Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems

Grieves, Michael W.; Vickers, John

doi:10.1007/978-3-319-38756-7_4

Cited by 1,869 publications

(1,204 citation statements)

References 11 publications

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“…1). With some similarity to this, Grieves defines the digital twin as "a set of virtual information constructs that fully describes a potential or actual physical manufactured product from the micro atomic level to the macro geometrical level" [11]. …”

Section: The Origin and Evolution Of The Digital Twinmentioning

confidence: 99%

Shaping the digital twin for design and production engineering

et al. 2017

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Abstract:The digitalization of manufacturing fuels the application of sophisticated virtual product models, which are referred to as digital twins, throughout all stages of product realization. Particularly, more realistic virtual models of manufactured products are essential to bridge the gap between design and manufacturing and to mirror the real and virtual worlds. In this paper, we propose a comprehensive reference model based on the concept of Skin Model Shapes, which serves as a digital twin of the physical product in design and manufacturing. In this regard, model conceptualization, representation, and implementation as well as applications along the product life-cycle are addressed.

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Section: The Origin and Evolution Of The Digital Twinmentioning

confidence: 99%

Shaping the digital twin for design and production engineering

et al. 2017

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“…In a sufficiently large learning health care system “digital twins” (Grieves and Vickers, 2017) will begin to emerge as useful benchmarks for defining the individualized optimal health range for specific health parameters as well as predictors of health outcomes overall (Figure 4). Unlike the engineering concept of the digital twin, a digital copy of a physical asset, a high definition medicine digital twin is an actual person, or composite of people, who share relevant health parameters.…”

Section: Billions Of High Resolution People - the Knowledge Resourcementioning

confidence: 99%

High-Definition Medicine

Torkamani

Andersen

Steinhubl

et al. 2017

Cell

192

139

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The foundation for a new era of data-driven medicine has been set by recent technological advances that enable the assessment and management of human health at an unprecedented level of resolution – what we refer to as high definition medicine. Our ability to assess human health in high definition is enabled, in part, by advances in DNA sequencing, physiological and environmental monitoring, advanced imaging and behavioral tracking. Our ability to understand and act upon these observations at equally high precision is driven by advances in genome editing, cellular reprogramming, tissue engineering, and information technologies, especially artificial intelligence. In this review, we will examine the core disciplines that enable high definition medicine, and project how these technologies will alter the future of medicine.

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“…These Twins could enable to predict the motion of target areas during surgery with predefined accuracy [54][55][56] or fuel virtual reality engines [57] enabling the surgeons to "see through" the patient, investigate the potential response of a patient to a given treatment [58]. Digital Twins could also enable to transition from "factors of safety" and associated over-engineering to adaptive structures and systems which adapt to their environment [59][60][61][62][63][64]. For this revolution to take place, Data Science approaches must be harnessed by computational scientists.…”

Section: Case Study 2: Digital Twins In Engineering and Personalised mentioning

confidence: 99%

What makes Data Science different? A discussion involving Statistics2.0 and Computational Sciences

Ley

Bordas

2018

Int J Data Sci Anal

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Data Science is today one of the main buzzwords, be it in business, industrial or academic settings. Machine learning, experimental design, data-driven modelling are all, undoubtedly, rising disciplines if one goes by the soaring number of research papers and patents appearing each year. The prospect of becoming a "Data Scientist" appeals to many. A discussion panel organised as part of the European Data Science Conference (European Association for Data Science (EuADS)) https:// euads.org/edsc/ asked the question: "What makes Data Science different?" In this paper, we give our own, personal and multi-faceted view on this question, from a Statistics and an Engineering perspective. In particular, we compare Data Science to Statistics and discuss the connection between Data Science and Computational Sciences.

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Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems

Cited by 1,869 publications

References 11 publications

Shaping the digital twin for design and production engineering

Shaping the digital twin for design and production engineering

High-Definition Medicine

What makes Data Science different? A discussion involving Statistics2.0 and Computational Sciences

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