Disclosure of Invention
The embodiment of the invention aims to provide a standardized quality management early warning method and system based on big data analysis, and aims to solve the problems in the background technology.
The embodiment of the invention is realized in such a way that, on one hand, the standardized quality management early warning method based on big data analysis comprises the following steps:
acquiring a quality inspection instruction and positioning a target product;
acquiring and analyzing target product parameters to generate product control proportion;
based on the product control proportion, generating quantitative detection feedback data;
Acquiring and analyzing quantitative detection feedback data to generate a production regulation and control early warning instruction;
and generating a traceability analysis result based on the production regulation and control early warning instruction.
As a further aspect of the present invention, the obtaining and analyzing the target product parameters, and generating the product control ratio specifically includes:
extracting a first sub-parameter, a second sub-parameter and a third sub-parameter in the targeted product parameters;
judging whether the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than corresponding parameter threshold values or not respectively;
if at least one of the first sub-parameter, the second sub-parameter and the third sub-parameter is smaller than the corresponding parameter threshold value;
generating a low-proportion control instruction;
If at least two sub-parameters of the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold;
Generating a medium proportion control instruction;
if the first sub-parameter, the second sub-parameter and the third sub-parameter are all smaller than the corresponding parameter threshold;
a high-ratio control instruction is generated.
As still further aspects of the present invention, the generating the quantized detection feedback data based on the product control ratio specifically includes:
Acquiring the production task amount of a product;
if a low-proportion control instruction is generated;
Detecting the production task quantity of the three products based on the production task quantity of the products, and generating first feedback data;
If a medium proportion control instruction is generated;
Detecting six product production task amounts based on the product production task amounts, and generating second feedback data;
If a high-proportion control instruction is generated;
And detecting all the production task amounts of the products based on the production task amounts of the products, and generating third feedback data.
As a still further scheme of the invention, the acquisition and analysis of the quantitative detection feedback data specifically comprises the following steps of:
retrieving the first feedback data, the second feedback data, and the third feedback data;
If the first feedback data or the second feedback data is retrieved, generating a speed control instruction;
If the third feedback data is retrieved, generating a production stopping instruction.
As a further scheme of the invention, the generation of the traceability analysis result based on the production regulation and control early warning instruction specifically comprises the following steps:
retrieving a production stopping instruction;
If the production stopping instruction exists;
Generating a control product range based on the high-proportion control instruction;
acquiring a management and control product range, and extracting the product problem types in the management and control product range;
Based on the type of the product problem, matching and recording corresponding production procedures;
and matching and recording corresponding production personnel based on the corresponding production procedures.
As a further aspect of the present invention, in another aspect, a standardized quality management early warning system based on big data analysis, the system includes:
the acquisition module is used for acquiring the quality inspection instruction;
The positioning module is used for positioning the target product;
the first acquisition and analysis module is used for acquiring and analyzing the target product parameters;
the first generation module is used for generating a product control proportion;
the second generation module is used for generating quantitative detection feedback data based on the product control proportion;
The second acquisition and analysis module is used for acquiring and analyzing the quantitative detection feedback data;
The third generation module is used for generating a production regulation and control early warning instruction;
and the fourth generation module is used for generating a traceability analysis result.
As a further aspect of the present invention, the first acquisition and analysis module specifically includes:
The extraction unit is used for extracting a first subparameter, a second subparameter and a third subparameter in the targeted product parameters;
The judging unit is used for judging whether the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold value or not respectively;
The first generation unit is used for generating a low-proportion control instruction if at least one of the first sub-parameter, the second sub-parameter and the third sub-parameter is smaller than a corresponding parameter threshold value;
the second generation unit is used for generating a middle proportion control instruction if at least two sub-parameters of the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold value;
and the third generation unit is used for generating a high-proportion control instruction if the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold values.
As a further aspect of the present invention, the second generating module specifically includes:
The acquisition unit is used for acquiring the production task quantity of the product;
The first detection unit is used for detecting the production task quantity of the three products based on the production task quantity of the products if a low-proportion control instruction is generated;
A fourth generation unit for generating the first feedback data;
the second detection unit is used for detecting the production task quantity of the six products based on the production task quantity of the products if the medium-proportion control instruction is generated;
a fifth generation unit for generating second feedback data;
the third detection unit is used for detecting all the production task amounts of the products based on the production task amounts of the products if a high-proportion control instruction is generated;
and a sixth generation unit for generating third feedback data.
As a further aspect of the present invention, the third generating module specifically includes:
The retrieval unit is used for retrieving the first feedback data, the second feedback data and the third feedback data;
A seventh generating unit, configured to generate a speed control instruction if the first feedback data or the second feedback data is retrieved;
and the eighth generation unit is used for generating a production stopping instruction if the third feedback data is retrieved.
According to the standardized quality management early warning method and system based on big data analysis, the method and system can conduct proportional control and analysis on products of a production line, conduct quality analysis on the products in a diversified mode, conduct quantitative detection based on the number of types of problems in the quality analysis, further generate production control early warning instructions and traceability analysis results according to quantitative detection results, and improve standardized quality of the products and quality control management improvement efficiency.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Specific implementations of the invention are described in detail below in connection with specific embodiments.
The standardized quality management early warning method and system based on big data analysis provided by the invention solve the technical problems in the background technology.
As shown in fig. 1, a main flow chart of a standardized quality management early warning method based on big data analysis according to an embodiment of the present invention includes:
Step S100: acquiring a quality inspection instruction and positioning a target product;
step S200: acquiring and analyzing target product parameters to generate product control proportion;
Step S300: based on the product control proportion, generating quantitative detection feedback data;
step S400: acquiring and analyzing quantitative detection feedback data to generate a production regulation and control early warning instruction;
Step S500: and generating a traceability analysis result based on the production regulation and control early warning instruction.
When the embodiment is applied, the production line is provided with automatic acquisition equipment, automatic parameter acquisition and detection can be carried out on the production line products, quality control instructions can be sent at any time in the production process of the production line, when the quality control instructions are sent, the production line products can be positioned, targeted products are positioned to serve as punctuation quality control products, automatic detection of various parameters is carried out on the targeted products, targeted product parameters are generated, first sub-parameters, second sub-parameters and third sub-parameters in the targeted product parameters are extracted, whether the first sub-parameters, the second sub-parameters and the third sub-parameters are smaller than parameter thresholds or not is judged respectively, if at least one of the first sub-parameters, the second sub-parameters and the third sub-parameters is smaller than the parameter thresholds, a low-proportion control instruction is generated, if at least two of the first sub-parameters, the second sub-parameters and the third sub-parameters are smaller than the parameter thresholds, a medium-proportion control instruction is generated, if the first sub-parameters, the second sub-parameters and the third sub-parameters are smaller than the parameter thresholds, a high-proportion control instruction is generated, the production line quality control instruction is correspondingly detected, the quality control instruction is generated, the quality control instruction is quantitatively, the quality control instruction is generated, the quality control instruction is correspondingly is detected, the quality control instruction is generated, and the quality control instruction is judged, and the quality control instruction is has a quality control instruction is correspondingly, and the quality control instruction is reduced by comparing quality control instruction, and (5) finishing standardized quality management.
As shown in fig. 2, as a preferred embodiment of the present invention, the obtaining and analyzing the target product parameters, and generating the product control ratio specifically includes:
step S201: extracting a first sub-parameter, a second sub-parameter and a third sub-parameter in the targeted product parameters;
step S202: judging whether the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than corresponding parameter threshold values or not respectively;
step S203: if at least one of the first sub-parameter, the second sub-parameter and the third sub-parameter is smaller than the corresponding parameter threshold value, generating a low-proportion control instruction;
step S204: if at least two sub-parameters of the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold value, a medium proportion control instruction is generated;
step S205: if the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold values, a high-proportion control instruction is generated;
When the embodiment is applied, first, a first sub-parameter, a second sub-parameter and a third sub-parameter in the targeted product parameter are extracted, specific types of the first sub-parameter, the second sub-parameter and the third sub-parameter can be freely set, such as a product size parameter, a product color standard parameter, a product surface flaw parameter and the like, each type of sub-parameter is provided with a corresponding parameter threshold value, whether the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold value is respectively judged, if at least one of the first sub-parameter, the second sub-parameter and the third sub-parameter is smaller than the corresponding parameter threshold value, a low-proportion control instruction is generated, if at least two of the first sub-parameter, the second sub-parameter and the third sub-parameter is smaller than the corresponding parameter threshold value, a medium-proportion control instruction is generated, and if the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the corresponding parameter threshold value, a high-proportion control instruction is generated.
As shown in fig. 3, as a preferred embodiment of the present invention, the generating the quantized detection feedback data based on the product control ratio specifically includes:
step S301: acquiring the production task amount of a product;
step S302: if a low-proportion control instruction is generated, detecting the production task quantity of the three products based on the production task quantity of the products;
step S303: generating first feedback data;
step S304: if a medium-proportion control instruction is generated, detecting the production task quantity of six products based on the production task quantity of the products;
step S305: generating second feedback data;
step S306: if a high-proportion control instruction is generated, detecting all the production task amounts of the products based on the production task amounts of the products;
step S307: generating third feedback data;
When the method is applied, firstly, the product production task quantity is obtained, if a low-proportion control instruction is generated, the three-product production task quantity is detected based on the product production task quantity, the quality detection is carried out on the three-product of the total production task quantity, first feedback data is generated, if a medium-proportion control instruction is generated, the six-product production task quantity is detected based on the product production task quantity, the quality detection is carried out on the six-product of the total production task quantity, second feedback data is generated, if a high-proportion control instruction is generated, the total product production task quantity is detected based on the product production task quantity, and third feedback data is generated.
As shown in fig. 4, as a preferred embodiment of the present invention, the obtaining and analyzing the quantized detection feedback data, generating the production control early warning command specifically includes:
step S401: retrieving the first feedback data, the second feedback data, and the third feedback data;
Step S402: if the first feedback data or the second feedback data is retrieved, generating a speed control instruction;
step S403: if the third feedback data is retrieved, generating a production stopping instruction.
It should be understood that after the first feedback data, the second feedback data or the third feedback data are generated, the first feedback data, the second feedback data and the third feedback data are retrieved, if the first feedback data or the second feedback data are retrieved, the production quality is low, but the first feedback data and the second feedback data are in a controllable range, a speed control instruction is generated, the production speed is reduced, and if the third feedback data are retrieved, the production quality is low and uncontrollable, a production stopping instruction is immediately generated, and the production is stopped.
As shown in fig. 5, as a preferred embodiment of the present invention, the generating the traceability analysis result based on the production regulation and control early warning command specifically includes:
Step S501: retrieving a production stopping instruction;
Step S502: if the production stopping instruction exists;
step S503: generating a control product range based on the high-proportion control instruction;
step S504: acquiring a management and control product range, and extracting the product problem types in the management and control product range;
step S505: based on the type of the product problem, matching and recording corresponding production procedures;
step S506: matching and recording corresponding production personnel based on the corresponding production procedures;
When the method is applied, the production stopping instruction is firstly searched, if the production stopping instruction exists, the production controlling product range is generated based on the high-proportion control instruction, namely, a plurality of products to be inspected are obtained, the product problem types in the production controlling product range are extracted after the production controlling product range is obtained, the corresponding production procedures are matched and recorded based on the product problem types, the corresponding production procedures are matched and recorded based on the corresponding production procedures, and the corresponding production personnel are matched and recorded, so that the problem procedures are improved conveniently after the corresponding production procedures and the corresponding production personnel are determined, the problem production personnel are trained, and the overall production quality of the production line is improved.
As another preferred embodiment of the present invention, as shown in fig. 6, in another aspect, a standardized quality management early warning system based on big data analysis, the system comprising:
an acquisition module 100, configured to acquire a quality inspection instruction;
A positioning module 200 for positioning a targeted product;
a first acquisition and analysis module 300 for acquiring and analyzing the targeted product parameters;
A first generation module 400, configured to generate a product control ratio;
The second generation module 500 is configured to generate quantized detection feedback data based on the product control proportion;
a second acquisition and analysis module 600, configured to acquire and analyze the quantized detection feedback data;
The third generation module 700 is configured to generate a production regulation and control early warning instruction;
a fourth generating module 800, configured to generate a traceability analysis result.
In this embodiment, when the method is applied, the acquisition module 100 acquires the quality inspection instruction, the positioning module 200 positions the target product, the first acquisition and analysis module 300 acquires and analyzes the target product parameter, the first generation module 400 generates the product control proportion, the second generation module 500 generates the quantized detection feedback data based on the product control proportion, the second acquisition and analysis module 600 acquires and analyzes the quantized detection feedback data, the third generation module 700 generates the production regulation and control early warning instruction, and the fourth generation module 800 generates the traceability analysis result.
As shown in fig. 7, as another preferred embodiment of the present invention, the first acquisition and analysis module 300 specifically includes:
An extracting unit 301, configured to extract a first sub-parameter, a second sub-parameter, and a third sub-parameter of the targeted product parameters;
a judging unit 302, configured to respectively judge whether the first sub-parameter, the second sub-parameter, and the third sub-parameter are smaller than the corresponding parameter threshold;
A first generating unit 303, configured to generate a low-proportion control instruction if at least one of the first sub-parameter, the second sub-parameter, and the third sub-parameter is smaller than the corresponding parameter threshold;
A second generating unit 304, configured to generate a middle-scale control instruction if at least two sub-parameters of the first sub-parameter, the second sub-parameter, and the third sub-parameter are smaller than the corresponding parameter threshold;
The third generating unit 305 is configured to generate a high-proportion control instruction if the first sub-parameter, the second sub-parameter and the third sub-parameter are all smaller than the corresponding parameter threshold.
In this embodiment, when the method is applied, the extracting unit 301 is configured to extract a first sub-parameter, a second sub-parameter, and a third sub-parameter of the target product parameter, the judging unit 302 respectively judges whether the first sub-parameter, the second sub-parameter, and the third sub-parameter are smaller than the corresponding parameter threshold, the first generating unit 303 generates a low-proportion control instruction if at least one of the first sub-parameter, the second sub-parameter, and the third sub-parameter is smaller than the corresponding parameter threshold, the second generating unit 304 generates a medium-proportion control instruction if at least two of the first sub-parameter, the second sub-parameter, and the third sub-parameter are smaller than the corresponding parameter threshold, and the third generating unit 305 generates a high-proportion control instruction.
As shown in fig. 8, as another preferred embodiment of the present invention, the second generating module 500 specifically includes:
an acquisition unit 501 for acquiring a product production task amount;
the first detection unit 502 is configured to detect a three-product production task amount based on the product production task amount if a low-proportion control instruction is generated;
a fourth generating unit 503, configured to generate first feedback data;
The second detecting unit 504 is configured to detect a six-product production task amount based on the product production task amount if the intermediate ratio control instruction is generated;
a fifth generating unit 505, configured to generate second feedback data;
a third detecting unit 506, configured to detect all the product production task amounts based on the product production task amounts if a high-proportion control instruction is generated;
a sixth generating unit 507 for generating third feedback data.
In this embodiment, when applied, the obtaining unit 501 obtains the product production task amount, if a low-proportion control instruction is generated, based on the product production task amount, the first detecting unit 502 detects the three product production task amounts, the fourth generating unit 503 generates first feedback data, if a medium-proportion control instruction is generated, based on the product production task amount, the second detecting unit 504 detects the six product production task amounts, the fifth generating unit 505 generates second feedback data, if a high-proportion control instruction is generated, based on the product production task amount, the third detecting unit 506 detects all product production task amounts, and the sixth generating unit 507 generates third feedback data.
As shown in fig. 9, as another preferred embodiment of the present invention, the third generating module 700 specifically includes:
a retrieving unit 701, configured to retrieve the first feedback data, the second feedback data, and the third feedback data;
A seventh generating unit 702, configured to generate a speed control instruction if the first feedback data or the second feedback data is retrieved;
the eighth generating unit 703 is configured to generate a shutdown instruction if the third feedback data is retrieved.
In this embodiment, when the present invention is applied, the search unit 701 searches the first feedback data, the second feedback data, and the third feedback data, and if the first feedback data or the second feedback data is searched, the seventh generation unit 702 generates the speed control instruction, and if the third feedback data is searched, the eighth generation unit 703 generates the shutdown instruction.
The above embodiment of the present invention provides a standardized quality management early warning method based on big data analysis, and provides a standardized quality management early warning system based on big data analysis, the production line is provided with an automatic acquisition device, which can perform automatic parameter acquisition and detection on production line products, in the production process of the production line, a quality control instruction can be issued at any time, when the quality control instruction is issued, the production line products can be positioned, a targeted product is positioned as a punctuation quality control product, and automatic detection of each parameter is performed on the targeted product, a targeted product parameter is generated, whether a first sub-parameter, a second sub-parameter and a third sub-parameter in the targeted product parameter are smaller than a parameter threshold value is extracted, if the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the parameter threshold value, a low-ratio control instruction is generated, if the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the parameter threshold value, a medium-ratio control instruction is generated, if the first sub-parameter, the second sub-parameter and the third sub-parameter are smaller than the parameter, the quality control instruction is higher than the parameter, the quality control instruction is generated, and if the quality control instruction is higher than the parameter, the quality control instruction is lower than the parameter, the quality control instruction is generated, and the quality control instruction is lower than the parameter threshold value, and the quality control instruction is generated, and the quality control instruction is further, and the quality control instruction is reduced by the quality control instruction is performed by comparing the quality control instruction, then, based on the production regulation and control instruction, carrying out problem analysis on the product with quality inspection problem, generating a traceability analysis result, determining corresponding production procedures and corresponding production personnel, and completing standardized quality management; the method and the system can conduct proportional control and analysis on the production line products, conduct quality analysis on the products in a diversified mode, conduct quantitative detection based on the number of types of problems in the quality analysis, further generate production regulation and control early warning instructions and traceability analysis results according to quantitative detection results, and improve product standardization quality and quality control management improvement efficiency.
In order to be able to load the method and system described above to function properly, the system may include more or less components than those described above, or may combine some components, or different components, in addition to the various modules described above, for example, may include input and output devices, network access devices, buses, processors, memories, and the like.
The processor may be a central processing unit, or may be other general purpose processors, digital signal processors, application specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the above system, and various interfaces and lines are used to connect the various parts.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.