One of the main driving forces in the era of cyber-physical systems is the introduction of massive sensor networks into manufacturing processes, connected cars, precision agriculture, and so on. Therefore, large amounts of sensor data have to be ingested at the server side in order to generate and make the “twin digital model” or virtual factory of the existing physical processes for predictive simulation and scheduling purposes usable. In this paper, we focus on our ultimate goal, (...) a novel software container-based approach with cloud agnostic orchestration facilities that enable the system operators in the industry to create and manage scalable, virtual IT platforms on-demand for these two typical major pillars of CPS: server-side framework for sensor networks and configurable simulation tool for predicting the behavior of manufacturing systems. The paper discusses the scalability of the applied discrete-event simulation tool and the layered back-end framework starting from simple virtual machine-level to sophisticated multilevel autoscaling use case scenario. The presented achievements and evaluations leverage on the synergy of the existing EasySim simulator, our new CQueue software container manager, the continuously developed Occopus cloud orchestrator tool, and the latest version of the evolving MiCADO framework for integrating such tools into a unified platform. (shrink)

Since the 1970s, the application of microprocessor in industrial machinery and the development of computer systems have transformed the manufacturing landscape. The rapid integration and automation of production systems have outpaced the development of suitable human design criteria, creating a deepening gap between humans and systems in which human was seen as an important source of errors and disruptions. Today, the situation seems different: the scientific and public debate about the concept of Industry 4.0 has raised awareness (...) about the central role humans have to play in manufacturing systems, the design of which must be considered from the very beginning. The future of industrial systems, as represented by Industry 4.0, will rely on the convergence of several research fields such as Intelligent Manufacturing Systems (IMS), Cyber-Physical Systems (CPS), Internet of Things (IoT), but also socio-technical fields such as social approaches within technical systems. This article deals with different human social dimensions associated with CPS and IoT and focuses on their conceptual evolution regarding automated production systems’ sociability, notably by bringing humans back in the loop. Hereby, this paper aims to take stock of current research trends to show the importance of integrating human operators as a part of a socio-technical system based autonomous and intelligent products or resources. Consequently, different models of sociability as a way to integrate humans in the broad sense and/or the develop future automated production systems have been identified from the literature and analysed. (shrink)

The Fourth Industrial Revolution has become a global buzz word since the World Economic Forum adopted it as an annual issue in 2016. It is represented by hyper automation and hyper connectivity based on artificial intelligence, big data, robotics, and Internet of things. AI, big data, and robotics can contribute to developing hyper automation that can increase productivity and intensify industrial production. Particularly, robots using AI can make decision by themselves as human being on complicated processes. Along with the hyper (...) automation, the hyper connectivity increases not only at national, but also global level by using information and communication technologies. IoT is the core technology to create the hyper connectivity in Cyber Physical System that connects technology, nature, and human being. Accordingly, a perfect convergence between ICT and manufacturing can be completed in the Fourth Industrial Revolution era and an extremely efficient flexible production system by spreading IoT in CPS will be established. Under such a condition, innovative clusters must play their traditional roles in cradles of technology innovation and commercialization. It must be difficult challenges for innovative clusters to meet their targets and to be adjusted by the changing new environment at the same time. This paper argues how the Fourth Industrial Revolution can change the global production chain and how core technologies function in industries. Furthermore, it focuses on how innovative clusters have to evolve to respond the Fourth Industrial Revolution. Last, but not least it also analyzes whether or not innovative clusters can play their roles as technology innovation hubs in the real world and CPS in the Fourth Industrial Revolution era. (shrink)