Predictive maintenance with NOA: Application and insights for rotating equipment

Research output: Contribution to journalConference articleContributedpeer-review

Contributors

Abstract

This paper considers an implementation of the predictive maintenance for rotating equipment in a chemical process plant by means of the NAMUR Open Architecture (NOA). Various methods and challenges for monitoring of rotating equipment are described and compared. An approach based on the motor current measurement for the use case at a BASF plant was selected due to construction limitations. The focus is on connectivity aspects as well as details of implementation of the NOA concept. Use of the NOA concept made it possible to deploy the developed monitoring system into a real plant within one day during a planned maintenance window without any permanent alterations to the existing plant. The monitoring system works in parallel and affects neither the process nor the process control directly. Discussion of the first data gathered by the installed monitoring system showed that additional context information about the process are of great importance for the comprehensive analysis. At the end of the paper, improvements with regards to the connectivity and integration of additional sensors as well as further activities such as coupling of context information about the process and development of a decision making system are discussed.

Details

Original languageEnglish
Pages (from-to)761-767
Number of pages7
JournalIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Publication statusPublished - Sept 2020
Peer-reviewedYes

Conference

Title2020 25th IEEE International Conference on Emerging Technologies and Factory Automation
Abbreviated titleETFA 2020
Conference number25
Duration8 - 11 September 2020
Website
Degree of recognitionInternational event
LocationTU Wien & online
CityVienna
CountryAustria

External IDs

ORCID /0000-0001-5165-4459/work/142248239

Keywords

Keywords

  • modelling, motor current analysis, NOA, predictive maintenance, process industry, rotating equipment