AU2021105076A4 - Machine learning based Digital Twin Architecture Model and Communication Interfaces for Cloud based Cyber Physical Systems for Industry 4.0 - Google Patents
Machine learning based Digital Twin Architecture Model and Communication Interfaces for Cloud based Cyber Physical Systems for Industry 4.0 Download PDFInfo
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- 238000010801 machine learning Methods 0.000 title abstract description 4
- 238000004519 manufacturing process Methods 0.000 claims abstract description 25
- 238000005516 engineering process Methods 0.000 claims abstract description 10
- 230000006399 behavior Effects 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 5
- 238000004088 simulation Methods 0.000 claims description 5
- 238000012552 review Methods 0.000 claims description 4
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
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- G06N5/00—Computing arrangements using knowledge-based models
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- H—ELECTRICITY
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- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
Machine learning based Digital Twin Architecture Model and
Communication Interfaces for Cloud based Cyber Physical Systems for
Industry 4.0
ABSTRACT
Industry 4.0 pertains to technological developments which integrate the mechanical,
virtual, and biological realms, affecting all specializations, world economy, and
industrial sectors." These innovations have the capability to integrate billions more
individuals to the internet while also vastly maximizing the productivity of
businesses and organizations. The advancement in manufacturing and data
technology enabled by the internet of things (IoT), the cloud, intelligent machines,
robots, and humans. The streamlined incorporation of software, machinery, and
resources that improves the speed, efficiency, and distribution of knowledge among
all a vendor's processes. An essential criterion for industry 4.0 is cyber-physical
convergence, which is being rapidly promoted by vendors. Cyber-physical systems
(CPS) and digital twins (DTs) have obtained a broad recognition from industry
professionals and specialists. CPS and DTs can improve the performance, durability,
and knowledge of manufacturing technologies by incorporating reinforcement
mechanisms wherein tangible operations impact cyber components and conversely.
The fundamental principles of an integrated cyber-physical connectivity, real-time
collaboration, organizational incorporation, and in-depth cooperation are articulated
by CPS and DTs. CPS and DTs, on the other hand, are not similar in several ways,
such as its source, creation, technical processes, cyber-physical modeling, and
essential components. In attempt to illustrate the discrepancies and correlations
among these this innovation examines and compares CPS and DTs from various
standpoints.
1
Description
Machine learning based Digital Twin Architecture Model and Communication Interfaces for Cloud based Cyber Physical Systems for Industry 4.0
Description
Field of the Invention:
In an inevitable way, smart manufacturing has happened. To ensure cyber-physical connection and convergence in production, it is crucial to use CPS and DTs. Concerning these two new developments, in addition, they are not comparable. This invention examines the relationship and contrast of DTs and CPS. CPS and DTs are studied and analyzed from many perspectives, with specific focus on their fluctuation and association. However, CPS and DTs have distinct points of view, allowing for a better comprehension of CPS and DTs.
Background of the Invention:
With rapid advances in emerging technology, the industrial sector is confronting cyber obstacles against a backdrop of digital revolution. In this sense, innovative technological approaches including the Industrial Internet, Industry 4.0, and China's accompanying intervention have been launched. The objective of these techniques is to pursue technological advances, also regarded as industrial automation. A systematic review though, shows a distinction among the principles of sophisticated manufacturing and smart technology.
Cyber Physical System are multilayered and adaptive networks which combine the cyber and physical worlds. Cyber Physical System provides real-time perception, input feedback, dynamic control as well as other facilities by integrating and collaborating on computation, networking, and control, also known as the "3C." Another term correlated with cyber-physical incorporation is the DT. A DT produces high simulated representations of physical structures in virtual environment in addition to replicate and offer data on their real-world actions. A DT is an example of a bi-directional adaptive mapping procedure it dissolves obstacles in the production process and offers a full internet presence of commodities. Therefore, DTs allow businesses to forecast and diagnose physical problems more effectively and earlier, simplify manufacturing operations, and deliver healthier goods.
Combined RFID with agent technologies to allow intelligent machines to compromise manufacturing process data explicitly with manufacturing equipment. Fortunately, minimal consideration has been paid to the pairing interactionbetween cyber and physical spaces, and these findings were still to use the gathered data to continuously improve device efficiency.
CPS were developed because of the widespread use of embedded devices; their origins can be attributed away to 2006. Cyber Physical System were later identified as a high demand topic for scientific funding in the United States. Cyber Physical System are regarded as the heart and base of Industry 4.0 in Germany. There is no question that Cyber Physical System will have significant socioeconomic advantages and can radically alter current manufacturing processes.
Even so, modem Cyber Physical System literature emphasizes mostly on descriptions of the philosophy, design, technology, and problems, whereas examples of CPS in experience in the industry remain in their adolescence. Cyber Physical System are often more fundamental than embedded systems, IoT, sensors, as well as other developments because they do not explicitly influence deployment techniques or specific implementations. As a result, Cyber Physical System are much more comparable to a science classification than a technological class, as suggested by the NSF declaration that the Cyber Physical System research initiative seeks modem research principles and innovations.
A distributed system architecture is proposed with numerous expert systems who cooperate on resources and employment, increasing output productivity.
Promoted a real-time output management and decision making in industrial automation and suggested a data-driven deterministic manufacturing design methodology. Implemented an agent-based decentralized development system that can respond to a changing world, and they used intelligent devices to wirelessly control factory floor equipment and render appropriate decisions.
Now, developments in modem IT are allowing the expansion of Digital Twins. Digital Twins have considered a common subject of research because they provide a novel approach to synchronize physical movements with the digital reality. Digital Twins have currently been used in a variety of sectors for activities such as product development, manufacturing line layout, DT shop floors, manufacturing process automation, and diagnosis and healthcare. Digital Twin industrial activities can also be seen in several major corporations, including Siemens, General Electric, PTC, Tesla and Dassault Systems which leverage Digital Twins to improve production efficiency, production stability, and productivity.
The deployment of MCPS necessitates exposure to a vast number of sensors, actuators, equipment, and other industrial equipment instruments configured with integrated computing processors capable of interacting with one another and developing a cohesive highly integrated network. Increased accessibility of these infrastructure facilities would provide significant opportunities for improved operation of individualized production service networks. The cornerstone of the digital twin concept is modeling and smooth data migration from one life cycle process to the next. From the standpoint of device lifecycle management, combining all cyber-physical data resources into a comprehensive management platform will support different digital twin structures for evaluating background data and implementing virtual automation, including such industrial process reliability.
The term "digital twin vision" corresponds to a detailed physical and operational representation of an element, device, or device, which contains nearly all details that may be valuable in the present and ensuing lifecycle processes.
According to the virtual twinning means the formation of relationships amongst physical systems and their virtual models which facilitates the productive performance of product design, production, maintenance, and other operations during the material existence.
Objective of the Invention:
In other words, we are focused on two things: helping companies correlate and compare Digital Twins and Cyber-Physical Systems in order to help businesses use Smart Manufacturing and Industry 4.0.
CPS Data Twins in smart manufacturing is the second of the company's objectives.
Summary of the Invention:
The purpose of CPS is to use simulation and connection to add groundbreaking functionality to physical characteristics. CPS' real-time monitoring, dynamic control, and information services are delivered through efficient automation of the 3C.Whereas DTs concentrate on the cyber world's efficient computation and networking abilities, CPS puts a higher focus on the cyber world's more efficient and accurate computation and networking. When experienced architects propose new CPS designs, they almost always depend on controls rather than synchronized versions.
Feedback loops are essential in CPS, just as they are in DTs. CPS processes are enabled by mutual networking, real-time connectivity, and effective communication across the cyber and physical realms. The analytical method on the other hand, can influence more than one physical entity. A device, for example, can have many sensory perceptions. As a result, the mapping interaction between both the virtual and tangible domains of CPS is a one-to-many communications or perhaps a one-to one communication.
The goal of Digital Twins is to provide a complete representation of an element, device, or machine, both physically and functionally. It is a milestone for the project because its physically realistic virtual models can replicate anything found in the actual world.These computer simulations are not only geometrically and structurally compatible with the physical components, but they can also emulate their spatiotemporal position, actions, features, and more. In most other phrases, the computer prototypes and real beings have the similar look, as if they were twins, and the identical actions, as if they were mirror images.
Simulations in the digital realm allow processes to be optimised, while physical processes may be altered with reviews. The simultaneous co-evolution of real events and virtual models occurs via hierarchical bi-directional mapping.As a result, the mapping collaboration among a DT's real and digital domains is a one to-one interaction. A computational design describes a complex physical entity by integrating geometry, configuration, actions, laws, and sensory attributes.
Detailed Description of the Invention:
These tools include human, mechanical, and material tools that are often known as the physical environment. Industrial activities are performed using these physical services. To sum up, the cyber/digital component, which covers a broad variety of ubiquitous applications and services including smart data processing, automation, and computational technologies, comprises everything from smart data processing to computational technologies. Industrial players are empowered by having a myriad of services and software tools that enable them to enhance their performance. In the physical world, information is collected and analysed, and the final conclusions are derived from that analysis. In the cyber/digital world, the data analysis and evaluation occur before choices are made.
Demonstrated digital physical systems and Digital Twins demonstrate how to achieve industrial automation by generating a dynamic loop between the digital/cyber and physical realms focused on determining an object's current status, monitoring the system in real time, using data to make scientific decisions, and executing tasks accurately. In Cyber Physical System projects, virtual modelling may supplement the setup and operations of Cyber Physical System, while Digital Twins serves as a crucial groundwork for creating Cyber Physical System and laying the foundation for Cyber Physical System implementation. By merging Cyber Physical Systems (CPS) with Digital Twins, manufacturers may complete their projects more accurately, at a lower cost, and with better results.
The Cyber Physical System which incorporates 3C technology to provide accurate control remote communication, automated administration, and other applications to physical operations. Cyber Physical System are inextricably linked to physical systems. Data is the source of knowledge Sensors and actuators are used to communicate with the real life for information sharing, that is the most critical aspect of Cyber Physical System, since they oversee interpreting situations from physical devices and the atmosphere and implementing control instructions. To allow connectivity among the cyber and physical worlds, numerous sensors deployed on physical equipment and in the environment are used, as well as large, deployed data processing and system identifications.
Promotes the models that incorporates the layout, form, mechanical characteristics, laws, operation, and allows the automation and simulation of the development mechanism and operation. When used in conjunction with information processing, a DT allows producers to make more precise forecasts, sound decisions, and balanced output. The models act as a coordination and tracking tool, assisting in the interpretation of computer or device actions and predicting their future outcome dependent on real observations historical information, practice, and information, and relevant information from simulations.
The crucial factor behind a DT is to construct a digital version of sensory perceptions in effect to emulate and represent their conditions and behaviors via modelling and prediction evaluation, as well as to forecast and monitor their potential flows and behaviors via reviews. Since the state, actions, and resources of the real environment evolve continuously, all types of data are continually generated, employed, and processed from the time a commodity is created unless it is discarded. To improve continuity the DT combines whole components, the entire enterprise, and process knowledge.
Machine learning based Digital Twin Architecture Model and Communication Interfaces for Cloud based Cyber Physical Systems for Industry 4.0
1. Digital Twins and Cyber-Physical Systems toward Smart Manufacturing and Industry 4.0 comprising: One or more sensors, RFIDs and embedded devices which is used to sense the different values of one or more parameters of the manufacturing devices. A computer processor is used to acquire the information from one or sensors. A communication device connected to the computer processor for transmitting data related to an outcome obtained by the processor. A computational model depicts a complex physical entity by integrating geometry, configuration, behaviour, rules, and operational resources.
2. According to claim, both CPS and DTs in industrial manufacturing consists of two components: the physical and the cyber/digital component.
3. Based on claim 2, the objective of Cyber Physical System is to apply unique innovations to physical structures through computing and connectivity, which communicate with physical mechanisms vigorously. CPS incorporate 3C incorporation to offer real-time monitoring, dynamic control, and data processing for complicated systems.
Claims (1)
- CPS relies heavily on feedback loops. CPS functions are enabled by collaborative mapping, real-time connectivity, and effective communication among the cyber and physical environments. 4. According to claim 3, Digital Twin's key concept is to construct a simulated version of sensory perceptions in order to manage and represent their states and behaviour by modelling and simulation review, as well as to determine and monitor their possible states and behaviours via feedback. 5. Function deployment of Cyber Physical System and Digital Twin, sensors, and actuators allow data and control sharing among the physical and cyber environments. Models, on the other hand, perform a significant role in a Digital Twin and enables demonstrate and simulating the behaviour of the physical environment based on different observations. Thus, sensors and actuators are the essential principles of a CPS, whereas models and data are the major components of a DT. 6. Cyber Physical System and Digital Twins can improve the functionality of production processes by providing integrated technologies that aid in the integration of innovative manufacturing.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114918976A (en) * | 2022-06-16 | 2022-08-19 | 慧之安信息技术股份有限公司 | Joint robot health state assessment method based on digital twinning technology |
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2021
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114918976A (en) * | 2022-06-16 | 2022-08-19 | 慧之安信息技术股份有限公司 | Joint robot health state assessment method based on digital twinning technology |
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