, enabling promising advancements in sustainability, efficiency and adaptability. Focusing on Hong Kong and Sri Lanka, which are developed and developing regions respectively, this study investigates the decision-making criteria for selecting smart systems as retrofits for office buildings. Using the analytic network process (ANP), 24 expert interviews were conducted in Hong Kong and Sri Lanka to determine the importance weights of the decision-making criteria. The findings show varied importance weights for each criterion between the two regions, with Hong Kong emphasizing upfront financial considerations, specifically 'investment cost' while Sri Lanka emphasizing long-term operational sustainability, specifically 'recurring operation, maintenance and repair cost.' Despite these differences, there are similarities in the importance of core criteria such as 'reliability of retrofit option' and 'ability to increase returns.' The lack of focus on user-centric issues in Hong Kong and implementation of retrofit projects in Sri Lanka underscore the need for decision-makers to prioritize these aspects in future projects. The principal contribution of this study is in offering insights from a thorough analysis of the importance weights of the essential criteria in making decisions regarding smart retrofitting (SR). It is also beneficial to various stakeholders, including building owners and facility managers. The cross-region study approach, enabling the investigation on both developed and developing regions, further serves as a foundation for future research aiming to explore and analyze the influence of regional difference in decision-making for SR.

Analysis of postdisaster economy using high-resolution disaster and economy simulations.

We present an integrated framework that utilizes high-resolution seamless simulations of disasters and national economies for estimating the economic impacts of disasters. The framework consists of three components: a physics-based simulator to simulate the disaster and estimate the response of the infrastructure; a tool that estimates the losses suffered by the infrastructure based on its response; and an agent-based economic model (ABEM) that simulates the national economy considering the infrastructure damage and postdisaster decisions of the economic entities. The ABEM used in the framework has been implemented in a high-performance computing environment to simulate large economies at 1:1 scale. Furthermore, it has been calibrated to the Japanese economy using publicly available macroeconomic data and validated to the Japanese economy under the business-as-usual scenario. We demonstrate the integrated framework by simulating a potential Nankai-trough earthquake disaster and estimating its impacts on the Japanese economy. The seismic response of 1.8 million buildings of the Osaka-bay area has been estimated using a large-scale earthquake disaster simulator and corresponding repair costs are estimated using the Performance Assessment Calculation Tool. As per our estimates, repair costs amount to approximately 15 trillion Yen. Considering the investments made by impacted households and firms toward recovery, the postdisaster economy is simulated using the ABEM for 5 years under two recovery scenarios. Industrial production is expected to recover in three quarters whereas 10-13 quarters will be required to finish all the repairwork.

Electrical resistivity of cement-based materials through ion conduction mechanisms for enhancing resilient infrastructures

Cement-based materials (CBM) in humid environments, influenced by their inherent defects and the presence of pore solution, exhibit poor electrical insulation performance. Low electrical resistivity of cement-based materials poses a threat to the safety of resilient infrastructures, shortens the lifespan of materials, and increases the costs of maintenance and repair. In this work, we first elucidate two primary mechanisms for enhancing electrical resistivity: (1) inhibition of ion electromigration and (2) disruption of conduction paths. We then systematically summarize and discuss 16 potential methods for improving their electrical resistivity based on these mechanisms. It is indicated that among these 16 methods, early carbonation curing, the addition of high-activity mineral admixtures, and surface hydrophobic modification are particularly effective approaches. The combination of two or more methods can simultaneously exert their functions, thus maximizing the overall effectiveness. Future work is outlined with the aim of meeting the growing demand for cement-based materials with high electrical resistivity in the construction of resilient infrastructures.

An aero-engine remaining useful life prediction model based on clustering analysis and the improved GRU-TCN

Abstract Accurately predicting the remaining useful life (RUL) of engines is paramount for implementing effective preventive maintenance strategies, preventing injuries and fatalities caused by equipment failures, and significantly reducing routine repair and replacement costs. However, existing deep learning models often ignore the variable operating conditions in real engineering applications and do not sufficiently consider the interaction between time series and degradation laws, which directly leads to the inability to effectively extract to degradation feature extraction. To address this problem, this study developed a novel combined network model named CA-DRGRU-TTCN, aimed at accurately predicting the RUL of engines. Firstly, a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to identify multiple operating conditions, and incorporate the recognition results into the model as additional new features. The first degradation time point is determined by JS divergence. Secondly, the deep connectivity of the residual Gated Recurrent Unit (GRU) module is designed to extract deeper degradation features, and an improved TMSE loss function based on the first degradation time point is applied to Temporal Convolutional Networks (TCN) to better capture the dependency between the time series and the real degradation degree of the engine. Finally, experiment results on the C-MAPSS dataset show that the proposed method achieves better performance compared to existing state-of-the-art methods.

The study of an Economic Integration of a Microgrid for the University of Management and Technology Sialkot

The finest microgrid design has been proposed in this research to ensure a smooth energy supply for the University of Management and Technology (UMT) Lahore, Sialkot Iqbal campus, Pakistan at the cheapest price. The design methodology considered resource availability, environmental feasibility, economic feasibility, and renewable integration. The university can utilize the energy from the Sun, fossil fuel, and national grid. Integrating the available energy resources, data collection, and forecasting multiple parameters were simulated to design the optimal microgrid. The optimal design is selected based on the net present cost (NPC), renewable fraction (RF), operating cost (OC), repair and maintenance cost (O and MC), etc. Out of the 48 viable simulated designs, the optimal design has a PV system, generators, and the grid to fulfill energy demand at a net present cost of $116,987, with a renewable portion of 95%. In contrast, the worst simulated design depends on generators and battery backup, resulting in a $2.93 million NPC with a renewable segment of 24.3%.

INFLUENCE OF MOISTURE CONDITION AND SILICA SAND ON FRICTION COEFFICIENT OF WIND TURBINE BRAKE SYSTEM

Major drive train parts for the horizontal wind turbines including the gearbox, generator, and brake system have very high repair and replacement costs and take a long time to complete. This paper investigates the impact of environmental air pollution on drivetrain tribology behaviors. Experimental research of the wind turbine's drive train system is simulated and investigated. The mechanical brake system of wind turbines is the subject of one case study chosen for this research paper. This research paper is examined how impurities affect the friction coefficient of the brake on wind turbines. According to the findings, the friction coefficient rises with each increase in wind turbine shaft speed. Also, it has been discovered that the size of the contaminants' particles significantly affects the friction coefficient. Furthermore, the findings may offer helpful insights of the drive train system that as humidity increased from 30 mm3 to 90 mm3, the coefficient of friction significantly decreased.

ANALYSIS OF MODERN SCIENTIFIC AND PRACTICAL RESEARCH IN THE FIELD OF WATER DISTRIBUTION SYSTEM

Solving the problem of ensuring the reliable functioning of drainage systems is important not only for Ukraine, but also for scientists around the world. Since these systems are critically important for life support, their uninterrupted operation is of strategic national importance. The issue of preservation and restoration of existing underground communications is gaining particular relevance due to increased environmental requirements. To protect groundwater from contamination with aggressive reagents, it is important to understand the reasons for the destruction of underground communications structures and effective methods of their repair. The article analyzes scientific works related to the problems of ensuring the trouble-free operation of objects that are part of the complex of constructions of sewer tunnels of the city. Grouped according to the direction of research work: research on the corrosion process in water drainage networks; analysis of modern ones; materials, laboratory tests; technologies for restoring drainage networks. Analysis of studies of the condition of structures of objects; research of materials and methods of repair and restoration of sewage tunnels and inspection shafts, which are currently used with high efficiency in domestic and foreign practice; development of technological and organizational solutions and restoration of destroyed sewage structures of drainage networks. The analysis of the researches of domestic scientists showed that the sewer tunnels of large cities of Ukraine are worn out as a result of long-term operation, ineffective solutions to protect structures from the influence of an aggressive environment, low-quality materials and structures used during construction. Restoring normative operational characteristics, increasing the durability of sewage tunnels is a costly and technically complex task, the solution of which is urgently needed to prevent accidents, including those with serious environmental consequences. Existing modern technologies of work performance, materials and structures used for repair and restoration works with different efficiency solve these problems, at the same time, the need to reduce costs for repair and restoration works requires the search for cost-effective materials, structures and methods of work performance. The analysis of the conducted studies shows that the problem of increasing the durability of sewage network structures should be solved comprehensively, taking into account the current situation.

Қазба айналасындағы тау массивінің жағдайын ескере отырып, контурға жақын топырақ жыныстарын бекіту

The maintenance of excavation workings will also require significant repair costs both before and after they are put into operation, especially in the zone of influence of stoping operations. Maintaining and increasing the volume of underground coal mining is possible only if there is a highly efficient technology for conducting and maintaining development workings. The purpose of the research was to evaluate the stability control parameters of the contours of mine workings, fixed with anchor bolting, in order to create a technology for intensive and safe excavation of excavation workings based on the identified patterns of behavior of adjacent rock masses. The idea of the approach is to use the technogenic stress-strain state to develop an effective technology for fastening the near-contour rock mass. The mechanism of deformation, displacement and collapse of rocks in a structurally disturbed heterogeneous rock mass was studied to assess the state of the rock mass around mine workings. A technology for fastening near-contour soil rocks has been developed, taking into account the state of the rock mass around the working, and the parameters for the operation of rock bolts in mines for fixing rods in workings in order to ensure the safety of mining operations in the mines of the Karaganda coal basin have been determined.

Synergistic Effects of Ternary Microbial Self-Healing Agent Comprising Bacillus pasteurii, Saccharomyces cerevisiae, and Bacillus mucilaginosus on Self-Healing Performance in Mortar

In order to prevent structural damage or high repair costs caused by concrete crack propagation, the use of microbial-induced CaCO3 precipitation to repair concrete cracks has been a hot topic in recent years. However, due to environmental constraints such as oxygen concentration, the width and depth of repaired cracks are seriously insufficient, which affects the further development of microbial self-healing agents. In this paper, a ternary microbial self-healing agent composed of different proportions of Bacillus pasteurii, Saccharomyces cerevisiae, and Bacillus mucilaginosus was designed, and its crack repair ability was evaluated. When the mixing ratio was 7:1:2, the cell concentration was the highest, the precipitation amount of CaCO3 was the highest, and the crystallinity of calcite crystal was the highest. Compared to the single microorganism, the mortar specimens with ternary microorganisms had the largest repair area (up to 100%) and the deepest repair depth (CaCO3 presents at 9–12 mm from the crack surface). This is because when the concrete breaks, all three microorganisms are activated by water, O2, and CO2. Saccharomyces cerevisiae and Bacillus mucilaginosus accelerated the growth of Bacillus pasteurii and more mineralized products; CaCO3 was rapidly formed and quickly filled on the crack surface. When CaCO3 seals the surface of the crack, the internal Saccharomyces cerevisiae and Bacillus mucilaginosus continue to play a role. Bacillus mucilaginosus can accelerate the dissolution of CO2 produced by the anaerobic fermentation of Saccharomyces cerevisiae and the hydrolysis of CO32−, thereby improving the repair of the crack depth direction.

Possibility of using industrial by-product combinations to remediate cadmium and arsenic contaminated soil

It is inevitable to produce by-products in industrial and mining production, and how to deal with these by-products has become a major environmental issue. Meanwhile, many studies have shown that applying soil amendments is a feasible measure for effectively controlling soil pollution. Finding low-cost and efficient soil passivators is an effective way to safely utilize polluted soil. This article provides a method of “treating contamination with waste”. Through spinach pot experiments, different proportions and doses of granite powder (A, quarry waste), market purchased conditioner (B), “granite powder+iron sulfate mineral (titanium powder industrial waste)” (C), and “granite powder+iron sulfate mineral+market purchased conditioner” (CB) were used to treat soil co-contaminated with cadmium (Cd) and arsenic (As). The results indicate that amendments affect the available Cd and As in soil by changing soil pH and cation exchange capacity. The amendment of A, B, C, and CB all has remarkable reduction rates of soil available Cd at 65.48 %, 57.02 %, 61.37 %, and 43.15 %, respectively, compared to the control. Both A and B increase the available As content in the soil and the As content in spinach. However, both C and CB reduced the available As content in the soil by 60.32 % and 12.48 %. CB treatment could simultaneously reduce the accumulation of Cd and As in spinach, increase chlorophyll content, and promote spinach growth. It was worth noting that the 3 % CB treatment has the best effect, with Cd and As content in spinach stems and leaves decreasing by 51.13 % - 69.62 % and 35.46 % - 59.53 %, respectively, and the repair cost being as low as 76.5 $ ton−1. Therefore, the combined application of granite powder, market purchased conditioner, and iron sulfate minerals for the remediation of Cd and As co-polluted soil was a cost-effective and environmentally friendly technology. However, applying these soil composite amendments also requires attention to adjusting with the soil type and with pollution type, which we are currently studying.

Study to determine medical imaging devices costs of maintenance and repair: case of a university hospital in turkey

Abstract Objectives: Unperformed maintenance and repairs cause medical devices to become idle or unusable before their useful life. In this study, it was aimed to determine a standard for maintenance and spare parts expenditures of medical imaging devices. Methods: In the study conducted on nearly 30 medical imaging devices of a university hospital, firstly, the economic life of the devices was determined depending on the intensity of use. It was determined that the expenditures changed in the first five years, the second five years and after the economic life. Expenditures were categorized according to the period and technological level. Results: According to the results obtained, the annual expenditure of medium technology devices varies between 2% and 7% of the current price. For high-tech devices, expenditures vary between 4% and 13%. In the study, the required expenditure rates for the devices according to the technology level were also predicted. Conclusions: It has been determined that the maintenance and repair practices of imaging devices in health institutions in Turkey are inadequate. Managers should closely monitor the inventory of medical imaging devices for effective use, quality service delivery and employee health.

Optimization of monitoring systems power cable lines

RELEVANCE. The length and complexity of the geography of medium voltage cable lines is at a high level. Such lines extend underground, on supports in the air. In order to constantly maintain the reliability of city power supply at a high level, any interruptions and accidents should be promptly corrected.TARGET. The main goal of the work is to develop the theory of medium voltage CL research, to practically and theoretically substantiate the search for the most convenient and effective installation for CL diagnostics, to study and develop possible modifications of CL diagnostic installations.METHODS. A variant of CL diagnostics based on the CPDA-60 installation is proposed, which makes it possible to find and localize the places where defects occur in the insulation based on the measurement and analysis of partial discharges (PD). Suitable for insulation monitoring in all types of high voltage cables. The CPDA installation can be used when testing new cable lines being put into operation, and to analyze the condition of old cables in operation.RESULTS. Cable lines require an integrated approach to diagnostics and monitoring, since the reliability of modern authentication systems for the generation and distribution of electricity is largely determined by the electrical reliability of electrical equipment. Technical diagnostics of equipment is a key link, the quality of which determines the efficiency of the processes of organizing production activities, strategic planning and renovation of electric grid assets.CONCLUSION. The study and analysis of the presented data and research allows us to form a conclusion regarding the method of measuring and localizing partial discharges (PD) in power cable lines (CL) using the Online Wire Testing System (OWTS) diagnostic system. The OWTS system allows real-time measurements without interrupting cable lines, making it especially valuable to the energy industry. Thanks to the introduction of advanced technologies and signal processing algorithms, the method has high accuracy and sensitivity to minimal manifestations of private discharges, which allows not only to detect, but also to accurately localize the location of defects in the insulation. The use of this method can significantly increase the service life of power cables, reduce the likelihood of sudden accidents and, as a result, reduce the cost of repair and maintenance of electrical power equipment. Ultimately, improvements in diagnostic and monitoring techniques, including the method of measuring and localizing PD in power lines using OWTS, represent a significant step towards improving the reliability and safety of electrical power systems. This will not only reduce operating costs, but also ensure uninterrupted and high-quality power supply to consumers.

Hail hazard modeling with uncertainty analysis and roof damage estimation of residential buildings in North America

This research presents a statistical approach for hail risk modeling that incorporates the uncertainties of hail model prediction to provide insight into assessing the roof damage of a residential house in hail events. By quantifying the inherent uncertainties in evaluating hailstorm characteristics, this study extends the current existing hail models. The hail data are sourced from the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) in the U.S. In the modeling process, the largest hail diameter reported in the CoCoRaHS database serves as a primary input variable to estimate the number of observations for the largest hail diameter, hailstorm duration, and hit rate. The assessment of hail risk in this study focuses on the probability of hail damage and resultant repair costs for five types of roofs in North America (unrated roof and impact-resistant roofs with UL 2218 rating classes 1 to 4). The probability of hail damage is calculated as the failure probability by integrating all individual hailstone hits having variable diameters during a hailstorm with fragility curves, which estimate the probability that hailstones will fracture asphalt shingles (allowing water infiltration) or that they dislodge enough granules to cause visible damage requiring replacement for aesthetic reasons. The results reveal that an impact-resistant roof (impact-resistant rating classes 1 to 4) is associated with lower hail risks, with 60 % to 98 % reduction on average compared to unrated roofs. This study provides a comprehensive uncertainty modeling approach for hail hazard and risk, enabling better-informed decision-making and risk management strategies.

Experimental evaluation of bonded/unbonded prestressed precast concrete joints under repetitive loading scenarios: Seismic performance and retrofit intervention

Recently, demands for mitigating structural damage and post-earthquake repair costs have spurred considerable research on prestressed precast frames. In this study, quasi-static tests were conducted on bonded and unbonded prestressed precast beam-column joints (BPPJs and UPPJs) to investigate the influences of bonded/unbonded post-tensioned (PT) strands, evaluate the performance of BPPJs under repeated loading, and verify the effectiveness of post-earthquake retrofitting with external buckling-restrained rods (BRRs). Additionally, the difference between the bonded and unbonded joints was further revealed from the perspective of the tensile forces of the strands at the beamcolumn interface. Test results showed that compared with the UPPJ, the BPPJ exhibited superior performance in terms of lateral stiffness, lateral resistance, and energy dissipating capacity, with a 76.4 % increase in the load-bearing capacity. The compressive zone at the beam end was also deeper in the BPPJ, accompanied by a denser distribution of compressive cracks in the concrete. Furthermore, the bond between the strands and grouting material in the duct accelerated the increase in the tensile forces of the strands at the interface, resulting in considerably more prestress loss in the BPPJ after the tests, which was 120.0 % greater than that in the UPPJ. Under repetitive loading scenarios, although the yielding resistance of the BPPJ decreased by 35.0 % compared with that of the first loading owing to the reduced tensile forces in the strands, relatively minor variations in the load-bearing capacity and energy dissipation were observed. After retrofitting with BRRs, the BPPJ exhibited substantial enhancements in both lateral stiffness and resistance, validating the effectiveness of post-earthquake retrofitting with BRRs.

Comparative Study on Housing Defect Repair Cost through Linear Regression Model

Comparative Study on Housing Defect Repair Cost through Linear Regression Model

PENCEGAHAN OVERHEATING MELALUI EDUKASI PERAWATAN PADA KENDARAAN RODA DUA

Overheat is a condition when a vehicle's engine temperature reaches a higher level than it should and cannot be maintained at a normal operating temperature. This is a serious problem that can cause damage to the engine if not addressed immediately. The purpose of this community service program is to prevent overheating in Sukaragam Village by educating the community about two-wheeled vehicle maintenance. Therefore, this community service aims to complete community service by providing counseling on simple maintenance of motorized vehicles. The community service method applies counseling in the form of brief socialization and training on how to care for motorbikes to avoid overheating. The success of this community service activity is expected to reduce cases of overheating in two-wheeled vehicles in the community. With a better understanding of vehicle maintenance, it is hoped that the community can take preventive actions such as checking the condition of the engine coolant regularly, using the appropriate oil, and avoiding driving when the engine is too hot. This not only improves driving safety, but also extends the life of the vehicle and reduces repair costs. In addition, this activity also contributes to reducing exhaust emissions produced by motor vehicles, thus supporting environmental conservation efforts.

Explainable, Deep Reinforcement Learning–Based Decision Making for Operations and Maintenance

This paper presents research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance aimed at reducing lifetime maintenance and repair costs. Additionally, a focal point of this research is to make the decisions explainable to operators, improving the trustworthiness of the decisions from what can be considered a black box model. In this work, we develop and evaluate an explainable, online asset management methodology to help reduce lifetime maintenance and repair costs. Using the latest advancements in condition monitoring, inventory management, deep reinforcement learning, and explainable artificial intelligence methods, we create a predictive maintenance methodology that can optimize the maintenance and spare part management of a repairable nuclear power plant system. To demonstrate these methods, preliminary studies were conducted on a representative maintenance system undergoing a stochastic degradation process that requires repairs or replacement to continue operation. Using deep reinforcement learning, we were able to reduce maintenance spending by approximately 50% compared to optimized, time-based maintenance strategies for the chosen system. A key component of our methodology is the integration of Shapley values to quantify the contribution of various factors to the decision-making process. This addition enhances the explainability and trustworthiness of our decisions, providing operators with transparent and understandable insights into the rationale behind maintenance strategies. The robustness and resiliency of our decision policy against observation noise were also thoroughly evaluated, demonstrating its effectiveness in uncertain operational environments.

INVESTIGATION OF THE INFLUENCE OF CHOOSING THE TYPE OF FACADE SYSTEM USING ABC ANALYSIS ON THE COST OF THE LIFE CYCLE OF THE BUILDING OBJECT

The article is devoted to a comprehensive study of the influence of the choice of the type of facade systems on the total cost of the life cycle of the construction object, with a special emphasis on the application of ABC-analysis as a tool for determining the optimal option for arranging the facade, taking into account economic and quality aspects. The main purpose of the article is to justify the feasibility of using ABC analysis to select the type of facade systems and assess its impact on the costs associated with the life cycle of the building. The article provides a detailed analysis of various types of facade systems from the point of view of their fastening, materials, design and method implementation. Such systems as ventilated and non-ventilated facades, hinged ventilated facade systems, facades with cladding made of natural stone, composite materials and other modern materials are considered. Special attention is paid to the study of technological characteristics, durability and maintenance costs of various types of facade systems. The application of ABC analysis allows classifying facade systems according to their impact on the cost and quality of construction. In this context, facade systems are divided into three categories: A - the most important and expensive, B - medium importance and expensive, C - less important and with minimal expenses. This approach allows builders and designers to focus their attention on the most critical elements that affect the overall cost and efficiency of construction.As a result of the study, it becomes possible to make an informed decision regarding the choice of the optimal facade system, which best meets the specific needs of the project and contributes to the optimization of the cost of the life cycle of the building. In particular, the selection of appropriate materials and technologies allows to reduce construction costs, ensure durability and reduce maintenance and repair costs in the future. In addition, the results of the study can become the basis for the development of practical recommendations for professionals in the construction industry, including builders, designers and architects. This makes it possible to create more efficient, economical and ecologically sustainable construction objects. Also, the article emphasizes the importance of creating specialist training schools and conditions for the successful implementation of life cycle assessment technologies in the construction industry.