University of Limerick Institutional Repository

Remote acoustic analysis for tool condition monitoring

DSpace Repository

Show simple item record Coady, James Toal, Daniel Newe, Thomas Dooly, Gerard 2020-04-27T11:21:08Z 2020-04-27T11:21:08Z 2019
dc.description peer-reviewed en_US
dc.description.abstract Within the manufacturing industry, predictive maintenance is a well-established concept, dating back to the 1990‘s [1]. Practice has shown it to have a proven track record of minimising unnecessary machine downtime. The methods of predictive maintenance have varied widely, including visual inspection (i.e. human monitoring), thermal imaging, ultrasonic analysis, vibration analysis, power consumption, acoustic emission, to name a few. As manufacturing technologies have developed, maintenance in general has become a more complex task, presenting many challenges for researchers, engineers and scientists. These challenges have been met through research and development of new technologies and methods of maintenance. Some of these methods currently involve installing intricate sensor systems which are placed on, or in close proximity to the system Practice is now moving towards using remote monitoring systems (RMS) as a possible method to reduce some of these issues. Thisis due to the ability to carry out monitoring without having to install the monitoring system on the structure of the SUT, hence minimising the potential for damage to the sensor systems. This paper aims to describe the importance of predictive maintenance (PdM) over other maintenance methods (e.g. Peer review under the responsibility of the scientific committee of the Flexible Automation and Intelligent Manufacturing 2019 under test (SUT). Although some of these monitoring methods have been slow to catch on within industry, much of the reason for this can be accredited to the high cost of these sensors along with the high probability of damage to and the replacement of them. reactive, corrective etc.), the importance of PdM for the metal cutting industry (focusing on cutting tool wear), while also discussing some common methods of predictive maintenance monitoring system methods already being utilised within industry. The final method discussed is remote monitoring systems used to monitor transmitted sound, while also identifying how this monitoring system could be integrated within the smart manufacturing environment that is being driven by Industry 4.0. en_US
dc.language.iso eng en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Procedia Manufacturing . 29th (FAIM2019);38, pp. 840–847
dc.subject Predictive Maintenance en_US
dc.subject Remote Monitoring System en_US
dc.subject Tool Condition Monitoring System en_US
dc.title Remote acoustic analysis for tool condition monitoring en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.contributor.sponsor SFI en_US
dc.contributor.sponsor ERC en_US
dc.relation.projectid 16/RC/3918 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US

Files in this item

This item appears in the following Collection(s)

Show simple item record

Search ULIR


My Account