We are pleased to announce the following invited sessions at the IFAC AMEST 2020 workshop. We welcome high-quality contributions that investigate main research challenges, technology developments and advancements, case studies, and applications related to these topics. When submitting your papers to these sessions, please submit your paper as an “invited paper” to the Papercept system, and provide the session code in order to associate your paper to the session.
1. Low Cost Industrial Monitoring Approaches
[Session Code: xpnxm]
This session will address a common concern that recent developments in monitoring are unlikely to accessible by most companies owing to the associated capital cost of upgrading industrial computing and communication environments. The session will focus on low cost monitoring technologies and tackle the challenges associated with integrating these safely and securely into manufacturing or infrastructure environments, and their impact on reliability, maintenance and asset management.
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2. Digital Twins for Maintenance
[Session Code: g5i3u]
The development of computer modelling, simulations and connectivity between products introduces new and unique opportunities to elicit service value through optimised decision making. Applications of digital twins for the in-service phase of the product have focused on the evaluation of modification effects, health management and predicting and extending lives. However, the opportunities, risks, development procedures, and requirements of digital twins are not fully understood.
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3. Maintenance and Circular Economy 4.0
[Session Code: t4544]
Circular Manufacturing is considered among the six disruptive manufacturing trends according to the World Manufacturing Forum. While Maintenance Engineering and Management has been studied extensively and recently its relationship with production, supply chain management, and logistics has received increased attention, it is still considered in many fields as a cost source, rather than a value adding activity. This session aims to highlight the critical role of Maintenance in the Circular Economy.
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4. Digital Twins for Infrastructure and Construction
[Session Code: 8pq36]
Concepts such as Internet of Things, Industry 4.0 and Digital Twins are now seen as major opportunities for actors in the building and infrastructure sectors to improve their products, processes and services. The linkage between the real world and the virtual world enabled by these emerging technologies - supported by new data models and innovative data management strategies - allow to set up Dynamic Digital representations of the real World, called Digital Twins. This invited session will focus on Digital Twins applied to the construction and infrastructure section.
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5. Data-driven decision-making in smart maintenance
[Session Code: gde1n]
Over the last decade, manufacturing has been experiencing a relevant shift towards “digitalization”. The decrease of sensors costs, the reliability and availability of pervasive wireless connectivity, and the generation and collection of big amounts of data are determinant factors to change business processes and decision-making models. Given this trend, maintenance is amongst the business processes that will experience a major transition. This session will discuss all aspects of digital transformation towards data-driven decision-making in smart maintenance.
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6. Artificial intelligence for predictive maintenance
[Session Code: 7b71d]
This session will focus on particularly on Condition Monitoring, Diagnostics and Prognostics, Predictive Maintenance, and AI in Maintenance. It will bring experts in AI, data-driven based Structure Health Monitoring (SHM), Non-destructive Testing (NDT) and predictive maintenance from academia and industry to discuss the latest innovative research and challenges within the Industry 4.0 framework.
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7. Versatile predictive maintenance strategies for the industry of the future
[Session Code: tua49]
ForeSee cluster links six projects doing research on the aspects of Predictive maintenance with more than 80 organisations involved and a large number of industrial pilots. This session aims to bring together leading partners from each project allowing for knowledge exchange and experiences sharing as well as guiding the agenda for future research on Predictive maintenance.