Preliminary communication

https://doi.org/10.31803/tg-20210504111400

A Knowledge-Based Digital Lifecycle-Oriented Asset Optimisation

Theresa Passath ; Montanuniversitaet Leoben, Department of Economic- and Business Management, Franz Josef Straße 18, 8700 Leoben, Austria
Cornelia Huber ; Montanuniversitaet Leoben, Department of Economic- and Business Management, Franz Josef Straße 18, 8700 Leoben, Austria
Linus Kohl orcid.org/0000-0002-3019-4403 ; TU Wien, Research Group of Smart and Knowledge-Based Maintenance, Theresianumgasse 27, 1040 Vienna, Austria
Hubert Biedermann ; Montanuniversitaet Leoben, Department of Economic- and Business Management, Franz Josef Straße 18, 8700 Leoben, Austria
Fazel Ansari ; TU Wien, Research Group of Smart and Knowledge-Based Maintenance, Theresianumgasse 27, 1040 Vienna, Austria

Abstract

The digitalisation of the value chain promotes sophisticated virtual product models known as digital twins (DT) in all asset-life-cycle (ALC) phases. These models. however, fail on representing the entire phases of asset-life-cycle (ALC), and do not allow continuous life-cycle-costing (LCC). Hence, energy efficiency and resource optimisation across the entire circular value chain is neglected. This paper demonstrates how ALC optimisation can be achieved by incorporating all product life-cycle phases through the use of a RAMS²-toolbox and the generation of a knowledge-based DT. The benefits of the developed model are demonstrated in a simulation, considering RAMS2 (Reliability, Availability, Maintainability, Safety and Sustainability) and the linking of heterogeneous data, with the help of a dynamic Bayesian network (DBN).

Keywords

criticality analysis; digital twin; dynamic Bayesian network; knowledge-based maintenance; RAMS²

Hrčak ID:

258431

URI

https://hrcak.srce.hr/258431

Publication date:

8.6.2021.

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