Digital Twin Technology in Internet of Things (IOT)

Developments in virtual technology and data acquisition technology put way to digital twin (DT) technology. Digital twin is a virtual entity that is linked to a real-world entity. Both the link and the virtual representation can be realized in several different ways. Digital Technology plays a very much key role in different areas like in production management, manufacturing, health care, smart cities and so on. Mainly Digital Twin Technology is developed to improve manufacturing processes. With the development of new-generation information and digitalization technologies, more data can be collected, and it is time to find a way for the deep application of all these data. As a result, the concept of digital twin has aroused much concern and is developing rapidly. Digital twins facilitate to monitor, understand, and optimize the functions of all physical entities and for humans and also provide continuous feedback to improve quality of life and well-being.  Digital Twin is best described as the effortless integration of data between a physical and virtual machine in either direction. This paper provides an overview of the Digital Twin technology used in different work spaces and also how it will be effective in the Internet of Things network

TOWARDS DIGITAL TWIN-DRIVEN PERFORMANCE EVALUATION METHODOLOGY OF FMS

The paper presents a method of automated modelling and performance evaluation of concurrent production flows carried out in Flexible Manufacturing Systems. The method allows for quick assessment of various variants of such systems, considering their structure and the organization of production flow of possible ways of their implementation. Its essence is the conditions imposed on the designed model, limiting the space of possible variants of the production flow only to deadlock-free variants. The practical usefulness of the model implemented in the proposed method illustrates the example, which describes the simultaneous assessment of alternative variants of the flexible machining module's structure and the planned multi-assortment production. The ability of the method to focus on feasible solutions offers attractive perspectives for guiding the Digital Twin-like scenario in situations caused by the need to change the production flow

Development of a Digital Twin of a Flexible Manufacturing System for Assisted Learning

Learning Factories provide a propitious learning environment for nurturing production related competencies. However, several problems continue to plague their widespread adoption. Further, assessment of attained competencies continue to remain a concern. This study proposes the use of digital twins as an alternative learning platform for production engineering courses. It is proposed that in the context of manufacturing pedagogy, digital twins of manufacturing processes can play a significant role in delivering efficacious learning experiences. The high-fidelity replication of the physical system aids with reflective observation of the entailed processes in the greatest possible detail, fostering concrete learning experiences. An iterative research methodology towards modelling a pedagogic digital twin is undertaken to build a learning environment that is characterized by ontologies that model learning objectives, learning outcomes and assessment of the said outcomes. This environment facilitates automated assessment of the learner via ontological reasoning mechanisms. The underlying schema takes into account the learner’s profile and focuses on competency attainment through reasoning of behavioural assessment of aligned learning outcomes. The thesis presents also a case study that demonstrates how the learner’s competency level may be evaluated and compared with other learners thus warranting its use a learning tool that proves beneficial in an academic setting

Digital Twins:An enabler for digital transformation

Digital Twins are a virtual representation of anything of value for an organization that create a link between the real and virtual worlds by a continuous bidirectional data/information exchange. In this chapter we present the origins of the concept and how it evolved with the advent of new technological trends. In addition, we describe the main characteristics of a Digital Twin, the benefits of its use, and real-world examples of the usage of digital twins’. Finally, the challenges for its adoption, and the elements to be considered for managing the quality of the Digital Twin are presented to give a complete overview of this new technology.Full book available: https://www.rug.nl/gdbc/the-gdbc-book

Digital twin testbed and practical applications in production logistics with real-time location data

Nowadays, digital twins exist everywhere in various fields. However, an analysis of existing applications in manufacturing and logistics revealed that many entirely apply the concept. To identify when a complete implementation of the concept is beneficial, we analyse the need and the implications within production logistics. This study also presents an architecture supporting integrating a digital twin into production logistics and a corresponding application scenario. Based on this, we have derived practical applications. Each application is applied to different situations, and actual benefits can overcome the limitations of the previous studies

Digital Twin in the IoT context: a survey on technical features, scenarios and architectural models

Digital Twin is an emerging concept that is gaining attention in various industries. It refers to the ability to clone a physical object into a software counterpart. The softwarized object, termed logical object, reflects all the important properties and characteristics of the original object within a specific application context. To fully determine the expected properties of the Digital Twin, this paper surveys the state of the art starting from the original definition within the manufacturing industry. It takes into account related proposals emerging in other fields, namely, Augmented and Virtual Reality (e.g., avatars), Multi-agent systems, and virtualization. This survey thereby allows for the identification of an extensive set of Digital Twin features that point to the “softwarization” of physical objects. To properly consolidate a shared Digital Twin definition, a set of foundational properties is identified and proposed as a common ground outlining the essential characteristics (must-haves) of a Digital Twin. Once the Digital Twin definition has been consolidated, its technical and business value is discussed in terms of applicability and opportunities. Four application scenarios illustrate how the Digital Twin concept can be used and how some industries are applying it. The scenarios also lead to a generic DT architectural Model. This analysis is then complemented by the identification of software architecture models and guidelines in order to present a general functional framework for the Digital Twin. The paper, eventually, analyses a set of possible evolution paths for the Digital Twin considering its possible usage as a major enabler for the softwarization process

Diseño e implementación de un prototipo de " Digital Twin" aplicado a una planta PSA generadora de oxígeno, con el uso de internet de las cosas

El presente trabajo de investigación trata sobre el diseño e implementación de un “Digital Twin”.Empezando con el diseño del activo físico, desde la integración de sensores previamente instaladosen el lugar, pasando por la programación usada en todos los controladores. Posteriormente se diseña el activo digital, escogiendo el procesador teniendo en cuenta su mínimocosto y consumo de energía, pasando por la selección de servicios y la arquitectura que estos usaron, para finalmente interconectarlos. Luego se generaron dashboards para poder observar con claridad la información recogida por lossensores y enviadas previamente, como muestra de esto también se implementa un sistema SCADA, reforzando la facilidad de integración que trae el “Digital Twin”. También como parte de la investigación se desarrolla un modelo de Machine Learning como retroalimentación del “Digital Twin” hacia el activo físico, mejorando con esto la automatizacióndel proceso de generación de oxígeno, regulando el flujo para poder mantener la pureza de oxígen