Detection of wear parameters using existing sensors in the machines environment to reach higher machine precision

• Autorzy: Schmitt R. R. , Decressin R. , Dietrich F. , Dröder K.

Identyfikatory

DOI

10.5604/01.3001.0012.0935

• Języki publikacji: EN

Abstrakty

EN

This paper presents methods to plan predictive maintenance for precision assembly tasks. One of the key aspects of this approach is handling the abnormalities during the development phase, i.e. before and during process implementation. The goal is to identify abnormalities which are prone to failure and finding methods to monitor them. To achieve this, an example assembly system is presented. A Failure Mode and Effects Analysis is then applied to this assembly system to show which key elements influence the overall product quality. Methods to monitor these elements are presented. A unique aspect of this approach is exploring additional routines which can be incorporated in the process to identify machine specific problems. As explained within the paper, the Failure Mode and Effects Analysis shows that the resulting quality in a case study from a precision assembly task is dependent on the precision of the rotational axis. Although the rotational axis plays a significant role in the resulting error, it is hard to explicitly find a correlation between its degradation and produced parts. To overcome this, an additional routine is added to the production process, which directly collects information about the rotational axis. In addition to the overall concept, this routine is discussed and its ability to monitor the rotational axis is confirmed in the paper.

Słowa kluczowe

EN

predictive maintenance; analysis; precision; predictive model

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2018
• Tom: Vol. 18, No. 2
• Strony: 85--96
• Opis fizyczny: Bibliogr. 19 poz., rys., tab.

Twórcy

autor

Schmitt R. R.

• TU Braunschweig, Institute of Machine Tools and Production Technology, Braunschweig, Germany

autor

Decressin R.

• TU Braunschweig, Institute of Machine Tools and Production Technology, Braunschweig, Germany

autor

Dietrich F.

• TU Braunschweig, Institute of Machine Tools and Production Technology, Braunschweig, Germany

autor

Dröder K.

• TU Braunschweig, Institute of Machine Tools and Production Technology, Braunschweig, Germany

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).