Design of a multi-sided platform supporting CPS deployment in the automation market

Landolfi, Giuseppe; Barni, Andrea; Menato, Silvia; Cavadini, Franco; Rovere, Diego; Maso, Giovanni Dal

doi:10.1109/icphys.2018.8390790

Cited by 19 publications

(6 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Digital platforms are transforming nearly every industry today [36] revolutionizing future value creation in the manufacturing industry as they enable companies to become more digitalized [46]. The advent of industry 4.0 fosters digital platforms and the concept of a digital twin to attract scholarly attention and interest as the industries start to realize and understand related technological and business opportunities [47]. Digital twin as an emerging concept represents new research issues crossing the disciplines of industrial engineering, software engineering, cyber-physical systems, AI and machine learning, and ecosystem and platforms.…”

Section: Discussionmentioning

confidence: 99%

Digital Twins as Software and Service Development Ecosystems in Industry 4.0: Towards a Research Agenda

Päivärinta

Kuvaja

2020

Communications in Computer and Information Science

View full text Add to dashboard Cite

While research on digital twins of cyber-physical systems within industry 4.0 is emerging, the software development perspective on digital twins remains under-explored. Contemporary definitions and examples of digital twins have covered company-or product-specific solutions or discussed the use of digital twins in rather proprietary value chains. This paper addresses the importance of taking an ecosystem view on software development on digital twins for industry 4.0 and outlines a framework for building a research agenda for such ecosystems. The framework includes three dimensions: scope of the digital twin software platform (internal, value chain, ecosystem), life-cycle phases of the industry 4.0 system related with the digital twin (creation, production, operation & maintenance, disposal), and level of integration between the twin and the physical system (model, shadow, twin). As this research-in-progress addresses examples of research questions in light of the framework, further research to build a fullscale research agenda based on a systematic literature review is suggested.

show abstract

Section: Discussionmentioning

confidence: 99%

Digital Twins as Software and Service Development Ecosystems in Industry 4.0: Towards a Research Agenda

Päivärinta

Kuvaja

2020

Communications in Computer and Information Science

View full text Add to dashboard Cite

show abstract

“…Sometimes it is also necessary to take a more radical approach, i.e., to test partial changes directly in production. For this reason, we developed and built a real cyber-physical third-generation system, capable of storing, analyzing and processing larger data sets, as mentioned in [ 33 , 34 , 35 ]. This suggestion has been initiated based on our presentation of optimizations performed in the form of digital twin output animations and calculations in the Siemens Tecnomatix Plant Simulate environment.…”

Section: Methodsmentioning

confidence: 99%

Design and Implementation of Universal Cyber-Physical Model for Testing Logistic Control Algorithms of Production Line’s Digital Twin by Using Color Sensor

Vachálek

Šišmišová

Vašek

et al. 2021

Sensors

View full text Add to dashboard Cite

This paper deals with the design and implementation of a universal cyber-physical model capable of simulating any production process in order to optimize its logistics systems. The basic idea is the direct possibility of testing and debugging advanced logistics algorithms using a digital twin outside the production line. Since the digital twin requires a physical connection to a real line for its operation, this connection is substituted by a modular cyber-physical system (CPS), which replicates the same physical inputs and outputs as a real production line. Especially in fully functional production facilities, there is a trend towards optimizing logistics systems in order to increase efficiency and reduce idle time. Virtualization techniques in the form of a digital twin are standardly used for this purpose. The possibility of an initial test of the physical implementation of proposed optimization changes before they are fully implemented into operation is a pragmatic question that still resonates on the production side. Such concerns are justified because the proposed changes in the optimization of production logistics based on simulations from a digital twin tend to be initially costly and affect the existing functional production infrastructure. Therefore, we created a universal CPS based on requirements from our cooperating manufacturing companies. The model fully physically reproduces the real conditions of simulated production and verifies in advance the quality of proposed optimization changes virtually by the digital twin. Optimization costs are also significantly reduced, as it is not necessary to verify the optimization impact directly in production, but only in the physical model. To demonstrate the versatility of deployment, we chose a configuration simulating a robotic assembly workplace and its logistics.

show abstract

“…Digital twins not only facilitate administration of physical assets but also aid in modelling the physical characteristics of the asset, so that the digital representation can be transferred or replicated on computing nodes [11]. In a software system, it is important to enable deployment and maintenance of digital twins [6,8,14]. The edge computing paradigm has further closed the gap of application of digital twin concepts in manufacturing industries [2,3,12,15].…”

Section: Related Workmentioning

confidence: 99%

IoTwins: Design and Implementation of a Platform for the Management of Digital Twins in Industrial Scenarios

Borghesi

Modica

Bellavista

et al. 2021

2021 IEEE/ACM 21st International Symposium on Cluster, Cloud and Internet Computing (CCGrid)

View full text Add to dashboard Cite

With the increase of the volume of data produced by IoT devices, there is a growing demand of applications capable of elaborating data anywhere along the IoT-to-Cloud path (Edge/Fog). In industrial environments, strict real-time constraints require computation to run as close to the data origin as possible (e.g., IoT Gateway or Edge nodes), whilst batch-wise tasks such as Big Data analytics and Machine Learning model training are advised to run on the Cloud, where computing resources are abundant. The H2020 IoTwins project leverages the digital twin concept to implement virtual representation of physical assets (e.g., machine parts, machines, production/control processes) and deliver a software platform that will help enterprises, and in particular SMEs, to build highly innovative, AI-based services that exploit the potential of IoT/Edge/Cloud computing paradigms. In this paper, we discuss the design principles of the IoTwins reference architecture, delving into technical details of its components and offered functionalities, and propose an exemplary software implementation.

show abstract

Design of a multi-sided platform supporting CPS deployment in the automation market

Cited by 19 publications

References 15 publications

Digital Twins as Software and Service Development Ecosystems in Industry 4.0: Towards a Research Agenda

Digital Twins as Software and Service Development Ecosystems in Industry 4.0: Towards a Research Agenda

Design and Implementation of Universal Cyber-Physical Model for Testing Logistic Control Algorithms of Production Line’s Digital Twin by Using Color Sensor

IoTwins: Design and Implementation of a Platform for the Management of Digital Twins in Industrial Scenarios

Contact Info

Product

Resources

About