Department of Business Development and Technology

Comparison between data maturity and maintenance strategy: A case study

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

From Industry 4.0 there has been a substantial drive towards sensor networks for enabling predictive maintenance as essential in asset management. This paper analyze sensor data maturity and asset management strategy. A model is proposed for establishing a best-fit correlation between data maturity and maintenance strategy both as for the current situation and guide for future development. The findings are based on literature and case studies in the SME segment. Research implications are to view enterprise strategy as a balance between chosen maturity and operational needs. Practical implications are the possibility to sustain or improve and qualify investment planning.
Original languageEnglish
Publication year15 Jan 2021
Publication statusSubmitted - 15 Jan 2021

    Research areas

  • Manufacturing, Asset management, Data Maturity, Sensor Networks, Predictive Maintenance, Internet-of-things, SME

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ID: 208292728