Improving condition based maintenance with early warning systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

With the evolution of Internet of Things and cheap sensors, it is now easier to install fault detection systems in production lines, which can contribute to reducing costs with unscheduled machines down time and unexpected breakdowns. In this study we discuss a fuzzy early warning approach for improving pro-active Condition Based Maintenance (CBM) strategies. The main objective is to prevent production line break-downs or other hazardous situations, before happening, and to support informed decisions on maintenance strategies using historical data. To demonstrate the approach usefulness an illustrative example is presented.

Original languageEnglish
Title of host publicationProceedings - 47th International Conference on Computers and Industrial Engineering
Subtitle of host publicationHow Digital Platforms and Industrial Engineering are Transforming Industry and Services, CIE 2017
PublisherCurran Associates, Inc.
ISBN (Electronic)978-000000000-2
Publication statusPublished - 1 Oct 2017
Event47th International Conference on Computers and Industrial Engineering: How Digital Platforms and Industrial Engineering are Transforming Industry and Services, CIE 2017 - Lisbon, Portugal
Duration: 11 Oct 201713 Oct 2017

Conference

Conference47th International Conference on Computers and Industrial Engineering: How Digital Platforms and Industrial Engineering are Transforming Industry and Services, CIE 2017
CountryPortugal
CityLisbon
Period11/10/1713/10/17

Keywords

  • Condition Based Maintenance.
  • Decision Support
  • Fuzzy Early Warning System
  • Maintenance

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