scholarly journals An architecture of an Intelligent Digital Twin in a Cyber-Physical Production System

2019 ◽  
Vol 67 (9) ◽  
pp. 762-782 ◽  
Author(s):  
Behrang Ashtari Talkhestani ◽  
Tobias Jung ◽  
Benjamin Lindemann ◽  
Nada Sahlab ◽  
Nasser Jazdi ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Production Systems ◽  
Heterogeneous Data ◽  
Use Cases ◽  
Added Value ◽  
Automation System ◽  
The Real ◽  
Digital Twin ◽  
Digital Twins ◽  
Cyber Physical Production Systems

Abstract The role of a Digital Twin is increasingly discussed within the context of Cyber-Physical Production Systems. Accordingly, various architectures for the realization of Digital Twin use cases are conceptualized. There lacks, however, a clear, encompassing architecture covering necessary components of a Digital Twin to realize various use cases in an intelligent automation system. In this contribution, the added value of a Digital Twin in an intelligent automation system is highlighted and various existing definitions and architectures of the Digital Twin are discussed. Flowingly, an architecture for a Digital Twin and an architecture for an Intelligent Digital Twin and their required components are proposed, with which use cases such as plug and produce, self-x and predictive maintenance are enabled. In the opinion of the authors, a Digital Twin requires three main characteristics: synchronization with the real asset, active data acquisition from the real environment and the ability of simulation. In addition to all the characteristics of a Digital Twin, an Intelligent Digital Twin must also include the characteristics of Artificial Intelligence. The Intelligent Digital Twin can be used for the realization of the autonomous Cyber-Physical Production Systems. In order to realize the proposed architecture for a Digital Twin, several methods, namely the Anchor-Point-Method, a method for heterogeneous data acquisition and data integration as well as an agent-based method for the development of a co-simulation between Digital Twins were implemented and evaluated.

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.

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 Simulation von Cyber-Physischen Produktionssystemen in einer Forschungsinfrastruktur

2020 ◽  
Author(s):  
Iris Gräßler
Keyword(s):  
Communication Technology ◽  
Information Acquisition ◽  
Industry 4.0 ◽  
Production Control ◽  
Production Systems ◽  
General Concept ◽  
Radio Network ◽  
Systems Research ◽  
Digital Twins ◽  
Cyber Physical Production Systems

The article describes the setup of an experimentation and validation environment by extending a production laboratory: All relevant elements of the production laboratory were equipped with computer systems, so-called "industry 4.0 boxes", and interconnected via a peer-to-peer radio network. The "industry 4.0 boxes" are used to upgrade dedicated sensors for recording machine behaviour and communication technology to be integrated into decentralized production control. In addition, digital twins were implemented to map machine and user behaviour, enable control and support information acquisition and processing. Thereby, a research infrastructure is created for research on potentials of cyber-physical production systems. Research outcomes will be used as a decision basis for companies and for validation of production optimizations. This paper describes the concept and implementation of industry 4.0 functionalities and derives a general concept of simulation platforms for CPPS.

Digital Tools to Capture Manufacturing Tacit Knowledge to Support Next Generation Automation Systems

2019 ◽  
Author(s):  
David A. Guerra-Zubiaga ◽  
Kathy S. Schwaig ◽  
Sabih Nasir ◽  
Alex Bondar
Keyword(s):  
Tacit Knowledge ◽  
Digital Tools ◽  
Automation System ◽  
Digital Manufacturing ◽  
Next Generation ◽  
Knowledge Modeling ◽  
Digital Twin ◽  
Digital Twins ◽  
Automation Systems ◽  
Manufacturing Knowledge

Abstract In today’s complex environment, it is not only important to handle/control digital manufacturing tools, but also essential to capture tacit knowledge from people. Creating a digital twin, it is an extensive effort including different fields and subjects. For example, creating a physical prototype and connecting it with a virtual prototype. From this, two questions arise. What will be the framework used to create the digital twin and what method will be used to capture the experiences to develop Next Generation Automation System (NGAS). This research explores a new method capturing tacit knowledge creating a digital twin for a NGAS, worked at station level connecting machines and humans implementing knowledge modelling and providing guidance in design for manufacturability at NGAS. The motivation of this research is that capturing tacit knowledge is an important aspect in Industry 4.0. According to literature review, different researchers have been exploring digital twins using digital tools. This research proposal explores the effects of automation in the workplace using Digital Manufacturing Tools (DMT). The proposed approach demonstrates how to capture valuable experiences we can transfer or communicate between the digital twins, increasing productivity to fulfill the need to adopt new and emerging technologies in the workplace. The research will talk about capturing Tacit Knowledge in different forms like experiences, analysis, and intuitions etc and how this type of knowledge is processed by DMT and communicated to the other digital twin. Tacit knowledge modeling and sharing is used by implementing the Internet of Things (IoT) to understand the interaction among humans, instruments, controls, and robots. Understanding tacit manufacturing knowledge types is required to create better digital twins.

Exploring applicability, interoperability and integrability of Blockchain-based digital twins for asset life cycle management

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Christopher Santi Götz ◽  
Patrik Karlsson ◽  
Ibrahim Yitmen
Keyword(s):  
Life Cycle ◽  
Management Practice ◽  
Life Cycle Management ◽  
Use Cases ◽  
Content Type ◽  
Digital Twin ◽  
Digital Twins ◽  
Current Asset ◽  
User Expectations ◽  
Technological Platform

PurposeThe blockchain-based digital twin has been recognized as a prominent technological ecosystem featuring synergies with both established and emergent information management practice. The purpose of this research is to explore the applicability, interoperability and integrability of a blockchain-based digital twin for asset life cycle management and develop a model of framework which positions the digital twin within a broader context of current management practice and technological availability.Design/methodology/approachA systematic literature review was performed to map use cases of digital twin, IoT, blockchain and smart contract technologies. Surveys of industry professionals and analyses were conducted focussing on the mapped use cases' life cycle–centric applicability, interoperability and integrability with current asset life cycle management practice, exploring decision support capabilities and industry insights. Lastly, a model of framework was developed based on the use case, interoperability and integrability findings.FindingsThe results support approaching digitization initiatives with blockchain-based digital twins and the positioning of the concept as both a strategic tool and a multifunctional on-field support application. Integrability enablers include progression towards BIM level 3, decentralized program hubs, modular cross-technological platform interfaces, as well as mergeable and scalable blockchains.Practical implicationsKnowledge of use cases help highlight the functionality of an integrated technological ecosystem and its connection to comprehensive sets of asset life cycle management aspects. Exploring integrability enablers contribute to the development of management practice and solution development as user expectations and technological prerequisites are interlinked.Originality/valueThe research explores asset life cycle management use cases, interoperability and integrability enablers of blockchain-based digital twins and positions the technological ecosystem within current practice and technological availability.

scholarly journals The Digital Twin: Demonstrating the Potential of Real Time Data Acquisition in Production Systems

2017 ◽  
Vol 9 ◽  
pp. 113-120 ◽  
Author(s):  
Thomas H.-J. Uhlemann ◽  
Christoph Schock ◽  
Christian Lehmann ◽  
Stefan Freiberger ◽  
Rolf Steinhilper
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Production Systems ◽  
Time Data ◽  
Digital Twin ◽  
Real Time Data
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