scholarly journals Digital Twin of Experimental Smart Manufacturing Assembly System for Industry 4.0 Concept

2020 ◽  
Vol 12 (9) ◽  
pp. 3658 ◽  
Author(s):  
Kamil Židek ◽  
Ján Piteľ ◽  
Milan Adámek ◽  
Peter Lazorík ◽  
Alexander Hošovský
Keyword(s):  
Vision System ◽  
Smart Manufacturing ◽  
Assembly System ◽  
Inspection System ◽  
Main Task ◽  
Digital Twin ◽  
Open Platform ◽  
Twin Model ◽  
Digital Twins ◽  
Manufacturing Assembly

This article deals with the creation of a digital twin for an experimental assembly system based on a belt conveyor system and an automatized line for quality production check. The point of interest is a Bowden holder assembly from a 3D printer, which consists of a stepper motor, plastic components, and some fastener parts. The assembly was positioned in a fixture with ultra high frequency (UHF) tags and internet of things (IoT) devices for identification of status and position. The main task was parts identification and inspection, with the synchronization of all data to a digital twin model. The inspection system consisted of an industrial vision system for dimension, part presence, and errors check before and after assembly operation. A digital twin is realized as a 3D model, created in CAD design software (CDS) and imported to a Tecnomatix platform to simulate all processes. Data from the assembly system were collected by a programmable logic controller (PLC) system and were synchronized by an open platform communications (OPC) server to a digital twin model and a cloud platform (CP). Digital twins can visualize the real status of a manufacturing system as 3D simulation with real time actualization. Cloud platforms are used for data mining and knowledge representation in timeline graphs, with some alarms and automatized protocol generation. Virtual digital twins can be used for online optimization of an assembly process without the necessity to stop that is involved in a production line.

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.

scholarly journals A Workflow for Synthetic Data Generation and Predictive Maintenance for Vibration Data

Information ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 386
Author(s):  
Şahan Yoruç Selçuk ◽  
Perin Ünal ◽  
Özlem Albayrak ◽  
Moez Jomâa
Keyword(s):  
Real Life ◽  
Synthetic Data ◽  
Predictive Maintenance ◽  
Classification Model ◽  
Classification Algorithms ◽  
Digital Twin ◽  
Vibration Data ◽  
Twin Model ◽  
Industrial Sectors ◽  
Digital Twins

Digital twins, virtual representations of real-life physical objects or processes, are becoming widely used in many different industrial sectors. One of the main uses of digital twins is predictive maintenance, and these technologies are being adapted to various new applications and datatypes in many industrial processes. The aim of this study was to propose a methodology to generate synthetic vibration data using a digital twin model and a predictive maintenance workflow, consisting of preprocessing, feature engineering, and classification model training, to classify faulty and healthy vibration data for state estimation. To assess the success of the proposed workflow, the mentioned steps were applied to a publicly available vibration dataset and the synthetic data from the digital twin, using five different state-of-the-art classification algorithms. For several of the classification algorithms, the accuracy result for the classification of healthy and faulty data achieved on the public dataset reached approximately 86%, and on the synthetic data, approximately 98%. These results showed the great potential for the proposed methodology, and future work in the area.

scholarly journals On Digital Twin Condition Monitoring Approach for Drivetrains in Marine Applications

2019 ◽  
Author(s):  
Sigrid S. Johansen ◽  
Amir R. Nejad
Keyword(s):  
Fault Detection ◽  
Condition Monitoring ◽  
Offshore Wind ◽  
Test Rig ◽  
Digital Twin ◽  
Model Based ◽  
Twin Model ◽  
Digital Twins ◽  
Fidelity Model

Abstract A digital twin is a virtual representation of a system containing all information available on site. This paper presents condition monitoring of drivetrains in marine power transmission systems through digital twin approach. A literature review regarding current operations concerning maintenance approaches in todays practices are covered. State-of-the-art fault detection in drivetrains is discussed, founded in condition monitoring, data-based schemes and model-based approaches, and the digital twin approach is introduced. It is debated that a model-based approach utilizing a digital twin could be recommended for fault detection of drivetrains. By employing a digital twin, fault detection would be extended to relatively highly diagnostic and predictive maintenance programme, and operation and maintenance costs could be reduced. A holistic model system approach is considered, and methodologies of digital twin design are covered. A physical-based model rather than a data based model is considered, however there are no clear answer whereas which type is beneficial. That case is mostly answered by the amount of data available. Designing the model introduces several pitfalls depending on the relevant system, and the advantages, disadvantages and appropriate applications are discussed. For a drivetrain it is found that multi-body simulation is advised for the creation of a digital twin model. A digital twin of a simple drivetrain test rig is made, and different modelling approaches were implemented to investigate levels of accuracy. Reference values were derived empirically by attaching sensors to the drivetrain during operation in the test rig. Modelling with a low fidelity model showed high accuracy, however it would lack several modules required for it to be called a digital twin. The higher fidelity model showed that finding the stiffness parameter proves challenging, due to high stiffness sensitivity as the experimental modelling demonstrates. Two industries that could have significant benefits from implementing digital twins are discussed; the offshore wind industry and shipping. Both have valuable assets, with reliability sensitive systems and high costs of downtime and maintenance. Regarding the shipping industry an industrial case study is done. Area of extra focus is operations of Ro-Ro (roll on-roll off) vessels. The vessels in the case study are managed by Wilhelmsen Ship Management and a discussion of the implementation of digital twins in this sector is comprised in this article.

Digital Twins Concepts, Challenges, and Future Trends

2021 ◽  
pp. 48-60
Author(s):  
Amged Sayed A. Mahmoud ◽  
Ezz El-Din Hemdan
Keyword(s):  
Life Cycle ◽  
Product Life Cycle ◽  
Smart Cities ◽  
Sensor Technology ◽  
Smart Manufacturing ◽  
Future Trends ◽  
Functional Description ◽  
Digital Twin ◽  
Research Areas ◽  
Digital Twins

Digital twin has gained a great interest during the last few years from academia and industry because of the development in IT technology, communication field, and sensor technology. The general vision of the DT is to provide a detailed physical and functional description of a component, product, and systems. Nevertheless, the digital twin is a highly dynamic concept growing in complexity during the product life cycle, which leads to an enormous amount of data and information. Motivated by these, this chapter investigates the concepts and architecture of DT to cover its challenges and explore its applications in various fields such as smart cities, smart manufacturing and factories, and healthcare sectors. In the end, the challenges and research areas will be presented.

scholarly journals Process Modelling of Geothermal Drilling System Using Digital Twin for Real-Time Monitoring and Control

Designs ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 45 ◽  
Author(s):  
Nahashon O. Osinde ◽  
Jean B. Byiringiro ◽  
Michael M. Gichane ◽  
Hasan Smajic
Keyword(s):  
Real Time ◽  
Energy Demand ◽  
Assembly System ◽  
Monitoring And Control ◽  
Real Time Monitoring ◽  
Drilling Tool ◽  
Digital Twin ◽  
Twin Model ◽  
Study Results ◽  
Geothermal Drilling

Currently, Kenya supplies its energy demand predominantly through hydroelectric power, which fluctuates due to poor and unpredictable rainfall in particular years. Geothermal energy is proposed as a clean and reliable energy source in meeting Kenya’s increasing energy demand. During geothermal drilling operations, disruptions due to tool wear and breakages increases the cost of operation significantly. Some of these causes can be mitigated by real-time monitoring of the tool head during operations. This paper presents the design and implementation of a digital twin model of a drilling tool head, represented as a section of a mechatronic assembly system. The system was modelled in Siemens NX and programmed via the TIA portal using S7 1200 PLC. The digital model was programmed to exactly match the operations of the physical system using OPC (open platform communications) standards. These operations were verified through the motion study by simultaneous running of the assembly system and digital twin model. The study results substantiate that a digital twin model of a geothermal drilling operation can closely mimic the physical operation.

Developing the digital twin of the economic, financial, information and logistics inter-cluster cooperation mechanism

2020 ◽  
Vol 26 (7) ◽  
pp. 1448-1468
Author(s):  
S.N. Yashin ◽  
Yu.V. Trifonov ◽  
E.V. Koshelev
Keyword(s):  
Federal District ◽  
Industrial Clusters ◽  
Linear Regression Method ◽  
The Public ◽  
Digital Twin ◽  
Twin Model ◽  
Cooperation Mechanism ◽  
Digital Twins ◽  
Further Development

Subject. This article deals with the issues related to the use of digital twins in order to manage innovation and industrial clusters and the liaison between them. Objectives. The article aims to develop a digital twin model of inter-cluster cooperation within a Federal district of Russia. The Volga (Privolzhsky) Federal District is considered a case study. Methods. For the study, we used a multiple non-linear regression method and a fast simulated annealing (FSA). Results. The article offers and describes a designed digital twin model of inter-cluster cooperation mechanism. Conclusions and Relevance. When reallocating investment and human resources within one federal district, the interests of the population of innovation and industrial clusters should be taken into account, as only just an increase in fixed investment does not always lead to the growth of the region's population. The use of the digital twin model of inter-cluster cooperation mechanism will help avoid premature unreasonable management decisions of the public-policy level regarding the further development of innovation-industrial clusters.

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.

Edge Computing Enhanced Digital Twins for Smart Manufacturing

2021 ◽  
Author(s):  
Huiyue Huang ◽  
Xun Xu
Keyword(s):  
Real Time ◽  
Information And Communication Technologies ◽  
Research Work ◽  
Edge Computing ◽  
Smart Manufacturing ◽  
Data Mapping ◽  
Digital Twin ◽  
Mapping Strategy ◽  
Digital Twins ◽  
Automation Systems

Abstract Digital Twin is one of the key enabling technologies for smart manufacturing in the context of Industry 4.0. The combination with advanced data analytics and information and communication technologies allows Digital Twins to perform real-time simulation, optimization and prediction to their physical counterparts. Efficient bi-directional data exchange is the foundation for Digital Twin implementation. However, the widely mentioned cloud-based architecture has disadvantages, such as high pressure on bandwidth and long latency time, which limit Digital Twins to provide real-time operating responses in dynamic manufacturing processes. Edge computing has the characteristics of low connectivity, the capability of immediate analysis and access to temporal data for real-time analytics, which makes it a fit-for-purpose technology for Digital Twin development. In this paper, the benefits of edge computing to Digital Twin are first explained through the reviews of the two technologies. The Digital Twin functions to be performed at the edge are then elaborated. After that, how the data model will be used in the edge for data mapping to realize the Digital Twin is illustrated and the data mapping strategy based on the EXPRESS schemas is discussed. Finally, a case study is carried out to verify the data mapping strategy based on EXPRESS schema. This research work refers to ISO/DIS 23247 Automation systems and integration — Digital Twin framework for manufacturing.

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