Exploring the role of Digital Twin for Asset Lifecycle Management

Macchi, Marco; Roda, Irene; Negri, Elisa; Fumagalli, Luca

doi:10.1016/j.ifacol.2018.08.415

Cited by 171 publications

(86 citation statements)

References 15 publications

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“…This concept has first been utilised in the aerospace industry for service-life management of airplanes. Several use cases which used the digital twins for life-cycle management of different systems have been examined in the work of Macchi et al (2018) . Examples of such cases used in different industries include (i) Optimised maintenance planning and decision making on the structure subjected to different failure modes ( Kampczyk, 2020 ; Wang et al, 2019 ; Xiao et al, 2019 ), (ii) System life-cycle modelling ( Kaewunruen and Lian, 2019 ; Lim et al, 2019 ), and (iii) System performance optimisation ( Zhang et al, 2017 ; Guerra et al, 2019 ).…”

Section: Reliability Analysis Of the Integrated Systemmentioning

confidence: 99%

Reliability of multi-purpose offshore-facilities: Present status and future direction in Australia

Aryai

Abdussamie

Salehi

et al. 2021

Process Safety and Environmental Protection

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Sustainable use of the ocean for food and energy production is an emerging area of research in different countries around the world. This goal is pursued by the Australian aquaculture, offshore engineering and renewable energy industries, research organisations and the government through the “Blue Economy Cooperative Research Centre”. To address the challenges of offshore food and energy production, leveraging the benefits of co-location, vertical integration, infrastructure and shared services, will be enabled through the development of novel Multi-Purpose Offshore-Platforms (MPOP). The structural integrity of the designed systems when being deployed in the harsh offshore environment is one of the main challenges in developing the MPOPs. Employing structural reliability analysis methods for assessing the structural safety of the novel aquaculture-MPOPs comes with different limitations. This review aims at shedding light on these limitations and discusses the current status and future directions for structural reliability analysis of a novel aquaculture-MPOP considering Australia’s unique environment. To achieve this aim, challenges which exist at different stages of reliability assessment, from data collection and uncertainty quantification to load and structural modelling and reliability analysis implementation, are discussed. Furthermore, several solutions to these challenges are proposed based on the existing knowledge in other sectors, and particularly from the offshore oil and gas industry. Based on the identified gaps in the review process, potential areas for future research are introduced to enable a safer and more reliable operation of the MPOPs.

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Section: Reliability Analysis Of the Integrated Systemmentioning

confidence: 99%

Reliability of multi-purpose offshore-facilities: Present status and future direction in Australia

Aryai

Abdussamie

Salehi

et al. 2021

Process Safety and Environmental Protection

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“…Recently, sustainability in maintenance management has attracted much attention from both researchers and practitioners (Franciosi et al 2017;Maletič et al 2018;Singh and Gupta 2020;Boral et al 2019;Franciosi et al 2020a). Through innovative management practices, incorporating sustainability goals into maintenance management strategies and utilizing the potential available through new Maintenance 4.0 technologies at all stages of the machine's life cycle, maintenance should and can contribute to promoting sustainable development (Bilge et al 2017;Bokrantz et al 2017;Chen et al 2018;Franciosi et al 2018;Macchi et al 2018;Jasiulewicz-Kaczmarek and Gola 2019;Franciosi 2020b;Bevilacqua et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Fuzzy set theory driven maintenance sustainability performance assessment model: a multiple criteria approach

Jasiulewicz-Kaczmarek

Żywica

Gola

2021

J Intell Manuf

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During the last five decades, manufacturing has radically changed not only due to the technology development but also because of the new market and environmental requirements. Nowadays, companies are focused not only on cost-reduction and effectiveness or realized processes but also on reducing the negative impact on natural and social environment. Therefore, the maintenance is also transforming its role in order to better support value creation, both contributing to the economic dimension as well as extending its care for the environmental and social aspects. The paper presents a new method to solve the problem of the initial maintenance indicator merge into a new synthetic index that allows measuring the level of maintenance sustainability. The proposed approach allows to look at the process of combining indicators from a different perspective (i.e. through interactions between criteria) to help decision-makers in improving economic, social and environmental results of maintenance system. To justify effectiveness of proposed approach, it was applied to Composite Maintenance Sustainability Indicator, which was therefore generalized and expanded, so that it could be used in decision support system. The included case study shows the real benefit of using the proposed approach to analyse the actual results of maintenance system from sustainability point of view and forecasting future actions.

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“…1, showing examples of DT-based functionalities for different application domains (production, energy, quality, maintenance …) in the industrial practice. Moreover, DT represents the virtual counterpart of the physical asset along all its life cycle, then it aids in the management of physical assets by supporting decision-making throughout the lifecycle (Macchi et al 2018), also using the integration with an intelligence layer (Negri et al 2020). Essentially being a simulation, the DT is persistent and exists even when disconnected from the physical counterpart (Borangiu et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Field-synchronized Digital Twin framework for production scheduling with uncertainty

et al. 2020

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Research on scheduling problems is an evergreen challenge for industrial engineers. The growth of digital technologies opens the possibility to collect and analyze great amount of field data in real-time, representing a precious opportunity for an improved scheduling activity. Thus, scheduling under uncertain scenarios may benefit from the possibility to grasp the current operating conditions of the industrial equipment in real-time and take them into account when elaborating the best production schedules. To this end, the article proposes a proof-of-concept of a simheuristics framework for robust scheduling applied to a Flow Shop Scheduling Problem. The framework is composed of genetic algorithms for schedule optimization and discrete event simulation and is synchronized with the field through a Digital Twin (DT) that employs an Equipment Prognostics and Health Management (EPHM) module. The contribution of the EPHM module inside the DT-based framework is the real time computation of the failure probability of the equipment, with data-driven statistical models that take sensor data from the field as input. The viability of the framework is demonstrated in a flow shop application in a laboratory environment.

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Exploring the role of Digital Twin for Asset Lifecycle Management

Cited by 171 publications

References 15 publications

Reliability of multi-purpose offshore-facilities: Present status and future direction in Australia

Reliability of multi-purpose offshore-facilities: Present status and future direction in Australia

Fuzzy set theory driven maintenance sustainability performance assessment model: a multiple criteria approach

Field-synchronized Digital Twin framework for production scheduling with uncertainty

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