Online Condition Monitoring Tool for Automated Machinery


Date

2017

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

In order to increase machinery resource, energy and time efficiency, Condition Monitoring (CM) offers a wide set of beneficial tools. Those tools can basically be segmented in maintenance improvements or the optimization of process parameters. CM requires data input from a component, which is then analyzed using data based or physical models, which return an estimate of the component_s current condition. The use of high quality sensors in a stable laboratory environment generally leads to an overemphasizing of the results which CM systems achieve in an industrial environment. Additionally, the installation of sensors is not always economically feasible for low-cost machinery. To overcome this, the CM system which is presented in this paper uses data, which is usually present in the PLC, as a consequence thereof, the data quality is significantly lower compared to dedicated sensor equipment. A real production machinery is further used to demonstrate the capabilities of condition monitoring in an industrial environment. The data driven CM process, which is used in this application example is compared to a model driven approach, conducted on a test equipment machine.

Publication status

published

Book title

16th CIRP Conference on Modelling of Machining Operations

Journal / series

Volume

58

Pages / Article No.

323 - 328

Publisher

Elsevier

Event

16th CIRP Conference on Modeling of Machining Operations (CIRP CMMO 2017)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Monitoring; Diagnostics; Optimisation of Machining Processes

Organisational unit

03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus) check_circle
08844 - Kunz, Andreas (Tit.-Prof.) / Kunz, Andreas (Tit.-Prof.) check_circle

Notes

Funding

Related publications and datasets