Product Quality Improvement Research Articles

THE ROLE OF PRECISION METROLOGY IN ENHANCING MANUFACTURING QUALITY: A COMPREHENSIVE REVIEW

Precision metrology plays a pivotal role in modern manufacturing processes by ensuring the attainment of high-quality standards and the optimization of production efficiency. This comprehensive review delves into the significance of precision metrology in enhancing manufacturing quality across diverse industries. The review encompasses an examination of advanced metrological techniques, their applications, challenges, and future prospects. The review begins by elucidating the fundamental principles of precision metrology, emphasizing its critical role in quantifying dimensional accuracy, surface finish, and other crucial parameters in manufacturing. It explores the evolution of metrology from conventional methods to state-of-the-art technologies such as coordinate measuring machines (CMMs), optical metrology, and 3D scanning systems. The integration of these techniques into modern manufacturing environments has revolutionized quality control processes, enabling real-time monitoring and rapid feedback mechanisms. Furthermore, the review highlights the multifaceted applications of precision metrology across various industries, including automotive, aerospace, electronics, and medical devices. It elucidates how metrological advancements have facilitated the production of intricate components with tight tolerances, thereby enhancing product performance, reliability, and safety. Additionally, the review examines the role of metrology in ensuring compliance with regulatory standards and certifications, crucial for industries with stringent quality requirements. Despite its numerous benefits, precision metrology also poses challenges, such as measurement uncertainties, calibration complexities, and data interpretation issues. The review discusses these challenges in detail and explores emerging strategies and technologies aimed at mitigating them. Furthermore, it addresses the need for standardized metrological practices and international collaboration to foster interoperability and harmonization in global manufacturing ecosystems. Looking ahead, the review outlines future directions and opportunities in precision metrology, including advancements in artificial intelligence, machine learning, and Internet of Things (IoT) integration for predictive maintenance and autonomous quality control systems. It underscores the importance of continued research and innovation in metrology to address evolving manufacturing demands and ensure sustained improvements in product quality and competitiveness. In conclusion, this comprehensive review underscores the indispensable role of precision metrology in enhancing manufacturing quality, driving innovation, and shaping the future of modern industry.
 Keywords: Precision, Metrology, Manufacturing, Quality, Review.

Currency overvaluation and export product quality: Evidence from China

Based on Chinese industrial firm information and international transaction data from 2003 to 2013, we construct a currency overvaluation index across 297 cities in China. Using the innovative index, we present that currency overvaluation significantly promotes export product quality of Chinese manufacturing enterprises, which is conceivably due to increased import of intermediate goods. Heterogeneity analysis reveals that the impact is more pronounced for medium-sized firms, domestic invested firms, and firms in non-mega cities. By investigating the driving forces of export product quality improvement, we provide clear policy implications for government and firms pursuing long-term development.

Water saving irrigation mediates bioactive pigments metabolism and storage capacity in tomato fruit

Tomato fruit consumption is influenced by flavor and nutrient quality. In the present study, we investigate the impact of water saving irrigation (WSI) as a pre-harvest management on flavor and nutrient quality of tomato fruit. Our results demonstrate that WSI-treated tomato fruit exhibited improved sensory scores as assessed by a taste panel, accompanied by elevated levels of SlGLK2 expression, sugars, acids, and carotenoid contents compared to non-treated fruit. Notably, WSI treatment significantly enhanced the development of chloroplast and plastoglobulus in chromoplast, which served as carotenoid storage sites and upregulated the expression of carotenoid biosynthetic genes. Furthermore, integrated transcriptome and metabolome analysis revealed heightened expression of sugar and flavonoid metabolism pathways in WSI-treated tomato fruit. Remarkably, the master regulator SlMYB12 displayed a substantially increased expression due to WSI. These findings suggest that WSI is an effective and sustainable approach to enhance the pigments metabolism and storage capacity as well as the organoleptic characteristics and nutritional value of tomato fruit, offering a win-win solution for both water conservation and quality improvement in agro-food production.

Life cycle assessment of waste tire recycling: Upgraded pyrolytic products for new tire production

Waste tire (WT) pyrolysis is an attractive option for material and energy recovery. Further upgrading of pyrolytic products demonstrates greater environmental and economic advantages than conventional pyrolysis. However, the advance in economic benefits brought by quality improvement of pyrolytic products is not significant. Therefore, this study proposed the circulation case of upgraded pyrolytic products for new tire production from WTs. This case recycles the products produced from WT pyrolysis into new tire production to establish a closed-loop between end-life and beginning-life of WTs. Three circulation cases using different modification methods of pyrolytic carbon black (CBp) were evaluated by several circular economy indicators. Results show that Case M1 (modified CBp (M-CBp) by physical modification) has the best resource-environmental performance (resource benefit to environmental cost ratio, RBECR), which is 20.35 % and 4.62 % higher than those of Cases M2 (M-CBp by nitric acid modification) and M3 (M-CBp by plasma modification), respectively. Case M3 has the best comprehensive performance (economic profit to environmental cost ratio, EPECR), which is 1.62 % and 2.82 % higher than that of Case M1 and Case M2, respectively. To acquire higher profits, the coupled-circulation case that combined M-CBp and reclaimed rubber for new tire production was further proposed, as reclaimed rubber was a major raw material for tire production with higher profitability. The proposed process recycles more materials into new tire production so that the EPECR and RBECR of coupled-circulation case increase by 55.7 % and 147.7 % as compared to the basic circulation case, respectively. Therefore, the coupled-circulation case demonstrates an efficient pathway for WT utilization. The sensitivity analyses further show that both the replacement rate of M-CBp prepared by plasma modification (M3-CBp) and price of crude oil significantly influence the resource-environmental performance, with the sensitivities reaching 101.3 % and 100 %, respectively. The replacement rate of reclaimed rubber is the most important factor for comprehensive environmental-economic performance, with the sensitivity reaching 44.1 %. Generally, coupled-circulation case can maintain good comprehensive benefits when various influencing factors change within the scope discussed in this paper.

Identification of the Causes that Hinder Innovation in Companies in Chihuahua, Mexico

Innovation is a fundamental activity for product diversification and market expansion through the improvement of production processes and product quality. Understanding the causes that hinder innovation within organizations will allow the establishment of mechanisms to reactivate this important activity. With the aim of identifying the causes that hinder innovation in commercial and industrial organizations, the survey identified as CIS-4 was applied to 169 organizations in the state of Chihuahua, with 101 corresponding to organizations in the industrial sector and the rest in the services sector. The results showed cost as the main obstacle, followed by the knowledge factor. By applying the standard instrument for measuring innovation CIS-4, a comparison was made with the application to 20,747 companies in the countries of France and Italy, similarly obtaining cost as the main determinant hindering innovation. The results help us understand how innovation can be stimulated and supported.

Minimalisasi Defect Produk Granite Tile Pada Proses Sorting & Polishing Dengan Pendekatan Root Cause Analysis (RCA) (Studi Kasus di PT. Niro Ceramic Nasional Indonesia, Bogor–Jawa Barat )

Competition in the industry makes manufacturing companies do continuous improvement of production in order to achieve good quality. PT. XYZ is a company engaged in the manufacturing industries that produce granite tile. The problems that often arise on the production floor, especially in the process of sorting and polishing that is, the high defect products produced in the process. The purpose of this study is to minimize damage to the product on the S & P, Useful and finished product quality improvement plans. To support solving this problem, researchers used a method approach Root Cause Analysis (RCA). In the histogram obtained from the check sheets, Pareto diagrams visible damage in the S & P damage type of disability the most dominant is the Crack (57%), followed Thick (18%), Glaze Drop (11%), Black Coring (8%), and the last is the Scraper Defect (6%). From the research, a result that most of the damage is Crack. Factors causing these defects are the factors that cause deviations quality raw materials such factors, factors working methods irregularities in the implementation of the work, a factor that is less engine preventive maintenance, factor of fewer operators do not obey the standard factory operations. From the productivity results in the S & P, generate some suggestion in terms of minimizing the product is defective is implementing kaizen. Keywords: Root Cause Analysis (RCA), Application of Process Improvement, Kaizen, 5S, Granite Tile.

Metabolomic and Growth Responses of Houttyunia cordata to Varying Light Intensities and Subsequent Effects on Fermented Products

Suitable light intensities were studied to enable sustainable and efficient cultivation of Houttuynia cordata with a high yield of bioactive compounds which later can be a good quality material for fermentation. To achieve this goal, the evaluation of physiological adaptation and elucidation of the metabolic alterations of Houttuynia cordata in response to different light intensities were conducted. Four-month-old H. cordata was exposed to 3 different light intensities: high light, control, and low light (100, 50 and 20 % natural irradiances, respectively). Physiological responses were measured using leaf gas exchange. The same leaf samples were either methanolic extracted for LC-QTOF-MS analysis to generate metabolite fingerprints or fermented for 3 months prior to quercetin quantification. High light treatment had the greatest effects on both the physiology and metabolisms of H. cordata compared to control and low light treatments. Compared to the control, the key results observed in high-light-grown H. cordata were a significant increase in photosynthesis, a decrease in relative chlorophyll contents, the enrichment of the top 3 metabolic pathways (phenylpropanoid biosynthesis, pyruvate metabolism and fatty acid degradation) and increasing quercetin concentrations in both fresh and fermented leaves. Metabolite fingerprints of high light-grown H. cordata were distinctively different from those of the other 2 treatments according to PCA and hierarchical clustering analysis. In conclusion, H. cordata responded to high light intensity by enriching the phenylpropanoid biosynthetic pathway to elevate sunscreen pigments. Additional acetyl-CoA generated from pyruvate metabolism and fatty acid degradation was a key supporting factor in the above response. As high quercetin concentration was observed in both fresh and fermented leaves, this will lead to quality improvement of the fermented products. HIGHLIGHTS The remarkable effects of light intensities on Houttuynia cordata growth and abundance of bioactive compounds are substantial, but the underlying mechanism has never been investigated. Metabolomics technology was applied to gain insight into light-induced metabolic reconfiguration. GRAPHICAL ABSTRACT

A Deep-Reinforcement-Learning-Based Digital Twin for Manufacturing Process Optimization

In the context of Industry 4.0 and smart manufacturing, production factories are increasingly focusing on process optimization, high product customization, quality improvement, cost reduction, and energy saving by implementing a new type of digital solutions that are mainly driven by Internet of Things (IoT), artificial intelligence, big data, and cloud computing. By the adoption of the cyber–physical systems (CPSs) concept, today’s factories are gaining in synergy between the physical and the cyber worlds. As a fast-spreading concept, a digital twin is considered today as a robust solution for decision-making support and optimization. Alongside these benefits, sectors are still working to adopt this technology because of the complexity of modeling manufacturing operations as digital twins. In addition, attempting to use a digital twin for fully automatic decision-making adds yet another layer of complexity. This paper presents our framework for the implementation of a full-duplex (data and decisions) specific-purpose digital twin system for autonomous process control, with plastic injection molding as a practical use-case. Our approach is based on a combination of supervised learning and deep reinforcement learning models that allows for an automated updating of the virtual representation of the system, in addition to an intelligent decision-making process for operational metrics optimization. The suggested method allows for improvements in the product quality while lowering costs. The outcomes demonstrate how the suggested structure can produce high-quality output with the least amount of human involvement. This study shows how the digital twin technology can improve the productivity and effectiveness of production processes and advances the use of the technology in the industrial sector.

Strategies With A Wask Cake Trade in The Way of Fighting Online Shop Rivalities in Sikur Village

Strategy is, in fact, planning and managing to a goal. It is also understood as a process of determining a summit leader's plan that focuses on the long-term goals of the organization, accompanied by the elaboration of a way of achieving a specific goal or to face competition. The objective of this research is to find out where wet cake traders are in the midst of online shop competition and to know what strategies the wet cookie traders in Sikur Village use in the face of online store competition. This research uses qualitative methods. The subject of the study is 10 wet pie dealers in Sikur Village. The data in this study is obtained through three methods observation, interview, and documentation. The results of this study are analyzed by reducing data, presenting data and drawing conclusions. The results of this study show that; 1) The situation of wet cake merchants in Sikur Village experienced a slight decline in buyers caused by the presence of a new trading system i.e. trading through online shops. The presence of this new trading system has strengthened the competition between traders, and it has been coupled with advances in society that have made conventional trade abandoned. As a result, the income of most wet cake traders in Sikur Village has fallen. 2) Most wet cake dealers in Sikur Village have a special strategy to survive. The strategy used is product quality improvement strategy, price strategy, service strategy and promotion strategy.

Development of an Adaptive Fuzzy-Neural Controller for Temperature Control in a Brick Tunnel Kiln

This research focuses on developing an adaptive fuzzy-neural control system to manage and maintain temperature in brick tunnel kilns. The problem is how to optimize performance and energy consumption in the brick production process. A control algorithm using a combination of a fuzzy logic system and neural network is proposed to automatically adjust temperature parameters, optimize production efficiency, and reduce energy consumption. Simulation and experimental results demonstrate the outstanding performance of the presented system, with significant improvements in energy efficiency and product quality compared to traditional control methods. Moreover, the obtained results exhibit the potential for wide application of the adaptive neuro-fuzzy control method in academic study or industrial production processes.

OPPORTUNITIES AND CHALLENGES FOR INDIAN RETAIL STORES AND THEIR MARKETING STRATEGIES

Purpose: Recognize consumer needs, seek out new business opportunities, create the best marketing plan, cut costs, and keep an eye on the competition. Because of retailers, consumers have access to a vast array of goods and services from around the globe, and the retail sector boosts employment and the country’s economy. As the studys title suggests, the goal is to look into the Opportunities and Challenges for Indian retail stores and their Marketing strategy. Design/Methodology/Approach: The secondary data for this paper was gathered from a range of sources about the opportunities and challenges of retail stores and their marketing strategies, including research papers, journal articles, and literature reviews. These sources were found by searching for relevant keywords in the Google Scholar search engine, finding relevant websites, and gathering additional information from reports on the opportunities and challenges of retail stores in India. Findings: Price wars among competitors can erode profit margins and negatively impact the industry. Retail stores need to find ways to differentiate themselves beyond just price, such as by offering superior customer service or unique product selections. Retailers can analyse sales data to identify trends, such as which products are selling well and at what times of the year. Understanding the age, gender, and preferences of customers can help tailor marketing and product offerings. Finding out if there is excess stock, understocking, or slow-moving items is crucial for efficient inventory management. Collecting and analysing customer feedback can reveal areas for improvement in customer service or product quality. Originality/Value: A research-based case study on analysis of the opportunities and challenges for Indian retail store and their marketing strategy. Paper Type: Research Case Study KEYWORDS: Opportunities and challenges, Retail store, Profit Margins, Marketing Strategy, Preferences, SWOT Analysis.

Export product quality and inclusivity in developing countries

AbstractImproving the quality of export products is critical for promoting economic development, including for the achievement of sustainable development goals. The present study has examined the effect of export product quality improvement on inclusivity in developing countries. Inclusivity reflects a concomitant increase in the real per capita income, reduction in within‐country income inequality, and poverty reduction. The analysis covers 101 developing countries over the period from 1980 to 2014, and uses primarily the two‐step system Generalized Method of Moments estimator. It shows that export product quality improvement results in greater inclusivity, especially in countries that face high levels of economic growth volatility, including large magnitudes of external shocks. Likewise, export product quality improvement leads to greater inclusivity in countries that experience high levels of export product concentration. The analysis sheds light on the positive contribution of export product quality improvement to inclusivity in developing countries.

Utilization Of Big Data In Business Analysis In Micro, Small And Medium Enterprises (MSME) In Order To Increase The Scale Of Economic Business In The Sumatra Region

The purpose of this study is to analyze the potential and inhibiting factors in MSME businesses in North Sumatra in order to increase the economic scale of these businesses. This research uses a mixed method approach, combining quantitative and qualitative analysis. Secondary data was obtained from sources such as the Central Bureau of Statistics, the Office of Communication and Information, and Bank Indonesia. The quantitative approach was used to provide an overview of MSMEs and economic conditions in the region. The qualitative approach provides an in-depth understanding of the challenges, opportunities and factors affecting the development of MSME. The results revealed that MSME growth in North Sumatra Province still faces a number of challenges. MSME growth is not yet optimal, digital technology adaptation is limited, marketing strategies and product quality need to be improved, and access to capital is still an obstacle. Determinants such as product registration in ecatalogue, management training, increased utilization of information technology, improved product quality, and expanded market access were identified as important measures to improve MSME growth. This research shows that MSME in North Sumatra Province have the potential to contribute more to regional economic growth if the challenges faced can be overcome. Better marketing strategies, adaptation of digital technology, improvement of product quality, and expansion of market access can be key in improving the growth of MSME. Through the recommendations generated, it is expected that the government and businesses can design effective measures to support the sustainable growth of MSME and the regional economy in North Sumatra Province

Empowering Former Women Migrant Workers: Enhancing Socio-Economic Opportunities and Inclusion for Sustainable Development

This research aims to design and implement participatory empowerment programs for former migrant workers, with a focus on non-formal socio-economic initiatives. Utilizing the Participatory Learning and Action (PLA) method in Cilacap Regency, Central Java Province, Indonesia, the study collected data through observations, dialogues, and Participatory Decision-Making (PDM). Purposive sampling involved selecting subjects from the village government, community leaders, and former women migrant workers belonging to entrepreneurial groups. The participatory analysis approach was used to identify, categorize, and prioritize essential and strategic initiatives. The research findings led to the development of non-formal education programs for former women migrant workers, aimed at fostering creativity and innovation in entrepreneurship, administrative management, digital accounting, product quality improvement, product innovation, labeling and packaging, and promotion management with digital marketing. Collaborative efforts between village and district governments, academics, and the community of former women migrant workers were emphasized in planning and implementing these creative socio-economic non-formal education programs. The programs were tailored to address the unique problems, needs, and local resources of the community of former women migrant workers, providing them with the knowledge, motivation, and skills to independently operate economic ventures and improve the well-being of their families.
 
 Received: 1 September 2023 / Accepted: 26 November 2023 / Published: 5 January 2024

Product Quality Improvement of Stainless Steel Round Trash Can with Six Sigma Approach and Fuzzy Analytical Hierarchy process Method at PT. XYZ

PT. XYZ is a manufacturing industry that produces various cleaning equipment. One of the products that has a high level of defects are trash bins made of stainless steel. The purpose of this research is to improve the quality of stainless steel waste products. The method used is Six Sigma and Fuzzy Analytical Hierarchy Process. In the Define stage, the types of defects found were body dents, scratches, spots, and rough covers. In the Measure stage, the initial DPMO value obtained is 3.422. In the Analyze stage, the results of the analysis process are defects with the highest Risk Priority Number of 280. The next stage is Improve, where defects with the highest RPN value are prioritized for proposed improvements using Fuzzy AHP. Based on the results of the Fuzzy AHP assessment, it was found that the highest weight was alternative 3, namely the machine must be cleaned regularly after being used at 0.4322, alternative 2, namely the addition of material handling to facilitate product transfer of 0.2048, and alternative 4, namely the establishment of SOPs for product handling. of 0.2041. After the Improve stage, the final stage in the form of Control is carried out to see whether the implementation of the proposed improvements has a positive impact on the company. The DPMO results obtained after implementation were 3.6061.

ВКЛАД ИННОВАЦИЙ И ЧЕЛОВЕЧЕСКОГО КАПИТАЛА В РОСТ РОССИЙСКОЙ ЭКОНОМИКИ

Russia, as one of the largest economies in the world, strives for sustainable and dynamic growth. To achieve this goal, it is necessary to actively develop innovations and invest in human capital. Innovations, playing a key role in the modern economy, make it possible to create new products, services and technologies that increase production efficiency and competitiveness of enterprises. Also, the introduction of innovations contributes to the growth of labor productivity, improvement of product quality and cost reduction. However, the successful development of innovations requires the availability of highly qualified specialists. Human capital, that is, the knowledge, skills and experience of employees, is one of the main resources determining the competitiveness of the economy. In Russia, there is a need to improve the level of education and professional training in order to ensure access to the latest technologies and innovations. For the development of innovation and human capital in Russia, it is necessary to create a favorable investment environment. This includes improving legal regulation, protecting intellectual property, reducing the bureaucratic burden and encouraging investment in research activities. It is also important to develop cooperation between government, business and scientific institutions for the exchange of knowledge and experience. One of the important tasks is the development of innovative infrastructure. This includes the creation of technology parks, innovation centers and accelerators that provide support and financing for startups and innovative projects. Such infrastructure facilities contribute to the development of entrepreneurship and attract investment in innovative projects. In addition, it is necessary to pay attention to the development of research activities. Public and private investments in science and research allow the creation of new knowledge and technologies that can then be commercialized. It is also important to develop cooperation between universities, research institutes and enterprises for the exchange of experience and the implementation of joint projects.

Deep Learning Algorithms in Industry 5.0: A Comprehensive Experimental Study

This extensive experimental research provides strong empirical proof of the revolutionary power of deep learning algorithms when integrated into Industry 5.0. Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), Generative Adversarial Networks (GAN), and Transformers are a few examples of deep learning algorithms that have shown remarkable accuracy rates of 92.3%, 88.7%, and 95.1%, respectively. Furthermore, the processing durations, which vary between 15 and 25 milliseconds, confirm their ability to make decisions in real time. The abundance of various data accessible in Industry 5.0 is highlighted by data collection sources such as picture databases (300 GB), text corpora (150 GB), equipment records (250 GB), and IoT sensor data (500 GB). The significant energy savings, shown by 20% reductions across a range of machine types, highlight the financial and ecological advantages of deep learning integration. Moreover, the noteworthy improvements in production quality, exhibiting up to 50% reductions in defect rates, highlight the potential of deep learning in quality assurance. These results provide tangible proof of the critical roles deep learning algorithms play in streamlining production lines, increasing energy economy, and boosting product quality in the ever-changing Industry 5.0 environment.

AI Applications in Emotion Recognition: A Bibliometric Analysis

This paper conducts a preliminary exploration of Artificial Intelligence (AI) for emotion recognition, particularly in its business applications. Employing adaptive technologies like machine learning algorithms and computer vision, AI systems analyze human emotions through facial expressions, speech patterns, and physiological signals. Ethical considerations and responsible deployment of these technologies are emphasized through an intense literature review. The study employs a comprehensive bibliometric analysis, utilizing tools such as VOSViewer, to trace the evolution of emotion-aware AI in business. Three key steps involve surveying the literature on emotion analysis, summarizing information on emotion in various contexts, and categorizing methods based on their areas of expertise. Comparative studies on emotion datasets reveal advancements in model fusion methods, exceeding human accuracy and enhancing applications in customer service and market research. The bibliometric analysis sheds light on a shift towards sophisticated, multimodal approaches in emotion recognition research, addressing challenges such as imbalanced datasets and interpretability issues. Visualizations depict keyword distributions in research papers, emphasizing the significance of “emotion recognition” and “deep learning.” The study concludes by offering insights gained from network visualization, showcasing core keywords and their density in research papers. Based on the literature, a SWOT analysis is also conducted to identify the strengths, weaknesses, opportunities, and threats associated with applying emotion recognition to business. Strengths include the technology’s high accuracy and real-time analysis capabilities, enabling diverse applications such as customer service and product quality improvement. However, weaknesses include data bias affecting the AI model’s quality and challenges in processing complex emotional expressions. Opportunities lie in the increasing number of studies, market size, and improving research outcomes, while threats include privacy concerns and growing competition.

Research on the Mechanism and Implementation Path of Enhancing Innovation Capability in Manufacturing Enterprises Based on Human-Machine Collaboration

In today's rapidly evolving business landscape, manufacturing enterprises face the challenge of enhancing their innovation capabilities to remain competitive. This research aims to investigate the mechanism and implementation path of enhancing innovation capability in manufacturing enterprises through human-machine collaboration. By examining the case of Xingyu Co., Ltd., this study explores the effects of human-machine collaboration on production efficiency, cost reduction, product quality improvement, and employee innovation potential. Additionally, it discusses the need for further research to explore the long-term impact of human-machine collaboration on innovation capability, the differences in innovation capability among enterprises of different scales and industries, and the relationship between human-machine collaboration and innovation capability in conjunction with other factors such as organizational culture and management models. The findings suggest that human-machine collaboration significantly enhances innovation capability in manufacturing enterprises, and future research should focus on optimizing implementation strategies to enhance competitiveness and sustainable development capabilities.

ИНТЕЛЛЕКТУАЛЬНЫЕ СИСТЕМЫ УПРАВЛЕНИЯ ПРОИЗВОДСТВЕННЫМИ ПРОЦЕССАМИ

The paper reviews modern intelligent manufacturing process control systems that are based on artificial intelligence and machine learning technologies. Key areas of their application, such as predictive maintenance, real-time optimization of manufacturing operations, and product quality improvement, are analyzed. Real-world examples of the implementation of such systems in industrial enterprises are described, and the main challenges and prospects for further development are discussed. Findings on the impact of intelligent systems on improving the efficiency and competitiveness of manufacturing enterprises are presented.