scholarly journals DIGITAL TWINS - DEFINITIONS, CLASSES AND BUSINESS SCENARIOS FOR DIFFERENT INDUSTRY SECTORS

2021 ◽  
Vol 1 ◽  
pp. 1293-1302
Author(s):  
Fabian Wilking ◽  
Benjamin Schleich ◽  
Sandro Wartzack
Keyword(s):  
Product Portfolio ◽  
Digital Twin ◽  
Digital Twins ◽  
Definition Of ◽  
Industry Sectors ◽  
New Industry

AbstractOver the recent years, several attempts were made to define the concept of the Digital Twin and to create a generic view for utilizing it within the industry. Still, many industry sectors are not able to transfer a generic definition into their product portfolio, as Digital Twins differ from each other to the same degree as physical products differ from each other. Hence, it is crucial to enlarge the definition towards a classification and business scenarios which enable sector specific views on the concept of the Digital Twin and help SME to utilize the concept towards their products. Future engineers will have to design physical products besides a digital counterpart and therefore have to identify interdependencies between these two products during the development. This paper discusses a generic definition of a Digital Twin that can be applied throughout different sectors as well as a classification for Digital Twins to enable the implementation of the concept on several maturity levels regarding the constraints of the product portfolio. In addition, these classes are viewed in different business scenarios and an outlook is given to further increase the usability of Digital Twins within new industry sectors.

scholarly journals Analysis of Digital Twin Definition and Its Difference from Simulation Modelling in Practical Application

2020 ◽  
Author(s):  
I.I. Krasikov ◽  
A. N. Kulemin
Keyword(s):  
Mathematical Model ◽  
Model Simulation ◽  
Simulation Modelling ◽  
Practical Application ◽  
Product Lifecycle ◽  
Digital Twin ◽  
Common Definition ◽  
Model And Simulation ◽  
Digital Twins ◽  
Definition Of

The digital twin is widely known as a tool for digitalization of a product, but there is no common definition concerning this term. This article discusses the definition and utilization of digital twin. Areas of use, it’s implementation in the product lifecycle and most importantly it’s benefits. The lack of a standardized concept of a digital  twin leads to a misunderstanding between mathematical models and digital twin. Several definitions of digital twin were analyzed and compared with the definition of mathematical model and simulation modelling. The basic concept of areas of use for digital twin is introduced. The differences and similarities between the two definitions were found. The article aims first of all to help the management of digital twins in practical application. Keywords: Digital twin, Mathematical modelling, Mathematical model, Lifecycle of a product, Simulation modelling, Practical use of digital twin, Difference between the digital twin and mathematical model, Simulation.

The DIM Approach for Digital Twin

2021 ◽  
pp. 153-171
Author(s):  
Matteo Del Giudice
Keyword(s):  
Information And Communication Technologies ◽  
Communication Technologies ◽  
Heterogeneous Data ◽  
Digital Twin ◽  
Innovative Methods ◽  
Digital Twins ◽  
Modelling Methodology ◽  
Information And Communication ◽  
Virtual City ◽  
Definition Of

In the era of connections and information and communication technologies, the building industry is facing the challenge of digitization at the building and urban scale. Several researches have been carried out to generate virtual city models to manage and represent a variety of data to reach the smart city concept. Therefore, the development of building/urban digital twins is directly linked to the definition of innovative methods and tools that are able to collect, organize, query heterogeneous data to make it available for the various involved actors. This chapter aims at presenting the district information modelling methodology that is strictly related to the digital twin concept, starting with data domains, arriving at the various tools developed to reach the users' needs.

scholarly journals WHAT IS A DIGITAL TWIN? – DEFINITIONS AND INSIGHTS FROM AN INDUSTRIAL CASE STUDY IN TECHNICAL PRODUCT DEVELOPMENT

2020 ◽  
Vol 1 ◽  
pp. 757-766 ◽  
Author(s):  
J. Trauer ◽  
S. Schweigert-Recksiek ◽  
C. Engel ◽  
K. Spreitzer ◽  
M. Zimmermann
Keyword(s):  
Product Development ◽  
Physical System ◽  
Data Exchange ◽  
Literature Study ◽  
Industrial Case Study ◽  
Technical Product ◽  
Digital Twin ◽  
Digital Twins ◽  
Definition Of

AbstractOver the last two decades, a concept called Digital Twin has evolved rapidly. Yet, there is no unified definition of the term. Based on a literature study and an industrial case study, an overarching definition of Digital twins is presented. Three characteristics were identified – representation of a physical system, bidirectional data exchange, and the connection along the entire lifecycle. Further, three sub-concepts are presented, namely: Engineering Twin, Production Twin, and Operation Twin. The presented paper thus formulates a consistent and detailed definition of Digital Twins.

scholarly journals Digital Twins: From Personalised Medicine to Precision Public Health

2021 ◽  
Vol 11 (8) ◽  
pp. 745
Author(s):  
Maged N. Kamel Boulos ◽  
Peng Zhang
Keyword(s):  
Public Health ◽  
Ethical Issues ◽  
Personalised Medicine ◽  
Physical Entity ◽  
New Era ◽  
Digital Twin ◽  
Digital Twins ◽  
Industry Sectors ◽  
New Hypothesis ◽  
Radical Transformation

A digital twin is a virtual model of a physical entity, with dynamic, bi-directional links between the physical entity and its corresponding twin in the digital domain. Digital twins are increasingly used today in different industry sectors. Applied to medicine and public health, digital twin technology can drive a much-needed radical transformation of traditional electronic health/medical records (focusing on individuals) and their aggregates (covering populations) to make them ready for a new era of precision (and accuracy) medicine and public health. Digital twins enable learning and discovering new knowledge, new hypothesis generation and testing, and in silico experiments and comparisons. They are poised to play a key role in formulating highly personalised treatments and interventions in the future. This paper provides an overview of the technology’s history and main concepts. A number of application examples of digital twins for personalised medicine, public health, and smart healthy cities are presented, followed by a brief discussion of the key technical and other challenges involved in such applications, including ethical issues that arise when digital twins are applied to model humans.

scholarly journals Pipeline for ontology-based modeling and automated deployment of digital twins for planning and control of manufacturing systems

2021 ◽  
Author(s):  
Amon Göppert ◽  
Lea Grahn ◽  
Jonas Rachner ◽  
Dennis Grunert ◽  
Simon Hort ◽  
...  
Keyword(s):  
Data Exchange ◽  
Manufacturing Systems ◽  
Digital Model ◽  
Use Case ◽  
Digital Twin ◽  
Planning And Control ◽  
Digital Twins ◽  
Definition Of ◽  
Fully Connected ◽  
And Control

AbstractThe demand for individualized products drives modern manufacturing systems towards greater adaptability and flexibility. This increases the focus on data-driven digital twins enabling swift adaptations. Within the framework of cyber-physical systems, the digital twin is a digital model that is fully connected to the physical and digital assets. A digital model must follow a standardization for interoperable data exchange. Established ontologies and meta-models offer a basis in the definition of a schema, which is the first phase of creating a digital twin. The next phase is the standardized and structured modeling with static use-case specific data. The final phase is the deployment of digital twins into operation with a full connection of the digital model with the remaining cyber-physical system. In this deployment phase communication standards and protocols provide a standardized data exchange. A survey on the state-of-the-art of these three digital twin phases reveals the lack of a consistent workflow from ontology-driven definition to standardized modeling. Therefore, one goal of this paper is the design of an end-to-end digital twin pipeline to lower the threshold of creating and deploying digital twins. As the task of establishing a communication connection is highly repetitive, an automation concept by providing structured protocol data is the second goal. The planning and control of a line-less assembly system with manual stations and a mobile robot as resources and an industrial dog as the product serve as exemplary digital twin applications. Along this use-case the digital twin pipeline is transparently explained.

Digital Twin for Smart Manufacturing: The Practitioner’s Perspective

2020 ◽  
Author(s):  
Maja Bärring ◽  
Björn Johansson ◽  
Goudong Shao
Keyword(s):  
Conceptual Development ◽  
Production Systems ◽  
Manufacturing Sector ◽  
Smart Manufacturing ◽  
Digital Twin ◽  
Adoption And Implementation ◽  
New Information ◽  
Digital Twins ◽  
Discrete Manufacturing ◽  
Design Production

Abstract The manufacturing sector is experiencing a technological paradigm shift, where new information technology (IT) concepts can help digitize product design, production systems, and manufacturing processes. One of such concepts is Digital Twin and researchers have made some advancement on both its conceptual development and technological implementations. However, in practice, there are many different definitions of the digital-twin concept. These different definitions have created a lot of confusion for practitioners, especially small- and medium-sized enterprises (SMEs). Therefore, the adoption and implementation of the digital-twin concept in manufacturing have been difficult and slow. In this paper, we report our findings from a survey of companies (both large and small) regarding their understanding and acceptance of the digital-twin concept. Five supply-chain companies from discrete manufacturing and one trade organization representing suppliers in the automotive business were interviewed. Their operations have been studied to understand their current digital maturity levels and articulate their needs for digital solutions to stay competitive. This paper presents the results of the research including the viewpoints of these companies in terms of opportunities and challenges for implementing digital twins.

Machine learning-based digital twins reduce seasonal remapping in aeroderivative gas turbines

2021 ◽  
pp. 1-7
Author(s):  
Nick Petro ◽  
Felipe Lopez
Keyword(s):  
Machine Learning ◽  
Ambient Temperature ◽  
Gas Turbines ◽  
Operating Conditions ◽  
Pilot Site ◽  
Digital Twin ◽  
Digital Twins ◽  
Machine Learning Model ◽  
Unacceptable Behavior ◽  
External Conditions

Abstract Aeroderivative gas turbines have their combustion set points adjusted periodically in a process known as remapping. Even turbines that perform well after remapping may produce unacceptable behavior when external conditions change. This article introduces a digital twin that uses real-time measurements of combustor acoustics and emissions in a machine learning model that tracks recent operating conditions. The digital twin is leveraged by an optimizer that select adjustments that allow the unit to maintain combustor dynamics and emissions in compliance without seasonal remapping. Results from a pilot site demonstrate that the proposed approach can allow a GE LM6000PD unit to operate for ten months without seasonal remapping while adjusting to changes in ambient temperature (4 - 38 °C) and to different fuel compositions.

Digital Twins: Review and Challenges

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Maria G. Juarez ◽  
Vicente J. Botti ◽  
Adriana S. Giret
Keyword(s):  
Computer Science ◽  
Industry 4.0 ◽  
Multi Agent System ◽  
Agent System ◽  
Digital Twin ◽  
Digital Twins ◽  
Science Approach ◽  
Multi Agent ◽  
Current Operating

Abstract With the arises of Industry 4.0, numerous concepts have emerged; one of the main concepts is the digital twin (DT). DT is being widely used nowadays, however, as there are several uses in the existing literature; the understanding of the concept and its functioning can be diffuse. The main goal of this paper is to provide a review of the existing literature to clarify the concept, operation, and main characteristics of DT, to introduce the most current operating, communication, and usage trends related to this technology, and to present the performance of the synergy between DT and multi-agent system (MAS) technologies through a computer science approach.

The Digital Twin of a System: A Structure for Networks of Digital Twins

2021 ◽  
Author(s):  
Leif- Thore Reiche ◽  
Claas Steffen Gundlach ◽  
Gian Frederik Mewes ◽  
Alexander Fay
Keyword(s):  
Digital Twin ◽  
System A ◽  
Digital Twins

Engine Fleet-Management: The Use of Digital Twins From a MRO Perspective

2017 ◽  
Author(s):  
Joern Kraft ◽  
Stefan Kuntzagk
Keyword(s):  
Multilevel Models ◽  
Operating Cost ◽  
Maintenance Cost ◽  
Fleet Management ◽  
Component Level ◽  
The Real ◽  
Digital Twin ◽  
Digital Twins ◽  
The Individual ◽  
Life Consumption

Engine operating cost is a major contributor to the direct operating cost of aircraft. Therefore, the minimization of engine operating cost per flight-hour is a key aspect for airlines to operate successfully under challenging market conditions. The interaction between maintenance cost, operating cost, asset value, lease and replacement cost describes the area of conflict in which engine fleets can be optimized. State-of-the-art fleet management is based on advanced diagnostic and prognostic methods on engine and component level to provide optimized long-term removal and work-scoping forecasts on fleet level based on the individual operation. The key element of these methods is a digital twin of the active engines consisting of multilevel models of the engine and its components. This digital twin can be used to support deterioration and failure analysis, predict life consumption of critical parts and relate the specific operation of a customer to the real and expected condition of the engines on-wing and at induction to the shop. The fleet management data is constantly updated based on operational data sent from the engines as well as line maintenance and shop data. The approach is illustrated along the real application on the CFM56-5C, a mature commercial two-spool high bypass engine installed on the Airbus A340-300. It can be shown, that the new methodology results in major improvements on the considered fleets.

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