TU Darmstadt / ULB / TUbiblio

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

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

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.

Item Type: Article
Erschienen: 2018
Creators: Bauerdick, Christoph and Helfert, Mark and Petruschke, Lars and Sossenheimer, Johannes and Abele, Eberhard
Title: An Automated Procedure for Workpiece Quality Monitoring Based on Machine Drive-Based Signals in Machine Tools
Language: English
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.

Journal or Publication Title: Procedia CIRP, 51st CIRP Conference on Manufacturing Systems, Stockholm (Sweden), Elsevier B.V.
Volume: 72
Uncontrolled Keywords: Quality; Monitoring; Tool wear; Data analysis
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Management, Technology and Machine Tools (PTW)
16 Department of Mechanical Engineering > Institute of Production Management, Technology and Machine Tools (PTW) > Sustainable Production (new name since 01.07.2018 ETA Energy Technologies and Applications in Production)
Date Deposited: 03 Jul 2018 09:19
DOI: 10.1016/j.procir.2018.03.245
Official URL: https://doi.org/10.1016/j.procir.2018.03.245
Export:
Suche nach Titel in: TUfind oder in Google

Optionen (nur für Redakteure)

View Item View Item