Towards a Cyber-Physical Manufacturing Cloud through Operable Digital Twins and Virtual Production Lines

In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services for direct monitoring and operations through Internet. Fundamentally, CPMC differs with contemporary modern manufacturing paradigms. For instance, CPMC virtualizes machining tools in cloud using remote services and establish direct Internet-based communication, which is overlooked in existing Cloud Manufacturing systems. Another contemporary, namely cyber-physical production systems enable networked access to machining tools. Nevertheless, CPMC virtualizes manufacturing resources in cloud and monitor and operate them over the Internet. This dissertation defines the fundamental concepts of CPMC and expands its horizon in different aspects of cloud-based virtual manufacturing such as Digital Twins and Virtual Production Lines. Digital Twin (DT) is another evolving concept since 2002 that creates as-is replicas of machining tools in cyber space. Up to 2018, many researchers proposed state-of-the-art DTs, which only focused on monitoring production lifecycle management through simulations and data driven analytics. But they overlooked executing manufacturing processes through DTs from virtual space. This dissertation identifies that DTs can be made more productive if they engage directly in direct execution of manufacturing operations besides monitoring. Towards this novel approach, this dissertation proposes a new operable DT model of CPMC that inherits the features of direct monitoring and operations from cloud. This research envisages and opens the door for future manufacturing systems where resources are developed as cloud-based DTs for remote and distributed manufacturing. Proposed concepts and visions of DTs have spawned the following fundamental researches. This dissertation proposes a novel concept of DT based Virtual Production Lines (VPL) in CPMC in 2019. It presents a design of a service-oriented architecture of DTs that virtualizes physical manufacturing resources in CPMC. Proposed DT architecture offers a more compact and integral service-oriented virtual representations of manufacturing resources. To re-configure a VPL, one requirement is to establish DT-to-DT collaborations in manufacturing clouds, which replicates to concurrent resource-to-resource collaborations in shop floors. Satisfying the above requirements, this research designs a novel framework to easily re-configure, monitor and operate VPLs using DTs of CPMC. CPMC publishes individual web services for machining tools, which is a traditional approach in the domain of service computing. But this approach overcrowds service registry databases. This dissertation introduces a novel fundamental service publication and discovery approach in 2020, OpenDT, which publishes DTs with collections of services. Experimental results show easier discovery and remote access of DTs while re-configuring VPLs. Proposed researches in this dissertation have received numerous citations both from industry and academia, clearly proving impacts of research contributions

Adding Virtualization Capabilities to Grid'5000

Ce rapport révisé a fait l'objet d'une publication, voir hal-00946971Almost ten years after its premises, the Grid'5000 testbed has become one of the most complete testbed for designing or evaluating large-scale distributed systems. Initially dedicated to the study of High Performance Computing, the infrastructure has evolved to address wider concerns related to Desktop Computing, the Internet of Services and more recently the Cloud Computing paradigm. This report present recent improvements of the Grid'5000 software and services stack to support large-scale experiments using virtualization technologies as building blocks. Such contributions include the deployment of customized software environments, the reservation of dedicated network domain and the possibility to isolate them from the others, and the automation of experiments with a REST API. We illustrate the interest of these contributions by describing three different use-cases of large-scale experiments on the Grid'5000 testbed. The first one leverages virtual machines to conduct larger experiments spread over 4000 peers. The second one describes the deployment of 10000 KVM instances over 4 Grid'5000 sites. Finally, the last use case introduces a one-click deployment tool to easily deploy major IaaS solutions. The conclusion highlights some important challenges of Grid'5000 related to the use of OpenFlow and to the management of applications dealing with tremendous amount of data.Dix ans environ après ses prémisses, la plate-forme Grid'5000 est devenue une des plates-formes les plus complètes utilisée pour la conception et l'évaluation de systèmes distribués à grande échelle. Dédiée initialement au calcul à haute performance, l'infrastructure a évolué pour supporter un ensemble de problèmes plus vaste liés au calcul de type Desktop, l'internet des objets et plus récemment l'informatique dans les nuages (aussi appelé Cloud Computing). Ce rapport présente les améliorations récentes apportées au logiciels et pile de services pour supporter les expérimentations à grande échelle utilisant les technologies de virtualisation comme blocs de base. Nos contributions incluent le déploiement d'environnements logiciels customisés, la réservation de domaines réseaux dédiés et la possibilité de les isoler entre eux, et l'automatisation des expérimentations grâce à une API REST. Nous illustrons l'intérêt de ces contributions en décrivant trois expériences à large échelle sur la plate-forme Grid'5000. La première expérience utilise des machines virtuelles pour conduire des expérimentations de grande taille sur 4000 pairs. La seconde expérience décrit le déploiement de 10000 instances KVM sur 4 sites Grid'5000. Enfin le dernier exemple présente un outil de déploiement simple pour déployer des solutions de Cloud de type IaaS. La conclusion discute de prochains défis importants de Grid'5000 liés à l'utilisation d'OpenFlow et à la gestion d'applications gérant des grandes masses de données