Digital Thread Enabled Manufacturing Automation Towards Mass Personalization

Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability ◽

10.1115/msec2020-8429 ◽

2020 ◽

Author(s):

Akhilnandh Ramesh ◽

Zhaojun Qin ◽

Yuqian Lu

Keyword(s):

Information Flow ◽

Data Exchange ◽

Large Scale ◽

Field Performance ◽

Manufacturing Automation ◽

Digital Twin ◽

Digital Twins ◽

Type Mass ◽

Mass Personalization ◽

Self Organizing

Abstract Manufacturing industries are moving towards mass personalization, which refers to the rapid production of individualized products, with large scale efficiencies. This shift from push-type mass customization to pull-type mass personalization will pose critical operational challenges to manufacturing businesses, with complexities ranging from effective requirements elicitation to design, manufacturing, commissioning and after-sales support. Aiming at addressing these challenges, a feasible operational framework for enabling efficient manufacturing automation for mass personalization is proposed in this paper. A key element of this operational framework is the Digital Thread, which streamlines information flow associated with design, manufacturing, maintenance and servicing of a personalized product, each of which are represented as Digital Twins. An As-Designed Digital Twin is created from the beginning of the product co-design process, which then evolves into the subsequent design and manufacturing process and systems resulting in As-Designed Digital Twin evolving to As-Planned Digital Twin and then to As-Built Digital Twin. The personalized product, after it’s commissioning and installation constitutes the As-Maintained Digital Twin of the product, which stores product data related to field performance. The data exchange and communications between these Digital Twins that reside in the various departments of the organization and the management systems create a seamless Digital Thread, capturing the lifecycle information of each personalized product. Personalized product is proposed to be developed through a self-organizing shopfloor, working on a multi-agent mechanism and controlled by a central agent control algorithm, which can coordinate and provide individualized process plans. The Digital Twins, interlinked by a Digital Thread and realized by a self-organizing shopfloor, thus result in increased level of automated control in engineering and manufacturing. To validate the feasibility of this proposed framework, we tested the information flow in the Digital Thread with a case study in the construction industry. Finally the challenges faced by such an automation framework and the area of future work are also discussed.

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

Symmetry ◽

10.3390/sym13091717 ◽

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.

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Urban Digital Twins – A FIWARE-based model

at - Automatisierungstechnik ◽

10.1515/auto-2021-0083 ◽

2021 ◽

Vol 69 (12) ◽

pp. 1106-1115

Author(s):

Martin Bauer ◽

Flavio Cirillo ◽

Jonathan Fürst ◽

Gürkan Solmaz ◽

Ernö Kovacs

Keyword(s):

Smart City ◽

Data Exchange ◽

Reference Model ◽

Smart Cities ◽

Digital Twin ◽

Data Exchange Platform ◽

City Community ◽

Digital Twins ◽

The City ◽

Different Time Scales

Abstract This article describes the use of digital twins for smart cities, i. e., the Urban Digital Twin (UDTw) concept. It shows how UDTws can be realized using the open source components from the FIWARE ecosystem that are already used in more than 200 cities worldwide. The used NGSI-LD standard is supported by the European Connecting Europe Facility, the Open and Agile Smart City community, the Indian Urban Data Exchange platform, and the Japanese Smart City Reference Model. Unlike digital twins in other domains, e. g., manufacturing, where digital twins are co-developed with their physical counterparts, UDTws often evolve driven by different stakeholders, on different time scales, as well as by utilizing many different data sources from the city. This article builds on a well-established lifecycle model for Digital Twins and combines this with a conceptual model for digital twins consisting of data, reactive, predictive and forecasting (“what if”) digital twin functionalities. The article also describes how AI-based technologies can be used to extract knowledge to build the UDTws from the IoT-based infrastructure of a smart city.

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Methods of creating and using a digital twin of a mobile transport and transshipment rope complex

Advanced Engineering Research ◽

10.23947/2687-1653-2020-20-3-243-251 ◽

2020 ◽

Vol 20 (3) ◽

pp. 243-251

Author(s):

I. A. Lagerev ◽

V. I. Tarichko ◽

A. V. Panfilov

Keyword(s):

Large Scale ◽

Load Capacity ◽

Video Stream ◽

Transport Systems ◽

Work Processes ◽

Digital Twin ◽

Digital Twins ◽

Ongoing Work ◽

The Creation ◽

High Load Capacity

Introduction. The paper considers the creation and application of digital twins at various stages of the life cycle of mobile transport and transshipment rope complexes (mobile ropeways), the equipment of which is mounted on the basis of wheeled or tracked chassis of high load capacity. The work objective is to improve safety in using such transport systems based on real-time forecasting of potential failures. This will prevent the occurrence of emergencies in a timely manner. Materials and Methods. The structure of the digital twin of the mobile transport and transshipment rope complex is proposed. Approaches to the analysis of ongoing work processes in order to prevent accidents have been developed. They are based on simulation modeling of the system dynamics using new complex mathematical models built through the system approach. Results. The developed method was tested on a large-scale layout of a mobile transport and transshipment rope complex created by 3D printing methods. A mathematical model of this system was developed; it was used to construct a digital double of the experimental model. The possibility of predicting failures in the layout is shown experimentally through the example of a rope slipping case. To do this, the actual value of the load suspension point coordinate obtained through the video stream processing method was compared to the predicted value calculated using a digital twin.Discussion and Conclusions. The research results provide the creation of an industrial digital twin of a mobile transport and transshipment rope complex mounted on cross-country wheeled chassis.

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Getting Real: The Challenge of Building and Validating a Large-Scale Digital Twin of Barcelona’s Traffic with Empirical Data

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi11010024 ◽

2021 ◽

Vol 11 (1) ◽

pp. 24

Author(s):

Javier Argota Sánchez-Vaquerizo

Keyword(s):

Big Data ◽

Empirical Data ◽

Large Scale ◽

Smart Cities ◽

Digital Twin ◽

Fine Grained ◽

Mobility Data ◽

Digital Twins ◽

Alternative Scenarios ◽

Hourly Distribution

Large-scale microsimulations are increasingly resourceful tools for analysing in detail citywide effects and alternative scenarios of our policy decisions, approximating the ideal of ‘urban digital twins’. Yet, these models are costly and impractical, and there are surprisingly few published examples robustly validated with empirical data. This paper, therefore, presents a new large-scale agent-based traffic microsimulation for the Barcelona urban area using SUMO to show the possibilities and challenges of building these scenarios based on novel fine-grained empirical big data. It combines novel mobility data from real cell phone records with conventional surveys to calibrate the model comparing two different dynamic assignment methods for getting an operationally realistic and efficient simulation. Including through traffic and the use of a stochastic adaptive routing approach results in a larger 24-hour model closer to reality. Based on an extensive multi-scalar evaluation including traffic counts, hourly distribution of trips, and macroscopic metrics, this model expands and outperforms previous large-scale scenarios, which provides new operational opportunities in city co-creation and policy. The novelty of this work relies on the effective modelling approach using newly available data and the realistic robust evaluation. This allows the identification of the fundamental challenges of simulation to accurately capture real-world dynamical systems and to their predictive power at a large scale, even when fed by big data, as envisioned by the digital twin concept applied to smart cities.

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WHAT IS A DIGITAL TWIN? – DEFINITIONS AND INSIGHTS FROM AN INDUSTRIAL CASE STUDY IN TECHNICAL PRODUCT DEVELOPMENT

Proceedings of the Design Society: DESIGN Conference ◽

10.1017/dsd.2020.15 ◽

2020 ◽

Vol 1 ◽

pp. 757-766 ◽

Cited By ~ 1

Author(s):

J. Trauer ◽

S. Schweigert-Recksiek ◽

C. Engel ◽

K. Spreitzer ◽

M. Zimmermann

Keyword(s):

Product Development ◽

Physical System ◽

Data Exchange ◽

Literature Study ◽

Industrial Case Study ◽

Technical Product ◽

Digital Twin ◽

Digital Twins ◽

Definition Of

AbstractOver the last two decades, a concept called Digital Twin has evolved rapidly. Yet, there is no unified definition of the term. Based on a literature study and an industrial case study, an overarching definition of Digital twins is presented. Three characteristics were identified – representation of a physical system, bidirectional data exchange, and the connection along the entire lifecycle. Further, three sub-concepts are presented, namely: Engineering Twin, Production Twin, and Operation Twin. The presented paper thus formulates a consistent and detailed definition of Digital Twins.

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Pipeline for ontology-based modeling and automated deployment of digital twins for planning and control of manufacturing systems

Journal of Intelligent Manufacturing ◽

10.1007/s10845-021-01860-6 ◽

2021 ◽

Author(s):

Amon Göppert ◽

Lea Grahn ◽

Jonas Rachner ◽

Dennis Grunert ◽

Simon Hort ◽

...

Keyword(s):

Data Exchange ◽

Manufacturing Systems ◽

Digital Model ◽

Use Case ◽

Digital Twin ◽

Planning And Control ◽

Digital Twins ◽

Definition Of ◽

Fully Connected ◽

And Control

AbstractThe demand for individualized products drives modern manufacturing systems towards greater adaptability and flexibility. This increases the focus on data-driven digital twins enabling swift adaptations. Within the framework of cyber-physical systems, the digital twin is a digital model that is fully connected to the physical and digital assets. A digital model must follow a standardization for interoperable data exchange. Established ontologies and meta-models offer a basis in the definition of a schema, which is the first phase of creating a digital twin. The next phase is the standardized and structured modeling with static use-case specific data. The final phase is the deployment of digital twins into operation with a full connection of the digital model with the remaining cyber-physical system. In this deployment phase communication standards and protocols provide a standardized data exchange. A survey on the state-of-the-art of these three digital twin phases reveals the lack of a consistent workflow from ontology-driven definition to standardized modeling. Therefore, one goal of this paper is the design of an end-to-end digital twin pipeline to lower the threshold of creating and deploying digital twins. As the task of establishing a communication connection is highly repetitive, an automation concept by providing structured protocol data is the second goal. The planning and control of a line-less assembly system with manual stations and a mobile robot as resources and an industrial dog as the product serve as exemplary digital twin applications. Along this use-case the digital twin pipeline is transparently explained.

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Digital Twins in Livestock Farming

10.20944/preprints202101.0620.v1 ◽

2021 ◽

Author(s):

Suresh Neethirajan ◽

Bas Kemp

Keyword(s):

Large Scale ◽

Well Being ◽

Farm Animals ◽

Emotional States ◽

Space Technology ◽

Livestock Farming ◽

Digital Twin ◽

Technological Advances ◽

Digital Twins ◽

Cost And Benefit Analysis

Digital twin technology is already improving efficiencies and reducing costs across multiple industries and sectors. As the earliest adopters, space technology and manufacturing sectors have made the most sophisticated gains with automobile and natural resource extraction industries following close behind with recent investments in digital twin technology. The application of digital twins within the livestock farming sector is the next frontier. The possibilities that this technology may fuel are nearly endless as digital twins can be used to improve large-scale precision livestock farming practices, machinery and equipment usage, and the health and well-being of a wide variety of farm animals. Currently, many pioneers of digital twins in livestock farming are already applying sophisticated AI technology to monitor both animals and environment around the clock, which leads to a better understanding of animal behavior and distress, disease control and prevention, and smarter business decisions for the farmer. Mental and emotional states of animals can be monitored using recognition technology that examines facial features such as ear postures and eye white regions. Used with modeling, simulation and augmented reality technologies, digital twins can help farmers build more energy-efficient housing structures, predict heat cycles for breeding, discourage negative behaviors of livestock, and potentially much more. As with all disruptive technological advances, the implementation of digital twin technology will demand a thorough cost and benefit analysis by individual farms. Digital twin application will need to overcome challenges and accept limitations that arise. However, regardless of these issues, the potential of digital twins promises to revolutionize livestock farming in the future.

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Digital Twins in Livestock Farming

Animals ◽

10.3390/ani11041008 ◽

2021 ◽

Vol 11 (4) ◽

pp. 1008

Author(s):

Suresh Neethirajan ◽

Bas Kemp

Keyword(s):

Large Scale ◽

Animal Husbandry ◽

Well Being ◽

Farm Animals ◽

Emotional States ◽

Livestock Farming ◽

Digital Twin ◽

Technological Advances ◽

Digital Twins ◽

Cost And Benefit Analysis

Artificial intelligence (AI), machine learning (ML) and big data are consistently called upon to analyze and comprehend many facets of modern daily life. AI and ML in particular are widely used in animal husbandry to monitor both the animals and environment around the clock, which leads to a better understanding of animal behavior and distress, disease control and prevention, and effective business decisions for the farmer. One particularly promising area that advances upon AI is digital twin technology, which is currently used to improve efficiencies and reduce costs across multiple industries and sectors. In contrast to a model, a digital twin is a digital replica of a real-world entity that is kept current with a constant influx of data. The application of digital twins within the livestock farming sector is the next frontier and has the potential to be used to improve large-scale precision livestock farming practices, machinery and equipment usage, and the health and well-being of a wide variety of farm animals. The mental and emotional states of animals can be monitored using recognition technology that examines facial features, such as ear postures and eye white regions. Used with modeling, simulation and augmented reality technologies, digital twins can help farmers to build more energy-efficient housing structures, predict heat cycles for breeding, discourage negative behaviors of livestock, and potentially much more. As with all disruptive technological advances, the implementation of digital twin technology will demand a thorough cost and benefit analysis of individual farms. Our goal in this review is to assess the progress toward the use of digital twin technology in livestock farming, with the goal of revolutionizing animal husbandry in the future.

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Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

Advances in Meteorology ◽

10.1155/2017/8576150 ◽

2017 ◽

Vol 2017 ◽

pp. 1-11 ◽

Cited By ~ 9

Author(s):

Adeoluwa Akande ◽

Ana Cristina Costa ◽

Jorge Mateu ◽

Roberto Henriques

Keyword(s):

Extreme Precipitation ◽

Large Scale ◽

Northern Region ◽

Extreme Weather Events ◽

Self Organizing Map ◽

Spatial And Temporal Patterns ◽

Self Organizing Maps ◽

The North ◽

Precipitation Regimes ◽

Self Organizing

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

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