CN114819636A - Industrial production data processing method and system based on SPC detection - Google Patents
Industrial production data processing method and system based on SPC detection Download PDFInfo
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Abstract
本申请公开了一种基于SPC检测的工业生产数据处理方法及系统，属于数据处理领域，所述方法包括：基于SPC工作站获得多个预设采集周期内的生产工件测量数据信息集合，按照工件质量检测指标集合，获得生产工件质量分类数据信息，然后根据预设标准对分类数据进行质量比对，获得工件生产质量变化参数，将工件生产质量变化参数输入所述生产质量预测模型中，获得工件生产质量能力系数，对工件生产参数进行调整管理。解决了现有技术中存在生产中信息反馈滞后，质量控制手段落后，导致生产质量无法稳定控制，生产成本高的技术问题。达到了准确预测当前生产质量，精准的对工件生产参数进行调整，提高生产质量的稳定性的技术效果。
The application discloses an industrial production data processing method and system based on SPC detection, belonging to the field of data processing. Detect the set of indicators, obtain the classification data information of the quality of the production workpiece, and then compare the quality of the classification data according to the preset standard to obtain the change parameter of the workpiece production quality, input the change parameter of the workpiece production quality into the production quality prediction model, and obtain the workpiece production quality. The quality ability coefficient is used to adjust and manage the production parameters of the workpiece. The technical problems in the prior art that the information feedback in the production is lagging behind and the quality control means are outdated, resulting in the inability to stably control the production quality and the high production cost are solved. It achieves the technical effect of accurately predicting the current production quality, accurately adjusting the production parameters of the workpiece, and improving the stability of the production quality.
Description
Technical Field
The application relates to the field of data processing, in particular to an industrial production data processing method and system based on SPC detection.
Background
With the development of economy and science and technology, the quality requirement of industrial production is higher and higher. Under the condition of market competition aggravation, the research on how to improve the production quality and control the stable production quality has important significance for the long-term stable development of industrial production in China.
At present, most enterprises have a set of complete quality assurance system and quality management system, and generally adopt advanced measuring instruments and meters to improve the quality detection precision so as to control the product quality, and the product quality is ensured by inspecting, analyzing and checking data and feeding back to the production stage after a finished product is produced.
However, a large amount of data obtained from instruments and meters is lack of an accurate statistical analysis method of a system, and feedback cannot be summarized in time, so that problems are often found after products are produced and then corrected, the feedback period is long, the product elimination rate is high, the cost is increased, and the quality cannot be stably controlled for a long time. The technical problems that the production quality cannot be stably controlled and the production cost is high are caused by lagging information feedback and lagging quality control means in production.
Disclosure of Invention
The application aims to provide an industrial production data processing method and system based on SPC detection, which are used for solving the technical problems that the production quality cannot be stably controlled and the production cost is high due to lagging information feedback and lagging quality control means in production in the prior art.
In view of the above problems, the present application provides a method and a system for processing industrial production data based on SPC detection.
In a first aspect, the present application provides a SPC detection-based industrial production data processing method, which is implemented by an SPC detection-based industrial production data processing system, wherein the method comprises: acquiring a production workpiece measurement data information set in a plurality of preset acquisition periods through an SPC workstation; obtaining a workpiece quality detection index set, and performing data classification on the production workpiece measurement data information set according to the workpiece quality detection index set to obtain production workpiece quality classification data information; comparing the quality of the production workpiece quality classification data information according to a preset workpiece quality qualified standard to obtain the quality qualified information of the production workpiece; obtaining a qualified coefficient of the production quality of the workpiece based on the qualified information of the quality of the produced workpiece; analyzing the variation trend of the qualified coefficient of the production quality of the workpiece in the preset acquisition periods to obtain variation parameters of the production quality of the workpiece; constructing a production quality prediction model, and inputting the workpiece production quality variation parameters into the production quality prediction model to obtain a workpiece production quality capability coefficient; and adjusting and managing the production parameters of the workpieces based on the production quality capability coefficient of the workpieces.
In another aspect, the present application further provides an industrial production data processing system based on SPC detection, for executing the industrial production data processing method based on SPC detection as described in the first aspect, wherein the system includes: obtaining, by a first obtaining unit, a set of production workpiece measurement data information within a plurality of preset acquisition periods through an SPC workstation; a second obtaining unit, configured to obtain a workpiece quality detection index set, perform data classification on the production workpiece measurement data information set according to the workpiece quality detection index set, and obtain production workpiece quality classification data information; the third obtaining unit is used for comparing the quality of the production workpiece quality classification data information according to a preset workpiece quality qualified standard to obtain the quality qualified information of the production workpiece; a fourth obtaining unit, configured to obtain a workpiece production quality qualification coefficient based on the production workpiece quality qualification information; the fifth obtaining unit is used for analyzing the variation trend of the qualified coefficient of the production quality of the workpieces in the preset acquisition periods to obtain the variation parameter of the production quality of the workpieces; a sixth obtaining unit, configured to construct a production quality prediction model, input the workpiece production quality variation parameter into the production quality prediction model, and obtain a workpiece production quality capability coefficient; and the first adjusting unit is used for adjusting and managing the production parameters of the workpieces based on the production quality capability coefficient of the workpieces.
In a third aspect, the present application further provides an industrial production data processing system based on SPC detection, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to the first aspect when executing the program.
In a fourth aspect, a computer-readable storage medium has stored thereon a computer program which, when executed by a processor, implements the method of any of the first aspects described above.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the method, an SPC workstation is used for obtaining production workpiece measurement data information sets in a plurality of preset acquisition periods, production workpiece quality classification data information is obtained according to a workpiece quality detection index set, classification data are compared according to preset standards, workpiece production quality change parameters are obtained, the workpiece production quality change parameters are input into a production quality prediction model, workpiece production quality capability coefficients are obtained, and workpiece production parameters are adjusted and managed. The technical effects of accurately predicting the current production quality, accurately adjusting the production parameters of the workpiece and improving the stability of the production quality are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
In order to more clearly illustrate the technical solutions in the present application or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only exemplary, and for those skilled in the art, other drawings can be obtained according to the provided drawings without inventive effort.
FIG. 1 is a schematic flow chart of a method for processing industrial production data based on SPC detection according to the present application;
FIG. 2 is a schematic flow chart illustrating the process of obtaining quality classification data information of a manufactured workpiece in an industrial data processing method based on SPC detection according to the present application;
FIG. 3 is a schematic flow chart illustrating the modification of the variation parameter of the manufacturing quality of the workpiece in the SPC detection-based industrial data processing method of the present application;
FIG. 4 is a schematic flow chart illustrating a process of performing quality multi-dimensional evaluation on the quality information of the substandard production workpieces to obtain a production qualification set of the substandard production workpiece quality information in the SPC detection-based industrial production data processing method of the present application;
FIG. 5 is a schematic diagram of an industrial data processing system based on SPC detection according to the present application;
fig. 6 is a schematic structural diagram of an exemplary electronic device of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a sixth obtaining unit 16, a first adjusting unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303, and a bus architecture 304.
Detailed Description
The application provides an industrial production data processing method and system based on SPC detection, and solves the technical problems that in the prior art, information feedback is lagged in production, quality control means is lagged behind, production quality cannot be stably controlled, and production cost is high. The technical effects of accurately predicting the current production quality, accurately adjusting the production parameters of the workpiece and improving the stability of the production quality are achieved.
According to the technical scheme, the data acquisition, storage, use, processing and the like meet relevant regulations of national laws and regulations.
In the following, the technical solutions in the present application will be clearly and completely described with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application, and it is to be understood that the present application is not limited by the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the elements relevant to the present application are shown in the drawings.
The application provides an industrial production data processing method based on SPC detection, which is applied to an industrial production data processing system based on SPC detection, wherein the method comprises the following steps: acquiring a production workpiece measurement data information set in a plurality of preset acquisition periods through an SPC workstation; obtaining a workpiece quality detection index set, and performing data classification on the production workpiece measurement data information set according to the workpiece quality detection index set to obtain production workpiece quality classification data information; comparing the quality of the production workpiece quality classification data information according to a preset workpiece quality qualified standard to obtain the quality qualified information of the production workpiece; obtaining a qualified coefficient of the production quality of the workpiece based on the qualified information of the quality of the produced workpiece; analyzing the variation trend of the qualified coefficient of the production quality of the workpiece in the preset acquisition periods to obtain variation parameters of the production quality of the workpiece; constructing a production quality prediction model, and inputting the workpiece production quality variation parameters into the production quality prediction model to obtain a workpiece production quality capability coefficient; and adjusting and managing the production parameters of the workpieces based on the production quality capability coefficient of the workpieces.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, the present application provides an industrial production data processing method based on SPC detection, wherein the method is applied to an industrial production data processing system based on SPC detection, and the method specifically includes the following steps:
step S100: acquiring a production workpiece measurement data information set in a plurality of preset acquisition periods through an SPC workstation;
specifically, the SPC workstation is a high-end general-purpose microcomputer that performs work based on SPC. The SPC (statistical Process control) is a Process control tool by means of a mathematical statistical method, monitors the production Process in real time by applying a statistical analysis technology, scientifically distinguishes random fluctuation and abnormal fluctuation of the product quality in the production Process, takes measures to eliminate the influence of the random fluctuation, and improves and controls the product quality by enabling the position of the production Process to be in a state of being only influenced by random fluctuation factors. The preset acquisition cycle is a preset time period in which workpiece data information in the production process is acquired. Preferably, the preset acquisition period may be 3 working days. Specifically, the setting is set by the staff, and is not limited herein. Production conditions in different time periods can be obtained through a plurality of preset acquisition cycles, so that the obtained production conditions are more perfect.
Specifically, the production workpiece measurement data information set refers to a summary set of relevant data information representing workpiece quality. Wherein the production workpiece measurement data information comprises: dimensional information, shape information, mutual position information between surfaces, surface quality information, and heat treatment quality information of the workpiece. Therefore, the measuring data information of the workpiece in different acquisition periods is obtained, the technical effect of providing basic data for subsequent quality analysis and evaluation of the workpiece is achieved, and a foundation is laid for subsequent adjustment and management.
Step S200: obtaining a workpiece quality detection index set, and performing data classification on the production workpiece measurement data information set according to the workpiece quality detection index set to obtain production workpiece quality classification data information;
specifically, the workpiece quality inspection index set is an index set representing items for quality inspection of a workpiece. Optionally, the workpiece quality detection index includes: dimensional qualification rate, shape qualification rate, mutual position qualification rate, surface quality qualification rate, heat treatment quality qualification rate, and the like. And then, carrying out data classification on the production workpiece measurement data information set according to indexes, summarizing classification information, and obtaining classified production workpiece quality classification data information. The quality classification data information of the production workpieces is classified and ordered information data according to the indexes. Therefore, the efficiency of judging whether the production quality of the workpiece is qualified or not in the follow-up process is improved, the comparison operation is simplified, the processing accuracy is improved, and the technical effect of laying the cushion for accurately analyzing the production quality condition in the follow-up process is achieved.
Step S300: comparing the quality of the production workpiece quality classification data information according to a preset workpiece quality qualified standard to obtain the quality qualified information of the production workpiece;
specifically, the preset workpiece quality qualification standard is a standard for judging whether the quality of the produced workpiece is qualified or not, and is established according to the product of the production and manufacturing standard of the workpiece by enterprises according to the country and the industry. Qualified product information can be obtained by comparing the quality classification data information of the production workpieces with standards. The information of qualified quality of the production workpiece comprises information of whether the production workpiece is qualified or not. Thereby providing the technical effect of basic data for the subsequent evaluation of the production quality and the production capacity of the workpiece.
Step S400: obtaining a qualified coefficient of the production quality of the workpiece based on the qualified information of the quality of the produced workpiece;
specifically, the workpiece production quality qualified coefficient is a coefficient representing the qualified rate of the workpieces in a preset acquisition period, and is a ratio of the number of products with qualified quality of the produced workpieces to the total number of products of the produced workpieces. Therefore, the qualification rate condition of the workpiece in the preset acquisition period can be visually and clearly seen, and the technical effect of visually judging the quality condition of the workpiece is achieved.
For example, if the total number of workpieces produced in 3 days is 350, and the number of qualified products is 200, the workpiece production qualification coefficient is 57.12%.
Step S500: analyzing the variation trend of the qualified coefficient of the production quality of the workpiece in the preset acquisition periods to obtain variation parameters of the production quality of the workpiece;
specifically, the variation condition of the workpiece production quality qualified coefficient in the plurality of preset acquisition periods is analyzed, wherein the variation trend refers to the fluctuation condition of the workpiece production quality qualified coefficient in different acquisition periods. The workpiece production quality variation parameter is a parameter for representing the fluctuation condition of the workpiece production quality. Therefore, the prediction of the quality condition of workpiece production is realized, so that the production quality is controlled, and the technical effect of improving the stability of the production quality is achieved.
Step S600: constructing a production quality prediction model, and inputting the workpiece production quality variation parameters into the production quality prediction model to obtain a workpiece production quality capability coefficient;
specifically, the workpiece production quality variation parameter is input into the production quality prediction model, so that the current production quality can be predicted, and the workpiece production quality capability coefficient can be obtained. The component of the production quality prediction model is a mathematical model obtained by performing data training by using the workpiece production quality change parameters as input data, and can predict the production quality. Furthermore, the production quality prediction model is also a mathematical logic model constructed based on a neural network model, and can be analyzed by using the characteristic that mathematical data is converged continuously, so that converged information is output based on machine learning, namely, the simulation result outputs the workpiece production quality capability coefficient. The technical effects of intelligently predicting the production quality and improving the accuracy of adjustment are achieved.
Step S700: and adjusting and managing the production parameters of the workpieces based on the production quality capability coefficient of the workpieces.
Specifically, after the workpiece production quality capability coefficient is obtained, the workpiece production parameters are adjusted based on the current production quality situation, so that the current production situation is optimized, and the technical effect of improving the stability of the production quality is realized. Wherein the workpiece production parameters include: machine tool speed, heat treatment temperature, tool alignment accuracy, angle, etc.
Further, as shown in fig. 2, in the obtaining of the quality classification data information of the production workpieces, step S200 of the present application further includes:
step S210: normalizing the production workpiece measurement data information set to obtain an initial workpiece measurement data information set;
step S220: performing data conversion on the initial workpiece measurement data information set according to a predetermined digit format to obtain a standard workpiece measurement data information set;
step S230: constructing a preset quality information label library according to the workpiece quality detection index set;
step S240: and classifying and marking the standard workpiece measurement data information set based on the preset quality information label library to obtain the production workpiece quality classification data information.
Specifically, the normalization processing is a method for changing a dimensional expression into a dimensionless expression, namely, a processing method for uniformly mapping the measured data information of the production workpiece to a range of 0-1, so that data analysis can be clearer and more intuitive. The initial workpiece measurement data information set is a data information set which is subjected to normalization processing and converts workpiece data information into dimensionless data information.
Specifically, the data conversion according to the predetermined digit format is that the number of digits after the decimal point in the initial workpiece measurement data information after the normalization processing is large, which is inconvenient for calculation, and the simplified calculation can be performed on the basis of ensuring the data accuracy by limiting the number of digits after the decimal point. Optionally, the predetermined number is two digits after the decimal point. The standard workpiece measurement data information set is a data information set which standardizes the initial workpiece measurement data information set and has data in a specific interval. The predetermined quality information tag library is a collection of identifying tags that contain all of the workpiece quality inspection indicators. And classifying the standard workpiece measurement data information set according to the labels in the label library, wherein the production workpiece quality classification data information is data obtained by classifying the workpiece measurement data according to the detection indexes, and the marking realizes convenient follow-up data comparison and analysis, so that complicated and complicated data are clearer, and the technical effects of improving the data processing efficiency and accuracy are achieved.
Further, as shown in fig. 3, in the obtaining of the variation parameter of the production quality of the workpiece, step S500 in the embodiment of the present application further includes:
step S510: obtaining quality information of the production workpieces which do not reach the standard according to the quality qualified information of the production workpieces;
step S520: performing quality multi-dimensional evaluation on the quality information of the unqualified production workpieces to obtain a production qualification degree set of the quality information of the unqualified production workpieces;
step S530: carrying out mean value processing on the production qualification set to obtain a workpiece production quality correction coefficient;
step S540: and correcting the workpiece production quality change parameters according to the workpiece production quality correction coefficient.
Specifically, the quality information of the unqualified production workpieces is the quality information that the quality of the production workpieces does not meet the qualified standard. Through carrying out multi-dimensional evaluation on the quality information of the unqualified production workpieces, the relevant information with qualified quality can be further analyzed. The production qualification degree information set is a set containing numerical values obtained by dividing qualified quality information in quality information of unqualified production workpieces by total quality information. By performing the averaging processing on the sets, the condition of the quality information can be more comprehensively reflected. The workpiece production quality correction coefficient is a coefficient for representing correction of fluctuation in current production quality. Furthermore, the work production quality change parameters are corrected according to the correction parameters, so that the change parameters can be more accurate, the production quality requirements and the production conditions can be adjusted in time, and the technical effect of the production quality is improved.
Further, as shown in fig. 4, the performing quality multidimensional evaluation on the quality information of the substandard production workpieces to obtain a production qualification set of the quality information of the substandard production workpieces, in step S520 of the embodiment of the present application, further includes:
step S521: performing quality multi-dimensional evaluation on the quality information of the unqualified production workpieces to obtain a quality scoring matrix of the unqualified production workpieces;
step S522: constructing a workpiece quality grading reticular map, and projecting element values in the quality grading matrix of the unqualified production workpiece to the workpiece quality grading reticular map to obtain the unqualified workpiece quality grading reticular map;
step S523: and acquiring a production qualification set of the quality information of the unqualified production workpieces based on the area value of the unqualified workpiece quality grading reticular map.
Specifically, quality information of unqualified production workpieces meeting production qualification can be obtained by performing multi-angle analysis and evaluation on the quality information of the unqualified production workpieces, converting the quality information into a grading reticular map, and visualizing and quantifying the evaluation.
Specifically, the quality multi-dimensional evaluation is to further refine and decompose the quality information of the unqualified production workpieces, and obtain unqualified quality information and qualified quality information from different dimensions. The quality scoring matrix of the unqualified production workpieces is a matrix used for representing the evaluation result of the quality information of the unqualified production workpieces. Wherein the workpiece quality score mesh is built based on different dimensions. And then, taking the scoring mesh graph as a framework, and projecting element values in the obtained quality scoring matrix into the mesh graph. The area value is the area of the region formed by the grading values of the workpiece quality information on all dimensions. The production qualification set is a condition set which comprises qualified quality information in the quality information of the unqualified production workpieces in the total quality information, wherein the production qualification is a numerical value obtained by dividing the qualified quality information in the quality information of the unqualified production workpieces by the total quality information. Therefore, the production quality condition can be further analyzed, and the technical effect of data analysis accuracy is improved.
For example, the mesh of workpiece quality scores may be a radar map with different dimensions as vertices of the radar map. Evaluating the quality information of the unqualified production workpiece through five dimensions of size information, shape information, surface mutual position information, surface quality information and heat treatment quality, projecting a grading result to a workpiece quality grading reticular map to obtain an area value consisting of all the dimensions, and then obtaining the qualified degree of the quality information in the unqualified production quality information of the workpiece.
Further, in the obtaining the workpiece throughput quality capability coefficient, step S600 in this embodiment of the present application further includes:
step S610: constructing a workpiece production scheme coordinate system, wherein the workpiece production scheme coordinate system takes the time urgency as an abscissa and takes the production complexity as an ordinate;
step S620: inputting the order information of the production workpiece into the coordinate system of the workpiece production scheme to obtain the initial area information of the workpiece production;
step S630: taking the workpiece production quality capability coefficient as a coordinate axis logic dividing line;
step S640: and carrying out region segmentation on the workpiece production initial region information based on the coordinate axis logical segmentation line, determining workpiece production division region information, and taking the area value of the workpiece production division region information as a workpiece production scheme optimization value.
Specifically, the workpiece production order information is visually processed according to the time urgency and the production complexity, and then the order information is divided according to the workpiece production quality capability coefficient to obtain a workpiece production scheme meeting the workpiece production quality capability range, so that the production quality requirement and the production workpiece parameters are adjusted, and the technical effect of ensuring the production quality can be achieved.
Specifically, the workpiece production scheme coordinate system takes the time urgency as an abscissa and the production complexity as an abscissa, and can represent information of two dimensions of time and difficulty of workpiece production. The time urgency is a numerical value obtained by evaluating the time urgency of the scheme, and optionally, the time urgency is judged by using the length of the remaining time from the order completion time as a standard. The production complexity is a numerical value obtained after comprehensively evaluating the process quantity and the process difficulty of the scheme.
Specifically, the production workpiece order information is the obtained production plan. The workpiece production initial area information is visualized area information in all workpiece production coordinate systems in the order and comprises time emergency degree and production complexity degree information of an order scheme. Furthermore, the step of taking the workpiece production quality capability coefficient as a coordinate axis logical dividing line means that the current workpiece production quality capability condition is taken as a distinction, and the order scheme is used for obtaining a scheme which can ensure the production quality under the current production condition. The workpiece division region information is a region enclosed by an intersection point and a coordinate axis, wherein the intersection point and the coordinate axis are obtained by taking the workpiece production quality capacity coefficient as a coordinate axis logic division line. The area value of the region can be used for representing the production quality condition of the current workpiece production to the order information, and the actual workpiece production scheme can be optimized based on the area value. The technical effect of improving the industrial production quality is realized.
Further, in the step S100 of obtaining the set of measurement data of the production workpiece in the multiple preset acquisition periods through the SPC workstation, the method further includes:
step S110: determining a data desensitization grade according to the sensitivity coefficient of the production workpiece;
step S120: performing data desensitization on the production workpiece measurement data information set based on a desensitization algorithm and the data desensitization coefficient grade to obtain a production workpiece desensitization data information set;
step S130: and encrypting and storing the production workpiece desensitization data information set.
Specifically, in the production process, the production data information of different workpieces needs to be kept secret to different degrees, and the sensitivity coefficient of the workpiece is obtained from the production task. And determining the level of data desensitization according to the sensitivity degree, and desensitizing through a desensitization algorithm to obtain a desensitized data information set of the production workpiece, and further encrypting and storing the desensitized data information set. Sensitive data are converted or modified through privacy removal of production workpiece data information, and the technical effects of ensuring that production data are not leaked and improving the safety of workpiece information are achieved.
Specifically, the sensitivity coefficient of the production workpiece is a coefficient for representing the degree of secrecy required for the production workpiece, and optionally, the higher the secrecy degree is, the higher the sensitivity coefficient of the production workpiece is. The data desensitization level refers to a level of the degree to which data needs to be desensitized as determined based on the susceptibility coefficient. Optionally, the data desensitization level can be primary, secondary, and tertiary, with the primary desensitization level being the lowest.
Specifically, the desensitization algorithm is an algorithm that can maintain the original characteristics of the data and convert or modify the sensitive data. And performing data desensitization on the production workpiece measurement data information set, namely converting and modifying sensitive data in the data information. Optionally, the data desensitization mode includes static data desensitization and dynamic data desensitization. And the production workpiece desensitization data information set is a workpiece data information set subjected to desensitization treatment. Further, in order to ensure data security, the data information set is encrypted and stored. Optionally, the encrypted storage mode includes: the host software encryption, the encrypted storage security switch, the embedded special encryption device and the storage layer-based storage device may be specifically selected according to the situation, and are not limited herein.
Further, in the constructing the production quality prediction model, step S600 in the embodiment of the present application further includes:
step S650: evaluating the prediction effect of the production quality prediction model to obtain the accuracy of the production quality prediction;
step S660: if the production quality prediction accuracy does not reach the preset prediction accuracy, obtaining a production quality prediction optimization coefficient based on the difference value between the production quality prediction accuracy and the preset prediction accuracy;
step S670: and optimizing and updating the production quality prediction model based on a model optimization algorithm and the production quality prediction optimization coefficient.
Specifically, the output result of the production quality prediction model, namely the predicted workpiece production quality situation is compared with the actual workpiece production quality situation for analysis, and the prediction accuracy situation of the model is evaluated. Further, if the prediction effect does not reach the expected target, the parameter for optimizing the model may be obtained based on a difference between the production quality prediction accuracy and the preset prediction accuracy. And then optimizing and updating the production quality prediction model according to a model optimization algorithm and the production quality prediction optimization coefficient, so that the production quality prediction model is more accurate, and the current production quality condition can be accurately predicted based on the accurate model, thereby realizing the technical effects of improving the accuracy of adjusting the workpiece parameters and improving the production quality and efficiency.
Specifically, the production quality prediction accuracy is a numerical value obtained by evaluating the production quality model, and can be used for representing the prediction condition of the model. The preset prediction accuracy is the precision of the preset model, and specifically, the preset prediction accuracy can be set by a worker, and is not limited herein. The production quality prediction optimization coefficient is used for adjusting data of the model, and the model can be optimized. The model optimization algorithm is an algorithm which can continuously optimize the model to find the model with the highest output accuracy.
In summary, the industrial production data processing method based on SPC provided by the present application has the following technical effects:
1. according to the method, an SPC workstation is used for obtaining production workpiece measurement data information sets in a plurality of preset acquisition periods, production workpiece quality classification data information is obtained according to a workpiece quality detection index set, classification data are compared according to preset standards, workpiece production quality change parameters are obtained, the workpiece production quality change parameters are input into a production quality prediction model, workpiece production quality capability coefficients are obtained, and workpiece production parameters are adjusted and managed. The method and the device have the advantages that the change trend of the production quality of the workpieces in different time periods is analyzed, the production quality is predicted based on model analysis, the production quality requirement and the parameters of the produced workpieces are adjusted according to the order requirement, and the production quality is improved.
2. And normalizing the production workpiece measurement data information set to obtain an initial workpiece measurement data information set, further standardizing the initial workpiece measurement data information set, and classifying and marking the standard workpiece measurement data information set based on the preset quality information label library to obtain the production workpiece quality classification data information. The data comparison and analysis can be conveniently and subsequently carried out, complex and complicated data can be clearer, and the technical effects of improving the data processing efficiency and accuracy are achieved.
3. The change condition of the qualified coefficient of the production quality of the workpieces in the preset acquisition periods is analyzed, and the change parameter of the production quality of the workpieces is corrected according to the correction parameter, so that the quality condition of the production of the workpieces is predicted, the production quality is controlled, and the technical effect of improving the stability of the production quality is achieved.
Example two
Based on the same inventive concept as the industrial production data processing method based on SPC detection in the foregoing embodiments, as shown in fig. 5, the present application further provides an industrial production data processing system based on SPC detection, the system comprising:
a first obtaining unit 11, wherein the first obtaining unit 11 is used for obtaining the production workpiece measurement data information sets in a plurality of preset acquisition periods through the SPC workstation;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain a workpiece quality detection index set, and perform data classification on the production workpiece measurement data information set according to the workpiece quality detection index set to obtain production workpiece quality classification data information;
a third obtaining unit 13, where the third obtaining unit 13 is configured to perform quality comparison on the production workpiece quality classification data information according to a preset workpiece quality qualification standard to obtain production workpiece quality qualification information;
a fourth obtaining unit 14, wherein the fourth obtaining unit 14 is configured to obtain a workpiece production quality qualified coefficient based on the production workpiece quality qualified information;
a fifth obtaining unit 15, where the fifth obtaining unit 15 is configured to perform trend analysis on the qualified coefficient of production quality of the workpiece in the multiple preset acquisition periods to obtain a parameter of change of production quality of the workpiece;
a sixth obtaining unit 16, where the sixth obtaining unit 16 is configured to construct a production quality prediction model, and input the workpiece production quality variation parameter into the production quality prediction model to obtain a workpiece production quality capability coefficient;
a first adjusting unit 17, wherein the first adjusting unit 17 is configured to adjust and manage the workpiece production parameters based on the workpiece production quality capability coefficient.
Further, the system further comprises:
a seventh obtaining unit, configured to perform normalization processing on the production workpiece measurement data information set to obtain an initial workpiece measurement data information set;
an eighth obtaining unit, configured to perform data conversion on the initial workpiece measurement data information set according to a format of a predetermined number of bits, to obtain a standard workpiece measurement data information set;
the first construction unit is used for constructing a preset quality information label library according to the workpiece quality detection index set;
a ninth obtaining unit, configured to perform classification marking on the standard workpiece measurement data information set based on the predetermined quality information tag library, so as to obtain the production workpiece quality classification data information.
Further, the system further comprises:
a tenth obtaining unit, configured to obtain quality information of the production workpiece that does not reach the standard according to the quality qualified information of the production workpiece;
an eleventh obtaining unit, configured to perform quality multidimensional evaluation on the quality information of the substandard production workpieces, and obtain a production qualification set of the quality information of the substandard production workpieces;
a twelfth obtaining unit, configured to perform mean processing on the production qualification set to obtain a workpiece production quality correction coefficient;
the first correcting unit is used for correcting the workpiece production quality change parameters according to the workpiece production quality correction coefficient.
Further, the system further comprises:
a thirteenth obtaining unit, configured to perform quality multidimensional evaluation on the quality information of the substandard production workpieces, and obtain a quality scoring matrix of the substandard production workpieces;
the second construction unit is used for constructing a workpiece quality grading reticular map, projecting element values in the quality grading matrix of the unqualified production workpiece to the workpiece quality grading reticular map, and obtaining the unqualified workpiece quality grading reticular map;
a fourteenth obtaining unit, configured to obtain a production qualification set of the quality information of the substandard production workpieces based on the area value of the substandard workpiece quality scoring reticule.
Further, the system further comprises:
the third construction unit is used for constructing a workpiece production scheme coordinate system, and the workpiece production scheme coordinate system takes the time urgency as a horizontal coordinate and takes the production complexity as a vertical coordinate;
a fifteenth obtaining unit, configured to input order information of a production workpiece into the workpiece production plan coordinate system, and obtain initial area information of workpiece production;
the first setting unit is used for taking the workpiece production quality capability coefficient as a coordinate axis logical dividing line;
and a second setting unit configured to perform region division on the workpiece production initial region information based on the coordinate axis logical dividing line, determine workpiece production divisional region information, and take an area value of the workpiece production divisional region information as a workpiece production plan optimization value.
Further, the system further comprises:
the first determining unit is used for determining a data desensitization level according to the sensitivity coefficient of the production workpiece;
a sixteenth obtaining unit, configured to perform data desensitization on the production workpiece measurement data information set based on a desensitization algorithm and the data desensitization coefficient level, and obtain a production workpiece desensitization data information set;
a first storage unit for encrypted storage of the set of production workpiece desensitization data information.
Further, the system further comprises:
a seventeenth obtaining unit configured to perform prediction effect evaluation on the production quality prediction model to obtain a production quality prediction accuracy;
an eighteenth obtaining unit configured to obtain a production quality prediction optimization coefficient based on a difference between the production quality prediction accuracy and a preset prediction accuracy if the production quality prediction accuracy does not reach the preset prediction accuracy;
a first optimization unit configured to perform optimization updating on the production quality prediction model based on a model optimization algorithm and the production quality prediction optimization coefficient.
In the present specification, the various embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, the industrial production data processing method based on SPC detection in the first embodiment of fig. 1 and the specific example are also applicable to the industrial production data processing system based on SPC detection in the present embodiment, and through the foregoing detailed description of the industrial production data processing method based on SPC detection, a person skilled in the art can clearly know the industrial production data processing system based on SPC detection in the present embodiment, so for the brevity of the description, detailed description is omitted here. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
EXAMPLE III
Based on the same inventive concept as one of the industrial production data processing methods based on SPC detection in the foregoing embodiments, the present application further provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method according to the first embodiment.
Exemplary electronic device
The electronic device of the present application is described below with reference to figure 6,
based on the same inventive concept as the industrial production data processing method based on SPC detection in the foregoing embodiments, the present application also provides an industrial production data processing system based on SPC detection, comprising: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes the system to perform the steps of the method of embodiment one.
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
The communication interface 303 may be any device, such as a transceiver, for communicating with other devices or communication networks, such as an ethernet, a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a wired access network, and the like.
The memory 301 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable Programmable read-only memory (EEPROM), a compact-read-only-memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through a bus architecture 304. The memory may also be integral to the processor.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. The processor 302 is used for executing the computer executable instructions stored in the memory 301, so as to implement the industrial production data processing method based on SPC detection provided by the above embodiments of the present application.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are for convenience of description and are not intended to limit the scope of this application nor to indicate the order of precedence. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one (one ) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the present application are generated in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The various illustrative logical units and circuits described in this application may be implemented or operated through the design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in this application may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside as discrete components in a terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and its equivalent technology, it is intended that the present application include such modifications and variations.
Claims (10)
1. An industrial production data processing method based on SPC detection, which is characterized by comprising the following steps:
acquiring a production workpiece measurement data information set in a plurality of preset acquisition periods through an SPC workstation;
obtaining a workpiece quality detection index set, and performing data classification on the production workpiece measurement data information set according to the workpiece quality detection index set to obtain production workpiece quality classification data information;
comparing the quality of the production workpiece quality classification data information according to a preset workpiece quality qualified standard to obtain the quality qualified information of the production workpiece;
obtaining a qualified coefficient of the production quality of the workpiece based on the qualified information of the quality of the produced workpiece;
analyzing the variation trend of the qualified coefficient of the production quality of the workpiece in the preset acquisition periods to obtain variation parameters of the production quality of the workpiece;
constructing a production quality prediction model, and inputting the workpiece production quality variation parameters into the production quality prediction model to obtain a workpiece production quality capability coefficient;
and adjusting and managing the production parameters of the workpieces based on the production quality capability coefficient of the workpieces.
2. The method of claim 1, wherein said obtaining production workpiece quality classification data information comprises:
normalizing the production workpiece measurement data information set to obtain an initial workpiece measurement data information set;
performing data conversion on the initial workpiece measurement data information set according to a predetermined digit format to obtain a standard workpiece measurement data information set;
constructing a preset quality information label library according to the workpiece quality detection index set;
and classifying and marking the standard workpiece measurement data information set based on the preset quality information label library to obtain the production workpiece quality classification data information.
3. The method of claim 1, wherein the method comprises:
obtaining quality information of the production workpieces which do not reach the standard according to the quality qualified information of the production workpieces;
performing quality multi-dimensional evaluation on the quality information of the unqualified production workpieces to obtain a production qualification degree set of the quality information of the unqualified production workpieces;
carrying out mean value processing on the production qualification set to obtain a workpiece production quality correction coefficient;
and correcting the workpiece production quality change parameters according to the workpiece production quality correction coefficient.
4. The method of claim 3, wherein the method comprises:
performing quality multi-dimensional evaluation on the quality information of the unqualified production workpieces to obtain a quality scoring matrix of the unqualified production workpieces;
constructing a workpiece quality grading reticular map, and projecting element values in the quality grading matrix of the unqualified production workpiece to the workpiece quality grading reticular map to obtain the unqualified workpiece quality grading reticular map;
and acquiring a production qualification set of the quality information of the unqualified production workpieces based on the area value of the unqualified workpiece quality grading reticular map.
5. The method of claim 1, wherein the method comprises:
constructing a workpiece production scheme coordinate system, wherein the workpiece production scheme coordinate system takes the time urgency as an abscissa and takes the production complexity as an ordinate;
inputting the order information of the production workpiece into the coordinate system of the workpiece production scheme to obtain the initial area information of the workpiece production;
taking the workpiece production quality capability coefficient as a coordinate axis logic dividing line;
and carrying out region segmentation on the workpiece production initial region information based on the coordinate axis logical segmentation line, determining workpiece production division region information, and taking the area value of the workpiece production division region information as a workpiece production scheme optimization value.
6. The method of claim 1, wherein the method comprises:
determining a data desensitization grade according to the sensitivity coefficient of the production workpiece;
performing data desensitization on the production workpiece measurement data information set based on a desensitization algorithm and the data desensitization coefficient grade to obtain a production workpiece desensitization data information set;
and encrypting and storing the production workpiece desensitization data information set.
7. The method of claim 1, wherein the method comprises:
evaluating the prediction effect of the production quality prediction model to obtain the accuracy of the production quality prediction;
if the production quality prediction accuracy does not reach the preset prediction accuracy, obtaining a production quality prediction optimization coefficient based on the difference value between the production quality prediction accuracy and the preset prediction accuracy;
and optimizing and updating the production quality prediction model based on a model optimization algorithm and the production quality prediction optimization coefficient.
8. An industrial process data processing system based on SPC detection, the system comprising:
a first obtaining unit for obtaining, by an SPC workstation, a set of production workpiece measurement data information within a plurality of preset acquisition periods;
a second obtaining unit, configured to obtain a workpiece quality detection index set, perform data classification on the production workpiece measurement data information set according to the workpiece quality detection index set, and obtain production workpiece quality classification data information;
the third obtaining unit is used for comparing the quality of the production workpiece quality classification data information according to a preset workpiece quality qualified standard to obtain the quality qualified information of the production workpiece;
a fourth obtaining unit, configured to obtain a workpiece production quality qualification coefficient based on the production workpiece quality qualification information;
the fifth obtaining unit is used for analyzing the variation trend of the qualified coefficient of the production quality of the workpieces in the preset acquisition periods to obtain the variation parameter of the production quality of the workpieces;
a sixth obtaining unit, configured to construct a production quality prediction model, input the workpiece production quality variation parameter into the production quality prediction model, and obtain a workpiece production quality capability coefficient;
and the first adjusting unit is used for adjusting and managing the production parameters of the workpieces based on the production quality capability coefficient of the workpieces.
9. An industrial process data processing system based on SPC detection, comprising: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes a system to perform the steps of the method of any of claims 1 to 7.
10. A computer program product, characterized in that a storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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Denomination of invention: A data processing method and system based on SPC detection Granted publication date: 20230324 Pledgee: China Construction Bank Corporation Wuxi Huishan sub branch Pledgor: WUXI RISHENG MEASURING TOOL Co.,Ltd. Registration number: Y2025980045474 |