Ontology-Driven Guidelines for Architecting Digital Twins in Factory Automation Applications
Abstract
:1. Introduction
- Conducting research for analyzing the techniques and the technologies that are adapted for developing and building digital twins using academic and commercial solutions as information sources.
- Reusing the available standards and techniques in manufacturing, computer science and industrial management domains for reshaping a generic paradigm for DTs.
- Presenting a guideline or paradigm for architecting a digital twin.
- Presenting an implementation example for architecture.
2. Digital Twins: Literature and Commercial Solutions Review
2.1. Literature Review on Designing and Developing Digital Twins
2.2. Commercial Solutions for Building Digital Twins
2.3. Review on Digital Twins Standards
3. Generic Paradigm for Architecting Digital Twins
3.1. Multi-Layer Concept
3.2. Multi-Level Concept
3.3. Multi-Perspective Concept
- Modularity: is the ability to build the DT using defined and interchangeable modules. These modules contribute to the flexibility of the overall system. In the context of the generic paradigm, the 9-block approach allows the developer to interchange the blocks based on the need of the application.
- Scalability: is the ability to grow the system in terms of resources and features. This quality is presented in the possibility of adding several perspectives to the digital twin in order to increase its capabilities.
- Reusability: is the ability to reuse legacy or existing assets in building newer versions. In this regard, the 9-block approach allows the user to reuse previously-developed blocks in newer versions of the DT.
- Interoperability: is the ability to work and to be compatible with other components or systems regardless of the vendor or the developer. For the 9-block approach, the use of standards and protocols permits such quality where different systems and applications can communicate easily.
- Composability: it is the ability to reassemble and reconstruct a system from other systems and components. In the context of this research, the 9-block architecture allows the development of a system of digital twins where the DT Level 0 includes the physics that each DT uses. Then, by connecting each Level 0 using spatial computing concepts, these DTs can form a system of digital twins.
4. The Approach of Architecting the Digital Twin
5. Use Case Example
5.1. FASTory Use Case
5.2. Function Block-Based Digital Twin Architecture
6. Discussion
7. Conclusions and Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Vendor | Brief Description |
---|---|
General Electric [36] | General Electric (GE) targets the concept of DT based on the application area. According to [37], Dr. Colin Parris presents the interest of GE in three main areas: assets, network and process. For each area, GE provides a set of applications in order to form and build the digital twin. As an example, for the Assets Digital Twin, GE employs the Assets Performance Management and for the Network digital twin, the applications named ADMS and GIS are employed. |
IBM Digital Twin Exchange [38] | IBM provides an open marketplace for asset owners and end users to exchange assets and build digital twins based on shared data. In this regard, the platform is open for anyone to introduce models and data to purchase or use. |
PTC Digital Twin [39] | Like IBM, PTC provides the customer with a marketplace that contains more than 130 tools. These tools can be utilized for building DTs. In addition, PTC provides guidance and development kits for building new tools that specifically suit their customers. Regarding the application domain, PTC considers DT to be beneficial in five key sectors. These sectors include: Corporate/CXO, Product Engineering, Sales and Marketing, Manufacturing Operations, and Customer and Technician Services [40]. |
Microsoft Azure Digital Twin [41] | Azure is a cloud-based platform from Microsoft. It is marketed as an IoT cloud platform for data acquisitions, modeling and estimation. According to the [42,43], the Azure DT allows the customer to build a virtual model based on the IoT data. Afterwards, these models are connected with each other to form the DT. |
Ansys Twin Builder [44] | Ansys is a corporation specializing in developing simulation tools for various industries and business sectors. According to [45,46], Ansys Twin Builder exploits predefined modules for building DTs. In addition, it allows integration with third-party applications such as Azure for data collection and modeling purposes. |
SAP SE [47] | The solution provided by SAP mainly addresses the resources, products and assets. This solution is marketed as a network of digital twins as described in the white paper [48]. It can provide simulation and real-time estimation of products during the lifecycle. In addition, it provides a modifiable interface for flexible interaction with the end user. |
Oracle [49] | Oracle’s DT is based on an IoT platform that permits data and information interconnectivity. According to Oracle, the implementation of a DT includes three main pillars. These pillars include Virtual Twins where devices are emulated, Predictive Twins where the data is analyzed, and Twin Projections where whole systems are simulated based on the analysis that is created by the Predictive Twins. |
Bosch GMBH [50] | Bosch is specialized in developing a building Digital Twin that consumes IoT data from sensors that are scattered in buildings using Bosch devices. According to Bosch, the Digital Twin is built using the Microsoft Azure IoT platform, and it employs the semantic technology for knowledge reasoning. |
Emerson [51] | The Digital Twin provided by Emerson holds features such as an automation system, vendor independence, selective fidelity, open architecture, and cloud ready [52]. In fact, the DT is utilized in safety, training, Knowledge transfer, environmental, regularity, and optimization applications. |
ABB [53] | ABB provides several solutions that form digital twins based on the end user needs. In this regard, ABB supports the customers with DTs for the design, system integration, diagnosis, and prediction activities and applications. For example, the virtual commissioning DT for discrete manufacturing, virtual drive tuning DT, and the predictive maintenance DT for vessels. |
MATLAB/ Simulink [54] | Even though they are known to be a programming language and/or a tool for mathematicians and engineering, MATLAB and Simulink are capable of providing virtual representation on a physical system for the purpose of testing. This is evident in [55] as there are two main methods reported for building a digital twin. The first method employs a data-driven approach exploiting the deep learning tools in MATLAB. The second method involves a Simulink block network. The latter is known as a physics-based approach. |
COMSOL Multiphysics® [56] | Like MATLAB, COMSOL Multiphysics is a multi-disciplinary simulation platform. This platform utilizes mathematical models of the physical systems for the simulation process. The models are flexibly added as an add-on where the user decides what is needed for the application and domain. In addition, the platform provides a very useful interface including visualization of the components based on the simulation parameters. |
NVIDIA Omniverse™ Enterprise [57] | Omniverse is a state-of-the-art platform that allows developers and designers to build and simulate systems with a high level of realism [58]. The platform is based on Pixar’s Universal Scene Description and it uses the NVIDIA RTX™ technology. The Omniverse platform includes five key elements: Nucleus is the database and collaboration engine, Connect is the data connections plugins engine, Kit is the Software Development Kit (SDK), Simulation is a set of realistic models that allows the user to select or create, and finally, RTX Renderer creates the high realistic simulations for users and developers. |
Visual Components [59] | Visual Components offers 3D manufacturing simulation tools for the manufacturing domain. These tools offer several functionalities such as factory layout configuration, process modeling, statistical analysis, shopfloor connectivity, and robotics simulation among other features. In fact, Visual Component also provides compatible adapters that can work with the omniverse of NVIDIA. |
Tecnomatix® by Siemens [60] | Tecnomatix is an industry-driven digital twin for manufacturing applications by Siemens. The solution provides features such as virtual commissioning, human-centered design and planning, plant simulation, robotics programming, statistical analysis, planning and processes optimization, assembly simulation, and shopfloor and layout configuration. This digital twin can be customized and scaled thanks to its development environment. |
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Mohammed, W.M.; Haber, R.E.; Martinez Lastra, J.L. Ontology-Driven Guidelines for Architecting Digital Twins in Factory Automation Applications. Machines 2022, 10, 861. https://doi.org/10.3390/machines10100861
Mohammed WM, Haber RE, Martinez Lastra JL. Ontology-Driven Guidelines for Architecting Digital Twins in Factory Automation Applications. Machines. 2022; 10(10):861. https://doi.org/10.3390/machines10100861
Chicago/Turabian StyleMohammed, Wael M., Rodolfo E. Haber, and Jose L. Martinez Lastra. 2022. "Ontology-Driven Guidelines for Architecting Digital Twins in Factory Automation Applications" Machines 10, no. 10: 861. https://doi.org/10.3390/machines10100861