TU Darmstadt / ULB / TUbiblio

An Automated Procedure for Workpiece Quality Monitoring Based on Machine Drive-Based Signals in Machine Tools

Bauerdick, Christoph ; Helfert, Mark ; Petruschke, Lars ; Sossenheimer, Johannes ; Abele, Eberhard :
An Automated Procedure for Workpiece Quality Monitoring Based on Machine Drive-Based Signals in Machine Tools.
[Online-Edition: https://doi.org/10.1016/j.procir.2018.03.245]
In: Procedia CIRP, 51st CIRP Conference on Manufacturing Systems, Stockholm (Sweden), Elsevier B.V., 72 pp. 526-532. ISSN 2212-8271
[Artikel], (2018)

Offizielle URL: https://doi.org/10.1016/j.procir.2018.03.245

Kurzbeschreibung (Abstract)

Currently, more and more cyber-physical systems that constantly collect a variety of data are introduced into production lines. This data is often not completely evaluated, even though it could provide new approaches to significantly increase the productivity, flexibility as well as resource and energy efficiency of the production. This paper presents a fully automated procedure to collect and analyze machine drive-based signals of a programmable logic controller. The goal is to derive a workpiece flaw diagnosis from the processed raw data of the machine tool and examine the influence of cutting parameters on the diagnosis and tool wear. In order to conduct this multi-sensor-analysis, the signals of the machine drives are measured at the frequency inverter and evaluated using a script, which is integrated in a monitoring software. It is shown that the cutting parameters have a strong influence on tool wear and the accuracy of the diagnosis.

Typ des Eintrags: Artikel
Erschienen: 2018
Autor(en): Bauerdick, Christoph ; Helfert, Mark ; Petruschke, Lars ; Sossenheimer, Johannes ; Abele, Eberhard
Titel: An Automated Procedure for Workpiece Quality Monitoring Based on Machine Drive-Based Signals in Machine Tools
Sprache: Englisch
Kurzbeschreibung (Abstract):

Currently, more and more cyber-physical systems that constantly collect a variety of data are introduced into production lines. This data is often not completely evaluated, even though it could provide new approaches to significantly increase the productivity, flexibility as well as resource and energy efficiency of the production. This paper presents a fully automated procedure to collect and analyze machine drive-based signals of a programmable logic controller. The goal is to derive a workpiece flaw diagnosis from the processed raw data of the machine tool and examine the influence of cutting parameters on the diagnosis and tool wear. In order to conduct this multi-sensor-analysis, the signals of the machine drives are measured at the frequency inverter and evaluated using a script, which is integrated in a monitoring software. It is shown that the cutting parameters have a strong influence on tool wear and the accuracy of the diagnosis.

Titel der Zeitschrift, Zeitung oder Schriftenreihe: Procedia CIRP, 51st CIRP Conference on Manufacturing Systems, Stockholm (Sweden), Elsevier B.V.
Band: 72
Freie Schlagworte: Quality; Monitoring; Tool wear; Data analysis
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement, Technologie und Werkzeugmaschinen (PTW)
16 Fachbereich Maschinenbau > Institut für Produktionsmanagement, Technologie und Werkzeugmaschinen (PTW) > Umweltgerechte Produktion
Hinterlegungsdatum: 03 Jul 2018 09:19
Offizielle URL: https://doi.org/10.1016/j.procir.2018.03.245
Export:

Optionen (nur für Redakteure)

Eintrag anzeigen Eintrag anzeigen