scholarly journals The use of digital twins in healthcare: socio-ethical benefits and socio-ethical risks

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Eugen Octav Popa ◽  
Mireille van Hilten ◽  
Elsje Oosterkamp ◽  
Marc-Jeroen Bogaardt
Keyword(s):  
Emerging Technologies ◽  
Ethical Issues ◽  
Research Policy ◽  
Equal Treatment ◽  
Responsible Innovation ◽  
Quadruple Helix ◽  
Digital Twin ◽  
Industry Research ◽  
Digital Twins ◽  
Desk Research

AbstractAnticipating the ethical impact of emerging technologies is an essential part of responsible innovation. One such emergent technology is the digital twin which we define here as a living replica of a physical system (human or non-human). A digital twin combines various emerging technologies such as AI, Internet of Things, big data and robotics, each component bringing its own socio-ethical issues to the resulting artefacts. The question thus arises which of these socio-ethical themes surface in the process and how they are perceived by stakeholders in the field. In this report we present the results of a qualitative study into the socio-ethical benefits and socio-ethical risks of using digital twins in healthcare. Employing insights from ethics of technology and the Quadruple Helix theory of innovation, we conducted desk research of white literature and 23 interviews with representatives from the four helixes: industry, research, policy and civil society. The ethical scan revealed several important areas where the digital twin can produce socio-ethical value (e.g., prevention and treatment of disease, cost reduction, patient autonomy and freedom, equal treatment) but also several important areas of socio-ethical risks (e.g., privacy and property of data, disruption of existing societal structures, inequality and injustice). We conclude with a reflection on the employed analytical tool and suggestions for further research.

A Critical Overview of Digital Twins

2020 ◽  
Vol 3 (1) ◽  
pp. 51-61
Author(s):  
Princess Adjei ◽  
Reza Montasari
Keyword(s):  
Supply Chains ◽  
Competitive Advantage ◽  
Business Models ◽  
Emerging Technologies ◽  
Critical Perspective ◽  
Digital Twin ◽  
Digital Twins ◽  
Critical Overview

In recent years, organisations have invested heavily in the digitisation of their processes to maximise productivity. A digital twin is one of the most recent emerging technologies that is to disrupt business models and to leverage competitive advantage; applications can be found in many industries including, but not limited to healthcare, manufacturing and supply chains, and engineering. This article provides a critical perspective to the benefits of digital twins, their applications as well as the challenges encountered following their use. Cybersecurity risks as one of these key challenges will be further discussed within the article.

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 Towards next generation cyber-physical systems and digital twins for construction

2021 ◽  
Vol 26 ◽  
pp. 505-525
Author(s):  
Abiola A. Akanmu ◽  
Chimay J. Anumba ◽  
Omobolanle O. Ogunseiju
Keyword(s):  
Construction Industry ◽  
Emerging Technologies ◽  
Cyber Physical Systems ◽  
Next Generation ◽  
Monitoring And Control ◽  
Virtual Design ◽  
Sensors And Actuators ◽  
Physical Systems ◽  
Digital Twin ◽  
Digital Twins

The construction industry continues to seek innovative ways to safely, timely and cost-effectively deliver construction projects. Several efforts have been made to automate construction processes but marginial success has been achieved in effectively reducing the long standing risks suffered by the industry. While industry 4.0 promises to improve project efficiency, reduce waste and improve productivity, the transition to this will depend on the successful adoption of many emerging technologies such as virtual design modeling technologies, sensing technologies, data analysis, storage and communication technologies, human-computer interaction technologies, and robotics. To accelerate innovation, digital twins and cyber-physical systems will be a necessity to advance automation and real-time control with these technologies. While digital twin represents a digital replica of the asplanned and as-built facility, cyber physical systems involve integration of physical systems with their digital replica through sensors and actuators. Despite evidence of the efficacy of cyber-physical systems and digital twins for reducing non-fatal injuries, enhancing safety management, improving progress monitoring and enhancing performance monitoring and control of facilities, their adoption in the construction industry is still in its infancy. This paper sheds light on the opportunities offered by cyber-physical systems and digital twins in other industry sectors and advocates for their increased deployment in the construction industry. This paper describes cyber-physical integration of emerging technologies with the physical construction or constructed facility as the next generation digital twin and cyber-physical systems. Potential scenarios of next generation cyber physical system and digital twin for improving workforce productivity, health, and safety, lifecycle management of building systems, and workforce competency are presented.

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.

Mapping the Ethical Issues of Digital Twins for Personalised Healthcare Service (Preprint)

2021 ◽  
Author(s):  
Pei-hua Huang ◽  
Ki-hun Kim ◽  
Maartje Schermer
Keyword(s):  
Ethical Issues ◽  
Digital Health ◽  
Personalised Medicine ◽  
Healthcare Services ◽  
Ethical Values ◽  
Ethical Concerns ◽  
Digital Twins ◽  
Research Gap ◽  
Process Oriented ◽  
Personalised Healthcare

BACKGROUND The concept of digital twins has great potential for transforming the existing healthcare system by making it more personalised. As a convergence of healthcare, artificial intelligence, and information and communication technologies, personalised healthcare services developed under the concept of digital twins raise a myriad of ethical issues. While some of the ethical issues are known to researchers working on digital health and personalised medicine, currently there is no comprehensive review that maps major ethical risks of digital twins for personalised healthcare services. OBJECTIVE This paper fills the research gap by identifying major ethical risks of digital twins for personalised healthcare services. We first propose a working definition for digital twins for personalised healthcare services (DTPHS) to facilitate future discussion on the ethical issues related to these emerging digital health services. We then developed a process-oriented ethical map to identify major ethical risks against each of the different data processing phases. METHODS This research aims to address this research gap by providing a comprehensive analysis of major ethical risks of DTPHSs. Due to the scarcity of literature on DTPHSs, we are unable to perform a systematic review of ethical concerns over DTPHSs. Thus, we resort to literature on eHealth, personalised medicine, precision medicine, and information engineering to identify potential issues. We develop a process-oriented ethical map to structure the inquiry in a more systematic way. The ethical map allows us to see how each of the major ethical concerns emerges during the process of transforming raw data into valuable information. RESULTS The process-oriented ethical analysis identified ten operational problems and the relevant ethical values. By structuring the operational problems and relevant ethical values in a clear logical flow, this process-oriented ethical map allows developers of DTPHSs and stakeholders to have a comprehensive overview of major ethical risks while refining the design of DTPHSs. The ethical values section on the map also helps developers of DTPHSs better understand which values they ought to consider while developing solutions for an operational problem they encounter.   CONCLUSIONS It is challenging to address all of the major ethical risks a DTPHS might encounter proactively without a conceptual map at hand. The process-oriented ethical map we propose here can assist developers of DTPHSs in analysing ethical risks in a more systematic manner. CLINICALTRIAL N/A

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.

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