Reduction In Operating Costs Research Articles

Towards Sustainable Healthcare: A Fuzzy Multi-Criteria Framework for Green Hospital Investments

It is very necessary to develop optimal investment strategies for green hospitals. Optimal investment strategies are necessary for these hospitals to achieve maximum efficiency. Moreover, the right investment strategies ensure that green hospitals use resources such as energy and water efficiently. This contributes to the reduction of operational costs in the long term. For these reasons, the development of optimal investment strategies is of vital importance for the successful construction of green hospitals. On the other hand, a comprehensive need is needed to determine the most accurate investment strategies. This study also aims to develop the most appropriate investment strategies for green hospitals. To achieve this goal, a new model is established in which fuzzy logic and multi-criteria decision-making techniques are integrated. Effective waste management is the most important factor to be considered in this process. In addition, reducing the carbon footprint is another important issue in this context.

Dynamic Resource Management in Healthcare: A Case Study of Kubernetes-Based Platform Scaling

This article presents a comprehensive analysis of a large-scale Kubernetes-based healthcare platform implementation, demonstrating the transformative potential of cloud-native architecture in healthcare operations. The article examines the design, implementation, and operational outcomes of a dynamically scalable infrastructure serving millions of patients while maintaining strict regulatory compliance. Through detailed analysis of the platform's architecture, monitoring systems, and resource management mechanisms, this article provides insights into achieving operational excellence in healthcare IT infrastructure. The article reveals significant improvements in resource utilization efficiency, operational cost reduction, and system reliability through intelligent container orchestration. The implementation successfully addresses common healthcare infrastructure challenges while establishing a framework for maintaining HIPAA compliance in a cloud-native environment. This case study contributes to the growing body of knowledge on healthcare IT modernization and provides valuable insights for organizations seeking to implement similar solutions. The results demonstrate the viability and effectiveness of container orchestration technologies in healthcare settings, offering a blueprint for future implementations while highlighting key considerations for maintaining regulatory compliance and operational efficiency.

Applying the PRiSM™ Methodology to Raise Awareness of the Importance of Using Sustainable Project Management Practices in Organizations

Sustainability has become crucial in today’s business landscape. Customers, suppliers, partners, and investors are increasingly demanding that companies be aware of their impacts on the environment and society. Achieving sustainability in business operations, including social, economic, and environmental aspects, is one of the major challenges for companies today. Integrating sustainability into project management fosters the development of more sustainable and responsible projects, considering environmental, social, and economic aspects. This integration allows for benefits such as risk and operational cost reduction, strengthening of the company’s reputation, and gaining stakeholders’ trust. This study takes an exploratory approach, focusing on a pilot test to investigate how the PRiSM™ (Projects Integrating Sustainable Methods) methodology can be applied in a business context to assess the level of maturity of sustainable project management practices and thus raise awareness of the importance of these issues. PRiSM™ was developed by GPM® Global (Global Project Management, Lees Summit, MO, USA) in 2013 to help organizations integrate project processes with sustainable initiatives and it is based on the P5 Standard, which incorporates tangible tools and methods to manage the balance between finite resources, social responsibility, and delivery of sustainable project outcomes. Based on the PRiSM™ methodology and the P5 Standard (2nd Edition), a comprehensive questionnaire was developed under the Portuguese Project Management Observatory® to assist companies in assessing their performance in terms of sustainable practices, resulting in a sustainable maturity level. The questionnaire aimed to evaluate companies in four impact categories: product/process impacts, social impacts, economic impacts, and environmental impacts. The results, obtained from 30 respondents, indicated that the majority of organizations achieved medium-level ratings, with an overall average of 65%. However, some still showed unsatisfactory performance, with a minimum score of 14%, indicating there is still a long way to go for the full integration of sustainability. Based on participants’ feedback, the study found that many recognized the importance of sustainability but were unaware of how to integrate sustainability practices into their project management activities, highlighting the importance of promoting education and raising awareness about sustainable project management practices. The findings, while based on a limited sample, provide valuable initial insights into the potential of PRiSM™ to foster sustainability in project management. This research underscores the need for further studies to expand and validate these preliminary conclusions.

ServiceNow: Boosting Productivity and Innovation in Healthcare, Manufacturing, and Research

ServiceNow has emerged as a transformative force in enterprise digital transformation across healthcare, manufacturing, and research sectors. The platform's multi-instance cloud architecture enables robust workflow automation and system integration capabilities, fundamentally changing how organizations operate and deliver services. In healthcare, ServiceNow optimizes patient care through automated scheduling, EHR integration, and clinical pathway management, while ensuring regulatory compliance. The manufacturing sector benefits from enhanced production workflows, quality control automation, and predictive maintenance through IoT integration and real-time analytics. In research institutions, the platform streamlines grant management, resource allocation, and regulatory compliance while enabling secure collaboration across organizations. The implementation of comprehensive security measures, including end-to-end encryption and multi-factor authentication, ensures data protection across all sectors. Through phased implementation approaches and continuous improvement processes, organizations achieve significant operational efficiencies and cost reductions. Future developments in AI/ML integration and advanced connectivity options promise to further enhance the platform's capabilities in process automation and decision support.

Advanced microgrid optimization using price-elastic demand response and greedy rat swarm optimization for economic and environmental efficiency

In this paper, a comprehensive energy management framework for microgrids that incorporates price-based demand response programs (DRPs) and leverages an advanced optimization method—Greedy Rat Swarm Optimizer (GRSO) is proposed. The primary objective is to minimize the generation cost and environmental impact of microgrid systems by effectively scheduling distributed energy resources (DERs), including renewable energy sources (RES) such as solar and wind, alongside fossil-fuel-based generators. Four distinct demand response models—exponential, hyperbolic, logarithmic, and critical peak pricing (CPP)—are developed, each reflecting a different price elasticity of demand. These models are integrated with a flexible elasticity matrix to assess the dynamic consumer response to fluctuating electricity prices. The study evaluates four operational scenarios, focusing on grid participation, DER utilization, and the impact of real-time pricing (RTP), time of use (TOU), and critical peak pricing strategies. Quantitative results demonstrate the significant cost-saving potential of integrating DRPs with microgrid operations. In the optimal scenario, the GRSO achieved a minimum generation cost of 882¥ for the base load profile. Further, when critical peak pricing (CPP) was applied, the generation cost was reduced to 746¥, representing a 15.4% reduction. For a scenario where the grid’s participation was limited, the logarithmic-based demand response model decreased the generation cost to 817¥, while full grid interaction led to higher cost reductions. Additionally, our results show a significant reduction in peak load, with load factor improvements of up to 87.7% across the studied demand profiles. Furthermore, limiting the grid’s upstream power capacity to 30 kW resulted in a 7% increase in generation cost across all cases, confirming the importance of grid participation in reducing operational costs. The GRSO algorithm outperformed traditional metaheuristics in terms of both execution time and convergence, making it a viable solution for real-time microgrid optimization. In conclusion, the proposed GRSO-based framework provides an efficient approach for microgrid cost minimization, achieving up to a 15.4% reduction in operational costs and notable environmental benefits by reducing emissions. This study highlights the importance of dynamic demand response strategies and grid participation for sustainable and cost-effective microgrid management.

Proposal for a Sustainable Model for Integrating Robotic Process Automation and Machine Learning in Failure Prediction and Operational Efficiency in Predictive Maintenance

This paper proposes a sustainable model for integrating robotic process automation (RPA) and machine learning (ML) in predictive maintenance to enhance operational efficiency and failure prediction accuracy. The research identified a key gap in the literature, namely the limited integration of RPA, ML, and sustainability in predictive manufacturing, which led to the development of this model. Using the PICO methodology (Population, Intervention, Comparison, Outcome), the study evaluated the implementation of these technologies in Alpha Company, comparing results before and after the model’s adoption. The intervention integrated RPA and ML to improve failure prediction accuracy and optimize maintenance operations. Results showed a 100% increase in mean time between failures (MTBF), a 67% reduction in mean time to repair (MTTR), a 37.5% decrease in maintenance costs, and a 71.4% reduction in unplanned downtime costs. Challenges such as initial implementation costs and the need for continuous training were also noted. Future research could explore integrating big data and AI to further improve prediction accuracy. This model demonstrates that integrating RPA and ML leads to operational improvements, cost reductions, and environmental benefits, contributing to the sustainability of industrial operations.

Analisis Biaya Dalam Perancangan Ulang Alat Pemotong Kripik Singkong Dalam Meningkatkan Kapasitas Dan Efisiensi Studi Kasus : UMKM Kripik Cassava

This study aims to design a cassava chip-cutting machine to increase production capacity and efficiency at the MSME in Bumi Ayu Village, Malang City. Manual cutting results in long working hours and uneven slices. The research methodology includes surveys, problem identification, tool design, testing, and cost and productivity analysis. The findings show that the new tool can speed up cutting, increase production capacity, and meet consumer demand. Before the new tool, cutting productivity was 1.248 kg per hour, with a total of 3.125 kg per day. After implementing the new tool, cutting capacity is expected to increase by 50%, cutting time reduced by 40%, and total production output increased from 170 kg to 255 kg per week. The cost analysis shows a reduction in operational costs and a faster return on investment. This study proves that the new cutting tool can improve efficiency, reduce costs, and enhance the competitiveness of MSMEs in the market. Keywords: Cost Analysis, Cassava Chips, Productivity Analysis, Tool Design

Diversification of Islamic financial products as a strategy to improve Algeria's financial inclusion

This study aims at elucidating how diversifying Islamic financial products can support financial inclusion in Algeria. It includes analysing key indicators of Islamic financial inclusion, assessing the significance and uses of Islamic financial products in extending access to financing, and determining the difficulties Algerian banks encounter when creating, implementing, and designing these products. The study uses an analytical approach, looking at financial inclusion indicators and evaluating how diversifying Islamic products affects increasing financial access. It also looks at the limitations and difficulties banks face when trying to meet market and customer demands while ensuring that these products comply with Sharia law. The results indicate that diversifying and developing Sharia-compliant financial products can enhance financial inclusion by attracting new segments financially excluded by the conventional financial system. Furthermore, achieving financial inclusion requires Islamic banks to prioritise economic efficiency and Sharia credibility in product development, adopt modern digital technologies, and enhance customer engagement. This approach not only strengthens competitive advantage but also boosts operational efficiency, effectiveness, and cost reduction, ultimately supporting broader financial.

Water Treatment Technologies: Development of a Test Bench for Optimizing Flocculation-Thickening Processes in Laboratory Applications

This study introduces an automated test bench designed to optimize flocculation-thickening processes in the wastewater treatment industry. Addressing current challenges in operational efficiency and cost reduction, the test bench employs Model-Based Systems Engineering (MBSE) principles, leveraging SysML modeling within the CESAM framework. By integrating advanced technologies, including PLC programming and a closed-loop control system, this bench provides precise and efficient testing under varying operational conditions. Economic implications are explored, demonstrating the cost-effectiveness of optimized flocculation processes, which reduce chemical use and operational expenditures while enhancing water clarity and sludge management. The system’s 3D modeling enables detailed simulations, aiding in both research and pedagogical applications. This platform highlights the potential of MBSE in creating scalable, robust solutions that contribute to sustainable water management.

The Role of Technology in Optimizing Customer-Centric Supply Chains For Hospitality and Retail

This systematic review explores the pivotal role of technology in optimizing customer-centric supply chains within the hospitality and retail sectors. As consumer demands evolve, businesses are leveraging advanced technologies such as artificial intelligence, Internet of Things, big data analytics, and blockchain to enhance operational efficiency and customer satisfaction. The study examines how these technologies enable real-time tracking, predictive analytics, personalized experiences, and improved transparency, transforming traditional linear supply chains into interconnected, intelligent networks. By analyzing 45 high-quality research articles, this review synthesizes current knowledge on how companies can create more agile and responsive supply chains that not only meet but anticipate consumer needs. The findings reveal significant improvements in key performance indicators, including inventory turnover rates, lead time reduction, and customer retention. Artificial intelligence and machine learning have shown to improve demand forecasting accuracy by up to 37%, while IoT implementation has led to an average 23% reduction in lead times. Big data analytics has driven a 28% increase in customer retention rates, and early blockchain adoption has resulted in a 34% reduction in product recalls. Furthermore, the study found that 82% of companies implementing these technologies reported improved overall supply chain visibility, and 69% experienced enhanced customer satisfaction scores. The integration of these technologies has also led to a 41% increase in supply chain responsiveness and a 19% reduction in operational costs. This comprehensive review provides valuable insights for practitioners and researchers in the rapidly changing hospitality and retail landscapes, offering a roadmap for future technological integration in customer-centric supply chain management.

Blockchain-Powered Energy Optimization in Metro Networks: A Case Study on Electric Braking

As urban populations continue to expand, the need for efficient and sustainable metro systems has become increasingly pressing. Traditional energy management methods, while somewhat effective, often fall short in fully utilizing the potential of regenerative braking systems within metro networks. These conventional approaches, which rely heavily on centralized control and energy storage systems, encounter scalability, security, and transparency limitations. Additionally, inefficient management of energy recovery data can result in significant energy losses and higher operational costs. In response to these challenges, this study proposes a blockchain-based solution utilizing Proof-of-Work (PoW) algorithms to optimize energy recovery, particularly during electric braking in metro systems. The developed model securely and transparently validates energy recovery events in real-time, eliminating the need for centralized oversight. By customizing the PoW algorithm, we achieved a balance between computational efficiency and strong security, making this solution scalable and practical for large metro networks. Initial simulations demonstrated a 12-15% improvement in energy recovery efficiency and a 10% reduction in operational costs compared to traditional systems. Furthermore, the comparison between net energy gains and the energy expended by the PoW process highlights the transformative potential of blockchain technologies in metro transportation, offering a pathway to more sustainable and environmentally friendly urban mobility solutions.

Improving Economic Efficiency Through Asset Management of Information Technology Asset Inventory at PT. Chandra Asri

Effective asset inventory is crucial for asset management, allowing organizations to optimize asset use, prevent loss, and ensure readiness. PT. Chandra Asri faces challenges in IT asset management, including incomplete and inconsistent data, hindering operational efficiency. This qualitative study examines the current state of IT asset management at PT. Chandra Asri and highlights the potential benefits and challenges of implementing advanced technologies like RFID, barcodes, and cloud-based systems. Case studies from various sectors demonstrate significant improvements in operational efficiency, cost reduction, and customer satisfaction with these technologies. This research offers valuable insights for practitioners, policymakers, and academics in developing better asset inventory strategies.

Integration of Blockchain-Based Decentralized Finance into Financial Planning and Analysis: A Framework for Corporate Finance Innovation

The integration of Decentralized Finance (DeFi) into Financial Planning and Analysis (FPA) systems marks a pivotal transformation in corporate financial management, presenting organizations with unprecedented opportunities for operational efficiency, risk management, and strategic advancement. This article provides a comprehensive examination of the implementation framework, challenges, and strategic implications of incorporating DeFi technologies into traditional FPA systems. The article analyzes the technical architecture required for successful integration, including smart contract implementation, decentralized liquidity mechanisms, and blockchain-based audit systems, while addressing critical considerations in regulatory compliance and organizational change management. The article reveals significant potential for cost reduction, improved process efficiency, and enhanced risk management capabilities through DeFi integration while highlighting the importance of robust security protocols and governance frameworks. The article also identifies emerging opportunities in artificial intelligence integration, cross-chain interoperability, and industry-specific applications, offering valuable insights for organizations navigating this technological transformation. Furthermore, the article examines implementation challenges and provides strategic solutions for organizations undertaking DeFi integration initiatives. The article demonstrates that while the integration process presents complex technical and organizational challenges, the potential benefits in terms of operational efficiency, cost reduction, and competitive advantage make it a compelling strategic initiative for forward-thinking organizations. This article contributes to the growing body of knowledge on DeFi implementation in corporate settings and provides practical guidelines for organizations seeking to leverage blockchain technology in their financial operations.

EQUIPMENT AND TECHNOLOGY USED FOR GREEN ENERGY

The effluents of a variety of industrial or commercial activities that include Oil and Grease OG were continuously seen as negative inputs for the receiving bodies that deteriorate their quality or the tentative efficiency. From the other hand and as economy is the major cart for such activities, the energy potential in these OG contents makes it a tempting goal to extract and reuse OG as an energy source whether inside the location or supplied to the market wherever needed. The goal of OG removal and their extraction as a source for biogas production is tested for the aqueous effluent of a vegetable oils and detergents factory via a laboratory-built system that consists of a pressurized flotation basin for the OG extraction from the aqueous industrial effluent via the induced micro-sized air bubbles, that are generated by type RC2, 217 W pressure regulator installed on a 0.75 KW single phase compressor. The skimmed OG is then directed to a 20 l working volume closed cylindrical bio digester to disintegrate the Carbon-Hydrogen bonds anaerobically under controlled thermal environment. Five digesters are built including single phase BG-3D-1 dual impellers rotary mixer and digital thermostat 8820 NTC sensor temperature controller to adjust the temperature of an interior coil heater to examine the impacts of operational time and temperature on the digestion performance for various OG: inoculum ratios and hence determine the performance indicators of the digesters. The chemical oxygen demand COD as the major environmental index in this regard, is determined to yield a reduction of 90.8% of its initial concentration, by the end of operating the bioreactor that worked for a 30 consecutive days at a temperature of 60 ˚C. That is in addition to the production of biogas in about 8.4 l/d (in a daily average of 3.64 l), for a mixture of 5:10 l extracted OG and livestock manure inoculum. These results declare the significant role of installing the suggested anaerobic digester in parallel to the industrial production lines to serve a reduction in overall operational costs via the removal of OG load from the final wastewater treatment plants and the revenue of the produced biogas as an energy source.

ИННОВАЦИОННЫЕ МЕХАНИЗМЫ СТИМУЛИРОВАНИЯ ЭКОНОМИЧЕСКОГО РОСТА НА ПРИМЕРЕ СЕЛЬСКИХ РЕГИОНОВ США

This study analyzes the key challenges and development prospects of US agricultural regions, which occupy more than 97% of the country's territory. It examines major challenges, including rural depopulation, economic stagnation, and limited access to modern technology. Special attention has been paid to effective mechanisms for solving these problems through digital transformation, educational initiatives, and cooperative movement development. The research demonstrates successful examples of public-private partnerships, where innovative approach implementation led to significant results: 15% yield increase in Iowa, 20% growth in farmers' income in Kansas, and a 30% reduction in operational costs in North Dakota. This material is valuable for specialists in agriculture and regional development.

INTEGRATION OF DIGITAL TECHNOLOGIES INTO MARKETING PROCESSES: CHALLENGES AND PROSPECTS

This article examines the challenges and prospects of integrating digital technologies into marketing processes, a critical topic given the increasing competitiveness of the global market. The study underscores the importance of developing effective strategies for adopting digital tools in marketing to retain existing customers, attract new target segments, and ensure long-term business growth. Additionally, it explores the potential of digital transformation in marketing to provide practical recommendations for optimizing resource use and enhancing profitability. By analyzing both theoretical frameworks and practical applications, the research highlights the dual significance of this topic: advancing academic understanding and offering actionable insights for improving organizational competitiveness in dynamic market environments. The findings of the study reveal that digital technologies, encompassing big data, AI, cloud computing, mobile applications, social media, the Internet of Things (IoT), and blockchain, offer multifaceted benefits for marketing. These benefits range from operational optimization and cost reduction to increased productivity and competitive positioning. The ability to automate routine processes reduces reliance on manual labor, accelerates order processing, and improves inventory management. Additionally, personalized customer interaction becomes feasible through advanced data analytics, enabling businesses to tailor marketing strategies to specific audience segments, thereby enhancing customer loyalty and boosting sales. A significant focus of the study is on the integration of digital tools with traditional marketing methods to achieve synergy rather than replacement. This approach ensures a balanced evolution of marketing strategies, leveraging the strengths of both digital and conventional techniques. The ethical and privacy implications of big data utilization also demand attention, requiring a nuanced approach to safeguard consumer trust while exploiting data-driven opportunities. In conclusion, this research highlights the critical role of digital technology integration in transforming marketing practices. By leveraging innovative tools and strategies, businesses can improve operational efficiency, enhance customer experiences, and secure a competitive advantage in the digital age. The insights presented here offer valuable guidance for academics and practitioners aiming to navigate the complexities of digital transformation in marketing.

Hybrid Proximal Policy Optimization—Wasserstein Generative Adversarial Network Framework for Hosting Capacity Optimization in Renewable-Integrated Power Systems

The rapid integration of distributed energy resources (DERs) such as photovoltaics (PV), wind turbines, and energy storage systems has transformed modern power systems, with hosting capacity optimization emerging as a critical challenge. This paper presents a novel Hybrid Proximal Policy Optimization-Wasserstein Generative Adversarial Network (PPO-WGAN) framework designed to address the temporal-spatial complexities and uncertainties inherent in renewable-integrated distribution networks. The proposed method combines Proximal Policy Optimization (PPO) for sequential decision-making with Wasserstein Generative Adversarial Networks (WGAN) for high-quality scenario generation, enabling robust hosting capacity enhancement and operational efficiency. Simulation results demonstrate a hosting capacity improvement of up to 128.6% in high-penetration scenarios (90% renewable), with average operational cost reductions of 22%. Voltage deviations are minimized to within ±5% of nominal levels, while energy losses are reduced by 18%. Scenario quality, evaluated using the Wasserstein metric, achieved convergence with an average score of 0.95 after 80 iterations, highlighting the WGAN’s ability to generate realistic and diverse scenarios. This study advances the state of the art in distribution network optimization by integrating machine learning techniques with robust mathematical modeling. The PPO-WGAN framework enhances scalability, ensures grid stability, and promotes efficient renewable integration, providing a robust foundation for future applications in modern power systems.

Co-Design Optimization and Total Cost of Ownership Analysis of an Electric Bus Depot Microgrid with Photovoltaics and Energy Storage Systems

Due to the increasing share of battery electric buses (BEBs) in cities, depots need to be adapted to the increasing load demand. The integration of renewable energy sources (RESs) into a depot can increase the self-consumption, but optimal sizing is required for a cost-efficient and reliable operation. Accordingly, this paper introduces a co-design optimization framework for a depot microgrid, equipped with photovoltaics (PVs) and an energy storage system (ESS). Three European cities are considered to evaluate the effect of different environmental conditions and electricity prices on the optimal microgrid design. Accurate models of the different subsystems are created to estimate the load demand and the power generation. Different energy management strategies (EMSs), developed to properly control the power flow within the microgrid, are compared in terms of operational costs reduction, one of which was also experimentally validated using a hardware-in-the-loop (HiL) test setup. In addition, the total cost of ownership (TCO) of the depot microgrid is analyzed, showing that an optimally designed depot microgrid can reduce the charging-related expenses for the public transport operator (PTO) by 30% compared to a scenario in which only the distribution grid supplies the BEB depot.

РОЗРОБКА ТА ВИРОБНИЦТВО ЛЕГКИХ ЛІТАЛЬНИХ АПАРАТІВ СІЛЬСЬКОГОСПОДАРСЬКОГО ПРИЗНАЧЕННЯ

Issues of protecting plants from diseases and pests are becoming more and more urgent. Climate change causes an increase in the activity of weedy plants and insects harmful to agriculture. Because of this, the chemical treatment of fields by aviation in modern agriculture should serve the purpose of preserving the future harvest in both a qualitative and quantitative sense. An important role in this is played by the biological method of plant protection, which is quite effective and environmentally friendly. It is based on the use of living organisms, their waste products and biologically active substances that regulate the development and reproduction of harmful plant organisms. Scientists have developed technologies for the breeding of such zoophages to protect plants from plant pests: Trichogramma, predatory mite Phytoseiulus, encarzia, Aphidimyza gallica, etc., as well as the production of microbiological preparations to protect plants from diseases and pests, the high efficiency of their use has been proven. Aircraft (planes, helicopters, ultralight aircraft) that are registered in the State Register of Civil Aviation Aircraft of Ukraine and have a certificate for the right to perform aerochemical work are allowed to carry out aerial work on the application of pesticides during agrochemical activities on agricultural and forest crops. The requirements for the characteristics of the aircraft, directive requirements for the technology of production, operation and maintenance of airworthiness were formulated. The evaluation of the manufacturability of the considered products (agricultural LA) cannot be evaluated without taking into account the operational manufacturability, which largely determines the costs when performing work in the field. Along with the requirements for the manufacturability of the aircraft design, the so-called operational requirements are of great importance. These requirements determine the suitability of the structure and equipment for its maintenance and repair during the operation of the aircraft, taking into account the high quality of work, the least consumption of time, labor and materials. Satisfying operational requirements ensures reliability, durability of the aircraft, high labor productivity during maintenance, reduction of operational costs and efficiency of use of the aircraft fleet. The appearance of the trichogram required the development of special means for its introduction. An attempt to use existing means showed their unsuitability due to their low functional efficiency and high cost of work. The task was solved by increasing the manufacturability of agricultural aircraft during their production and operation. This made it possible to organize its serial production and operation in many farms of the country.

Artificial Intelligence in Quality Control Systems: A Cross-Industry Analysis of Applications, Benefits, and Implementation Frameworks

This article presents a comprehensive analysis of artificial intelligence applications in quality control across manufacturing, service, and infrastructure maintenance sectors. The article examines how AI-driven systems are transforming traditional quality control processes through automated defect detection, real-time monitoring, and adaptive testing methodologies. Through systematic review of industry implementations and case studies, we investigate the impact of machine learning algorithms, computer vision systems, and deep learning applications on quality assurance processes. The findings demonstrate significant improvements in inspection accuracy, reduction in manual inspection requirements, and enhanced detection of subtle defects across various industrial applications. The article reveals that AI-driven quality control systems offer substantial benefits in terms of operational efficiency, cost reduction, and quality consistency, while also identifying key implementation challenges such as initial infrastructure requirements, data quality concerns, and workforce adaptation needs. Additionally, the article provides insights into emerging trends and future opportunities for AI integration in quality control systems, contributing to the broader understanding of Industry 4.0 implementation strategies. This work serves as a foundational reference for organizations considering AI implementation in their quality control processes and provides a framework for evaluating the potential benefits and challenges across different industrial contexts.