scholarly journals An approach for Industrie 4.0-compliant and data-sovereign Digital Twins

2021 ◽  
Vol 69 (12) ◽  
pp. 1051-1061
Author(s):  
Michael Jacoby ◽  
Friedrich Volz ◽  
Christian Weißenbacher ◽  
Ljiljana Stojanovic ◽  
Thomas Usländer
Keyword(s):  
Data Sharing ◽  
Industrial Production ◽  
Data Analytics ◽  
Integrated Approach ◽  
Industrie 4.0 ◽  
Application Domain ◽  
Digital Twins ◽  
Implementation Approach ◽  
Architectural Framework ◽  
International Data

Abstract Data sharing between enterprises requires both interoperability and data sovereignty. In the application domain of industrial production an integrated approach is required that encompasses standards and technologies of both Industrie 4.0 and the International Data Spaces (IDS). This paper describes how to combine them for the concept of Digital Twins following the architectural framework given in ISO DIS 23247. Furthermore, an implementation approach is described relying upon the Fraunhofer Advanced AAS Tools for Digital Twins (FA³ST). The resulting architectural approach may be combined with further open manufacturing standards, and may be applied for data analytics and the engineering of AI-based systems.

scholarly journals Methodology and Tools for Digital Twin Management—The FA3ST Approach

IoT ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 717-740
Author(s):  
Ljiljana Stojanovic ◽  
Thomas Usländer ◽  
Friedrich Volz ◽  
Christian Weißenbacher ◽  
Jens Müller ◽  
...  
Keyword(s):  
Decision Making ◽  
Industrial Applications ◽  
Industrie 4.0 ◽  
Conceptual Approach ◽  
Digital Twin ◽  
Digital Representations ◽  
Lifecycle Model ◽  
Digital Twins ◽  
International Data ◽  
Physical Assets

The concept of digital twins (DT) has already been discussed some decades ago. Digital representations of physical assets are key components in industrial applications as they are the basis for decision making. What is new is the conceptual approach to consider DT as well-defined software entities themselves that follow the whole lifecycle of their physical counterparts from the engineering, operation up to the discharge, and hence, have their own type description, identity, and lifecycle. This paper elaborates on this idea and argues the need for systematic DT engineering and management. After a conceptual description of DT, the paper proposes a DT lifecycle model and presents methodologies and tools for DT management, also in the context of Industrie 4.0 concepts, such as the asset administration shell (AAS), the international data spaces (IDS), and IEC standards (such as OPC UA and AML). As a tool example for the support of DT engineering and management, the Fraunhofer-advanced AAS tools for digital twins (FA3ST) are presented in more detail.

scholarly journals The truth must prevail: citizens’ rights to know the truth during the era of COVID-19

2020 ◽  
Author(s):  
Philip Joseph D Sarmiento ◽  
John Federick C Yap ◽  
Kevin Aldrin G Espinosa ◽  
Ria P Ignacio ◽  
Carisma A Caro
Keyword(s):  
Public Health ◽  
Data Sharing ◽  
Data Analytics ◽  
Data Driven ◽  
Short Report ◽  
Ordinary People ◽  
Health Crisis ◽  
Public Health Crisis

ABSTRACT In a recent short report, the necessity of sophisticated practices in gathering records that would facilitate data sharing yields data-driven analysis in time of COVID-19. Consequently, there is a need to present the truth in data analytics in the era of COVID-19. This paper discusses the urgent call for people handling the COVID-19 data to be ethically responsible in their handling, processing, and reporting that impacts the lives of ordinary people especially in this time of pandemic as public health crisis.

Big data analytics capabilities and knowledge management: impact on firm performance

2019 ◽  
Vol 57 (8) ◽  
pp. 1923-1936 ◽  
Author(s):  
Alberto Ferraris ◽  
Alberto Mazzoleni ◽  
Alain Devalle ◽  
Jerome Couturier
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Data Analytics ◽  
Structural Equation ◽  
Positive Impact ◽  
Big Data Analytics ◽  
Integrated Approach ◽  
Content Type ◽  
Decision Making Processes ◽  
External Sources

Purpose Big data analytics (BDA) guarantees that data may be analysed and categorised into useful information for businesses and transformed into big data related-knowledge and efficient decision-making processes, thereby improving performance. However, the management of the knowledge generated from the BDA as well as its integration and combination with firm knowledge have scarcely been investigated, despite an emergent need of a structured and integrated approach. The paper aims to discuss these issues. Design/methodology/approach Through an empirical analysis based on structural equation modelling with data collected from 88 Italian SMEs, the authors tested if BDA capabilities have a positive impact on firm performances, as well as the mediator effect of knowledge management (KM) on this relationship. Findings The findings of this paper show that firms that developed more BDA capabilities than others, both technological and managerial, increased their performances and that KM orientation plays a significant role in amplifying the effect of BDA capabilities. Originality/value BDA has the potential to change the way firms compete through better understanding, processing, and exploiting of huge amounts of data coming from different internal and external sources and processes. Some managerial and theoretical implications are proposed and discussed in light of the emergence of this new phenomenon.

Intelligent Data Sharing in Digital Twins: Positioning Paper

2020 ◽  
pp. 282-290
Author(s):  
Thomas Cassimon ◽  
Jens de Hoog ◽  
Ali Anwar ◽  
Siegfried Mercelis ◽  
Peter Hellinckx
Keyword(s):  
Data Sharing ◽  
Digital Twins

Integrated Research and Training in Enterprise Information Systems

2009 ◽  
pp. 195-208
Author(s):  
Chen-Yang Cheng
Keyword(s):  
Information Systems ◽  
Integrated Approach ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Integrated Research ◽  
Training Approach ◽  
Implementation Approach ◽  
Training And Research ◽  
And Control ◽  
And Training

The success of implementing Enterprise Information System (EIS) depends on exploring and improving the EIS software, and EIS software training. However, the synthesis of the EIS implementation approach has not been investigated. In this chapter, the authors propose an integrated research and training approach for students and employees about enterprise information systems (EIS) that are encountered in an organization. Our integrated approach follows the different stages of a typical EIS project from inception to completion. These stages, as identified, are modeling, planning, simulation, transaction, integration, and control. This ensures that an employee who is trained by this plan has an acquaintance with the typical information systems in an organization. Further, for training and research purposes the authors developed prototype information systems that emulate the ones usually found in organizations. This ensures the EIS software logic is consistent with the business logic. This chapter also discuss some of the case studies conducted with the prototype systems.

Industrie 4.0 und Data Analytics

2017 ◽  
pp. 115-117
Author(s):  
Wolfgang Becker ◽  
Patrick Ulrich ◽  
Tim Botzkowski
Keyword(s):  
Data Analytics ◽  
Industrie 4.0
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