CN117891859B - Data processing method and system for industrial Internet of things - Google Patents
Data processing method and system for industrial Internet of things Download PDFInfo
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Abstract
The invention discloses a data processing method and a system for industrial Internet of things, and particularly relates to the field of data processing. The invention realizes the comprehensive monitoring of the customer relationship, the manufacturing process, the product quality and the resource through accurate data acquisition, preprocessing and analysis. The method has the advantages that the method can accurately acquire and analyze the industrial Internet of things data and provide powerful decision support for enterprises.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a data processing method and system for industrial Internet of things.
Background
The industrial Internet of things is an application of the Internet of things technology in the industrial field, intelligent interconnection of equipment, products and services is realized, real-time acquisition, analysis and optimization of equipment data are realized through technologies such as sensors, cloud computing and big data, the production efficiency is improved, the cost is reduced, the industrial Internet of things not only changes the production mode of the traditional industry, but also promotes the development of industrial intellectualization, and industrial upgrading and transformation are promoted.
The existing industrial Internet of things collects industrial Internet of things data through sensors, equipment and other data sources, processes such as cleaning, denoising and normalization are performed on the collected raw data to improve data quality and usability, then the processed data are stored in a proper storage system, various data analysis technologies such as machine learning, deep learning and data mining are used for analyzing and mining the stored data to find rules, trends and anomalies in the data, and finally analysis results are presented to users in a visual, report or other form, so that the users can intuitively know the running state and performance of the industrial Internet of things.
However, when the method is actually used, some disadvantages still exist, such as although the industrial internet of things has made certain progress in terms of data processing, the existing method still has disadvantages, for example, for a large amount of real-time data, the traditional data processing method may not effectively perform real-time analysis, prediction and optimization, which results in low efficiency and quality of data processing, and the existing industrial internet of things system may not integrate various devices and systems well, which results in serious data island phenomenon, so that the data cannot flow and share among different systems, thereby limiting the overall efficiency of the industrial internet of things.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a data processing method and system for industrial internet of things, which solve the problems set forth in the above-mentioned background art through the following schemes.
In order to achieve the above purpose, the present invention provides the following technical solutions: a data processing method and system for industrial Internet of things comprises the following steps:
Step 1: data acquisition time division: the method comprises the steps of determining the data acquisition time of a target industrial Internet of things as a target time area, dividing the target time area into sub-time areas in an equal time division mode, and marking the sub-time areas as 1 and 2 … … n in sequence;
step 2: and (3) data acquisition: the method comprises the steps of acquiring client relation data, manufacturing data, product quality data and resource data of a target industrial Internet of things in each sub-time region, and transmitting the acquired data to a data preprocessing step;
Step 3: data preprocessing: the data processing device is used for preprocessing the data transmitted in the data acquisition step and transmitting the processed data to the data analysis step;
step 4: customer relationship data analysis: the data preprocessing step is used for analyzing the client relationship data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step;
Step 5: manufacturing data analysis: the manufacturing data transmission step is used for analyzing the manufacturing data transmitted in the data preprocessing step, and transmitting the data obtained by analysis to the comprehensive analysis step;
step 6: product quality data analysis: the product quality data transmitted in the data preprocessing step are analyzed, and the data obtained by analysis are transmitted to the comprehensive analysis step;
Step 7: and (3) analyzing resource data: the comprehensive analysis step is used for analyzing the resource data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step;
Step 8: comprehensive analysis: the data transmitted in the data analysis step is comprehensively analyzed, the analysis is carried out through an industrial Internet of things comprehensive analysis method, and the analysis result is transmitted to the judgment step;
step 9: judging: the method is used for judging the enterprise comprehensive optimization index of the target industrial Internet of things.
Preferably, the customer relationship data includes a customer feedback quantity, a customer positive feedback quantity, a customer negative feedback quantity, a customer quantity, an attrition customer purchase amount, a customer total purchase amount, a new customer marketing campaign fee, and a new customer quantity, respectively labeled as、/>、/>、/>、/>、/>、/>、/>/>The manufacturing data includes equipment run time, product demand, quantity produced, and quantity of rejects, labeled/>, respectively、/>、/>The product quality data includes total sales quantity, return quantity, inspection quantity, reject quantity, quality audit number, pass quality audit number, quality improvement quantity, quality improvement success quantity, respectively labeled/>、/>、、/>、/>、/>、/>/>The resource data includes total sales, inventory value, raw material costs, direct labor costs, manufacturing costs, liquidity assets, liquidity liabilities, and forecasted sales, respectively labeled/>、/>、、/>、/>、/>、/>/>Where i=1, 2 … … n, i denotes the i-th time region.
Preferably, the data acquisition step acquires customer relationship data of each sub-time region through customer interaction and sales data, acquires manufacturing data and product quality data of each sub-time region through RFID (radio frequency identification) tags, acquires resource data of each sub-time region through financial data entry, and performs data transmission in a wireless mode and is displayed in a form of a graph, a chart or an animation through a data visualization technology.
Preferably, in the data preprocessing step, the customer front feedback proportion of the ith time zone is calculated according to the customer feedback quantity and the customer front feedback quantity of the ith time zone, and a specific calculation formula is as follows: Calculating the customer negative feedback proportion of the ith time zone according to the customer feedback quantity and the customer negative feedback quantity of the ith time zone, wherein the specific calculation formula is as follows: /(I) Calculating the customer churn rate of the ith time zone according to the number of customers, the number of customers churn, the number of churn customers and the purchase amount of churn customers, wherein the specific calculation formula is as follows: Calculating the new customer acquisition cost of the ith time zone by the new customer marketing campaign cost of the ith time zone and the number of the new customers, wherein the specific calculation formula is as follows: /(I) The equipment utilization rate of the ith time zone is calculated through the equipment running time of the ith time zone and the time difference between the ith time zone and the (i-1) th time zone, and the specific calculation formula is as follows: /(I)The production beat of the ith time zone is calculated through the product demand of the ith time zone and the running time of the equipment, and the specific calculation formula is as follows: /(I)The rejection rate of the ith time zone is calculated through the rejection number and the production number of the ith time zone, and a specific calculation formula is as follows: The production efficiency of the ith time zone is calculated through the production quantity of the ith time zone and the standard production quantity, and a specific calculation formula is as follows: /(I) The product return rate of the ith time zone is calculated through the total sales quantity and the return quantity of the ith time zone, and the specific calculation formula is as follows: /(I)And calculating the failure rate of the ith time zone according to the checking quantity and the failure quantity of the ith time zone, wherein a specific calculation formula is as follows: the quality auditing passing rate of the ith time zone is calculated through the quality auditing times of the ith time zone and the quality auditing times, and the specific calculation formula is as follows: /(I) The success rate of quality improvement items in the ith time zone is calculated by the quality improvement quantity and the quality improvement success quantity of the ith time zone, and a specific calculation formula is as follows: the inventory turnover rate of the ith time zone is calculated through the total sales and the inventory value of the ith time zone, and a specific calculation formula is as follows: /(I) The production cost of the ith time zone is calculated through the raw material cost, the direct labor cost and the manufacturing cost of the ith time zone, and the specific calculation formula is as follows: Calculating the flow ratio of the ith time zone by the flow asset and the flow liability of the ith time zone, wherein the specific calculation formula is as follows: /(I) Calculating the sales prediction accuracy of the ith time zone according to the total sales of the ith time zone, wherein the specific calculation formula is as follows: /(I)And transmitting the processed data to a data analysis step.
Preferably, the client relationship data analysis method is used for establishing a client relationship data analysis model, and specifically comprises the following steps:，/> client experience index representing the ith time zone,/> Customer positive feedback ratio representing the ith time zone,/>Representing the customer negative feedback proportion of the ith time zone,/>Customer churn rate, representing the ith time zone,/>New customer acquisition cost representing the ith time zone,/>Other influencing factors representing customer experience index;
the manufacturing data analysis method is used for establishing a manufacturing data analysis model and specifically comprises the following steps: ，/> representing the overall device efficiency of the ith time zone,/> Representing the device utilization of the ith time zone,/>Representing the takt time of the ith time zone,/>Representing the rejection rate of the ith time zone,/>Representing the production efficiency of the ith time zone,/>Representing the time difference between the i-th time zone and the i-1 th time zone,/>Other influencing factors representing overall device efficiency;
the product quality data analysis method is used for establishing a product quality data analysis model and specifically comprises the following steps: ，/> product quality performance index representing the ith time zone,/> Representing the product return rate of the ith time zone,/>Representing the failure rate of the ith time zone,/>Representing the quality audit passing rate of the ith time zone,/>Quality improvement item success rate representing the ith time zone,/>Other influencing factors representing product quality performance indicators.
Preferably, the industrial internet of things comprehensive analysis method is used for establishing an industrial internet of things comprehensive analysis model, and specifically comprises the following steps:，/> Enterprise comprehensive optimization index for representing target industrial Internet of things (IOT)/> Client experience index representing the ith time zone,/>Representing the overall device efficiency of the ith time zone,/>Product quality performance index representing the ith time zone,/>Business performance index representing the ith time zone,/>Weights representing customer experience indices,/>Weights representing overall device efficiency,/>Weights representing product quality performance indicators,/>Weights representing business performance indicators,/>Other influencing factors of the enterprise comprehensive optimization index representing the target industrial Internet of things.
Preferably, the judging step is used for comprehensively optimizing the enterprise comprehensive optimization index of the target industrial internet of things transmitted in the comprehensive analysis stepAnd a preset enterprise comprehensive optimization index/>, of the target industrial Internet of thingsIn contrast, when/>When the enterprise comprehensive optimization index representing the target industrial Internet of things is larger than the preset enterprise comprehensive optimization index, the enterprise comprehensive performance of the target industrial Internet of things is good, the data processing of the industrial Internet of things on the enterprise is kept, and when/>When the enterprise comprehensive optimization index representing the target industrial Internet of things is smaller than the preset enterprise comprehensive optimization index, the fact that the enterprise comprehensive performance of the target industrial Internet of things is poor is indicated, and man-machine interaction is performed through a data visualization technology.
Preferably, a data processing system for industrial internet of things, comprising:
The data acquisition time dividing module: the method comprises the steps of determining the data acquisition time of a target industrial Internet of things as a target time area, dividing the target time area into sub-time areas in an equal time division mode, and marking the sub-time areas as 1 and 2 … … n in sequence;
And a data acquisition module: the system comprises a data preprocessing module, a client relation data acquisition module, a data preprocessing module and a data processing module, wherein the data preprocessing module is used for acquiring client relation data, manufacturing data, product quality data and resource data of a target industrial Internet of things in each sub-time region;
and a data preprocessing module: the data analysis module is used for preprocessing the data transmitted by the data acquisition module and transmitting the processed data to the data analysis module;
Customer relationship data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing the data of the clients and transmitting the data to the comprehensive analysis module;
Manufacturing data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing manufacturing data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
Product quality data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing product quality data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
and a resource data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing resource data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
and the comprehensive analysis module is used for: the data analysis module is used for comprehensively analyzing the data transmitted by the data analysis module, analyzing the data through the industrial Internet of things comprehensive analysis unit and transmitting an analysis result to the judgment module;
and a judging module: the method is used for judging the enterprise comprehensive optimization index of the target industrial Internet of things.
The invention has the technical effects and advantages that:
The invention can capture the dynamic change of the industrial Internet of things in different time periods more accurately by finely dividing the data acquisition time, thereby providing finer data analysis, providing comprehensive data support for the decision of enterprises by acquiring various types of data including client relation data, manufacturing data, product quality data and resource data, providing more intelligent decision making by the enterprises by the aid of the data, such as client feedback, product quality and other information, helping the enterprises to comprehensively know the operation conditions of the enterprises, making more intelligent decisions, cleaning, sorting and converting the data through the data preprocessing step, improving the quality and usability of the data, helping to reduce errors in the data analysis process, improving the accuracy of the analysis, and displaying the processed data in the form of graphics, charts or animations, so that the data is easier to understand and use, providing powerful data support for the enterprises, helping the enterprises to make more intelligent decision making, improving the operation efficiency, and improving the client satisfaction degree, thereby realizing sustainable development.
Drawings
Fig. 1 is a schematic diagram of the overall structure of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a data processing method for industrial internet of things specifically includes the following steps:
Step 1: data acquisition time division: the method is used for determining the data acquisition time of the target industrial Internet of things as a target time region, dividing the target time region into sub-time regions in an equal time division mode, and marking the sub-time regions as 1 and 2 … … n in sequence.
Step 2: and (3) data acquisition: the method is used for collecting client relation data, manufacturing data, product quality data and resource data of the target industrial Internet of things in each sub-time region, and transmitting the collected data to a data preprocessing step.
The customer relationship data includes a customer feedback quantity, a customer positive feedback quantity, a customer negative feedback quantity, a customer quantity, an attrition customer purchase amount, a customer total purchase amount, a new customer marketing campaign fee, and a new customer quantity, respectively labeled as、/>、/>、/>、/>、/>、/>、/>/>The manufacturing data includes equipment run time, product demand, quantity produced, and quantity of rejects, labeled/>, respectively、/>、/>AndThe product quality data includes total sales quantity, return quantity, inspection quantity, reject quantity, quality audit number, pass quality audit number, quality improvement quantity, quality improvement success quantity, respectively labeled/>、/>、/>、/>、、/>、/>/>The resource data includes total sales, inventory value, raw material costs, direct labor costs, manufacturing costs, liquidity assets, liquidity liabilities, and forecasted sales, respectively labeled/>、/>、/>、/>、、/>、/>/>Where i=1, 2 … … n, i denotes the i-th time region.
The data acquisition step acquires customer relationship data of each sub-time region through customer interaction and sales data, acquires manufacturing data and product quality data of each sub-time region through RFID (radio frequency identification) tags, acquires resource data of each sub-time region through financial data entry, and performs data transmission in a wireless mode and is displayed in a graph, chart or animation mode through a data visualization technology.
Step 3: data preprocessing: the data processing device is used for preprocessing the data transmitted in the data acquisition step and transmitting the processed data to the data analysis step.
The data preprocessing step calculates the customer positive feedback proportion of the ith time zone according to the customer feedback quantity and the customer positive feedback quantity of the ith time zone, and a specific calculation formula is as follows: Calculating the customer negative feedback proportion of the ith time zone according to the customer feedback quantity and the customer negative feedback quantity of the ith time zone, wherein the specific calculation formula is as follows: /(I) Calculating the customer churn rate of the ith time zone according to the number of customers, the number of customers churn, the number of churn customers and the purchase amount of churn customers, wherein the specific calculation formula is as follows: Calculating the new customer acquisition cost of the ith time zone by the new customer marketing campaign cost of the ith time zone and the number of the new customers, wherein the specific calculation formula is as follows: /(I) The equipment utilization rate of the ith time zone is calculated through the equipment running time of the ith time zone and the time difference between the ith time zone and the (i-1) th time zone, and the specific calculation formula is as follows: /(I)The production beat of the ith time zone is calculated through the product demand of the ith time zone and the running time of the equipment, and the specific calculation formula is as follows: /(I)The rejection rate of the ith time zone is calculated through the rejection number and the production number of the ith time zone, and a specific calculation formula is as follows: The production efficiency of the ith time zone is calculated through the production quantity of the ith time zone and the standard production quantity, and a specific calculation formula is as follows: /(I) The product return rate of the ith time zone is calculated through the total sales quantity and the return quantity of the ith time zone, and the specific calculation formula is as follows: /(I)And calculating the failure rate of the ith time zone according to the checking quantity and the failure quantity of the ith time zone, wherein a specific calculation formula is as follows: the quality auditing passing rate of the ith time zone is calculated through the quality auditing times of the ith time zone and the quality auditing times, and the specific calculation formula is as follows: /(I) The success rate of quality improvement items in the ith time zone is calculated by the quality improvement quantity and the quality improvement success quantity of the ith time zone, and a specific calculation formula is as follows: the inventory turnover rate of the ith time zone is calculated through the total sales and the inventory value of the ith time zone, and a specific calculation formula is as follows: /(I) The production cost of the ith time zone is calculated through the raw material cost, the direct labor cost and the manufacturing cost of the ith time zone, and the specific calculation formula is as follows: Calculating the flow ratio of the ith time zone by the flow asset and the flow liability of the ith time zone, wherein the specific calculation formula is as follows: /(I) Calculating the sales prediction accuracy of the ith time zone according to the total sales of the ith time zone, wherein the specific calculation formula is as follows: /(I)And transmitting the processed data to a data analysis step.
The customer relationship data processed by the data preprocessing step comprises a customer positive feedback proportion, a customer negative feedback proportion, a customer churn rate and a new customer acquisition cost, which are respectively marked as、/>、/>/>The manufacturing data includes device utilization, tact, scrap rate, and production efficiency, respectively labeled/>、/>、/>/>The product quality data includes product return rate, failure rate, quality audit pass rate, and quality improvement project success rate, respectively labeled/>、/>、/>/>The resource data includes inventory turnover, production cost, flow rate, and sales forecast accuracy, labeled/>, respectively、/>、/>/>Where i=1, 2 … … n, i denotes the i-th time region.
Step 4: customer relationship data analysis: the data preprocessing step is used for analyzing the client relation data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step.
The customer relationship data analysis method is used for establishing a customer relationship data analysis model and specifically comprises the following steps:，/> client experience index representing the ith time zone,/> Customer positive feedback ratio representing the ith time zone,/>Representing the customer negative feedback proportion of the ith time zone,/>Customer churn rate, representing the ith time zone,/>New customer acquisition cost representing the ith time zone,/>Other influencing factors representing customer experience index.
Step 5: manufacturing data analysis: the method is used for analyzing the manufacturing data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step.
The manufacturing data analysis method is used for establishing a manufacturing data analysis model and specifically comprises the following steps:，/> representing the overall device efficiency of the ith time zone,/> Representing the device utilization of the ith time zone,/>Representing the takt time of the ith time zone,/>Representing the rejection rate of the ith time zone,/>Representing the production efficiency of the ith time zone,/>Representing the time difference between the i-th time zone and the i-1 th time zone,/>Other factors of influence that represent overall device efficiency.
Step 6: product quality data analysis: the method is used for analyzing the product quality data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step.
The product quality data analysis method is used for establishing a product quality data analysis model and specifically comprises the following steps:，/> product quality performance index representing the ith time zone,/> Representing the product return rate of the ith time zone,/>Representing the failure rate of the ith time zone,/>Representing the quality audit passing rate of the ith time zone,/>Quality improvement item success rate representing the ith time zone,/>Other influencing factors representing product quality performance indicators.
Step 7: and (3) analyzing resource data: the method is used for analyzing the resource data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step.
The resource data analysis method is used for establishing a resource data analysis model and specifically comprises the following steps:，/> business performance index representing the ith time zone,/> Inventory turnover rate representing the ith time zone,/>Representing the production cost of the i-th time zone,Representing the flow ratio of the ith time zone,/>Representing sales prediction accuracy of the ith time zone,/>Other influencing factors representing the performance indicators of the business.
Step 8: comprehensive analysis: the data transmitted in the data analysis step is comprehensively analyzed, the analysis is performed through an industrial Internet of things comprehensive analysis method, and the analysis result is transmitted to the judgment step.
The industrial Internet of things comprehensive analysis method is used for establishing an industrial Internet of things comprehensive analysis model and specifically comprises the following steps:，/> Enterprise comprehensive optimization index for representing target industrial Internet of things (IOT)/> Client experience index representing the ith time zone,/>Representing the overall device efficiency of the ith time zone,/>Product quality performance index representing the ith time zone,/>Business performance index representing the ith time zone,/>Weights representing customer experience indices,/>Weights representing the efficiency of the overall device are,Weights representing product quality performance indicators,/>Weights representing business performance indicators,/>Other influencing factors of the enterprise comprehensive optimization index representing the target industrial Internet of things.
Step 9: judging: the method is used for judging the enterprise comprehensive optimization index of the target industrial Internet of things.
The judging step is used for comprehensively optimizing the enterprise comprehensive optimization index of the target industrial Internet of things transmitted in the comprehensive analysis stepAnd a preset enterprise comprehensive optimization index/>, of the target industrial Internet of thingsIn contrast, when/>When the enterprise comprehensive optimization index representing the target industrial Internet of things is larger than the preset enterprise comprehensive optimization index, the enterprise comprehensive performance of the target industrial Internet of things is good, the data processing of the industrial Internet of things on the enterprise is kept, and when/>When the enterprise comprehensive optimization index representing the target industrial Internet of things is smaller than the preset enterprise comprehensive optimization index, the fact that the enterprise comprehensive performance of the target industrial Internet of things is poor is indicated, and man-machine interaction is performed through a data visualization technology.
A data processing system for industrial internet of things, comprising:
The data acquisition time dividing module: the method comprises the steps of determining the data acquisition time of a target industrial Internet of things as a target time area, dividing the target time area into sub-time areas in an equal time division mode, and marking the sub-time areas as 1 and 2 … … n in sequence;
And a data acquisition module: the system comprises a data preprocessing module, a client relation data acquisition module, a data preprocessing module and a data processing module, wherein the data preprocessing module is used for acquiring client relation data, manufacturing data, product quality data and resource data of a target industrial Internet of things in each sub-time region;
and a data preprocessing module: the data analysis module is used for preprocessing the data transmitted by the data acquisition module and transmitting the processed data to the data analysis module;
Customer relationship data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing the data of the clients and transmitting the data to the comprehensive analysis module;
Manufacturing data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing manufacturing data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
Product quality data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing product quality data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
and a resource data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing resource data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
and the comprehensive analysis module is used for: the data analysis module is used for comprehensively analyzing the data transmitted by the data analysis module, analyzing the data through the industrial Internet of things comprehensive analysis unit and transmitting an analysis result to the judgment module;
and a judging module: the method is used for judging the enterprise comprehensive optimization index of the target industrial Internet of things.
According to the method, the data acquisition time of the target industrial Internet of things is divided into sub-time areas and numbered through the data acquisition time dividing step, the client relationship data, the manufacturing data, the product quality data and the resource data of the sub-time areas are acquired through the data acquisition step, the data transmitted through the data acquisition step are preprocessed through the data preprocessing step, the client experience index, the overall equipment efficiency, the product quality performance index and the service performance index of the time areas are calculated through the client relationship data analysis step, the manufacturing data analysis step, the product quality data analysis step and the resource data analysis step, the enterprise comprehensive optimization index of the target industrial Internet of things is calculated through the comprehensive analysis step, and the enterprise comprehensive optimization index of the target industrial Internet of things is judged through the judgment step.
The invention can capture the dynamic change of the industrial Internet of things in different time periods more accurately by finely dividing the data acquisition time, thereby providing finer data analysis, providing comprehensive data support for the decision of enterprises by acquiring various types of data including client relation data, manufacturing data, product quality data and resource data, providing more intelligent decision making by the enterprises by the aid of the data, such as client feedback, product quality and other information, helping the enterprises to comprehensively know the operation conditions of the enterprises, making more intelligent decisions, cleaning, sorting and converting the data through the data preprocessing step, improving the quality and usability of the data, helping to reduce errors in the data analysis process, improving the accuracy of the analysis, and displaying the processed data in the form of graphics, charts or animations, so that the data is easier to understand and use, providing powerful data support for the enterprises, helping the enterprises to make more intelligent decision making, improving the operation efficiency, and improving the client satisfaction degree, thereby realizing sustainable development.
Secondly: in the drawings of the disclosed embodiments, only the structures related to the embodiments of the present disclosure are referred to, and other structures can refer to the common design, so that the same embodiment and different embodiments of the present disclosure can be combined with each other under the condition of no conflict;
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (6)
1. A data processing method for industrial internet of things, comprising:
Step 1: data acquisition time division: the method comprises the steps of determining the data acquisition time of a target industrial Internet of things as a target time area, dividing the target time area into sub-time areas in an equal time division mode, and marking the sub-time areas as 1 and 2 … … n in sequence;
step 2: and (3) data acquisition: the method comprises the steps of acquiring client relation data, manufacturing data, product quality data and resource data of a target industrial Internet of things in each sub-time region, and transmitting the acquired data to a data preprocessing step;
Step 3: data preprocessing: the data processing device is used for preprocessing the data transmitted in the data acquisition step and transmitting the processed data to the data analysis step;
step 4: customer relationship data analysis: the data preprocessing step is used for analyzing the client relationship data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step;
the customer relationship data analysis is used for establishing a customer relationship data analysis model, and specifically comprises the following steps: ，/> client experience index representing the ith time zone,/> Customer positive feedback ratio representing the ith time zone,/>Representing the customer negative feedback proportion of the ith time zone,/>Customer churn rate, representing the ith time zone,/>New customer acquisition cost representing the ith time zone,/>Other influencing factors representing customer experience index;
Step 5: manufacturing data analysis: the manufacturing data transmission step is used for analyzing the manufacturing data transmitted in the data preprocessing step, and transmitting the data obtained by analysis to the comprehensive analysis step;
the manufacturing data analysis is used for establishing a manufacturing data analysis model, and is specifically expressed as follows: ，/> representing the overall device efficiency of the ith time zone,/> Representing the device utilization of the ith time zone,/>The tact time of the i-th time zone is represented,Representing the rejection rate of the ith time zone,/>Representing the production efficiency of the ith time zone,/>Representing the time difference between the i-th time zone and the i-1 th time zone,/>Other influencing factors representing overall device efficiency;
step 6: product quality data analysis: the product quality data transmitted in the data preprocessing step are analyzed, and the data obtained by analysis are transmitted to the comprehensive analysis step;
The product quality data analysis is used for establishing a product quality data analysis model, and specifically comprises the following steps: ，/> product quality performance index representing the ith time zone,/> Representing the product return rate of the ith time zone,/>Representing the failure rate of the ith time zone,Representing the quality audit passing rate of the ith time zone,/>Quality improvement item success rate representing the ith time zone,/>Other influencing factors representing product quality performance indicators;
Step 7: and (3) analyzing resource data: the comprehensive analysis step is used for analyzing the resource data transmitted in the data preprocessing step and transmitting the data obtained by analysis to the comprehensive analysis step;
Step 8: comprehensive analysis: the data transmitted in the data analysis step is comprehensively analyzed, the analysis is carried out through an industrial Internet of things comprehensive analysis method, and the analysis result is transmitted to the judgment step;
The industrial Internet of things comprehensive analysis method is used for establishing an industrial Internet of things comprehensive analysis model and specifically comprises the following steps: ，/> Enterprise comprehensive optimization index for representing target industrial Internet of things (IOT)/> Client experience index representing the ith time zone,/>Representing the overall device efficiency of the ith time zone,/>Product quality performance index representing the ith time zone,/>Business performance index representing the ith time zone,/>Weights representing customer experience indices,/>Weights representing overall device efficiency,/>Weights representing product quality performance indicators,/>Weights representing business performance indicators,/>Other influencing factors representing enterprise comprehensive optimization indexes of the target industrial Internet of things;
step 9: judging: the method is used for judging the enterprise comprehensive optimization index of the target industrial Internet of things.
2. The data processing method for industrial internet of things according to claim 1, wherein: the customer relationship data includes a customer feedback quantity, a customer positive feedback quantity, a customer negative feedback quantity, a customer quantity, an attrition customer purchase amount, a customer total purchase amount, a new customer marketing campaign fee, and a new customer quantity, respectively labeled as、/>、/>、/>、/>、/>、/>、/>/>The manufacturing data includes equipment run time, product demand, quantity produced, and quantity of rejects, labeled/>, respectively、/>、/>/>The product quality data includes total sales quantity, return quantity, inspection quantity, reject quantity, quality audit number, pass quality audit number, quality improvement quantity, quality improvement success quantity, respectively labeled/>、/>、/>、/>、/>、/>、/>/>The resource data includes total sales, inventory value, raw material costs, direct labor costs, manufacturing costs, liquidity assets, liquidity liabilities, and forecasted sales, respectively labeled/>、/>、/>、/>、/>、/>、/>/>Where i=1, 2 … … n, i denotes the i-th time region.
3. The data processing method for industrial internet of things according to claim 1, wherein: the data acquisition step acquires customer relationship data of each sub-time region through customer interaction and sales data, acquires manufacturing data and product quality data of each sub-time region through RFID (radio frequency identification) tags, acquires resource data of each sub-time region through financial data entry, and performs data transmission in a wireless mode and is displayed in a graph, chart or animation mode through a data visualization technology.
4. The data processing method for industrial internet of things according to claim 1, wherein: the data preprocessing step calculates the customer positive feedback proportion of the ith time zone according to the customer feedback quantity and the customer positive feedback quantity of the ith time zone, and a specific calculation formula is as follows: Calculating the customer negative feedback proportion of the ith time zone according to the customer feedback quantity and the customer negative feedback quantity of the ith time zone, wherein the specific calculation formula is as follows: Calculating the customer churn rate of the ith time zone according to the number of customers, the number of customers churn, the number of churn customers and the purchase amount of churn customers, wherein the specific calculation formula is as follows: /(I) Calculating the new customer acquisition cost of the ith time zone by the new customer marketing campaign cost of the ith time zone and the number of the new customers, wherein the specific calculation formula is as follows: /(I)The equipment utilization rate of the ith time zone is calculated through the equipment running time of the ith time zone and the time difference between the ith time zone and the (i-1) th time zone, and the specific calculation formula is as follows: /(I)The production beat of the ith time zone is calculated through the product demand of the ith time zone and the running time of the equipment, and the specific calculation formula is as follows: /(I)The rejection rate of the ith time zone is calculated through the rejection number and the production number of the ith time zone, and a specific calculation formula is as follows: /(I)The production efficiency of the ith time zone is calculated through the production quantity of the ith time zone and the standard production quantity, and a specific calculation formula is as follows: /(I)The product return rate of the ith time zone is calculated through the total sales quantity and the return quantity of the ith time zone, and the specific calculation formula is as follows: /(I)And calculating the failure rate of the ith time zone according to the checking quantity and the failure quantity of the ith time zone, wherein a specific calculation formula is as follows: /(I)The quality auditing passing rate of the ith time zone is calculated through the quality auditing times of the ith time zone and the quality auditing times, and the specific calculation formula is as follows: /(I)The success rate of quality improvement items in the ith time zone is calculated by the quality improvement quantity and the quality improvement success quantity of the ith time zone, and a specific calculation formula is as follows: /(I)The inventory turnover rate of the ith time zone is calculated through the total sales and the inventory value of the ith time zone, and a specific calculation formula is as follows: /(I)The production cost of the ith time zone is calculated through the raw material cost, the direct labor cost and the manufacturing cost of the ith time zone, and the specific calculation formula is as follows: /(I)Calculating the flow ratio of the ith time zone by the flow asset and the flow liability of the ith time zone, wherein the specific calculation formula is as follows: /(I)Calculating the sales prediction accuracy of the ith time zone according to the total sales of the ith time zone, wherein the specific calculation formula is as follows: /(I)And transmitting the processed data to a data analysis step.
5. The data processing method for industrial internet of things according to claim 1, wherein: the judging step is used for comprehensively optimizing the enterprise comprehensive optimization index of the target industrial Internet of things transmitted in the comprehensive analysis stepAnd a preset enterprise comprehensive optimization index/>, of the target industrial Internet of thingsIn contrast, when/>When the enterprise comprehensive optimization index representing the target industrial Internet of things is larger than the preset enterprise comprehensive optimization index, the enterprise comprehensive performance of the target industrial Internet of things is good, the data processing of the industrial Internet of things on the enterprise is kept, and when/>When the enterprise comprehensive optimization index representing the target industrial Internet of things is smaller than the preset enterprise comprehensive optimization index, the fact that the enterprise comprehensive performance of the target industrial Internet of things is poor is indicated, and man-machine interaction is performed through a data visualization technology.
6. A data processing system for industrial internet of things, for implementing a data processing method for industrial internet of things according to any one of the preceding claims 1-5, comprising:
The data acquisition time dividing module: the method comprises the steps of determining the data acquisition time of a target industrial Internet of things as a target time area, dividing the target time area into sub-time areas in an equal time division mode, and marking the sub-time areas as 1 and 2 … … n in sequence;
And a data acquisition module: the system comprises a data preprocessing module, a client relation data acquisition module, a data preprocessing module and a data processing module, wherein the data preprocessing module is used for acquiring client relation data, manufacturing data, product quality data and resource data of a target industrial Internet of things in each sub-time region;
and a data preprocessing module: the data analysis module is used for preprocessing the data transmitted by the data acquisition module and transmitting the processed data to the data analysis module;
Customer relationship data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing the data of the clients and transmitting the data to the comprehensive analysis module;
Manufacturing data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing manufacturing data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
Product quality data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing product quality data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
and a resource data analysis module: the system comprises a data preprocessing module, a comprehensive analysis module and a data processing module, wherein the data preprocessing module is used for preprocessing resource data transmitted by the data preprocessing module and transmitting the data obtained by the analysis to the comprehensive analysis module;
and the comprehensive analysis module is used for: the data analysis module is used for comprehensively analyzing the data transmitted by the data analysis module, analyzing the data through the industrial Internet of things comprehensive analysis unit and transmitting an analysis result to the judgment module;
and a judging module: the method is used for judging the enterprise comprehensive optimization index of the target industrial Internet of things.
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