scholarly journals Represent me: please! Towards an ethics of digital twins in medicine

2021 ◽  
pp. medethics-2020-106134
Author(s):  
Matthias Braun
Keyword(s):  
Special Focus ◽  
Digital Twin ◽  
Digital Twins ◽  
Different Types

Simulations are used in very different contexts and for very different purposes. An emerging development is the possibility of using simulations to obtain a more or less representative reproduction of organs or even entire persons. Such simulations are framed and discussed using the term ‘digital twin’. This paper unpacks and scrutinises the current use of such digital twins in medicine and the ideas embedded in this practice. First, the paper maps the different types of digital twins. A special focus is put on the concrete challenges inherent in the interactions between persons and their digital twin. Second, the paper addresses the questions of how far a digital twin can represent a person and what the consequences of this may be. Against the background of these two analytical steps, the paper defines first conditions for digital twins to take on an ethically justifiable form of representation.

scholarly journals Digital Twins for the Circular Economy

2021 ◽  
Vol 13 (18) ◽  
pp. 10467
Author(s):  
Anna Preut ◽  
Jan-Philip Kopka ◽  
Uwe Clausen
Keyword(s):  
Supply Chains ◽  
Circular Economy ◽  
Stakeholder Analysis ◽  
Relevant Information ◽  
Accurate Information ◽  
Special Focus ◽  
Successful Implementation ◽  
Digital Twin ◽  
Digital Twins ◽  
The Right

Accurate information plays an important role for the circulation of materials and products. It influences the economically and ecologically successful execution of processes such as reconditioning and the corresponding supply chain management. Digitization concepts, such as digital twins, enable the relevant information to be made available to the right actor at the right time in a decentralized manner. It is assumed that digital twins will play an important role in the future and can contribute, among other things, to the successful implementation of circular economy strategies. However, there is no uniform definition of the term digital twin yet and the exploration and use of digital twins in the context of circular economy products and supply chains is still in its infancy. This article presents potential contributions of digital twins to the circularity of products and the management of circular supply chains. To this end, the derivation and validation of a definition for the term digital twin is described. A stakeholder analysis with a special focus on the processes of the individual stakeholders results in an overview of potentials and information requirements of circular supply chains for a digital twin. The paper concludes that circular supply chains can benefit from digital twins, but that there is still a need for research and development, particularly regarding product and use case-specific implementations of the concept.

Digital twins for well-being: an overview

Digital Twin ◽  
2021 ◽  
Vol 1 ◽  
pp. 7
Author(s):  
Rahatara Fardousi ◽  
Fedwa Laamarti ◽  
M. Anwar Hossain ◽  
Chunsheng Yang ◽  
Abdulmotaleb El Saddik
Keyword(s):  
Potential Application ◽  
Well Being ◽  
Healthcare Industry ◽  
Digital Twin ◽  
Digital Twins ◽  
Different Types

Digital twin (DT) has gained success in various industries, and it is now getting attention in the healthcare industry in the form of well-being digital twin (WDT). In this paper, we present an overview of WDT to understand its potential scope, architecture and impact. We then discuss the definition  and the benefits of WDT. After that, we present the evolution of DT frameworks. Subsequently we discuss the challenges, the different types, the drawbacks, and potential application areas of WDT. Finally we present the requirements for a WDT framework extracted from the literature.

scholarly journals Digital Twin: Origin to Future

2021 ◽  
Vol 4 (2) ◽  
pp. 36
Author(s):  
Maulshree Singh ◽  
Evert Fuenmayor ◽  
Eoin Hinchy ◽  
Yuansong Qiao ◽  
Niall Murray ◽  
...  
Keyword(s):  
Real Time ◽  
Remote Access ◽  
Physical Entity ◽  
Industrial Systems ◽  
Digital Twin ◽  
Planning Optimization ◽  
Different Types ◽  
Pros And Cons ◽  
Number Of Publications ◽  
Digital Shadow

Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.

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.

scholarly journals Development and application of problem-oriented digital twins for magnetic observatories and variation stations

2021 ◽  
pp. 60-71
Author(s):  
Andrei Vorobev ◽  
Vyacheslav Pilipenko ◽  
Gulnara Vorobeva ◽  
Olga Khristodulo
Keyword(s):  
Time Series ◽  
Geomagnetic Field ◽  
Missing Values ◽  
Information Environment ◽  
Small Scale ◽  
Geomagnetic Variation ◽  
Digital Twin ◽  
Digital Twins ◽  
Geomagnetic Data ◽  
Magnetic Station

Introduction: Magnetic stations are one of the main tools for observing the geomagnetic field. However, gaps and anomalies in time series of geomagnetic data, which often exceed 30% of the number of recorded values, negatively affect the effectiveness of the implemented approach and complicate the application of mathematical tools which require that the information signal is continuous. Besides, the missing values ​​add extra uncertainty in computer simulation of dynamic spatial distribution of geomagnetic variations and related parameters. Purpose: To develop a methodology for improving the efficiency of technical means for observing the geomagnetic field. Method: Creation of problem-oriented digital twins of magnetic stations, and their integration into the collection and preprocessing of geomagnetic data, in order to simulate the functioning of their physical prototypes with a certain accuracy. Results: Using Kilpisjärvi magnetic station (Finland) as an example, it is shown that the use of digital twins, whose information environment is made up of geomagnetic data from adjacent stations, can provide the opportunity for reconstruction (retrospective forecast) of geomagnetic variation parameters with a mean square error in the auroral zone of up to 11.5 nT. The integration of problem-oriented digital twins of magnetic stations into the processes of collecting and registering geomagnetic data can provide automatic identification and replacement of missing and abnormal values, increasing, due to the redundancy effect, the fault tolerance of the magnetic station as a data source object. For example, the digital twin of Kilpisjärvi station recovers 99.55% of annual information, and 86.73% of it has an error not exceeding 12 nT. Discussion: Due to the spatial anisotropy of geomagnetic field parameters, the error at the digital twin output will be different in each specific case, depending on the geographic location of the magnetic station, as well as on the number of the surrounding magnetic stations and the distance to them. However, this problem can be minimized by integrating geomagnetic data from satellites into the information environment of the digital twin. Practical relevance: The proposed methodology provides the opportunity for automated diagnostics of time series of geomagnetic data for outliers and anomalies, as well as restoration of missing values and identification of small-scale disturbances.

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.

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