CN115130816A - Method and system for evaluating cloud level of enterprise - Google Patents
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Abstract
The invention relates to the technical field of evaluation, in particular to a method and a system for evaluating cloud level of an enterprise. The method comprises the following steps: (1) establishing an upper cloud practice module, an equipment upper cloud module, a service application module and an upper cloud effect module; (2) setting index weight by an entropy weight TOPSIS method; (3) and the enterprise logs in the evaluation system, online fills in relevant data of cloud of the enterprise, stores the data in the database, and obtains the cloud level evaluation of the enterprise through the evaluation system. According to the invention, through establishing the database and the classification quantization data indexes, different data quantization weights are distributed to each database data technical index in the classification quantization technical indexes, the system acquires enterprise data, a comprehensive index system and weights in the database, calculates the cloud effect index on the enterprise and calculates the cloud effect index on the region, and thus, a competent department can conveniently judge the cloud level on the enterprise.
Description
Technical Field
The invention relates to the technical field of evaluation, in particular to a method and a system for evaluating cloud level of an enterprise.
Background
The 'enterprise cloud' means that an industrial enterprise deploys infrastructure, equipment, a system, services, platforms and the like of the enterprise to the cloud through a high-speed internet, and resources such as calculation, storage, data and application and professional abilities such as design, production, logistics, sales and service are conveniently and rapidly acquired by using network elasticity, so that the information construction and operation and maintenance cost of the enterprise is reduced, the whole process, the whole industrial chain and the whole life cycle of products of the manufacturing industry are optimized, and the fusion development level of the manufacturing industry and the internet is improved. Cloud on enterprises is an important way and key step for promoting accelerated digitization, networking and intelligent transformation of manufacturing industry, and the society actively promotes deep application of industrial cloud and industrial internet platforms in industrial enterprises at present.
The effect evaluation is a key step and a powerful means for enterprises to grasp the cloud degree, develop cloud planning and promote deep application of industrial cloud and industrial internet. However, at present, a system is not formed by domestic and foreign research on cloud effect evaluation in industrial enterprises. Related researches mostly carry out test evaluation on the industrial cloud platform from the aspects of safety and performance, and an evaluation index system or an evaluation system for systematically developing application effects is not formed. And related research is based on limited data, the concept and the effect of cloud on enterprises are discussed briefly, and qualitative or quantitative analysis based on continuous data acquisition work is lacked.
Therefore, the enterprise still faces the problems of incomplete evaluation, inaccurate degree control and the like in the cloud using process, and a corresponding evaluation method and an evaluation system are needed to provide a basis and a reference for enterprise overall planning and continuous and comprehensive promotion of cloud using work.
Disclosure of Invention
In order to solve the technical problems described in the background art, the invention provides a method and a system for evaluating the cloud level of an enterprise.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a method for evaluating cloud level on an enterprise comprises the following steps:
(1) establishing an upper cloud practice module, an equipment upper cloud module, a service application module and an upper cloud effect module;
(2) setting index weight by an entropy weight TOPSIS method;
(3) and the enterprise logs in the evaluation system, online fills in relevant data of cloud of the enterprise, stores the data in the database, and obtains the cloud level evaluation of the enterprise through the evaluation system.
Specifically, the entropy weighted TOPSIS method comprises the following steps:
(1) calculating the index entropy weight, and calculating the index entropy weight,
constructing a scoring matrix G ═ (G) ij ) n×m And adopting an extreme method to carry out normalization processing on the expert scores, wherein the formula is as follows:
from this, the expert scoring normalization matrix R ═ (R) can be obtained ij ) n×m And calculating the information entropy Ei and the entropy weight Ki of each index according to the expert scoring normalization matrix R:
wherein m is the number of experts and n is the number of indexes;
(2) calculating the weight of the expert scheme to be calculated,
calculating by an expert scoring matrix G to obtain index weights in each expert scoring scheme:
normalizing the weight matrix of the expert scoring scheme by adopting an extreme method:
thus, the positive and negative ideal solutions in each expert scheme are respectively
The closeness of each expert scheme is:
wherein
And
respectively represent the distance between each expert scheme and the positive and negative ideal solutions,
closeness D according to expert schemes j The weights of the expert schemes can be determined:
(3) the weight of the index is calculated,
calculating evaluation index weight W according to index entropy weight and expert scheme weight i The formula is as follows:
(4) setting the weight of cloud effect evaluation model indexes in industrial enterprises,
according to an index weight formula given by TOPSIS, the weight of a first-level index in a cloud effect evaluation model in an industrial enterprise is WAi, the weight of a second-level index relative to the first-level index is WBj, and the absolute weight of the second-level index is W Ai *W Bj The weights of all primary indexes and secondary indexes in the cloud effect evaluation model in the industrial enterprise can be obtained;
the enterprise logs in the evaluation system to obtain the cloud level evaluation of the enterprise, and the method comprises the following steps:
(1) the user online fills in the cloud data of the enterprise;
(2) collecting enterprise data information and storing the enterprise data information into a database;
the evaluation system is used for analyzing and processing data to form cloud effect scores on enterprises, summarizing all enterprise data of regions and forming cloud effect indexes on the regions.
A system for evaluating the cloud level of an enterprise comprises a cloud practice module, an equipment cloud module, a business application module and a cloud effect module.
Specifically, the upper cloud practice module comprises an upper cloud background module for evaluating the requirement of an enterprise on the upper cloud practice module and an upper cloud scheme module for evaluating an enterprise implementation scheme.
Specifically, the cloud module on the device includes a device access module, an edge computing module, and a device service module.
The equipment access module comprises a high-energy-consumption equipment module for evaluating the functions of enterprise health monitoring, working condition optimization, fault diagnosis and remote operation and maintenance, a universal power equipment module for evaluating the functions of enterprise state monitoring, fault early warning and safety operation, a new energy equipment module for evaluating the functions of enterprise power prediction, scheduling optimization and state monitoring, and an intelligent equipment module for evaluating the functions of enterprise equipment asset management, operation monitoring, capability transaction and energy efficiency optimization;
the edge computing module comprises a data processing module for evaluating enterprise data cleaning, data compression and data encryption capabilities and a data analysis module for evaluating the data cleaning, data compression and data encryption capabilities of an enterprise edge side;
the equipment service module comprises an equipment account module for evaluating the capacity of forming the model, specification and function information of the cloud electronic management equipment of an enterprise into an equipment file, an equipment point inspection module for evaluating the timed reminding, positioning and card punching and point inspection capacity of the cloud equipment of the enterprise, a worksheet management module for evaluating the flexible management worksheet type, triggering conditions and closed-loop process capacity of the cloud equipment of the enterprise, a maintenance module for evaluating the maintenance plan and maintenance application capacity of the cloud management equipment of the enterprise, a real-time data module for evaluating the capacity of the real-time display equipment running state and running parameters of the enterprise, a data report module for evaluating the data analysis and display capacity of the enterprise data subsystem generated statistical report, an information module for evaluating the historical data capacity of the enterprise backtracking and inquiring equipment, and a configuration interface tool for evaluating the enterprise, the system comprises a configuration picture module for drawing a field topology simulation graph, realizing the centralized display of equipment information and mastering the capacity of equipment running conditions, an abnormal alarm module for evaluating an enterprise configuration alarm strategy and analyzing the capacity of abnormal alarm data, a reverse control module for evaluating the capacity of remote access control equipment of an enterprise, adjusting, stopping and starting equipment and executing equipment parameters, and an execution optimization module for evaluating the capacity of the enterprise for realizing the self optimization of an equipment algorithm by depending on a data analysis result and a knowledge base.
Specifically, the business application module comprises a basic cloud service module, an industrial APP application module and a data module.
Specifically, the basic cloud service module comprises a computing resource module for evaluating the utilization cloud object storage and file storage resource of an enterprise to promote enterprise resource management and distribution level, a storage resource module for evaluating the economic safety level of the utilization cloud object storage and file storage resource of the enterprise to promote enterprise data, a database module for evaluating the utilization cloud relational database, distributed database resource or database cloud hosting service of the enterprise, a database module for promoting cross-platform and cross-service management level of the enterprise data, a management tool module for evaluating the utilization cloud micro-service of the enterprise, applying an operation and maintenance management tool, realizing the cloud intelligent operation and maintenance level of an enterprise system, a data safety module for evaluating the utilization cloud safety service or product of the enterprise, realizing the tamper-proof and anti-theft level of the enterprise data, and a cloud safety service or product for evaluating the selection registration protection and login protection of the enterprise, the system comprises a business safety module for guaranteeing the stable and safe operation level of a business, a network safety module for evaluating the network safety level of an enterprise by utilizing sub-account management and access control, an industrial internet or an industrial cloud platform for evaluating the safety protection mechanism of the enterprise, an industrial system safety module for improving the safety level, a cloud disaster recovery module for evaluating the cloud disaster recovery backup production business system and business data of the enterprise and improving the reliability and availability level of the system and the data;
the industrial APP application module comprises a research and development design application module for evaluating enterprise utilization modeling, analysis and drawing cloud research and design services and sharing research and development design tool level, a research and development design case library for evaluating enterprise construction cloud research and development design case library, a research and development case library module for realizing on-line analysis, integration, sharing and management level, a research and development design cooperation module for evaluating enterprise utilization task distribution, task crowdsourcing and work-division writing cloud service design and realizing multi-regional and multi-language coordinated development level of departments and enterprise parts, a production scheduling management module for evaluating enterprise utilization cloud-based pre-scheduling plan, analyzing deviation between plan and field reality, dynamically adjusting scheduling plan level, a manufacturing execution system module for evaluating enterprise utilization cloud MES, performing manufacturing data management, planning scheduling management, creating enterprise manufacturing coordination management platform level, a production scheduling execution system module, a production scheduling management module, a production scheduling management module, a production management module, a system and a system, a system and a system, a system and a system, a system and a system, a method and a method for evaluating system, a system and a system, a method and a system, a system and a system, The system comprises a supply chain relationship management module for evaluating enterprise utilization cloud SRM and supplier classification selection and strategic relationship development service, maintaining the partner relationship of two parties, reducing the purchasing cost level, a purchasing management module for evaluating enterprise utilization cloud purchasing management system, realizing uniform management level of purchasing orders and delivery dates, a logistics management module for evaluating enterprise utilization cloud logistics management system, statistically analyzing the material inventory state and logistics planning information level, an enterprise resource planning module for evaluating enterprise utilization cloud ERP for arrangement and transmission of enterprise personnel, property and material information level, an e-commerce system module for evaluating utilization cloud of enterprise business, industrial internet or industrial cloud platform, promoting commodity display and popularization, cloud transaction management, reducing the e-commerce deployment cost level of enterprise, an e-commerce system module for evaluating enterprise utilization cloud, coordinating sales between enterprise and client, Marketing and service, which improves enterprise management mode, provides a client resource management module with innovative personalized service level for clients, and a client service module for evaluating the utilization of a call center and a client service workbench of an enterprise, creating a high-efficiency intelligent client service system and providing intelligent service and personalized service level for the clients;
the data module comprises basic data, design data, production data, logistics data, sales data and service data;
the basic data comprises cloud management human resources, finance and administrative data; the design data comprises cloud management drawing, simulation, reverse, test and optimization data; the production data comprises cloud analysis and data for showing capacity, progress and quality; the logistics data comprises cloud analysis and displayed fund flow, information flow and commodity flow data; the sales data comprises cloud analysis and sales amount, sales profits and order information data; the service data comprises cloud analysis, customer satisfaction and product operation data.
Specifically, the cloud-up effect module comprises a cloud-up time and investment module, a basic application effect module and an innovation application effect module.
Specifically, the cloud-up time and investment module comprises cloud-up time and cloud-up investment;
the basic application effect module comprises a cost reduction module for evaluating the cloud service utilization of enterprises to improve the informatization implementation capacity of the enterprises and reduce the cost levels of design, production, logistics, sales, service and operation, a data visualization module for evaluating the cloud tool utilization of the enterprises, realizing the visualization expression and management level of the enterprise design, production and operation information, an equipment visualization module for evaluating the cloud tool utilization of the enterprises, realizing the centralized visualization expression and management level of the equipment position, state and energy consumption data, an energy-saving and emission-reducing module for evaluating the cloud service utilization of the enterprises and collecting and analyzing the environmental data and the equipment energy consumption data by the cloud tool, carrying out corresponding optimization, improving the energy utilization efficiency, reducing the pollution emission level, an organization and management process for evaluating the digital centralized management of the human-machine material method annular data by the cloud service utilization of the enterprises and optimizing the whole life cycle of products, the system comprises an operation management and control capacity enhancing module for improving the operation management and control level, a production efficiency improving module for evaluating enterprise utilization cloud services, realizing digital production management and service system construction, optimizing resource allocation and improving production efficiency level, and a business mode optimizing module for evaluating enterprise utilization cloud services, optimizing resource allocation and production manufacturing service system and realizing enterprise business mode optimizing level;
the innovation application success module comprises a market transaction analysis and prediction module for evaluating enterprise utilization cloud computing, a big data technology, a cloud core business system, a product/equipment remote monitoring and operation and maintenance module for analyzing market transaction data and behaviors and predicting market development trend level, a product/equipment remote monitoring and operation and maintenance module for evaluating enterprise utilization artificial intelligence and a block chain technology, remotely monitoring, analyzing, diagnosing and predicting product and equipment state level by using cloud service and cloud tools, a product quality control and process optimization module for evaluating enterprise utilization cloud platform, integrating and analyzing logistics, fund flow and information flow of each link of an industrial chain, optimizing industrial chain configuration and promoting industrial chain cooperation level, a product/equipment remote monitoring and operation and maintenance module for evaluating enterprise utilization cloud service and analyzing, cleaning and analyzing product whole life cycle data, optimizing production manufacturing process and improving product quality level, and an industrial chain cooperation module for evaluating industrial chain utilization cloud platform, The system comprises an enterprise operation analysis and prediction module for evaluating enterprise utilization cloud platforms, a full-factor collection enterprise operation data, a model, a tool set and knowledge for evaluating enterprise utilization cloud safety production perception, monitoring, early warning, disposal and evaluation based on machine learning and model prediction technologies, a safety production module for realizing dynamic perception, prevention in advance and global linkage of safety production and improving the intrinsic safety level of industrial production, a novel intelligent manufacturing mode module for evaluating the level of a novel production mode with self-perception, self-learning, self-decision, self-execution and self-adaption functions for enterprise construction, a personalized customization module for evaluating the level of product design and production and manufacture by taking users or orders as the center and combining personalized requirements, a product design module for evaluating the product design in and across supply chains of enterprises, The system comprises a network coordination manufacturing module at the level of mutual cooperation of manufacturing, management and business, and a service type manufacturing module which is used for evaluating that an enterprise services and encapsulates physical or virtual resources and distributes the physical or virtual resources to an industrial cloud platform so as to provide service production and production service level.
The invention has the beneficial effects that: the invention provides a method and a system for evaluating cloud-up level of an enterprise, wherein different data quantization weights are distributed to each database data technical index in the classification quantization technical indexes by establishing a database and classification quantization data indexes, the system acquires enterprise data, a comprehensive index system and weights in the database, calculates an enterprise cloud-up effect index and calculates a regional cloud-up effect index, and a competent department can conveniently judge the cloud-up level of the enterprise.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a block diagram of the present invention;
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings.
FIG. 1 is a block diagram of the architecture of the present invention.
Examples
As shown in fig. 1, an enterprise cloud evaluation system includes a cloud practice module, a device cloud module, a service application module, and a cloud effect module.
The upper cloud practice module comprises an upper cloud background module and an upper cloud scheme module, and the upper cloud background module is used for evaluating the integrity, the standardization and the scientific degree of the enterprise implementation scheme and the concrete, comprehensive and systematic degree of implementation measures. And the cloud-going scheme module is used for judging whether the enterprise needs to go to the cloud or not and whether cloud-going work can be done or not.
The cloud module on the equipment comprises an equipment access module, an edge computing module and an equipment service module.
The equipment access module comprises a high-energy consumption equipment module, a universal power equipment module, a new energy equipment module and an intelligent equipment module.
The high-energy-consumption equipment module is used for evaluating the functions of enterprise health monitoring, working condition optimization, fault diagnosis and remote operation and maintenance. The universal power equipment module is used for evaluating the functions of enterprise state monitoring, fault early warning and safe operation. And the new energy equipment module is used for evaluating the functions of enterprise power prediction, scheduling optimization and state monitoring. The intelligent equipment module is used for evaluating the functions of enterprise equipment asset management, operation monitoring, capability trading and energy efficiency optimization.
The edge computing module comprises a data processing module for evaluating the data cleaning, data compression and data encryption capabilities of the enterprise and a data analysis module for evaluating the data cleaning, data compression and data encryption capabilities of the edge side of the enterprise.
The equipment service module comprises an equipment account module, an equipment point inspection module, a work order management module, a maintenance module, a real-time data module, a data report module, an information tracing module, a configuration picture module, an abnormity alarm module, a reverse control module and an execution optimization module.
The equipment account module is used for evaluating the ability of an enterprise to form equipment files by cloud electronic management equipment models, specifications and functional information. The equipment point inspection module is used for evaluating the timed reminding, positioning card punching and enterprise point inspection capabilities of enterprise cloud equipment. The work order management module is used for evaluating the capability of flexibly managing the work order types, the triggering conditions and the closed-loop processes at the cloud end of the enterprise. And the maintenance module is used for evaluating the maintenance plan and the maintenance application capability of the enterprise cloud management equipment. The real-time data module is used for evaluating the capability of the enterprise for displaying the running state and the running parameters of the equipment in real time. And the data report module is used for evaluating the capability of the enterprise data subsystem for generating a statistical report to analyze and display data. The information tracing module is used for evaluating the capability of the enterprise for tracing and inquiring the historical data of the equipment. The configuration picture module is used for evaluating the capability of an enterprise for drawing a field topology simulation graph by using a configuration interface tool, realizing centralized display of equipment information and grasping the running condition of the equipment. And the abnormal alarm module is used for evaluating the enterprise configuration alarm strategy and analyzing the capacity of abnormal alarm data. The reverse control module is used for evaluating the capability of the remote access control equipment of the enterprise for adjusting, stopping and starting the equipment and executing the equipment parameters. And the execution optimization module is used for evaluating the capability of an enterprise for realizing self optimization of the equipment algorithm by depending on the data analysis result and the knowledge base.
The business application module comprises a basic cloud service module, an industrial APP application module and a data module.
The basic cloud service module comprises a computing resource module, a storage resource module, a database module, a management tool module, a data security module, a business security module, a network security module, an industrial system security module and a cloud disaster recovery module.
And the computing resource module is used for evaluating the level of utilizing cloud object storage and file storage resources to improve enterprise resource management and distribution. The storage resource module is used for evaluating the level of economic safety of enterprise data improved by utilizing cloud object storage and file storage resources. The database module is used for evaluating the utilization of a cloud relational database, distributed database resources or database cloud hosting service by an enterprise, and the cross-platform and cross-business management level of enterprise data is improved. The management tool module is used for evaluating the cloud micro-service utilization and application operation and maintenance management tools of the enterprise to achieve the cloud intelligent operation and maintenance level of the enterprise system. The data security module is used for evaluating the cloud security service or product utilization of enterprises, and the levels of enterprise data tampering prevention and theft prevention are achieved. The service security module is used for evaluating cloud security services or products selected by enterprises for registration protection and login protection, and guaranteeing the level of stable and safe operation of the service. And the network security module is used for evaluating the level of the enterprise network security guaranteed by using sub-account management and access control. The industrial system security module is used for evaluating an industrial internet or an industrial cloud platform of an enterprise utilizing a security protection mechanism, and the security level is improved. The cloud disaster recovery module is used for evaluating the cloud disaster recovery backup production business system and business data of an enterprise, and improving the reliability and availability of the system and the data.
The industrial APP module comprises a research and development design application module, a research and development design case library module, a research and development design coordination module, a production scheduling management module, a manufacturing execution system module, a supply chain relation management module, a purchase management module, a logistics management module, an enterprise resource planning module, an e-commerce system module, a customer resource management module and a customer service module.
The research and development application module is used for evaluating the level of utilizing modeling, analyzing and drawing cloud research and development design services and sharing research and development design tools of enterprises. The research and development design case library module is used for evaluating an enterprise construction cloud research and development design case library and realizing the levels of online analysis, integration, sharing and management. The research, development and design cooperation module is used for evaluating the level of coordination development of departments and enterprise parts across regions and multiple languages by task distribution, task crowdsourcing and work-division writing cloud service design of enterprises. The production scheduling management module is used for evaluating that an enterprise utilizes a cloud end to make a pre-scheduling plan, analyzing deviation between the plan and the actual site, and dynamically adjusting the level of the scheduling plan. The manufacturing execution system module is used for evaluating the level of an enterprise for manufacturing coordination management platform by utilizing a cloud MES to perform manufacturing data management and planning and scheduling management. The supply chain relation management module is used for evaluating the level that enterprises utilize the cloud SRM, supplier classification selection and strategic relation development service, maintaining the partnership of both parties and reducing purchasing cost. And the purchase management module is used for evaluating the level of unified management of purchase orders and delivery dates by utilizing the cloud purchase management system by an enterprise. And the logistics management module is used for evaluating the level of the enterprise utilization cloud logistics management system and counting and analyzing the material inventory state and the logistics plan information. The enterprise resource planning module is used for evaluating the level of arranging and transmitting information of enterprise people, property and things by utilizing the cloud ERP. The e-commerce system module is used for evaluating that an enterprise utilizes an e-commerce cloud, an industrial internet or an industrial cloud platform to promote commodity display promotion and transaction management to be on the cloud, and the level of the e-commerce deployment cost of the enterprise is reduced. The client resource management module is used for evaluating the utilization of the cloud CRM by an enterprise, coordinating sales, marketing and service between the enterprise and a client, improving the enterprise management mode and providing the level of innovative personalized service for the client. The customer service module is used for evaluating the level of an enterprise utilizing the call center and the customer service workbench to build an efficient intelligent customer service system and provide intelligent service and personalized service for customers.
The data module comprises basic data, design data, production data, logistics data, sales data and service data;
the basic data comprises cloud management human resources, finance and administrative data. The design data comprises cloud management drawing, simulation, reverse, test and optimization data. The production data includes cloud analysis and data showing capacity, progress and quality. The logistics data comprises cloud analysis and displayed fund flow, information flow and business flow data. The sales data comprises cloud analysis and sales amount, sales profits and order information data. The service data comprises cloud analysis, customer satisfaction and product operation data.
The cloud-up effect module comprises a cloud-up time and input module, a basic application effect module and an innovation application effect module.
The cloud time and investment module comprises cloud time and cloud investment.
The basic application effect module comprises a cost reduction module, a data visualization module, an equipment visualization module, an energy conservation and emission reduction module, an operation management and control capability enhancement module, a production efficiency improvement module and a business mode optimization module.
The cost reduction module is used for evaluating the level of the enterprise utilization cloud service to improve the enterprise informatization implementation capacity and reduce the design, production, logistics, sales, service and operation and maintenance costs. The data visualization module is used for evaluating the level of visualization expression and management of enterprise design, production and operation information by utilizing a cloud tool of an enterprise. The equipment visualization module is used for evaluating the level of centralized visualization expression and management of the position, the state and the energy consumption data of the equipment by utilizing a cloud tool of an enterprise. The energy-saving emission-reducing module is used for evaluating the cloud service utilization of enterprises, collecting and analyzing environmental data and equipment energy consumption data by cloud tools, carrying out corresponding optimization, improving the energy utilization efficiency and reducing the level of pollution emission. The operation management and control capacity enhancement module is used for evaluating the environment data of the enterprise in a man-machine material method through cloud service digital centralized management, optimizing the organization management process of the whole life cycle of the product and improving the level of operation management and control. The production efficiency improving module is used for evaluating the cloud service utilization of enterprises, realizing digital production management and service system construction, optimizing resource allocation and improving the level of production efficiency. The business mode optimization module is used for evaluating the cloud service utilization of enterprises, optimizing resource allocation and a production and manufacturing service system and realizing the level of business mode optimization of the enterprises.
The innovation application effect module comprises a market transaction analysis and prediction module, a product/equipment remote monitoring and operation and maintenance module, a product quality control and process optimization module, an industrial chain cooperation module, an enterprise operation analysis and prediction module, a safe production module, an intelligent manufacturing new mode module, a personalized customization module, a network coordination manufacturing module and a service type manufacturing module.
The market transaction analysis and prediction module is used for evaluating the level of market development trend of enterprises by utilizing cloud computing, big data technology and a cloud core business system, analyzing market transaction data and behaviors and predicting the market development trend. The product/equipment remote monitoring and operation and maintenance module is used for evaluating the levels of the product and equipment states of enterprises, which are remotely monitored, analyzed, diagnosed and predicted by using artificial intelligence and a block chain technology and using cloud services and cloud tools. The product quality control and process optimization module is used for evaluating the full life cycle data of the enterprise collected, cleaned and analyzed by using cloud service, optimizing the production and manufacturing process and improving the level of product quality. The industrial chain cooperation module is used for evaluating the utilization of the cloud platform by enterprises, integrating and analyzing logistics, fund flow and information flow of each link of the industrial chain, optimizing industrial chain configuration and promoting the level of industrial chain cooperation. The enterprise operation analysis and prediction module is used for evaluating the utilization of the cloud platform by the enterprise, collecting enterprise operation data by all elements, and analyzing and predicting the level of the future trend of the enterprise based on machine learning and prediction model technology. The safety production module is used for evaluating models, tool sets and knowledge of enterprises utilizing cloud safety production perception, monitoring, early warning, disposal and assessment, realizing safety production dynamic perception, advance prevention and global linkage, and improving the level of essential safety of industrial production. The intelligent manufacturing new mode module is used for evaluating the level of a novel production mode with self-perception, self-learning, self-decision, self-execution and self-adaptation functions for enterprise construction. The personalized customization module is used for evaluating the level of the enterprise which takes a user or an order as a center and completes product design, production and manufacturing by combining personalized requirements. The network orchestration manufacturing module is used to evaluate the level of product design, manufacturing, management, and business interactions within and across the enterprise supply chain. The service type manufacturing module is used for evaluating the level that an enterprise performs service encapsulation on physical or virtual resources and releases the physical or virtual resources to an industrial cloud platform, so that service production and production service are provided.
An enterprise cloud evaluation method comprises the following steps:
(1) establishing an upper cloud practice module, an equipment upper cloud module, a service application module and an upper cloud effect module;
(2) setting index weight by an entropy weight TOPSIS method;
(3) and the enterprise logs in the evaluation system, online fills in relevant data of cloud of the enterprise, stores the data in the database, and obtains the cloud level evaluation of the enterprise through the evaluation system.
The entropy weighted TOPSIS method comprises the following steps:
(1) calculating the index entropy weight, and calculating the index entropy weight,
constructing a scoring matrix G ═ (G) ij ) n×m And adopting an extreme method to carry out normalization processing on the expert scores, wherein the formula is as follows:
from this, the expert scoring normalization matrix R ═ (R) can be obtained ij ) n×m And calculating the information entropy Ei and the entropy weight Ki of each index according to the expert scoring normalization matrix R:
wherein m is the number of experts, and n is the number of indexes;
(2) calculating the weight of the expert scheme to be calculated,
calculating by an expert scoring matrix G to obtain index weights in each expert scoring scheme:
normalizing the weight matrix of the expert scoring scheme by adopting an extreme method:
thus, the positive and negative ideal solutions in each expert scheme are respectively
The closeness of each expert scheme is:
wherein
And
respectively represent the distance between each expert scheme and the positive and negative ideal solutions,
closeness D according to expert schemes j The weights of the expert schemes can be determined:
(3) the weight of the index is calculated,
calculating evaluation index weight W according to index entropy weight and expert scheme weight i The formula is as follows:
(4) setting the weight of cloud effect evaluation model indexes in industrial enterprises,
according to an index weight formula given by TOPSIS, the weight of a first-level index in a cloud effect evaluation model in an industrial enterprise is WAi, the weight of a second-level index relative to the first-level index is WBj, and the absolute weight of the second-level index is W Ai *W Bj The weights of all primary indexes and secondary indexes in the cloud effect evaluation model in the industrial enterprise can be obtained;
the enterprise logs in the evaluation system to obtain the cloud level evaluation of the enterprise comprises the following steps:
(1) the user online fills in the cloud data of the enterprise;
(2) collecting enterprise data information and storing the enterprise data information into a database;
(3) the evaluation system is used for analyzing and processing data to form cloud effect scores on enterprises, summarizing all enterprise data of regions and forming cloud effect indexes on the regions.
In light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (10)
1. A method for evaluating cloud level on an enterprise is characterized by comprising the following steps: the method comprises the following steps:
(1) establishing an upper cloud practice module, an equipment upper cloud module, a service application module and an upper cloud effect module;
(2) setting index weight by an entropy weight TOPSIS method;
(3) and the enterprise logs in the evaluation system, online fills in relevant data of cloud of the enterprise, stores the data in the database, and obtains the cloud level evaluation of the enterprise through the evaluation system.
2. The method of assessing cloud level across an enterprise of claim 2, wherein: the entropy weighted TOPSIS method comprises the following steps:
(1) calculating the index entropy weight, and calculating the index entropy weight,
constructing a scoring matrix G ═ (G) ij ) n×m And adopting an extreme method to normalize the expert scores, wherein the formula is as follows:
from this, the expert scoring normalization matrix R ═ (R) can be obtained ij ) n×m Calculating the information entropy Ei and entropy weight Ki of each index according to the expert scoring normalization matrix R:
wherein m is the number of experts and n is the number of indexes;
(2) calculating the weight of the expert scheme to be calculated,
calculating by an expert scoring matrix G to obtain index weights in each expert scoring scheme:
adopting an extreme method to normalize the weight matrix of the expert scoring scheme:
thus, the positive and negative ideal solutions in each expert scheme are respectively
The closeness of each expert scheme is:
wherein
And
respectively represent the distance between each expert scheme and the positive and negative ideal solutions,
closeness D according to expert schemes j The weights of the expert schemes can be determined:
(3) the weight of the index is calculated,
calculating evaluation index weight W according to index entropy weight and expert scheme weight i The formula is as follows:
(4) setting the weight of cloud effect evaluation model indexes in industrial enterprises,
according to an index weight formula given by the improved entropy weight TOPSIS, the cloud effect of the industrial enterpriseIf the weight of the primary index in the evaluation model is WAi, and the weight of the secondary index relative to the primary index is WBj, the absolute weight of the secondary index is W Ai *W Bj The weights of all primary indexes and secondary indexes in the cloud effect evaluation model in the industrial enterprise can be obtained;
the enterprise logs in the evaluation system to obtain the cloud level evaluation of the enterprise, and the method comprises the following steps:
(1) the user online fills in the cloud data of the enterprise;
(2) collecting enterprise data information and storing the enterprise data information into a database;
the evaluation system is used for analyzing and processing data to form cloud effect scores on enterprises, summarizing all enterprise data of regions and forming cloud effect indexes on the regions.
3. The system for evaluating the cloud level on an enterprise according to any one of claims 1-2, comprising a cloud practice module, a cloud on device module, a business application module and a cloud effect module.
4. The system for evaluating the level of cloud over an enterprise of claim 3, wherein said modules for practicing cloud over include a module for evaluating cloud over background of an enterprise's own needs, a module for evaluating cloud over solutions of an enterprise's implementation.
5. The system for evaluating cloud level on an enterprise of claim 3, wherein said cloud on device module comprises a device access module, an edge computing module, and a device service module.
6. The system for evaluating the cloud level on the enterprise according to claim 5, wherein the device access module comprises a high energy consumption device module for evaluating the functions of enterprise health monitoring, working condition optimization, fault diagnosis and remote operation and maintenance, a universal power device module for evaluating the functions of enterprise state monitoring, fault early warning and safety operation, a new energy device module for evaluating the functions of enterprise power prediction, scheduling optimization and state monitoring, and an intelligent equipment module for evaluating the functions of enterprise device asset management, operation monitoring, capability transaction and energy efficiency optimization;
the edge computing module comprises a data processing module for evaluating enterprise data cleaning, data compression and data encryption capabilities and a data analysis module for evaluating the data cleaning, data compression and data encryption capabilities of an enterprise edge side;
the equipment service module comprises an equipment account module for evaluating the capacity of forming the model, specification and function information of the cloud electronic management equipment of an enterprise into an equipment file, an equipment point inspection module for evaluating the timed reminding, positioning and card punching and point inspection capacity of the cloud equipment of the enterprise, a worksheet management module for evaluating the flexible management worksheet type, triggering conditions and closed-loop process capacity of the cloud equipment of the enterprise, a maintenance module for evaluating the maintenance plan and maintenance application capacity of the cloud management equipment of the enterprise, a real-time data module for evaluating the capacity of the real-time display equipment running state and running parameters of the enterprise, a data report module for evaluating the data analysis and display capacity of the enterprise data subsystem generated statistical report, an information module for evaluating the historical data capacity of the enterprise backtracking and inquiring equipment, and a configuration interface tool for evaluating the enterprise, the system comprises a configuration picture module for drawing a field topology simulation graph, realizing the centralized display of equipment information and mastering the capacity of equipment running conditions, an abnormal alarm module for evaluating an enterprise configuration alarm strategy and analyzing the capacity of abnormal alarm data, a reverse control module for evaluating the capacity of remote access control equipment of an enterprise, adjusting, stopping and starting equipment and executing equipment parameters, and an execution optimization module for evaluating the capacity of self optimization of an equipment algorithm of the enterprise by means of a data analysis result and a knowledge base.
7. The system for assessing cloud level across an enterprise of claim 3, wherein: the business application module comprises a basic cloud service module, an industrial APP application module and a data module.
8. The system for evaluating cloud level on an enterprise of claim 7, wherein: the basic cloud service module comprises a computing resource module for evaluating the enterprise resource management and distribution level of the enterprise by utilizing cloud object storage and file storage resources, a storage resource module for evaluating the economic safety level of the enterprise data by utilizing the cloud object storage and the file storage resources, a database module for evaluating the enterprise data by utilizing a cloud relational database, distributed database resources or database cloud hosting service, a database module for evaluating the cross-platform and cross-service management level of the enterprise data, a management tool module for evaluating the enterprise cloud micro-service utilization and application operation and maintenance management tools, realizing the cloud system cloud intelligent operation and maintenance level of the enterprise, a data safety module for evaluating the enterprise cloud safety service or product utilization of the enterprise, realizing the enterprise data tamper-proof and anti-theft level, and a cloud safety service or product for evaluating the enterprise to select registration protection and login protection, the system comprises a business safety module for guaranteeing the stable and safe operation level of a business, a network safety module for evaluating the network safety level of an enterprise by utilizing sub-account management and access control, an industrial internet or an industrial cloud platform for evaluating the safety protection mechanism of the enterprise, an industrial system safety module for improving the safety level, a cloud disaster recovery module for evaluating the cloud disaster recovery backup production business system and business data of the enterprise and improving the reliability and availability level of the system and the data;
the industrial APP application module comprises a research and development design application module for evaluating enterprise utilization modeling, analysis and drawing cloud research and design services and sharing a research and development design tool level, a research and development design case library for evaluating enterprise construction cloud research and development design cases, a research and development case library module for realizing on-line analysis, integration, sharing and management levels, a research and development design cooperation module for evaluating enterprise utilization task distribution, task crowdsourcing and work division writing cloud service design and realizing the coordination development level of departments and enterprise parts across regions and multiple languages, a production scheduling management module for evaluating enterprise utilization cloud-end planning, analyzing deviation of planning and field reality, a production scheduling management module for dynamically adjusting scheduling planning level, a manufacturing execution system module for evaluating enterprise utilization cloud MES for manufacturing data management, planning scheduling management, creating enterprise manufacturing coordination management platform level, a production execution system module for creating enterprise production coordination management platform level, a production scheduling management module for managing production scheduling and management system for managing production of enterprise, The system comprises a supply chain relationship management module for evaluating enterprise utilization cloud SRM and supplier classification selection and strategic relationship development service, maintaining the partner relationship of two parties, reducing the purchasing cost level, a purchasing management module for evaluating enterprise utilization cloud purchasing management system, realizing uniform management level of purchasing orders and delivery dates, a logistics management module for evaluating enterprise utilization cloud logistics management system, statistically analyzing the material inventory state and logistics planning information level, an enterprise resource planning module for evaluating enterprise utilization cloud ERP for arrangement and transmission of enterprise personnel, property and material information level, an e-commerce system module for evaluating utilization cloud of enterprise business, industrial internet or industrial cloud platform, promoting commodity display and popularization, cloud transaction management, reducing the e-commerce deployment cost level of enterprise, an e-commerce system module for evaluating enterprise utilization cloud, coordinating sales between enterprise and client, Marketing and service, which improves enterprise management mode, provides a client resource management module with innovative personalized service level for clients, and a client service module for evaluating the utilization of a call center and a client service workbench of an enterprise, creating a high-efficiency intelligent client service system and providing intelligent service and personalized service level for the clients;
the data module comprises basic data, design data, production data, logistics data, sales data and service data;
the basic data comprises cloud management human resources, finance and administrative data; the design data comprises cloud management drawing, simulation, reverse, test and optimization data; the production data comprises cloud analysis and data showing productivity, progress and quality; the logistics data comprises cloud analysis and displayed fund flow, information flow and business flow data; the sales data comprises cloud analysis and sales amount, sales profits and order information data; the service data comprises cloud analysis, customer satisfaction and product operation data.
9. The system for evaluating cloud level on an enterprise of claim 3, wherein: the cloud-up effect module comprises a cloud-up time and investment module, a basic application effect module and an innovation application effect module.
10. The system for assessing cloud level over an enterprise of claim 9, wherein: the cloud time and investment module comprises cloud time and cloud investment;
the basic application effect module comprises a cost reduction module for evaluating the cloud service utilization of enterprises to improve the informatization implementation capacity of the enterprises and reduce the cost levels of design, production, logistics, sales, service and operation, a data visualization module for evaluating the cloud tool utilization of the enterprises, realizing the visualization expression and management level of the enterprise design, production and operation information, an equipment visualization module for evaluating the cloud tool utilization of the enterprises, realizing the centralized visualization expression and management level of the equipment position, state and energy consumption data, an energy-saving and emission-reducing module for evaluating the cloud service utilization of the enterprises and collecting and analyzing the environmental data and the equipment energy consumption data by the cloud tool, carrying out corresponding optimization, improving the energy utilization efficiency, reducing the pollution emission level, an organization and management process for evaluating the digital centralized management of the human-machine material method annular data by the cloud service utilization of the enterprises and optimizing the whole life cycle of products, the system comprises an operation management and control capacity enhancing module for improving the operation management and control level, a production efficiency improving module for evaluating enterprise utilization cloud services, realizing digital production management and service system construction, optimizing resource allocation and improving production efficiency level, and a business mode optimizing module for evaluating enterprise utilization cloud services, optimizing resource allocation and production manufacturing service system and realizing enterprise business mode optimizing level;
the innovation application success module comprises a market transaction analysis and prediction module for evaluating enterprise utilization cloud computing, a big data technology, a cloud core business system, a product/equipment remote monitoring and operation and maintenance module for analyzing market transaction data and behaviors and predicting market development trend level, an artificial intelligence and block chain technology for evaluating enterprise utilization, a product/equipment remote monitoring, analysis, diagnosis and prediction module for utilizing cloud service and cloud tools to remotely monitor, analyze, diagnose and predict product and equipment state level, a product quality control and process optimization module for evaluating enterprise utilization cloud platform, integrating and analyzing logistics, fund flow and information flow of each link of an industrial chain, optimizing industrial chain configuration and promoting industrial chain cooperation level, The system comprises an enterprise operation analysis and prediction module for evaluating enterprise utilization cloud platforms, a full-factor collection enterprise operation data, a model, a tool set and knowledge for evaluating enterprise utilization cloud safety production perception, monitoring, early warning, disposal and evaluation based on machine learning and model prediction technologies, a safety production module for realizing dynamic perception, prevention in advance and global linkage of safety production and improving the intrinsic safety level of industrial production, a novel intelligent manufacturing mode module for evaluating the level of a novel production mode with self-perception, self-learning, self-decision, self-execution and self-adaption functions for enterprise construction, a personalized customization module for evaluating the level of product design and production and manufacture by taking users or orders as the center and combining personalized requirements, a product design module for evaluating the product design in and across supply chains of enterprises, The system comprises a network coordination manufacturing module at the level of manufacturing, management and business mutual cooperation, and a service type manufacturing module used for evaluating that an enterprise performs service encapsulation on physical or virtual resources and releases the physical or virtual resources to an industrial cloud platform so as to provide service production and production service level.
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