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Insurability of cyber physical production systems: How does digital twin improve predictability of failure risk?

 
: Ansari, F.; Nixdorf, S.; Sihn, W.

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Volltext ()

IFAC-PapersOnLine 53 (2020), Nr.3, S.295-300
ISSN: 2405-8963
ISSN: 1474-6670
Workshop on Advanced Maintenance Engineering, Services and Technologies (AMEST) <4, 2020, Online>
Englisch
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer Austria ()

Abstract
Original equipment manufacturers (OEMs), machine operators and suppliers are three main stakeholders in today's industrial asset management lifecycle. Considering high rate of investment and prices to purchase and operationalize secured IoT-based production systems, insurance companies explore contributing into industrial asset management lifecycle by providing new products to transparently monitor online condition and operation status of industrial machines, and accordingly adjust the insurance prices and offers. Hence, joint efforts and cross-disciplinary research is vital to introduce a new insurance product, i.e. failure-based insurance, gaining benefits from AI technologies and knowledge-based maintenance approaches. This paper provides insights into the aforementioned problem, and presents the work-in-progress research on failure-based insurance model aided by Digital Twin technology. Finally, the practical implications and future research directions are outlined.

: http://publica.fraunhofer.de/dokumente/N-639520.html