An analysis of the operating parameters of the vacuum furnace with regard to the requirementsof predictive maintenance

• Autorzy: Kłos Sławomir , Papacz Władysław , Piechowicz Łukasz

Identyfikatory

DOI

10.24425/mper.2019.131444

• Języki publikacji: EN

Abstrakty

EN

The Industry 4.0 Concept assumes that the majority of industry’s resources will be able to self-diagnose; this will, therefore, enable predictive maintenance. Numerically controlled machines and devices involved in technological processes should, especially, have the facility to predict breakdown. In the paper, the concept of a predictive maintenance system for a vacuum furnace is presented. The predictive maintenance system is based on analysis of the operating parameters of the system and on the algorithms for identifying emergency states in the furnace. The algorithms will be implemented in the monitoring sub-system of the furnace. Analysis of the operating parameters of vacuum furnaces, recorded in the Cloud will lead to increased reliability and reduced service costs. In the paper, the research methodology for identification of the critical parameters of the predictive maintenance system is proposed. Illustrated examples of the thermographic investigation of a vacuum furnace are given.

Słowa kluczowe

EN

predictive maintenance; vacuum furnace; Industry 4.0; self-monitoring; thermo-visual investigation

• Wydawca: Production Engineering Committee of the Polish Academy of Sciences ; Polish Association for Production Management
• Czasopismo: Management and Production Engineering Review
• Rocznik: 2019
• Tom: Vol. 10, No. 4
• Strony: 48--54
• Opis fizyczny: Bibliogr. 23 poz., rys., wykr.

Twórcy

autor

Kłos Sławomir

• University of Zielona Góra, Faculty of Mechanical Engineering, Licealna 9, 65-417 Zielona Góra, Poland

autor

Papacz Władysław

• University of Zielona Góra, Faculty of Mechanical Engineering, Poland

autor

Piechowicz Łukasz

• Seco/Warwick S.A., Poland

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).