title: ÐÐ¾ÑÑÑÐ¾ÐµÐ½Ð¸Ðµ Ð±Ð¸Ð·Ð½ÐµÑ-Ð¿ÑÐ¾ÑÐµÑÑÐ¾Ð² Ð½Ð° Ð¿ÑÐµÐ´Ð¿ÑÐ¸ÑÑÐ¸Ð¸ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐºÐ²Ð¾Ð·Ð½ÑÑ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸Ð¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Building business processes based on end-to-end technologies
Creators: name: Ð¨ÑÐ²Ð°Ð»Ð¾Ð², ÐÐ¸ÐºÐ¸ÑÐ°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð±Ð¸Ð·Ð½ÐµÑ-Ð¿ÑÐ¾ÑÐµÑÑÑ
Ð´ÐµÑÐµÐºÑÐ¾ÑÐºÐ¾Ð¿Ð¸Ñ
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ ÑÑÐ¸ÑÐµÐ»ÐµÐ¼
ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ðµ Ð·ÑÐµÐ½Ð¸Ðµ
business processes
defectoscopy
supervised learning
computer vision

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description: Masters thesis topic: "Building business processes based on end-to-end technologies". The relevance of the topic is determined by the significant potential of machine learning and artificial intelligence in increasing labor productivity. In the context of the current movement towards the implementation of lean manufacturing philosophy, increasing labor productivity, green energy, sustainable development, optimizing energy use, and improving the quality of produced goods becomes increasingly important. Artificial intelligence and machine learning offer powerful tools to achieve these goals. The aim of the study is:Â  Building Quality Management Business Processes at the "Power Machin" JSC machine-building enterprise using software with the application of artificial intelligence technologies for data processing - computer vision. Object of Research: Quality management processes at the machine-building enterprise JSC "Power Machines", with a focus on the defectoscopy processes of weld seams. The research object encompasses both current quality control methods and the potential for implementing innovative technologies based on artificial intelligence and machine learning to optimize and enhance the efficiency of these processes. Subject of Research: The development and testing of software for the defectoscopy of weld seams, based on the application of neural network algorithms, within the context of quality management business processes at the enterprise. The subject of research includes the analysis and comparison of neural network methods with traditional approaches in defectoscopy, the development and testing of a new software solution, as well as evaluating its effectiveness and impact on the business processes of the enterprise. The following tasks were solved: - The current business process for managing the quality of welded products at the AO "Silovye Mashiny" Elektrosila Plant, Workshop â11, was analyzed to identify its shortcomings. - Study and Comparative analysis of neural network and classical data processing methods. - Research and analysis of neural network algorithms and training in the context of their applicability to defectoscopy tasks. - Development of an application for the defectoscopy of welds, based on the application of neural network algorithms. - Testing the developed software for the defectoscopy of welds and evaluating the developed application in real conditions of the production process. - Evaluation of the efficiency of the modified business process and subsequent optimization opportunities. - Research methods: Artificial intelligence methods, including neural networks, data analysis, mathematical modeling, and statistical analysis. Main research results: The developed method showed promising results when tested on simulated and real data, demonstrating its potential for application in the business process of quality control of products at "Power Machines" JSC. Field of application of the research results: Energy industry, Metalworking, Quality management, defectoscopy. The novelty of the research is: Developing a new approach to building a quality management business process for products using end-to-end technologies. Conclusions: The results of this study show that neural network algorithms for defectoscopy demonstrate promising results that allow designing business processes with a focus on greater efficiency and productivity.