Autors: Antoniy Petrov., Taneva, A. M.
Title: Process Inspection and Data Collection for Manufacturing
Keywords: data collection, quality management, production control, fau

Abstract: Manufacturing systems of the future will be characterized by the individualization of products, early detection, diagnosis of faults, forecast of equipment damage, loss of performance and profits and even more. Nowadays, based on informatics evolution and its application in industrial area, the so-called Smart Manufacturing (SM) has promised to ensure self-optimizing manufacturing in industry by its potential such as maintaining reliability of equipment. For this purpose, in this article the benefits and challenges of self-optimizing manufacturing concept regarding its capability and responsibility are presented describing the adaptation to changing manufacturing environment. The idea of the work is to obtain data, needed for Key Performance Indicators (KPIs) calculation, then to apply IIoT solutions for collecting, visualizing and store the information for further analysis. The major and desired effects are: the time decrease for decision taking, product quality improvement, delivery



    2022 International Conference Automatics and Informatics (ICAI), pp. 339 - 344, 2022, Bulgaria, IEEE, DOI 10.1109/ICAI55857.2022.9960027

    Copyright Automatics and Informatics (ICAI), International Conference

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    Цитирания (Citation/s):
    1. Abdul Rehan Khan Mohammed, Jiayi Zhang, Benjamin Silverstone, Ahmad Bilal, "Literature Survey on Manufacturing Shop Floor Performance Measurements: Frameworks, Models, and Categorizations", 2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS), pp.1-8, 2023. - 2023 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus и Web of Science