CN111932395A

CN111932395A - Manufacturing digital system based on hybrid cloud architecture

Info

Publication number: CN111932395A
Application number: CN202010804428.7A
Authority: CN
Inventors: 毕得
Original assignee: Tsinghua University
Current assignee: Tsinghua University
Priority date: 2020-08-11
Filing date: 2020-08-11
Publication date: 2020-11-13

Abstract

The present disclosure provides a manufacturing digital system based on a hybrid cloud architecture, comprising: the data source acquisition module is used for acquiring data information of a manufacturing factory; the network module is used for transmitting the data information acquired by the data source acquisition module; the hybrid cloud database module comprises a private cloud submodule and a public cloud submodule and is used for storing the data information; the application module comprises a private cloud application submodule and a public cloud application submodule, wherein the private cloud application submodule is used for acquiring data in the private cloud submodule to perform application layer operation; the public cloud application submodule is used for acquiring data in the public cloud submodule to perform application layer operation; and the access system module is used for accessing a specific service scene. The present disclosure provides an elastic and tailorable digital architecture construction scheme, which flexibly implements enterprise digital applications through a hybrid cloud architecture.

Description

Manufacturing digital system based on hybrid cloud architecture

Technical Field

The disclosure relates to the field of industrial internet, in particular to a manufacturing industry digital system based on a hybrid cloud architecture.

Background

International manufacturing is moving toward industry 4.0, and various countries are energetically pushing industrial intelligence and the industrial internet. Facing the international environment of remodeling manufacturing industry and manufacturing industry reflux in developed countries, the manufacturing industry in China is transformed into quality improvement with quality, efficiency and benefit, and a digital system with robust functions is an important supporting force of manufacturing industry enterprises advancing to industry 4.0.

A large number of modeling enterprises in China, particularly small and medium-sized enterprises, face some common difficulties and pain points in advancing to digitization and intellectualization.

(1) The existing IT framework of single machine application and local application in departments has the problem of information isolated island, is difficult to adapt to the rapid change and the demand of the market, can not meet the requirements of intelligent factories and transparent factories of comprehensive perception, transparent operation and real-time decision-making, and can not support the realization of industrial 4.0.

(2) The enterprise digital construction lacks clear planning and design, informatization and digital products are scattered, a unified framework and platform are lacked, and various development constraints such as construction disorder, operation and maintenance difficulty, upgrading iteration difficulty, development difficulty and the like exist.

(3) A large number of enterprises lack special informatization departments, are insufficient in digitalization and intellectualization, and often face the problems and pain points of personnel mobility.

(4) The enterprise has more and more digital tools and products, is fast to update and eliminate, and is more and more complex and difficult to operate and maintain.

(5) A large number of digitalized and informationized systems built by enterprises aim at business processes more, not all-round coverage of each production element of the enterprises is realized, data is taken as a new production element in the world in a new period, the data plays an important driving role in the production, manufacturing and operation of the enterprises, but most of the enterprises in China do not start, and the data is not effectively organized and applied.

Disclosure of Invention

Technical problem to be solved

The present disclosure provides a manufacturing digitization system based on a hybrid cloud architecture to at least partially address the above-identified problems.

(II) technical scheme

According to one aspect of the present disclosure, there is provided a manufacturing digitization system based on a hybrid cloud architecture, comprising:

the data source acquisition module is used for acquiring data information of a manufacturing factory;

the network module is used for transmitting the data information acquired by the data source acquisition module;

the hybrid cloud database module comprises a private cloud submodule and a public cloud submodule and is used for storing the data information;

the application module comprises a private cloud application submodule and a public cloud application submodule, wherein the private cloud application submodule is used for acquiring data in the private cloud submodule to perform application layer operation; the public cloud application submodule is used for acquiring data in the public cloud submodule to perform application layer operation; and

and the access system module is used for accessing the data information operated by the application module into a specific service scene.

According to the embodiment of the disclosure, the private cloud submodule constructs a private cloud underlying environment based on OpenStack, Kubernets and Docker.

According to an embodiment of the disclosure, the private cloud application submodule includes:

the workshop informatization system comprises at least one of MES, WMS and WCS deployed in a private cloud, and is connected with a real-time database and a distributed storage database; and

and the data storage unit is used for carrying out distributed storage on the data information.

According to the embodiment of the disclosure, the data storage unit comprises at least one of Kafka, MySQL, MongoDB and Hadoop, and elastic deployment is performed based on a cloud-native architecture.

According to the embodiment of the disclosure, the public cloud submodule adopts an AWS public cloud.

According to an embodiment of the present disclosure, the public cloud application submodule includes:

the operation informatization system comprises at least one of ERP, CRM and CAD;

the data lake is used as a data warehouse for carrying out big data processing, interactive query, operation analysis and data exchange, and realizing visualization and real-time analysis; and

e-commerce services and financial services.

According to an embodiment of the present disclosure, the data source acquisition module is used for data in the aspects of underlying sensors, automation equipment, process flows, production operations, marketing, and supply chains.

According to an embodiment of the present disclosure, a network module includes:

the Ethernet sub-module comprises an Ethernet and an industrial Internet;

a wireless network sub-module comprising at least one of a 5G, RFID and a WiFi module;

the Internet of things submodule, and

and the communication protocol sub-module comprises at least one of Profinet, Modbus, Ethercat, OPC UA, TCP/IP and QTT protocols.

According to an embodiment of the present disclosure, an access system includes: the system comprises a DaaS submodule, a BaaS submodule and a factory production resource-as-a-service submodule.

According to the embodiment of the disclosure, the digital equipment is elastically accessed to the cloud platform and is used for cloud services in the aspects of data query, visual interaction, predictive maintenance, test and debugging.

(III) advantageous effects

From the technical scheme, the manufacturing digital system based on the hybrid cloud architecture has at least one of the following advantages:

(1) the manufacturing industry digital system based on the hybrid cloud architecture has the characteristics of high digitization, informatization, system updating speed and frequent iteration, and is a digital system which can be light in weight, easy to expand and telescopic.

(2) The system effectively supports the manufacturing enterprises to respond to the customer demands quickly, produce in a customized manner, execute accurately, make lean and provide product services in the whole life cycle; supporting flexible manufacturing, realization of cooperative manufacturing and landing; and the realization of intelligent factory construction and intelligent manufacturing of manufacturing enterprises is supported.

(3) Software and hardware resources of an enterprise are fully decoupled, IT resources of the enterprise are fully utilized, and the risk that a digital system of the enterprise is increasingly bloated is reduced; the method realizes the opening of all elements, all processes and life cycles of enterprise data, and eliminates data islands to a great extent; the development and application of data values of enterprises are promoted, and the data assets of the enterprises are accelerated; and the large data processing and analysis with low threshold and flexibility are realized, and the enterprise insight and decision making supply are optimized.

Drawings

FIG. 1 is a block diagram of a hybrid cloud architecture based manufacturing digitizing system according to an embodiment of the present disclosure.

Detailed Description

The digital degree of manufacturing enterprises in China is very different, aiming at enterprises with different sizes and capacities, the elastic and tailorable digital architecture construction scheme is provided, IaaS (infrastructure as a service) and PaaS (platform as a service) of the enterprises are flexibly constructed by mixing clouds, the digital application of the enterprises is flexibly realized, the business requirements of the enterprises are supported, and the bottom equipment and the business process of the enterprises are opened.

For the purpose of promoting a better understanding of the objects, aspects and advantages of the disclosure, reference should be made to the following detailed description taken in conjunction with the accompanying drawings.

Certain embodiments of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the disclosure are shown. Indeed, various embodiments of the disclosure may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements.

As the development of manufacturing enterprises depends on data value discovery more and more, data and knowledge are precipitated to private clouds and public clouds through a mixed cloud architecture, and the conversion of the data to business value is realized through the application of lower knowledge thresholds such as data lakes, data analysis and mining, AI computing frames and the like provided by the public clouds. Meanwhile, new skills such as big data, AI, block chains, 5G and the like can be quickly docked, integrated and applied, and the new skills are combined with the requirements, pain points and upgrading development of factories and businesses of enterprises. The latest achievements and technologies of the digital science and technology are quickly applied to the production and management of enterprises, specific products are developed, scene application is formed, and productivity is formed.

In one exemplary embodiment of the present disclosure, a hybrid cloud architecture based manufacturing digitizing system is provided.

FIG. 1 is a block diagram of a hybrid cloud architecture based manufacturing digitizing system according to an embodiment of the present disclosure. As shown in fig. 1, the manufacturing digitization system based on a hybrid cloud architecture of the present disclosure comprises: the system comprises a data source acquisition module, a network module, a hybrid cloud database module, an application module and an access system module.

The following describes the details of the parts of the manufacturing digitizing system based on the hybrid cloud architecture.

The data source acquisition module is used for acquiring manufacturing factory data, and acquiring data of various aspects such as bottom layer sensors, automated equipment, process flows, production operation, marketing, supply chains and the like, for example, the data includes sensor data, equipment parameters, process flow data, operation data, research and development data, market data, financial data, employee behavior data and knowledge data.

The network module is used for transmitting the data information acquired by the data source acquisition module. The network module comprises an Ethernet submodule, a wireless network submodule, an Internet of things submodule and a communication protocol submodule. The Ethernet submodule comprises Ethernet, industrial Internet and the like, the wireless network submodule comprises 5G, RFID, WiFi and the like, and the communication protocol submodule uses Profinet/MOBbus/Ethercat, OPC UA, TCP/IP, MQTT protocols and the like to build a safe, reliable and high-speed network system. In some embodiments, the network module further comprises a blockchain network sub-module.

The 5G communication module in the wireless network sub-module deploys 5G communication in steps, layering times and sub-modules to factories, workshops, services and processes, is applied to a factory control system, multi-interconnection equipment cooperation, AGV mobile equipment control, supply chain management and real-time remote control of a production process, can simplify and optimize network wiring, facilitates movement and access of equipment, and facilitates data acquisition and transmission.

After the collection and transmission of enterprise production data and operation data are realized, the data are stored in a real-time database, namely a hybrid cloud database module, which comprises a private cloud distributed storage database and a public cloud end database.

The hybrid cloud database module comprises a private cloud submodule and a public cloud submodule. The private cloud sub-module constructs a private cloud bottom environment based on OpenStack, Kubernetes and Docker, and the public cloud sub-module adopts AWS public cloud. Through the cooperative interaction of the private cloud and the public cloud, data, services, enterprise resources and application programs are seamlessly connected and communicated, the integration and communication of the manufacturing enterprise subsystems are realized, and the IT resources of the enterprises are effectively mastered, effectively supervised and optimized in application.

In the private cloud submodule, based on Kubernets and Dockers, software and hardware decoupling of an enterprise digital system is further accelerated, development of application and micro-service is flexibly realized, and application is more flexibly configured and managed. The resources such as technology, knowledge, experience and the like are solidified into the industrial micro-service component library which can be transplanted and reused, and the universal micro-service and the module are provided.

The hybrid cloud database module realizes the butt joint and storage of bottom data, private clouds and public clouds, and realizes the vertical access from the inside of enterprises such as bottom sensors, automation equipment, process flows, production operation, marketing and supply chains and the horizontal access from the outside of the enterprises. The comprehensive management and the sufficient flow of data are realized through the hybrid cloud database module, and the high-efficiency coupling between the APP and the service is realized.

The application modules comprise a private cloud application sub-module and a public cloud application sub-module. The private cloud application submodule is used for acquiring data in the private cloud submodule to perform application layer operation. Specifically, the private cloud application submodule comprises a workshop informatization system and a data storage unit. Specifically, the workshop manufacturing management system comprises a MES, a WMS and a WCS which are deployed in a private cloud, and are connected with a real-time database and a distributed storage database. The data storage unit is used for performing distributed storage on big data from a sensor, an equipment terminal, a supply process and a service system, and is easy for knowledge precipitation and knowledge application and development. And the Kafka, MySQL, MongoDB, Hadoop and other cloud-native-based architectures in the data storage unit change the application of the monomers and perform elastic deployment. Most of tool types can use open source tools, development flexibility is improved, and cost is effectively controlled.

And the public cloud application submodule is used for acquiring data in the public cloud submodule to perform application layer operation. Specifically, the public cloud application submodule comprises an operation informatization system, a data lake and B2B e-commerce service and financial service deployed in a public cloud. The business informatization system comprises ERP, CRM, CAD and the like, and the application modules can be set according to actual needs.

Wherein the data lake may be included in a digitizing device. The digitalized equipment can be flexibly applied to resource and application modules in the hybrid cloud platform, elastic access is achieved, and remote operation and maintenance are conducted. And the digital equipment is connected to a cloud platform to realize cloud services such as data query, visual interaction, predictive maintenance, test and debugging and the like.

Compared with complex operation processes of data mining and analysis of a Hadoop system in a private cloud application module, in order to simplify application and value presentation of data, operations such as data warehouse, big data processing, interactive query, operation analysis, data exchange, visualization, real-time analysis and the like can be realized through a data lake of an AWS public cloud, the operation threshold of data analysis and application is reduced, and the method has operability and adaptability for large-scale enterprises and small and medium-sized enterprises. The application module realizes the efficient cooperation and utilization of resources inside and outside the enterprise, and realizes the intellectualization of value chains such as research and development, manufacture, operation maintenance, service and the like.

The access system module is used for accessing a specific service scene and comprises a DaaS submodule, a BaaS submodule and a factory production resource-as-a-service submodule. The access system module is easy to expand, can flexibly butt-joint AI, a block chain system and products to form DaaS (data as a service) and BaaS (block chain as a service), combines the data assets of an enterprise with the business scene, business requirements and pain points of a manufacturing enterprise, and converts the data assets into the productivity of the enterprise.

The BaaS submodule is used for accessing a block chain system, increasing the transparency and the credibility of data by utilizing components such as intelligent contracts, encryption algorithms and the like in a block chain and the characteristics of data which cannot be tampered, increasing the safe and credible sharing and flowing of data inside an enterprise, activating the data assets of the enterprise, and providing a credible environment and service for generating value for application data.

And the factory production resource, namely the service submodule forms credible manufacturing and shared manufacturing through a block chain and an industrial internet.

The network module, the hybrid cloud database module, the application module and the access system module in the manufacturing digital system based on the hybrid cloud architecture of the embodiment of the disclosure belong to information technology it (information technology); the data source acquisition module belongs to operation technology OT (operation technology), wherein OT is professional technology for providing support for an automatic control system by an automatic control system operation specialist in a factory and ensuring normal production, and comprises sensors, equipment, process flows and the like in a figure. The manufacturing digital system based on the hybrid cloud architecture fully integrates IT, OT and business, fully solves the problem of insufficient mutual cooperation of the IT, the OT and the business, simplifies the flows of field sensing, data acquisition, storage and analysis, operation insight and decision making by directly interacting the sensors on the edge layer and the equipment on the field layer with the cloud, and compresses the informationized multi-level structure of the traditional manufacturing enterprise.

The manufacturing digital system based on the hybrid cloud architecture constructs a tightly-butted, loosely-coupled and easily-expanded manufacturing digital architecture system, and creates an enterprise digital base and architecture which are not easily eliminated. The system can quickly integrate the existing information system, and avoid the problems of scattered construction, repeated construction and ineffective cooperation among the systems. Meanwhile, the system can promote and accelerate the enrichment of industrial data of manufacturing enterprises, the summarization and extraction of mechanisms, the construction and precipitation of models and promote the development of APP applied by the manufacturing enterprises.

So far, the embodiments of the present disclosure have been described in detail with reference to the accompanying drawings. It is to be noted that, in the attached drawings or in the description, the implementation modes not shown or described are all the modes known by the ordinary skilled person in the field of technology, and are not described in detail. In addition, the above definitions of the various elements and methods are not limited to the specific structures, shapes or modes mentioned in the embodiments, and those skilled in the art may easily modify or replace them.

Furthermore, the word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements.

The use of ordinal numbers such as "first," "second," "third," etc., in the specification and claims to modify a corresponding element does not by itself connote any ordinal number of the element, nor is the order of one element or component presented herein or method of manufacture, but are used merely to distinguish one element having a certain name from another element having a same name.

Moreover, unless specifically described or steps which must occur in sequence, the order of the steps is not limited to that set forth above and may be varied or rearranged as desired. The embodiments described above may be mixed and matched with each other or with other embodiments based on design and reliability considerations, i.e., technical features in different embodiments may be freely combined to form further embodiments.

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, this disclosure is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the present disclosure as described herein, and any descriptions above of specific languages are provided for disclosure of enablement and best mode of the present disclosure.

The disclosure may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. Various component embodiments of the disclosure may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components in the relevant apparatus according to embodiments of the present disclosure. The present disclosure may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present disclosure may be stored on a computer readable medium or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise. Also in the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the disclosure, various features of the disclosure are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various disclosed aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that is, the claimed disclosure requires more features than are expressly recited in each claim. Rather, as the following claims reflect, disclosed aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this disclosure.

The above-mentioned embodiments are intended to illustrate the objects, aspects and advantages of the present disclosure in further detail, and it should be understood that the above-mentioned embodiments are only examples of the present disclosure and are not intended to limit the present disclosure, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present disclosure should be included in the scope of the present disclosure.

Claims

1. A hybrid cloud architecture based manufacturing digitization system, comprising:

the application module comprises a private cloud application submodule and a public cloud application submodule, wherein the private cloud application submodule is used for acquiring data in the private cloud application submodule to perform application layer operation; the public cloud application submodule is used for acquiring data in the public cloud submodule to perform application layer operation; and

2. The manufacturing digitizing system of claim 1,

the private cloud submodule constructs a private cloud bottom environment based on OpenStack, Kubemeters and Docker.

3. The manufacturing digitizing system of claim 2, wherein the private cloud application submodule comprises:

4. The manufacturing digitizing system of claim 3, wherein the data storage unit comprises at least one of Kafka, MySQL, MongoDB, and Hadoop, the data storage unit being based on a cloud-native architecture for flexible deployment.

5. The manufacturing digitizing system of claim 1, wherein the public cloud sub-modules employ an AWS public cloud.

6. The manufacturing digitizing system of claim 1, wherein the public cloud application submodule comprises:

e-commerce services and financial services.

7. The manufacturing digitizing system of claim 1, wherein the data source acquisition module is to acquire data of underlying sensors, automation equipment, process flows, production operations, marketing, supply chain.

8. The manufacturing digitizing system of claim 1, wherein the network module comprises:

the Ethernet sub-module comprises an Ethernet and an industrial Internet;

the Internet of things submodule, and

9. The manufacturing digitizing system of claim 1, wherein the access system comprises: the system comprises a DaaS submodule, a BaaS submodule and a factory production resource-as-a-service submodule.

10. The manufacturing digitizing system of claim 1, wherein the digitizing equipment has flexible access to cloud platforms for cloud services in data query, visualization interaction, predictive maintenance, testing and debugging.