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Furthermore, successful predictive maintenance initiatives require that pre-conditions are fulfilled: Data must be available and accessible. Very important is also the support by the management. We identified four factors important for the implementation of predictive maintenance. The integration of data is highly facilitated by Cloud-based mechanisms. The detection of events is enabled by advanced analytics. The execution of predictive maintenance operations is supported by data-driven process automation and visualization.<\/p>","DOI":"10.4018\/ijeis.2020040102","type":"journal-article","created":{"date-parts":[[2020,2,21]],"date-time":"2020-02-21T10:37:18Z","timestamp":1582281438000},"page":"22-37","source":"Crossref","is-referenced-by-count":7,"title":["Predictive Maintenance Information Systems"],"prefix":"10.4018","volume":"16","author":[{"given":"Michael","family":"M\u00f6hring","sequence":"first","affiliation":[{"name":"Munich University of Applied Sciences, Lothstr, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1637-0589","authenticated-orcid":true,"given":"Rainer","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Munich University of Applied Sciences, Lothstr, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barbara","family":"Keller","sequence":"additional","affiliation":[{"name":"Munich University of Applied Sciences, Lothstr, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kurt","family":"Sandkuhl","sequence":"additional","affiliation":[{"name":"The University of Rostock, Rostock, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alfred","family":"Zimmermann","sequence":"additional","affiliation":[{"name":"Reutlingen University, Reutlingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJEIS.2020040102-0","author":"V. 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