OBRABOTKAMETALLOV Vol. 26 No. 3 2024 technology Product life cycle: machining processes monitoring and vibroacoustic signals filtering Mikhail Gimadeev a, *, Vadim Stelmakov b, Evgenii Shelenok c Pacific National University, 136 Tihookeanskaya st., Khabarovsk, 680035, Russian Federation a https://orcid.org/0000-0001-6685-519X, 009063@pnu.edu.ru; b https://orcid.org/0000-0003-2763-1956, 009062@pnu.edu.ru; c https://orcid.org/0000-0003-4495-9558, 007141@pnu.edu.ru Obrabotka metallov - Metal Working and Material Science Journal homepage: http://journals.nstu.ru/obrabotka_metallov Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science. 2024 vol. 26 no. 3 pp. 94–113 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2024-26.3-94-113 ART I CLE I NFO Article history: Received: 29 May 2024 Revised: 23 June 2024 Accepted: 12 July 2024 Available online: 15 September 2024 Keywords: Life cycle Equipment measurement sensors Acoustic diagnostics Vibration Tool status monitoring Online monitoring Machining process Funding This work has funded by the Ministry of science and higher education of Russian Federation (project № FEME– 2024–0010). ABSTRACT Introduction. In modern manufacturing, the product life cycle comprises various stages, from conception to disposal. Among these stages, machining plays a significant role, as it directly influences the durability and functionality of the finished product. With increasing competition and the need to reduce production costs, optimizing machining processes has become a crucial task. Traditionally, conservative technological approaches have been used to ensure processing quality. However, this often leads to decreased productivity and higher costs. Modern monitoring and diagnostic techniques can significantly improve process control, particularly through tool condition monitoring. The subject. This paper discusses the stages of the product life cycle and emphasizes the importance of monitoring machining processes. It explores the potential of using vibroacoustic signals to continuously monitor equipment and product conditions. Special attention is paid to the use of vibroacoustic signals for diagnostics and quality control. Modern approaches to filtering these signals, including the use of the fast Fourier transform and various window functions, are analyzed in order to improve the accuracy of the analysis and identify potential defects. The purpose of this work is to develop an algorithm for an online monitoring system that will monitor the condition of cutting tools based on the creation of a digital shadow using a vibroacoustic complex. The main tasks to be solved are to establish the ranges of applicability of frequency response of acoustic signals and optimal window functions, as well as to establish the relationship between the degree of wear on the cutting tool and the results of vibration diagnostics and surface roughness. The methods and technologies for filtering vibroacoustic signals and their application in real–world production settings are discussed. Special attention is given to the role of digital twins in integrating monitoring and filtering data, allowing for the creation of a virtual model of a product to predict its behavior and optimize processes throughout the life cycle. A comparison of various monitoring methods and technologies is conducted, as well as an analysis of practical examples of digital twin implementation in production processes and its impact on improved control. Results and discussion are presented, identifying current research and practical advancements, while also proposing existing challenges and promising areas for future research in the fields of monitoring, signal filtering, and the use of digital twins in mechanical manufacturing. For citation: Gimadeev M.R., Stelmakov V.A., Shelenok E.A. Product life cycle: machining processes monitoring and vibroacoustic signals filterings. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2024, vol. 26, no. 3, pp. 94–113. DOI: 10.17212/1994-6309-2024-26.3-94-113. (In Russian). ______ * Corresponding author Stelmakov Vadim A., Ph.D. (Engineering), Associate Professor Pacific National University, 136 Tihookeanskaya st., 680035, Khabarovsk, Russian Federation Tel.: +7 962 221-74-60, e-mail: 009062@pnu.edu.ru Introduction The transformation of industry during the implementation of the «Industry 4.0» concept opens up prospects for the use of new high-performance approaches to management at all life cycle stages [1], incl. through the use of digital twins (DT) [2, 3]. DT technology is the main component of a cyber physical system (CPS) [4], which allows collecting and managing large amounts of data (Big Data) [5], determining the behavior and reflecting the state of the production system in real time [6], and analyzing, modeling, predicting and optimizing various production processes [7–9].
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