Development and Assessment of a Nearly Autonomous Management and Control System During a Single Loss of Flow Accident

2020 ◽  
Author(s):  
Linyu Lin ◽  
Paridhi Athe ◽  
Pascal Rouxelin ◽  
Nam Dinh ◽  
Jeffrey Lane
Keyword(s):  
Knowledge Base ◽  
Confusion Matrix ◽  
Data Generation ◽  
Digital Twin ◽  
Control Functions ◽  
Digital Twins ◽  
Twin Models ◽  
Autonomous Management ◽  
And Performance ◽  
And Control

Abstract In this work, a Nearly Autonomous Management and Control (NAMAC) system is designed to diagnose the reactor state and provide recommendations to the operator for maintaining the safety and performance of the reactor. A three layer-hierarchical workflow is suggested to guide the design and development of the NAMAC system. The three layers in this workflow corresponds to knowledge base, digital twin developmental layer (for different NAMAC functions), and NAMAC operational layer. Digital twin in NAMAC is described as knowledge acquisition system to support different autonomous control functions. Therefore, based on the knowledge base, a set of digital twin models is trained to determine the plant state, predict behavior of physical components or systems, and rank available control options. The trained digital twin models are assembled according to NAMAC operational workflow to support decision-making process in selecting the optimal control actions during an accident scenario. To demonstrate the capability of the NAMAC system, a case study is designed, where a baseline NAMAC is implemented for operating a simulator of the Experimental Breeder Reactor II (EBR-II) during a single loss of flow accident. Training database for development of digital twin models is obtained by sampling the control parameters in the GOTHIC data generation engine. After the training and testing, the digital twins are assembled into a NAMAC system according to the operational workflow. This NAMAC system is coupled with the GOTHIC plant simulator, and a confusion matrix is generated to illustrate the accuracy and robustness of implemented NAMAC system. It is found that within the training databases, NAMAC can make reasonable recommendations with zero confusion rate. However, when the scenario is beyond the training cases, the confusion rate increases, especially when the scenarios are more severe. Therefore, a discrepancy checker is added to detect unexpected reactor states and alert operators for safety-minded actions.

scholarly journals Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1717
Author(s):  
Lei Wu ◽  
Jiewu Leng ◽  
Bingfeng Ju
Keyword(s):  
Information Asymmetry ◽  
Large Scale ◽  
Planning Process ◽  
Design Stage ◽  
Precision Machining ◽  
Digital Twin ◽  
Module Design ◽  
Digital Twins ◽  
Ultra Precision ◽  
And Control

Ultra-Precision Machining (UPM) is a kind of highly accurate processing technology developed to satisfy the manufacturing requirements of high-end cutting-edge products including nuclear energy producers, very large-scale integrated circuits, lasers, and aircraft. The information asymmetry phenomenon widely exists in the design and control of ultra-precision machining. It may lead to inconsistency between the designed performance and operational performance of the UPM equipment on stiffness, thermal stability, and motion accuracy, which result from its design, manufacturing, and control, and determine the form accuracy and surface roughness of machined parts. The performance of the UPM equipment should be improved continuously. It is still challenging to realize the real-time and self-adaptive control, in which building a high-fidelity and computationally efficient digital twin is a valuable solution. Nevertheless, the incorporation of the digital twin technology into the UPM design and control remains vague and sometimes contradictory. Based on a literature search in the Google Scholar database, the critical issues in the UPM design and control, and how to use the digital twin technologies to promote it, are reviewed. Firstly, the digital twins-based UPM design, including bearings module design, spindle-drive module design, stage system module design, servo module design, and clamping module design, are reviewed. Secondly, the digital twins-based UPM control studies, including voxel modeling, process planning, process monitoring, vibration control, and quality prediction, are reviewed. The key enabling technologies and research directions of digital twins-based design and control are discussed to deal with the information asymmetry phenomenon in UPM.

scholarly journals A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future

2020 ◽  
Vol 10 (13) ◽  
pp. 4482 ◽  
Author(s):  
Adrien Bécue ◽  
Eva Maia ◽  
Linda Feeken ◽  
Philipp Borchers ◽  
Isabel Praça
Keyword(s):  
Cognitive Modeling ◽  
Monitoring And Control ◽  
Security Testing ◽  
Digital Twin ◽  
Digital Twins ◽  
Support Tools ◽  
The Future ◽  
And Control ◽  
Comprehensive Modeling ◽  
Factories Of The Future

In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.

Smart Connected Digital Products and IoT Platform With the Digital Twin

2021 ◽  
pp. 330-350
Author(s):  
Mohamed Uvaze Ahamed Ayoobkhan ◽  
Yuvaraj D. ◽  
Jayanthiladevi A. ◽  
Balamurugan Easwaran ◽  
ThamaraiSelvi R.
Keyword(s):  
Associate Degree ◽  
Physical Object ◽  
Digital Products ◽  
Object A ◽  
Digital Twin ◽  
Physical Product ◽  
Digital Twins ◽  
And Performance ◽  
And Behavior ◽  
Insight Into

A digital illustration of a novel prevalence of a physical product helps one to gain larger insight into that product's state performance and behavior digital twin, which is an unequivocal advanced copy of an item, method, or control. This living model creates a thread between the physical and digital worlds. A model of a physical object—a 'twin'—enables you to observe its standing, diagnose problems, and take a look at solutions remotely. It's a dynamic virtual illustration of a tool that is unendingly fed with knowledge from embedded sensors and packages. This provides associate degree correct period of time standing of the physical device. Digital twins drive innovation and performance and offer development technicians prognostic analytics that give firms the flexibility to boost client expertise.

scholarly journals An Enabling Open-Source Technology for Development and Prototyping of Production Systems by Applying Digital Twinning

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Robert Kazała ◽  
Sławomir Luściński ◽  
Paweł Strączyński ◽  
Albena Taneva
Keyword(s):  
Open Source ◽  
Production Systems ◽  
Communication Technologies ◽  
Digital Twin ◽  
Twin System ◽  
Digital Twins ◽  
First Choice ◽  
Automation And Control ◽  
And Control

This article presents the most valuable and applicable open-source tools and communication technologies that may be employed to create models of production processes by applying the concept of Digital Twins. In recent years, many open-source technologies, including tools and protocols, have been developed to create virtual models of production systems. The authors present the evolution and role of the Digital Twin concept as one of the key technologies for implementing the Industry 4.0 paradigm in automation and control. Based on the presented structured review of valuable open-source software dedicated to various phases and tasks that should be realised while creating the whole Digital Twin system, it was demonstrated that the available solutions cover all aspects. However, the dispersion, specialisation, and lack of integration cause this software to usually not be the first choice to implement DT. Therefore, to successfully create full-fledged models of Digital Twins by proceeding with proposed open-source solutions, it is necessary to make additional efforts due to integration requirements.

scholarly journals Digital Technologies in the Smart Production Management System

2021 ◽  
Vol 93 ◽  
pp. 01024
Author(s):  
Evgeniy Starikov ◽  
Marina Evseeva ◽  
Irina Tkachenko
Keyword(s):  
Management System ◽  
Production Management ◽  
Manufacturing Sector ◽  
Digital Technologies ◽  
Digital Twin ◽  
Twin Model ◽  
Digital Twins ◽  
Industrial Internet ◽  
Production Management System ◽  
Twin Models

The article analyzes the possibility of using such digital technologies as the Industrial Internet of Things (IIoT), Big Data and the creation of models of digital twins in the formation of intelligent management systems for "smart" production within the framework of the concept of digital transformation of the manufacturing sector Industry 4.0. The essence and features of these technologies, problematic aspects of their implementation in real production enterprises are considered. The concept of the functional structure of the digital production management system of a "smart" enterprise based on the digital twin model is proposed. The conclusion is made about the integrating role of technologies for the development and application of digital twin models in the construction of intelligent control systems for "smart" production.

scholarly journals Beyond building predictive models: TwinOps in biomanufacturing

2021 ◽  
Author(s):  
Elisa Canzani ◽  
Sander W. Timmer
Keyword(s):  
Best Practices ◽  
Predictive Models ◽  
Paradigm Shift ◽  
Digital Technologies ◽  
Data Driven ◽  
Biopharmaceutical Industry ◽  
Digital Twin ◽  
Digital Twins ◽  
Technical Challenges ◽  
And Control

<div>On the wave of more and more manufacturers embracing the pervasive mission to build digital twins, also biopharmaceutical industry envisions a significant paradigm shift of digitalisation towards an intelligent factory where bioprocesses continuously learn from data to optimise and control productivity. While extensive efforts are made to build and combine the best mechanistic and data-driven models, there has not been a complete digital twin application in pharma. One of the main reasons is that production deployment becomes more complex regarding the possible impact such digital technologies could have on vaccine products and ultimately on patients. To address current technical challenges and fill regulatory gaps, this paper explores some best practices for TwinOps in biomanufacturing – from experiment to GxP validation – and discusses approaches to oversight and compliance that could work with these best practices towards building bioprocess digital twins at scale.</div>

scholarly journals Beyond building predictive models: TwinOps in biomanufacturing

2021 ◽  
Author(s):  
Elisa Canzani ◽  
Sander W. Timmer
Keyword(s):  
Best Practices ◽  
Predictive Models ◽  
Paradigm Shift ◽  
Digital Technologies ◽  
Data Driven ◽  
Biopharmaceutical Industry ◽  
Digital Twin ◽  
Digital Twins ◽  
Technical Challenges ◽  
And Control

<div>On the wave of more and more manufacturers embracing the pervasive mission to build digital twins, also biopharmaceutical industry envisions a significant paradigm shift of digitalisation towards an intelligent factory where bioprocesses continuously learn from data to optimise and control productivity. While extensive efforts are made to build and combine the best mechanistic and data-driven models, there has not been a complete digital twin application in pharma. One of the main reasons is that production deployment becomes more complex regarding the possible impact such digital technologies could have on vaccine products and ultimately on patients. To address current technical challenges and fill regulatory gaps, this paper explores some best practices for TwinOps in biomanufacturing – from experiment to GxP validation – and discusses approaches to oversight and compliance that could work with these best practices towards building bioprocess digital twins at scale.</div>

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