scholarly journals A Digital Twin Approach for the Improvement of an Autonomous Mobile Robots (AMR’s) Operating Environment—A Case Study

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7830
Author(s):  
Paweł Stączek ◽  
Jakub Pizoń ◽  
Wojciech Danilczuk ◽  
Arkadiusz Gola
Keyword(s):  
Real Life ◽  
Autonomous Mobile Robots ◽  
Shop Floor ◽  
Operating Environment ◽  
Digital Twin ◽  
Digital Twins ◽  
Management Processes ◽  
Physical Testing ◽  
Test Scenarios

The contemporary market creates a demand for continuous improvement of production, service, and management processes. Increasingly advanced IT technologies help designers to meet this demand, as they allow them to abandon classic design and design-testing methods in favor of techniques that do not require the use of real-life systems and thus significantly reduce the costs and time of implementing new solutions. This is particularly important when re-engineering production and logistics processes in existing production companies, where physical testing is often infeasible as it would require suspension of production for the testing period. In this article, we showed how the Digital Twin technology can be used to test the operating environment of an autonomous mobile robot (AMR). In particular, the concept of the Digital Twin was used to assess the correctness of the design assumptions adopted for the early phase of the implementation of an AMR vehicle in a company’s production hall. This was done by testing and improving the case of a selected intralogistics task in a potentially “problematic” part of the shop floor with narrow communication routes. Three test scenarios were analyzed. The results confirmed that the use of digital twins could accelerate the implementation of automated intralogistics systems and reduce its costs.

A Case Study for the Development and Use of a Well Control Simulator as a Digital Twin of a Real Scenario

2021 ◽  
Author(s):  
Francesco Curina ◽  
Ali Talat Qushchi ◽  
Ahmad Aldany
Keyword(s):  
Petroleum Industry ◽  
Real Life ◽  
Well Control ◽  
Safe Environment ◽  
Digital Twin ◽  
Digital Twins ◽  
Drilling Parameters ◽  
Real Life Situation ◽  
Real Scenario

Abstract Simulators in the petroleum industry have been used mainly for training purposes even though they present different applications like digital twins. In this regard, a simulator must approximate the well environment to reflect operative actions and reactions. This paper describes a case study where a well control simulator has been developed to be used as a digital twin where operators may try different scenarios in a safe environment before applying them to the physical well. To cover all aspects of the operation, the simulator should simulate surface equipment as well as a downhole environment. Numerical modeling techniques and hydraulic simulators are used to design the well response to operations. Different scenarios were established to cover most of the possible downhole problems and equipment malfunctions including electrical and hydraulic failures. The study compares a pre-determined set of KPIs common to three different types of simulation: well control, procedural and an integration of both. The target of the study is to collect the data resulting from the use of the simulator while it replicates a real-life situation. This virtual model of the rig and the well can be used to calibrate the main drilling parameters like SPM, RPM and WOB. The digital twin is also used to optimize operational procedures and improve performance and efficiency of rig crews as well as reduce their response time to possible problems. The results show an increase in performance when the knowledge of the rig is combined with the downhole feedback experience. This proves that training of the crew by reproducing their own equipment allows for a major jump in readiness and faster response with minimal mistakes. In addition, conducting the operation virtually allows the crew to uncover any possible issues before tackling the physical well. This in turn helps to reduce errors and safeguard both well and equipment integrity. This paper discusses the integration of the use of downhole environment behavior into a complete digital twin which will play an important role for providing a source of data for regular case studies concerning well control, Maintenance, Scheduling and other critical decisions. This new method candidates itself as a major contender for the future of simulation in the drilling business and shows the importance of that for reducing risks and errors.

Towards a Digital Twin for Cloud Manufacturing: Case Study

2018 ◽  
Author(s):  
Diane Ngo ◽  
David A. Guerra-Zubiaga ◽  
Germánico González-Badillo ◽  
Reza Vatankhah Barenji
Keyword(s):  
Real Life ◽  
Simulation Method ◽  
Cloud Manufacturing ◽  
Conveyor Belt ◽  
Life Change ◽  
Simulation Methods ◽  
Manufacturing Cell ◽  
Digital Twins ◽  
Resources And Capabilities

Cloud manufacturing (CMfg) is a new manufacturing paradigm designed to enable manufacturing enterprise to share their resources and capabilities. Prior to any real-life change in the system, for CMfg it is important to anticipate and optimize the response of the system through simulation. Digital Twins (DT) is a simulation method for this paradigm that is different from existing simulation methods in two ways. It is a virtual copy of the system containing all the components and can connect to the controller in real time. The goal of this work is to develop a DT for an educational manufacturing cell. The educational manufacturing cell is a FESTO Reconfigurable Mechatronics System (RMS). The cell has four stations that uses pallets to transport the product on the conveyor belt and assembles a part of the product. The Siemens Process Simulate: TECNOMATIX, was used to create the DT of the system. The system is modeled in a CAD program and then imported into TECNOMATIX Process Simulate, where it is programmed to replicate the processes.

scholarly journals Urban Digital Twins for Smart Cities and Citizens: The Case Study of Herrenberg, Germany

2020 ◽  
Vol 12 (6) ◽  
pp. 2307 ◽  
Author(s):  
Fabian Dembski ◽  
Uwe Wössner ◽  
Mike Letzgus ◽  
Michael Ruddat ◽  
Claudia Yamu
Keyword(s):  
General Public ◽  
Smart Cities ◽  
Flow Simulation ◽  
Urban Mobility ◽  
Communication Tool ◽  
Digital Twin ◽  
Collaborative Processes ◽  
Digital Twins ◽  
Collaboration And Communication

Cities are complex systems connected to economic, ecological, and demographic conditions and change. They are also characterized by diverging perceptions and interests of citizens and stakeholders. Thus, in the arena of urban planning, we are in need of approaches that are able to cope not only with urban complexity but also allow for participatory and collaborative processes to empower citizens. This to create democratic cities. Connected to the field of smart cities and citizens, we present in this paper, the prototype of an urban digital twin for the 30,000-people town of Herrenberg in Germany. Urban digital twins are sophisticated data models allowing for collaborative processes. The herein presented prototype comprises (1) a 3D model of the built environment, (2) a street network model using the theory and method of space syntax, (3) an urban mobility simulation, (4) a wind flow simulation, and (5) a number of empirical quantitative and qualitative data using volunteered geographic information (VGI). In addition, the urban digital twin was implemented in a visualization platform for virtual reality and was presented to the general public during diverse public participatory processes, as well as in the framework of the “Morgenstadt Werkstatt” (Tomorrow’s Cities Workshop). The results of a survey indicated that this method and technology could significantly aid in participatory and collaborative processes. Further understanding of how urban digital twins support urban planners, urban designers, and the general public as a collaboration and communication tool and for decision support allows us to be more intentional when creating smart cities and sustainable cities with the help of digital twins. We conclude the paper with a discussion of the presented results and further research directions.

scholarly journals When Digital Twin Meets Network Softwarization in the Industrial IoT: Real-Time Requirements Case Study

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8194
Author(s):  
Mehdi Kherbache ◽  
Moufida Maimour ◽  
Eric Rondeau
Keyword(s):  
Real Time ◽  
Industrial Systems ◽  
Digital Twin ◽  
Digital Twins ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Time Requirements ◽  
Loop Network ◽  
Sdn Controller

The Industrial Internet of Things (IIoT) is known to be a complex system because of its severe constraints as it controls critical applications. It is difficult to manage such networks and keep control of all the variables impacting their operation during their whole lifecycle. Meanwhile, Digital Twinning technology has been increasingly used to optimize the performances of industrial systems and has been ranked as one of the top ten most promising technological trends in the next decade. Many Digital Twins of industrial systems exist nowadays but only few are destined to networks. In this paper, we propose a holistic digital twinning architecture for the IIoT where the network is integrated along with the other industrial components of the system. To do so, the concept of Network Digital Twin is introduced. The main motivation is to permit a closed-loop network management across the whole network lifecycle, from the design to the service phase. Our architecture leverages the Software Defined Networking (SDN) paradigm as an expression of network softwarization. Mainly, the SDN controller allows for setting up the connection between each Digital Twin of the industrial system and its physical counterpart. We validate the feasibility of the proposed architecture in the process of choosing the most suitable communication mechanism that satisfies the real-time requirements of a Flexible Production System.

scholarly journals A Generic Asset Model for Implementing Product Digital Twins in Smart Remanufacturing

2021 ◽  
Author(s):  
Mairi Kerin ◽  
Duc Truong Pham ◽  
Jun Huang ◽  
Jeremy Hadall
Keyword(s):  
Real Time ◽  
Manufacturing Industry ◽  
Integrated System ◽  
Embedded Sensors ◽  
Functional Requirements ◽  
Digital Twin ◽  
Digital Twins ◽  
The Impact ◽  
The Internet Of Things

Abstract A digital twin is a “live” virtual replica of a sensorised component, product, process, human, or system. It accurately copies the entity being modelled by capturing information in real time or near real time from the entity through embedded sensors and the Internet-of-Things. Many applications of digital twins in manufacturing industry have been investigated. This article focuses on the development of product digital twins to reduce the impact of quantity, quality, and demand uncertainties in remanufacturing. Starting from issues specific to remanufacturing, the article derives the functional requirements for a product digital twin for remanufacturing and proposes a UML model of a generic asset to be remanufactured. The model has been demonstrated in a case study which highlights the need to translate existing knowledge and data into an integrated system to realise a product digital twin, capable of supporting remanufacturing process planning.

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.

scholarly journals Modelling for Digital Twins—Potential Role of Surrogate Models

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 476
Author(s):  
Ágnes Bárkányi ◽  
Tibor Chován ◽  
Sándor Németh ◽  
János Abonyi
Keyword(s):  
Model Building ◽  
Surrogate Models ◽  
Uncertain Information ◽  
Industrial Case Study ◽  
Continuous Processes ◽  
Digital Twin ◽  
Box Models ◽  
Digital Twins

The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin applications and to explore the fields where surrogate models can be utilised advantageously. In this sense, the paper discusses what types of surrogate models are suitable for different practical problems as well as introduces the appropriate techniques for building and using these models. A number of examples of digital twin applications from both continuous processes and discrete manufacturing are presented to underline the potentials of utilising surrogate models. The surrogate models and model-building methods are categorised according to the area of applications. The importance of keeping these models up to date through their whole model life cycle is also highlighted. An industrial case study is also presented to demonstrate the applicability of the concept.

scholarly journals Digital Twins: State-of-the-Art and Future Directions for Modeling and Simulation in Engineering Dynamics Applications

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
D. J. Wagg ◽  
K. Worden ◽  
R. J. Barthorpe ◽  
P. Gardner
Keyword(s):  
Asset Management ◽  
State Of The Art ◽  
Industrial Applications ◽  
Transport Systems ◽  
Synthesis Process ◽  
Small Scale ◽  
Mathematical Framework ◽  
Digital Twin ◽  
Digital Twins

Abstract This paper presents a review of the state of the art for digital twins in the application domain of engineering dynamics. The focus on applications in dynamics is because: (i) they offer some of the most challenging aspects of creating an effective digital twin, and (ii) they are relevant to important industrial applications such as energy generation and transport systems. The history of the digital twin is discussed first, along with a review of the associated literature; the process of synthesizing a digital twin is then considered, including definition of the aims and objectives of the digital twin. An example of the asset management phase for a wind turbine is included in order to demonstrate how the synthesis process might be applied in practice. In order to illustrate modeling issues arising in the construction of a digital twin, a detailed case study is presented, based on a physical twin, which is a small-scale three-story structure. This case study shows the progression toward a digital twin highlighting key processes including system identification, data-augmented modeling, and verification and validation. Finally, a discussion of some open research problems and technological challenges is given, including workflow, joints, uncertainty management, and the quantification of trust. In a companion paper, as part of this special issue, a mathematical framework for digital twin applications is developed, and together the authors believe this represents a firm framework for developing digital twin applications in the area of engineering dynamics.

scholarly journals A digital twin framework for improving energy efficiency and occupant comfort in public and commercial buildings

2021 ◽  
Vol 4 (S2) ◽  
Author(s):  
Anders Clausen ◽  
Krzysztof Arendt ◽  
Aslak Johansen ◽  
Fisayo Caleb Sangogboye ◽  
Mikkel Baun Kjærgaard ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Controlled Environment ◽  
Building Automation ◽  
Digital Twin ◽  
Digital Twins ◽  
Occupant Comfort

AbstractModel Predictive Control (MPC) can be used in the context of building automation to improve energy efficiency and occupant comfort.Ideally, the MPC algorithm should consider current- and planned usage of the controlled environment along with initial state and weather forecast to plan for optimal comfort and energy efficiency.This implies the need for an MPC application which 1) considers multiple objectives, 2) can draw on multiple data sources, and 3) provides an approach to effectively integrate against heterogeneous building automation systems to make the approach reusable across different installations.To this end, this paper presents a design and implementation of a framework for digital twins for buildings in which the controlled environments are represented as digital entities. In this framework, digital twins constitute parametrized models which are integrated into a generic control algorithm that uses data on weather forecasts, current- and planned occupancy as well as the current state of the controlled environment to perform MPC. This data is accessed through a generic data layer to enable uniform data access. This enables the framework to switch seamlessly between simulation and real-life applications and reduces the barrier towards reusing the application in a different control environment.We demonstrate an application of the digital twin framework on a case study at the University of Southern Denmark where a digital twin has been used to control heating and ventilation.From the case study, we observe that we can switch from rule-based control to model predictive control with no immediate adverse effects towards comfort or energy consumption. We also identify the potential for an increase in energy efficiency, as well as introduce the possibility of planning energy consumption against local electricity production or market conditions, while maintaining occupant comfort.

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