Industrial digital operation information storage management method and system

Abstract

The invention relates to the technical field of big data resource service, in particular to an industrial digital operation information storage management method and system, and the method comprises the steps: obtaining industrial digital operation information in a preset time period; determining a plurality of maximum values, maximum values and minimum values of the industrial digital operation information in a predetermined time period; according to the maximum value, the maximum value and the minimum value, determining the local protrusion; determining the influence according to the historical industrial digital operation information and the quality detection result of the plurality of historical time periods; determining the average local prominence of the local prominence of the historical industrial digital operation information; determining a storage priority according to the local prominence, the average local prominence and the influence of the industrial digital operation information; and determining a target storage device according to a preset corresponding relationship between the storage priority level and the storage device. In this way, waste of storage resources is avoided, and the management efficiency of industrial digital operation information is improved.

Description

Technical Field

[0001] The present invention relates to the field of big data resource service technology, and in particular to a method and system for storing and managing industrial digital operation information. Background Art

[0002] With the rapid development of information technology, enterprises are facing a rapidly changing production environment. Various industries such as manufacturing, energy, and logistics are increasingly undergoing digital transformation. In digital industries, a large amount of industry digital operation information is usually generated. Industry digital operation information includes production data, equipment status, supply chain information, and market trend analysis. These industry digital operation information plays a key role in the production planning, resource allocation, and marketing strategies of enterprises.

[0003] In some scenarios, the industrial digital operation information storage management method and system integrate, process and store various industrial digital operation information through big data processing technology. However, when storing various industrial digital operation information, different types of information from different data sources are integrated and stored in the same storage device, so the remaining storage resources will be wasted. In addition, when all industrial digital operation information is integrated and stored, when encountering abnormal situations, all industrial digital operation information needs to be analyzed and managed one by one, which makes it difficult to effectively manage industrial digital operation information, and the management efficiency of industrial digital operation information is low. Summary of the invention

[0004] In order to solve the technical problems of wasted storage resources and low management efficiency of industrial digital operation information, the purpose of the present invention is to provide an industrial digital operation information storage management method and system, and the technical solutions adopted are as follows:

[0005] In the first aspect, an embodiment of the present application provides a method for storing and managing industrial digital operation information, including: obtaining industrial digital operation information within a predetermined time period, the industrial digital operation information including various types of data in the processing process of the industry in producing products; determining multiple maximum values, maximum values ​​and minimum values ​​of the industrial digital operation information within the predetermined time period; determining the local prominence of each type of industrial digital operation information based on each of the maximum values, maximum values ​​and minimum values, the local prominence representing the importance of the type of industrial digital operation information to the industrial production, and the local prominence being proportional to the importance; determining based on historical industrial digital operation information for multiple historical time periods and quality inspection results of products produced in multiple historical time periods. The influence of each type of industrial digital operation information, wherein the influence represents the degree of influence of the type of industrial digital operation information on industrial production; determining the average local prominence of the local prominence of each type of historical industrial digital operation information in multiple historical time periods; determining the storage priority of the various types of industrial digital operation information according to the local prominence of each type of industrial digital operation information, the average local prominence and the influence; determining the target storage device for each type of industrial digital operation information according to the correspondence between the preset storage priority level and the storage device, so as to store the industrial digital operation information of each type in the target storage device, wherein the industrial digital operation information of different storage priorities is classified and stored in different target storage devices.

[0006] Optionally, determining the local prominence of each type of industrial digital operation information based on each of the maximum values, the maximum value and the minimum value includes: determining the degree of disorder of each type of industrial digital operation information based on each of the maximum values, the maximum value and the minimum value, the degree of disorder characterizing the degree of fluctuation of the industrial digital operation information, and the degree of fluctuation is inversely proportional to the importance of the industrial digital operation information; determining the local prominence of the current type of industrial digital operation information based on the degree of disorder of the current type of industrial digital operation information and the degree of disorder of other types of industrial digital operation information.

[0007] Optionally, determining the disorder degree of each type of the digital operation information of the industry according to the maximum value, the maximum value and the minimum value includes: calculating the first difference between any two maximum values ​​to obtain n groups of first differences, and taking the absolute value of each of the first differences and superimposing them to obtain a first superposition value, wherein n is a natural number greater than 0; calculating the second difference between the maximum value and the minimum value; and determining the ratio of the product of the first superposition value and the second difference to n as the disorder degree.

[0008] Optionally, determining the local prominence of the current type of industrial digital operation information based on the disorder degree of the current type of industrial digital operation information and the disorder degree of other types of industrial digital operation information includes: calculating in sequence the third differences between the disorder degree of the current type of industrial digital operation information and the disorder degree of other types of industrial digital operation information to obtain M groups of third differences, and taking the absolute value of each of the third differences and superimposing them to obtain a second superposition value, where M is the number of types of other types of industrial digital operation information; calculating a first ratio of the disorder degree of the current type of industrial digital operation information to M; and determining the product of the first ratio and the second superposition value as the local prominence.

[0009] Optionally, determining the influence of each type of industry digital operation information based on historical industry digital operation information of multiple historical time periods and quality inspection results of products produced in multiple historical time periods includes: performing curve fitting on the historical industry digital operation information of multiple historical time periods to obtain a data characteristic curve, wherein the horizontal axis of the data characteristic curve is the identifier of the historical time period, and the vertical axis of the data characteristic curve is the fluctuation variance of the historical industry digital operation information; performing curve fitting on the quality inspection results of products produced in the multiple historical time periods to obtain a quality inspection result curve, wherein the horizontal axis of the quality inspection result curve is the identifier of the historical time period, and the vertical axis of the quality inspection result curve is the numerical value of the quality inspection result; calculating a first slope value according to any adjacent data points in the data characteristic curve to obtain N groups of first slope values, and calculating a second slope value according to any adjacent data points in the quality inspection result curve to obtain N groups of second slope values, wherein N is a natural number greater than 0; and calculating the influence of each type of industry digital operation information according to each of the first slope values ​​and each of the second slope values.

[0010] Optionally, calculating the influence of each type of industrial digital operation information based on each of the first slope values ​​and each of the second slope values ​​includes: calculating the fourth difference between the first slope value and the corresponding second slope value to obtain N groups of fourth differences, and taking the absolute value of each of the fourth differences and superimposing them to obtain a third superimposed value; determining the second ratio of the third superimposed value to the N as the influence.

[0011] Optionally, determining the storage priority of each type of industrial digital operation information according to the local prominence of each type of industrial digital operation information, the average local prominence and the influence includes: determining the fault tolerance of the current type of industrial digital operation information according to the local prominence of the current type of industrial digital operation information and the average local prominence, the fault tolerance indicating the degree of abnormality of the current type of industrial digital operation information, and the fault tolerance is inversely proportional to the degree of abnormality; determining the storage priority of each type of industrial digital operation information according to the local prominence of each type of industrial digital operation information, the fault tolerance and the influence.

[0012] Optionally, determining the storage priority of each type of industrial digital operation information based on the local prominence, the fault tolerance and the influence of each type of industrial digital operation information includes: calculating a third ratio of the local prominence to the fault tolerance; normalizing the third ratio and the influence by using a hyperbolic tangent function to obtain a normalized ratio and a normalized influence; and determining the product of the normalized ratio and the normalized influence as the storage priority.

[0013] Optionally, based on the correspondence between preset storage priority levels and storage devices, determining the target storage device for each type of industrial digital operation information includes: if the storage priority of the type of industrial digital operation information is at a first storage priority level, determining the target storage device for the type of industrial digital operation information to be a high-speed solid-state drive or memory; if the storage priority of the type of industrial digital operation information is at a second storage priority level, determining the target storage device for the type of industrial digital operation information to be a disk or a cloud storage device, and the first storage priority level is higher than the second storage priority level.

[0014] In the second aspect, an embodiment of the present application provides an industrial digital operation information storage and management system, which includes: a processor and a memory; wherein the memory is used to store computer programs that can be run on the processor; the processor is used to execute the programs stored in the memory to implement the steps of the industrial digital operation information storage and management method mentioned in the first aspect above.

[0015] The present invention has the following beneficial effects: by acquiring the digital operation information of the industry within a predetermined time period, the digital operation information of the industry includes various types of data in the processing process of the industry in producing products; then determining multiple maxima, maximum values ​​and minimum values ​​of the digital operation information of the industry within the predetermined time period; then determining the local prominence of each type of digital operation information of the industry according to each maximum value, maximum value and minimum value, the local prominence of each type of digital operation information of the industry is determined, the local prominence characterizes the importance of the digital operation information of the industry to the industrial production, and the local prominence is proportional to the importance; secondly, according to the historical digital operation information of the industry in multiple historical time periods and the quality inspection results of the products produced in multiple historical time periods, the influence of each type of digital operation information of the industry is determined, and the influence characterizes the degree of influence of the digital operation information of the industry on the industrial production; and determining the average local prominence of the local prominence of each type of historical digital operation information of the industry in multiple historical time periods; according to the local prominence, average local prominence and influence of each type of digital operation information of the industry, the storage priority of each type of digital operation information of the industry is determined; finally, according to the correspondence between the preset storage priority level and the storage device, the target storage device of each type of digital operation information of the industry is determined, so as to store the digital operation information of the industry of the current type in the target storage device, wherein the digital operation information of the industry with different storage priorities is classified and stored in different target storage devices.

[0016] In this way, this application first determines the local prominence of the industry digital operation information, and then determines the influence of the industry digital operation information based on the historical industry digital operation information in the historical records, and finally judges the storage priority of this type of industry digital operation information, and then classifies and stores the industry digital operation information. Allocate storage resources according to the actual situation of the industry digital operation information to avoid storing all types of data on the same device and wasting the remaining storage resources. If the same device is a high-cost storage device, it can also effectively save storage costs. By classifying and storing different types of industry digital operation information, industry digital operation information can be located more quickly, thereby more effectively managing the data life cycle and improving the management efficiency of industry digital operation information. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1A flowchart of a method for storing and managing industrial digital operation information provided by an embodiment of the present invention;

[0019] Figure 2 A change curve of industrial digital operation information of industrial digital operation information provided by an embodiment of the present invention;

[0020] Figure 3 A fluctuation fitting curve of monitoring data characteristics of various types of industrial digital operation information in different production batches provided by an embodiment of the present invention;

[0021] Figure 4 A fluctuation fitting curve of quality inspection results of different production batches of a certain type of industrial digital operation information provided by an embodiment of the present invention;

[0022] Figure 5 A schematic diagram of the structure of an industrial digital operation information storage and management system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of an industrial digital operation information storage and management method proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0024] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0025] The specific scheme of the industrial digital operation information storage and management method provided by the present invention is described in detail below with reference to the accompanying drawings.

[0026] Embodiment 1:

[0027] See also Figure 1 , which shows a flow chart of an industrial digital operation information storage management method provided by an embodiment of the present invention, including:

[0028] Step S101, obtaining industry digital operation information within a predetermined time period.

[0029] Among them, industry digital operation information includes various types of data in the process of industry producing products.

[0030] Specifically, the length of the scheduled time period can be determined according to the actual situation, such as the length of the scheduled time period can be configured as 5 minutes. The source of industry digital operation information can be from multiple internal systems, external suppliers, partners or public data sources. When obtaining industry digital operation information from each data source, technical means such as application programming interface (API) calls, database queries, file transfers, web crawlers and sensor data can be used.

[0031] Furthermore, the industry digital operation information includes multiple types, which are not limited to the following:

[0032] (1) The production data and process parameters of the industry during the production process of the product. These data cover various types of parameters and indicators in the production process, such as the operating speed, temperature, pressure and humidity of the production line. These types of data are crucial to production efficiency and quality control.

[0033] (2) Equipment status and maintenance records: including equipment operating status, fault information, maintenance records, maintenance plans, etc. This information helps predict the health of equipment, reduce downtime and optimize maintenance arrangements.

[0034] (3) Quality control and inspection data: covers information such as product quality test results, defective rates, quality control indicators, etc. This data is used to ensure that products meet quality standards and support continuous improvement and problem solving.

[0035] The subsequent storage of these industrial operation information may involve network transmission, batch import, and real-time stream processing. Loading these industrial operation information into the storage system and determining the integrity and accessibility of data storage involve database management systems, data warehouses, and distributed storage systems.

[0036] Furthermore, in the actual processing process, since industry-related digital operation information may involve multiple data sources and a large amount of real-time data, if industry digital operation information is obtained from multiple sources at the same time, it may lead to inconsistencies in data formats, units or standards, requiring data integration and standardization.

[0037] In the industry digital operation information, the industry digital operation information in different event streams has different storage requirements and importance. For example, in the production process of the product, it generally includes several links such as product design, raw material procurement, production and processing, quality control, finished product packaging, inventory and distribution, and the industry digital operation information in the production and processing process has a relatively important position. It can make up for the deficiencies in the previous event flow, but if the data response capability of this link is not enough, it may cause irreversible effects on subsequent links. Therefore, in the embodiment of the present application, the data of the product in the production and processing process is analyzed and explained, that is, the production data and process parameters of the industry in the processing process of the product. Equipment status and maintenance records can be stored in high-speed solid-state hard drives or memory, and quality control and inspection data can be stored in disk storage or cloud storage. Storing equipment status and maintenance records and quality control and inspection data separately can effectively utilize storage resources, avoid waste of storage resources, and manage these data more effectively.

[0038] The digital operation information of the industry within the predetermined time period can be obtained by using sensor equipment to monitor and obtain monitoring data in the production and processing of products within the monitoring time, including but not limited to temperature, pressure, production line speed, humidity and other types of digital operation information of the industry. The monitoring time can be 5 minutes.

[0039] Step S102, determining multiple maxima, maximum values ​​and minimum values ​​of the industry digital operation information within a predetermined time period.

[0040] Specifically, analyze the changes in each type of industry digital operation information, and present the industry digital operation information within a predetermined time period in the form of a change curve. Obtain all the maximum value points in the change curve of the industry digital operation information in this section, and mark the data value corresponding to each maximum value point, which is the maximum value. There are also maximum and minimum values ​​in the change curve of the industry digital operation information in this section.

[0041] Step S103, determining the local prominence of each type of industrial digital operation information according to each maximum value, maximum value and minimum value.

[0042] Among them, the local prominence represents the importance of industrial digital operation information to industrial production, and the local prominence is positively proportional to the importance.

[0043] Specifically, the production and processing links also contain a large number of different types of industrial digital operation information. Processing these industrial digital operation information at the same time may result in untimely response to abnormal situations, or the simultaneous storage of a large amount of industrial digital operation information may cause some important information to be lost. Classified storage of industrial digital operation information can deal with the problem of untimely response to locally prominent industrial digital operation information. Therefore, the local prominence of each type of industrial digital operation information can be determined through the maximum, maximum and minimum values, and the local prominence can be used to indicate the importance of a certain type of industrial digital operation information to industrial production.

[0044] As an optional embodiment of the present application, determining the local prominence of each type of industrial digital operation information based on each maximum value, maximum value and minimum value includes: determining the degree of disorder of each type of industrial digital operation information based on each maximum value, maximum value and minimum value, the degree of disorder characterizing the degree of fluctuation of the industrial digital operation information, and the degree of fluctuation is inversely proportional to the importance of the industrial digital operation information; determining the local prominence of the current type of industrial digital operation information based on the degree of disorder of the current type of industrial digital operation information and the degree of disorder of other types of industrial digital operation information.

[0045] Specifically, a large number of different types of industrial digital operation information are included in the production and processing links. Processing these industrial digital operation information at the same time may result in untimely response to abnormal situations, or the simultaneous storage of a large amount of industrial digital operation information may cause some important information to be lost. Industrial digital operation information should have a high response to locally prominent industrial digital operation information. Therefore, the importance and authenticity of industrial digital operation information can be analyzed by calculating the local prominence of industrial digital operation information.

[0046] Among them, when calculating the local prominence of industrial digital operation information, it can be determined by the degree of disorder of industrial digital operation information. The degree of disorder can characterize the degree of fluctuation of industrial digital operation information. During the production and processing of products, industrial digital operation information should be kept within a stable range of changes. The greater the degree of fluctuation of industrial digital operation information, the greater the degree of disorder of this type of industrial digital operation information, the more unstable the industrial digital operation information, that is, the lower the importance of industrial digital operation information. As an optional embodiment of the present application, determining the degree of disorder of each type of industrial digital operation information according to each maximum value, maximum value and minimum value includes: calculating the first difference between any two maximum values ​​to obtain n groups of first differences, and taking the absolute value of each first difference and superimposing them to obtain a first superposition value, where n is a natural number greater than 0; calculating the second difference between the maximum value and the minimum value; determining the ratio of the product of the first superposition value and the second difference to n as the degree of disorder.

[0047] Specifically, the degree of disorder can be calculated by the following formula:

[0048]

[0049] In the above formula, JK r It represents the disorder degree of digital operation information of the rth category of industry in the current monitoring scheduled time period, U i It represents the monitoring value of the digital operation information of the rth category of industry at the i-th maximum point in the monitoring process during the current scheduled monitoring period; similarly, U j It represents the monitoring value at the jth maximum point in the digital operation information of the industry of the rth category; where i is not equal to j. There is a set of differences between the monitoring values ​​represented by any two maximum points, k represents one of the differences; there are n sets of differences in total; ΔU represents the extreme difference in the monitoring curve of the predetermined time period, that is, the difference between the maximum and minimum values ​​in the digital operation information of the industry in the monitoring curve of the predetermined time period.

[0050] Furthermore, It indicates the disorder degree of the digital operation information of the rth category of industries. The greater the disorder degree, the more disordered the fluctuation of the digital operation information of this category of industries during the monitoring period. Under normal circumstances, during the production and processing of products, the monitored digital operation information of industries should be kept within a stable range of changes; that is, the digital operation information of the rth category of industries may have a relatively high degree of importance. The greater the disorder degree of the fluctuation of the digital operation information of industries, the more unstable the digital operation information of industries, and the lower the importance of the digital operation information of this category of industries.

[0051] As an optional embodiment of the present application, determining the local prominence of the current type of industrial digital operation information according to the disorder degree of the current type of industrial digital operation information and the disorder degree of other types of industrial digital operation information includes: calculating the third differences between the disorder degree of the current type of industrial digital operation information and the disorder degree of other types of industrial digital operation information in sequence to obtain M groups of third differences, and taking the absolute value of each third difference and superimposing them to obtain a second superposition value, where M is the number of types of other types of industrial digital operation information; calculating a first ratio of the disorder degree of the current type of industrial digital operation information to M; and determining the product of the first ratio and the second superposition value as the local prominence.

[0052] Specifically, the local protrusion can be calculated using the following formula:

[0053]

[0054] In the above formula, P r It represents the local prominence of the digital operation information of the r-th industry, JK r It indicates the disorder degree of digital operation information of the r-th industry; JK u It represents the degree of disorder of the u-th category of industrial digital operation information in the production process; it is assumed that in addition to the r-th category of industrial digital operation information, there are M categories of industrial digital operation information that can be monitored by sensors.

[0055] Furthermore, It represents the local prominence of the digital operation information of this type of industry. The greater the local prominence, the higher the degree of disorder of the digital operation information of this type of industry and the greater the difference in disorder between the digital operation information of this type of industry and the digital operation information of other industries. That is, among all the digital operation information of all industries, the higher the local prominence of the digital operation information of this type of industry, which further indicates that the digital operation information of this type of industry is of certain importance for product production. In order to ensure the authenticity of the importance of the data, the authenticity of the importance of the digital operation information of this industry can be further analyzed.

[0056] Step S104, determining the influence of various types of industry digital operation information based on historical industry digital operation information in multiple historical time periods and quality inspection results of products produced in multiple historical time periods.

[0057] Among them, the influence representation type of industrial digital operation information affects the degree of influence on industrial production.

[0058] Specifically, it is not supported to evaluate the importance of a type of digital operation information of an industry based only on the changes in the digital operation information of that industry and its local prominence, and it should be verified from other data. For example, the contribution of the digital operation information of that industry to product production can be further verified based on the changes in different batches of digital operation information in historical records.

[0059] In the storage management system of industrial digital operation information, a large amount of historical batches of industrial digital operation information will be stored, and then the monitoring data of each batch of products in the production and processing process will be obtained, such as Figure 2 As shown, the monitoring data of a certain type of industry digital operation information can be reflected in the form of a curve. For a certain type of industry digital operation information, the degree of fluctuation of the industry digital operation information monitored in a batch can be expressed according to the fluctuation variance of the curve in the historical monitoring time period. The length of the historical monitoring time period can be a period of time or the entire production and processing link.

[0060] Furthermore, each batch of products will be subject to quality inspection and a quality inspection report will be issued, and the inspection result page of the quality inspection report of the batch of products will be extracted. For example, the qualified rate of the first batch of products extracted is 92%.

[0061] As an optional embodiment of the present application, determining the influence of various types of industrial digital operation information based on historical industrial digital operation information of multiple historical time periods and quality inspection results of products produced in multiple historical time periods includes: curve fitting the historical industrial digital operation information of multiple historical time periods to obtain a data characteristic curve, the horizontal axis of the data characteristic curve is the identifier of the historical time period, and the vertical axis of the data characteristic curve is the fluctuation variance of the historical industrial digital operation information; curve fitting the quality inspection results of products produced in multiple historical time periods to obtain a quality inspection result curve, the horizontal axis of the quality inspection result curve is the identifier of the historical time period, and the vertical axis of the quality inspection result curve is the numerical value of the quality inspection result; calculating a first slope value according to any adjacent data points in the data characteristic curve to obtain N groups of first slope values, calculating a second slope value according to any adjacent data points in the quality inspection result curve to obtain N groups of second slope values, where N is a natural number greater than 0; calculating the influence of various types of industrial digital operation information according to each first slope value and each second slope value.

[0062] Specifically, the industrial digital operation information of different batches of products within the monitoring period can be curve fitted, such as Figure 3As shown in the figure, it shows the fluctuation of the monitoring data characteristics (variance) of the industrial digital operation information of the rth, uth, eth and qth categories in different production batches. The horizontal axis represents the batch information in the historical records, and the vertical axis represents the fluctuation variance of the industrial digital operation information monitored during the production and processing of the product. Then the quality inspection results of different batches are curve fitted in the same way, and the obtained curve is as follows Figure 4 As shown. In the fitting curves of different batches of the digital operation information of the rth category of industries, there is a set of slope values ​​between two adjacent data points, and in the fitting curve of the quality inspection, a set of slope values ​​can also be calculated between adjacent data points. Among them, the slope value can be calculated according to the coordinate point of the data point in the coordinate system, and the slope value can be the ratio of the difference between the ordinate and the abscissa of the data point. The fluctuation variance can be calculated according to the numerical value of the digital operation information of the batch of industries. The calculation of the fluctuation variance can refer to the calculation method in the prior art, and the embodiments of the present application will not be repeated here. The numerical value of the quality inspection result can be the product qualification rate.

[0063] When calculating the influence, as an optional embodiment of the present application, calculating the influence of each type of industrial digital operation information according to each first slope value and each second slope value includes: calculating the fourth difference between the first slope value and the corresponding second slope value to obtain N groups of fourth differences, and taking the absolute value of each fourth difference and superimposing them to obtain a third superposition value; determining the second ratio of the third superposition value to N as the influence.

[0064] Specifically, the influence can be calculated using the following formula:

[0065]

[0066] In the above formula, JF r Indicates the influence of digital operation information of the rth industry, The bth group of slope values ​​(first slope values) in the characteristic fitting curve of the rth category of industry digital operation information in the fitting curve of the historical batch of industry digital operation information represented by ; It represents the slope value (second slope value) of group b in the fitting curve of the quality inspection results of the digital operation information of the R-th industry in the historical batch; it is assumed that there are N groups of first slope values ​​and second slope values.

[0067] in, It indicates the influence of this type of operation information data on industrial production. The greater the influence, the greater the impact of fluctuations in this type of digital operation information on product quality in the actual industrial operation process, that is, the importance may be relatively high. If the fluctuation of this type of digital operation information has little to do with the overall production process or product, its importance may be relatively low. This step mainly further highlights the importance of digital operation information based on the changes in digital operation information in historical batches, and provides data support for the subsequent storage and management methods of digital operation information.

[0068] Step S105 , determining the average local prominence of the local prominence of each type of historical industry digital operation information in multiple historical time periods.

[0069] Specifically, for qualified products produced in historical records, the difference between the industrial digital operation information monitored in the production and processing links of qualified products can be used as a fault tolerance reference for the operation information storage and management system in the current production process to further reflect the abnormality of the industrial digital operation information in the current monitoring time period. Therefore, the average local prominence can be determined through the historical industrial digital operation information in the historical monitoring time period, and then the average local prominence can be used to determine the storage priority of the industrial digital operation information.

[0070] The local prominence of the historical industry digital operation information can be calculated according to the calculation formula of the local prominence recorded in the above embodiment. To express.

[0071] Step S106, determining the storage priority of each type of industry digital operation information according to the local prominence, average local prominence and influence of each type of industry digital operation information.

[0072] Specifically, all industrial digital operation information of batches with a pass rate between 98% and 100% in historical batches can be obtained separately, and the fluctuation degree of the rth category of industrial digital operation information during the production and processing of these batches of products and the difference between the rth category of industrial digital operation information and other categories of industrial digital operation information can be obtained.

[0073] Furthermore, for a large amount of industrial digital operation information, the industrial digital operation information of important links should have a faster response speed, that is, the storage management method and system should perform faster storage operations on this type of industrial digital operation information so that the system can respond to abnormal situations more quickly. Among them, the storage priority can be used to characterize which storage device each industrial digital operation information should be stored in. The storage priority refers to the storage level of the industrial digital operation information in the corresponding storage device. The industrial digital operation information with a high storage priority can be stored in a storage device with a higher storage level.

[0074] As an optional embodiment of the present application, determining the storage priority of each type of industrial digital operation information according to the local prominence, average local prominence and influence of each type of industrial digital operation information includes: determining the fault tolerance of the current type of industrial digital operation information according to the local prominence and average local prominence of the current type of industrial digital operation information, the fault tolerance indicating the degree of abnormality of the current type of industrial digital operation information, and the fault tolerance is inversely proportional to the degree of abnormality; determining the storage priority of each type of industrial digital operation information according to the local prominence, fault tolerance and influence of each type of industrial digital operation information.

[0075] Specifically, fault tolerance can be calculated using the following formula:

[0076]

[0077] In the above formula, JH r represents fault tolerance, P r It indicates the local prominence of the digital operation information of the r-th industry in the current monitoring period. It represents the average value of the local prominence of the digital operation information of the rth industry in the selected historical batches (average local prominence).

[0078] in, The fault tolerance of the fluctuation of the digital operation information of the r-th industry within the current scheduled time period is represented by JH r The smaller it is, the higher the abnormality of the current digital operation information of the r-th industry; if the average value of the local prominence of historical batches (average local prominence) is relatively low, and the local prominence in the currently monitored predetermined time period is also low, then it means that the current change of the digital operation information of the r-th industry is within a relatively acceptable range, indicating that the system has good fault tolerance for the digital operation information of the r-th industry.

[0079] As an optional embodiment of the present application, determining the storage priority of various types of industrial digital operation information according to the local prominence, fault tolerance and influence of each type of industrial digital operation information includes: calculating a third ratio of local prominence to fault tolerance; normalizing the third ratio and the influence respectively using a hyperbolic tangent function to obtain a normalized ratio and a normalized influence; and determining the product of the normalized ratio and the normalized influence as the storage priority.

[0080] Specifically, the storage priority can be calculated using the following formula:

[0081]

[0082] In the above formula, F is the storage priority of the digital operation information of the rth industry, P r It indicates the local prominence of the digital operation information of the r-th industry in the current scheduled time period; JH r It represents the fault tolerance of industrial digital operation information in the operation information storage and management system; JF r It represents the influence of digital operation information of the rth industry on industrial production.

[0083] in, It represents the measure of the importance of digital operation information of the rth industry. The larger the value, the more important the digital operation information of the r-th industry is, and it should have a relatively high storage priority in the subsequent storage management process. r As the influence of the r-th industry's digital operation information on industrial production, it plays a penalty role in the above formula. The purpose is to penalize the storage priority of the r-th industry's digital operation information in the storage management system. That is, if the r-th industry's digital operation information has a low influence on industrial production, which means that the fluctuation of the r-th industry's digital operation information has little to do with the overall production process or product, then the storage priority of the r-th industry's digital operation information in the storage management system will not be too high.

[0084] Step S107, determining the target storage device for each type of industrial digital operation information according to the correspondence between the preset storage priority level and the storage device, so as to store each type of industrial digital operation information in the target storage device.

[0085] Among them, industrial digital operation information with different storage priorities is classified and stored in different target storage devices.

[0086] Specifically, storage devices include but are not limited to high-speed solid-state hard drives, memory, ordinary disks, and cloud storage devices. In advance, the corresponding relationship between storage priority levels and storage devices can be preset. For example, industrial digital operation information with high storage priority may be stored in high-speed solid-state hard drives or memory to provide fast access and processing capabilities, and improve the storage management system's response speed to abnormal situations; while industrial digital operation information with low storage priority can be stored in cheap disk storage or cloud storage to reduce costs.

[0087] As an optional embodiment of the present application, according to the correspondence between preset storage priority levels and storage devices, determining the target storage device for each type of industrial digital operation information includes: if the storage priority of the industrial digital operation information of a type is at the first storage priority level, then determining the target storage device for the industrial digital operation information of the type is a high-speed solid-state hard drive or memory; if the storage priority of the industrial digital operation information of a type is at the second storage priority level, then determining the target storage device for the industrial digital operation information of the type is a disk or a cloud storage device, and the first storage priority level is higher than the second storage priority level.

[0088] Specifically, the first storage priority level may be a high storage priority level, and the second storage priority level may be a low storage priority level. In addition, the storage device may also be of other types, which are not limited in the embodiments of the present application.

[0089] The embodiment of the present application can first determine the local prominence of the industry digital operation information, then determine the influence of the industry digital operation information based on the historical industry digital operation information in the historical records, and finally judge the storage priority of this type of industry digital operation information, and then classify and store the industry digital operation information. Allocate storage resources according to the actual situation of the industry digital operation information to avoid storing all types of data on the same device and wasting the remaining storage resources. If the same device is a high-cost storage device, it can also effectively save storage costs. By classifying and storing different types of industry digital operation information, the industry digital operation information can be located more quickly, thereby more effectively managing the data life cycle and improving the management efficiency of the industry digital operation information.

[0090] Embodiment 2:

[0091] Corresponding to the industrial digital operation information storage management method provided in the above embodiment, based on the same technical concept, the embodiment of the present application also provides an industrial digital operation information storage management system, which is used to execute the above industrial digital operation information storage management method. Figure 5A schematic diagram of a structure of an industrial digital operation information storage and management system for implementing each embodiment of the present application is shown as follows: Figure 5 The industrial digital operation information storage and management system may have relatively large differences due to different configurations or performances, and may include one or more processors 501 and memory 502, wherein the memory 502 is used to store computer programs that can be run on the processor, and the processor is used to execute the program stored in the memory to achieve the above Figure 1 The memory 502 may be a temporary storage or a permanent storage. The application stored in the memory 502 may include one or more modules (not shown in the figure), and each module may include a series of computer executable instructions in the industrial digital operation information storage management system.

[0092] Furthermore, the processor 501 can be configured to communicate with the memory 502 to execute a series of computer executable instructions in the memory 502 on the industrial digital operation information storage management system. The industrial digital operation information storage management system can also include one or more power supplies 503, one or more wired or wireless network interfaces 504, one or more input and output interfaces 505, and one or more keyboards 506.

[0093] Specifically in this embodiment, the industrial digital operation information storage and management system includes a processor, a communication interface, a memory and a communication bus; wherein the processor, the communication interface and the memory communicate with each other through the bus; the memory is used to store computer programs; the processor is used to execute the programs stored in the memory to achieve the above Figure 1 The various steps in the method embodiment are similar to those in the method embodiment, and have the beneficial effects of the above method embodiments. To avoid repetition, the embodiments of the present application will not be described again here.

[0094] It should be noted that the industrial digital operation information storage management system provided in the embodiment of the present application and the industrial digital operation information storage management method provided in the embodiment of the present application are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned industrial digital operation information storage management method, and has the same or similar beneficial effects, and the repetitions will not be repeated.

[0095] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0096] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for storing and managing industrial digital operation information, characterized in that: The industrial digital operation information storage management method includes: Acquire digital operation information of the industry within a predetermined time period, wherein the digital operation information of the industry includes various types of data during the processing of the industry in producing products; Determine multiple maxima, maximum values ​​and minimum values ​​of the digital operation information of the industry within the predetermined time period; Determine the local prominence of each type of industrial digital operation information according to each of the maximum values, the maximum values, and the minimum values, wherein the local prominence represents the importance of the type of industrial digital operation information to industrial production, and the local prominence is proportional to the importance; Determine the influence of each type of industry digital operation information based on historical industry digital operation information in multiple historical time periods and quality inspection results of products produced in multiple historical time periods, wherein the influence represents the degree of influence of the type of industry digital operation information on industry production; Determine the average local prominence of the local prominence of each type of historical industry digital operation information in multiple historical time periods; Determining the storage priority of each type of industrial digital operation information according to the local prominence of each type of industrial digital operation information, the average local prominence, and the influence; According to the correspondence between the preset storage priority levels and the storage devices, the target storage devices for each type of industrial digital operation information are determined, so as to store each type of industrial digital operation information in the target storage devices, wherein the industrial digital operation information of different storage priorities is classified and stored in different target storage devices.

2. The method for storing and managing industrial digital operation information according to claim 1, characterized in that: Determining the local prominence of each type of industry digital operation information according to each of the maximum values, the maximum values, and the minimum values ​​includes: Determine the disorder degree of each type of the digital operation information of the industry according to each of the maximum values, the maximum values ​​and the minimum values, wherein the disorder degree represents the fluctuation degree of the digital operation information of the industry, and the fluctuation degree is inversely proportional to the importance of the digital operation information of the industry; According to the disorder degree of the current type of industrial digital operation information and the disorder degree of other types of industrial digital operation information, the local prominence of the current type of industrial digital operation information is determined.

3. The method for storing and managing industrial digital operation information according to claim 2, characterized in that: Determining the disorder degree of each type of the digital operation information of the industry according to each of the maximum values, the maximum values ​​and the minimum values ​​includes: Calculate the first difference between any two maximum values ​​to obtain n groups of first differences, and take the absolute value of each of the first differences and then superimpose them to obtain a first superposition value, where n is a natural number greater than 0; calculating a second difference between the maximum value and the minimum value; The ratio of the product of the first superposition value and the second difference value to n is determined as the disorder degree.

4. The method for storing and managing industrial digital operation information according to claim 2, characterized in that: Determining the local prominence of the current type of industry digital operation information according to the disorder degree of the current type of industry digital operation information and the disorder degree of other types of industry digital operation information includes: The third difference between the disorder degree of the current type of industry digital operation information and the disorder degree of other types of industry digital operation information is calculated in sequence to obtain M groups of third difference values, and the absolute value of each of the third difference values ​​is taken and superimposed to obtain a second superposition value, where M is the number of types of other types of industry digital operation information; Calculate a first ratio of the disorder degree of the current type of industry digital operation information to M; The product of the first ratio and the second superposition value is determined as the local protrusion.

5. The method for storing and managing industrial digital operation information according to claim 1, characterized in that: Determining the influence of various types of industry digital operation information based on historical industry digital operation information in multiple historical time periods and quality inspection results of products produced in multiple historical time periods includes: Performing curve fitting on the historical industry digital operation information of multiple historical time periods to obtain a data characteristic curve, wherein the abscissa in the data characteristic curve is the identifier of the historical time period, and the ordinate in the data characteristic curve is the fluctuation variance of the historical industry digital operation information; Performing curve fitting on the quality inspection results of the products produced in the multiple historical time periods to obtain a quality inspection result curve, wherein the abscissa in the quality inspection result curve is the identifier of the historical time period, and the ordinate in the quality inspection result curve is the value of the quality inspection result; Calculating a first slope value according to any adjacent data points in the data characteristic curve to obtain N groups of first slope values, and calculating a second slope value according to any adjacent data points in the quality detection result curve to obtain N groups of second slope values, where N is a natural number greater than 0; The influence of each type of industry digital operation information is calculated based on each of the first slope values ​​and each of the second slope values.

6. The method for storing and managing industrial digital operation information according to claim 5, characterized in that: Calculating the influence of each type of industry digital operation information according to each of the first slope values ​​and each of the second slope values ​​includes: Calculating a fourth difference between the first slope value and the corresponding second slope value to obtain N groups of fourth difference values, and taking an absolute value of each of the fourth difference values ​​and superimposing them to obtain a third superimposed value; A second ratio of the third superposition value to N is determined as the influence.

7. The method for storing and managing industrial digital operation information according to claim 1, characterized in that: Determining the storage priority of each type of industrial digital operation information according to the local prominence, the average local prominence, and the influence of each type of industrial digital operation information includes: Determine the fault tolerance of the current type of industrial digital operation information according to the local prominence of the current type of industrial digital operation information and the average local prominence, wherein the fault tolerance indicates the abnormality degree of the current type of industrial digital operation information, and the fault tolerance is inversely proportional to the abnormality degree; The storage priority of each type of industrial digital operation information is determined according to the local prominence, the fault tolerance and the influence of each type of industrial digital operation information.

8. The method for storing and managing industrial digital operation information according to claim 7, characterized in that: Determining the storage priority of each type of industry digital operation information according to the local prominence, the fault tolerance, and the influence of each type of industry digital operation information includes: Calculating a third ratio of the local protrusion to the fault tolerance; Using a hyperbolic tangent function to normalize the third ratio and the influence respectively to obtain a normalized ratio and a normalized influence; The product of the normalized ratio and the normalized influence is determined as the storage priority.

9. The method for storing and managing industrial digital operation information according to any one of claims 1 to 8, characterized in that: Determining the target storage device for each type of industrial digital operation information according to the correspondence between the preset storage priority level and the storage device includes: If the storage priority of the industrial digital operation information of the type is at the first storage priority level, determining that the target storage device of the industrial digital operation information of the type is a high-speed solid-state hard disk or a memory; If the storage priority of the type of industrial digital operation information is at the second storage priority level, the target storage device of the type of industrial digital operation information is determined to be a disk or a cloud storage device, and the first storage priority level is higher than the second storage priority level.

10. An industrial digital operation information storage and management system, characterized in that: The industrial digital operation information storage and management system includes: a processor and a memory; wherein the memory is used to store computer programs that can be run on the processor; the processor is used to execute the program stored in the memory to implement the steps of the industrial digital operation information storage and management method as described in any one of claims 1-9.

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