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Cloud-based Factory Machinery Uptime Management using a Coupled Model Approach 

Cloud-based Factory Machinery Uptime Management using a Coupled Model Approach 

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With rising competition abroad, US manufacturers are looking to reinvest manufacturing capabilities to counterbalance costs by increasing productivity. Being a dynamic and technologically advanced industry, as well as constantly to meet changing market demands, manufacturers are now forced to evolve strategies to manage larger capacity with faster...

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... with ubiquitous connectivity offered by cloud computing technology, the coupled model also provides better accessibility of machine condition for factory managers in cases where physical access to actual equipment or machine data is limited. Figure 5 shows a demonstration system on cloud-based factory machinery uptime management using coupled model at NSF I/UCRC on Intelligent Maintenance Systems at the University of Cincinnati. The coupled model approach not only reflects current health information of the machinery but also keeps records of all the historical status of a machine. ...

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... One of the maintenance-related aims of this application was to estimate the remaining useful life of the vehicle (Glaessgen and Stargel, 2012;Reifsnider and Majumdar, 2013). DTs have since been adopted by the manufacturing sector, especially in the context of Smart Manufacturing (Lee et al., 2013;Lu et al., 2020;. Although consensus definition of and reference architecture for Digital Twins is still lacking (Lu et al., 2020;Kritzinger et al. 2018), most authors agree that a Digital Twin at least comprises of 1) the (real-time) reflection of a physical counterpart's state, 2) the representation of the physical counterpart's design and configuration and 3) the ability to reflect and predict the physical counterpart's behaviour. ...
... DTs include integrated "ultra-realistic, high-fidelity" (Glaessgen and Stargel, 2012;Shaſto et al., 2012) models describing their physical counterpart's behaviour (Rosen et al., 2015;Glaessgen and Stargel, 2012;Reifsnider and Majumdar, 2013;Lee et al., 2013). Besides multi-physics (Arkouli et al. 2020) and numerical modelling (e.g. ...
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This white paper presents a review of the lessons learned from the point of view of six EU funded H2020 research projects (PRECOM, PROPHESY, PROGRAMS, SERENA, UPTIME and Z-BREAK), funded under the topic “FOF-09-2017 - Novel design and PdM technologies for increased operating life of production systems”. These projects were active from 2017 to 2021 and together constituted the ForeSee cluster. Research and technology partners together with industrial end-users worked collaboratively to develop and deploy solutions that advance maintenance practice in industry towards more efficient, sustainable, human-centric and resilient factories. This white paper aims to share knowledge, vision and lessons learnt by ForeSee cluster partners on the topic of PdM, as well as to provide recommendations for advancing PdM in industrial practice. The core target groups of this report are industry practitioners, people in academia and policy makers at the local, national and EU levels.