CN114118878B - Online centralized quality analysis decision system based on hub detection and review framework - Google Patents
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Abstract
The invention provides an online centralized quality analysis decision-making system based on a hub detection review framework, which comprises: the system comprises hub defect detection equipment, a distributed file storage unit, a hub defect detection algorithm model, a message middleware, a hub online centralized quality analysis review platform, a message queue, a database and data display application; and the hub online centralized quality analysis review platform distributes the preliminary review result to corresponding reviewers according to the defect grade and the defect type of the hub defects. The invention carries out centralized manual secondary evaluation on the hub detection results of a plurality of factories in an online centralized evaluation mode, adopts an automatic assignment mode and increases the condition limit of assignment: the defect types are distributed according to the defect grades of the hubs, and the same reviewer only reviews the defects of the same type, so that the review quality and efficiency are ensured; and automatically feeding back the artificial secondary evaluation result to the algorithm model to be used as a training and tuning basis, so that the evaluation accuracy of the algorithm model is improved.
Description
Technical Field
The invention relates to the technical field of quality analysis systems, in particular to an online centralized quality analysis decision-making system based on a hub detection and review framework.
Background
During transportation or hub production, many defects such as air holes, cracks, slag inclusions, shrinkage cavities and the like are inevitably generated in the casting process, and various off-line or on-line hub defect detection methods are generally adopted for detection, such as a visual detection method, a fluorescence penetration method, an ultrasonic detection method, an eddy current detection method, an X-ray detection method and the like.
The results detected by all hub defect detection methods still have a certain proportion of misjudgments or inaccuracy, and the detection results need to be manually reviewed, recorded and analyzed for the second time, so that the reliability of the final hub defect detection results is further guaranteed.
However, in the existing hub production and casting process, the defect detection method has the following problems:
1) at present, in offline manual review, a special technician is required to wait for a primary hub defect result analyzed and judged by an algorithm model before each X-ray machine to perform secondary confirmation review on the defect result, so that great labor waste is caused;
2) the offline manual secondary evaluation of each X-ray machine is relatively independent, and the data such as the primary evaluation result, the secondary manual evaluation result and the like cannot be automatically gathered, counted and analyzed, so that a better adjustment scheme and decision suggestion can be made;
3) the existing off-line model and the feedback of the off-line manual review result have small and single sample data and are not beneficial to the training and optimization of the algorithm model;
4) the leadership decision layer cannot intuitively know the production and detection conditions of the hubs of the multiple factories in a simple mode, so that the operation decision is adjusted.
Therefore, the prior art has drawbacks and needs further improvement.
Disclosure of Invention
Aiming at more than one problem in the prior art, the invention provides an online centralized quality analysis decision-making system based on a hub detection and review framework.
In order to achieve the purpose, the invention adopts the following specific scheme:
an online centralized quality analysis decision-making system based on a hub detection review framework, comprising: the system comprises hub defect detection equipment, a distributed file storage unit, a hub defect detection algorithm model, a message middleware, a hub online centralized quality analysis review platform, a message queue, a database and data display application;
the hub defect detection equipment is used for acquiring an original picture of hub defects and storing the original picture in the distributed file storage unit; the hub defect algorithm model acquires original pictures of hub defects from the distributed file storage unit for preliminary review, and sends the preliminary review results to the message middleware, the message middleware sends the preliminary review results of the hub defects to the hub online centralized quality analysis review platform, the hub online centralized quality analysis review platform caches the preliminary review results needing manual secondary review in a message queue for gradual manual secondary review according to the sequence, the hub online centralized quality analysis review platform transmits the manual secondary review results to the message middleware, the message middleware sends the manual secondary review results to the hub defect detection algorithm model and the database, and the data display is used for displaying relevant data of the preliminary review results and the manual secondary review results;
the hub online centralized quality analysis review platform distributes the primary review result to the reviewers for manual secondary review, and distributes step by step according to the priority of the review task distribution strategy, the review task distribution strategy sets three priorities, and distributes step by step according to the sequence of the first, second and third levels:
a first stage: reviewers in an idle state in the same hub defect field;
and a second stage: when a plurality of idle reviewers exist in the first level, preferentially distributing to the reviewers with higher efficiency;
and a third stage: when a plurality of reviewers are in the second level of priority at the same time, the reviewers are firstly allocated to the reviewers with higher default priority;
wherein, higher efficiency means: the average value of the review time of the single task in the historical review tasks is shorter than that of other reviewers at the same level;
the default priority level refers to: setting according to the total amount of tasks processed in the past, wherein the priority level is higher when the total amount of the processed tasks is more, and the tasks can be received preferentially;
the field of hub defects is as follows: and classifying the review tasks of the same hub defect grade and hub defect type into the same hub defect field, and classifying and distributing the review tasks by the reviewer according to the hub defect field.
Preferably, the hub defect detecting apparatus includes: an ultrasonic detector, an eddy current detector and an X-ray machine;
the hub defect detection device is used for acquiring an original picture of hub defect detection and information of a hub, and storing the original picture of hub defect detection, the information of the hub and the information of the hub defect detection device into the distributed file storage unit;
the hub own information includes: the hub brand, the hub number, and the number of the mold used for producing the hub;
the information of the hub defect detection equipment comprises: equipment name, equipment number, position sensor data, valve status data.
Preferably, the hub defect algorithm model acquires an original picture of hub defect detection, hub information and hub defect detection device information from the distributed file storage unit, performs preliminary review to obtain a preliminary review result of hub defects, and then transmits the preliminary review result, the original picture of hub defect detection, the hub information and the hub defect detection device information to a message middleware;
the hub defect algorithm model stores the initial evaluation result and the information of the hub to a database;
the hub defect algorithm model adopts a fast-RCNN model;
the hub own information includes: the wheel hub brand, the wheel hub serial number, the serial number of the mould used for producing the wheel hub.
Preferably, the hub online centralized quality analysis review platform acquires a primary review result, an original picture of hub defect detection, hub self-information and hub defect detection equipment self-information from a message middleware, and caches the primary review result to a message queue according to the time sequence, and is used for performing manual secondary review on the primary review result and obtaining a secondary review result;
and the hub online centralized quality analysis review platform stores the information of the reviewers into a database.
Preferably, the message queue is used for temporarily caching the preliminary review result transmitted by the message middleware;
the message queue distributes the primary evaluation result to the logged corresponding examiners in the idle state for manual secondary evaluation according to the defect grade, the defect type and the time sequence;
and the message queue lists the overtime unviewed primary evaluation results into an abnormal alarm data queue according to the time sequence, and the primary evaluation results in the abnormal alarm data queue are distributed prior to the overtime unviewed primary evaluation results.
Preferably, the message middleware transmits the primary review result transmitted by the hub defect algorithm model, the original picture of the hub defect detection, the information of the hub and the information of the hub defect detection device to the hub online centralized quality analysis review platform, transmits the manual secondary review result transmitted by the hub online centralized quality analysis review platform to the hub defect algorithm model, and simultaneously stores the manual secondary review result to the database.
Preferably, the data display application is used for displaying the data transmitted by the hub online centralized quality analysis review platform;
the types of the data presentation application include: WEB, APP, or H5;
the data displayed by the data display application comprises: the method comprises the steps of obtaining queue data of preliminary review results to be reviewed, original pictures of hub defect detection, hub self information, hub defect detection equipment self information, overall hub qualification rate of manual secondary review, hub quantity detected by the hub defect detection equipment, hub quantity of the preliminary review of a hub defect algorithm model, and quantity and qualification rate of the manual secondary review.
Preferably, the hub online centralized quality analysis review platform comprises: the system comprises a user management module, a decision center module, a review center module, an X-ray machine state module and a statistical analysis module;
the user management module is used for managing the account number of the reviewer, and specifically comprises the following steps: adding, modifying, deleting and configuring authority;
the decision center module is used for counting, analyzing and predicting relevant data of hub production information, hub defect detection information, hub defect distribution information and manual review information;
the evaluation center module is used for manually rechecking the primary evaluation result of the hub defect algorithm model after the evaluation personnel log in;
the hub defect detection equipment state module is used for displaying the equipment state of the hub defect detection equipment in real time, so that a reviewer can conveniently judge whether the hub defect detection equipment is in a normal working state;
and the statistical analysis module is used for further performing statistics and analysis on the hub defect data subjected to the manual secondary review.
By adopting the technical scheme of the invention, the invention has the following beneficial effects:
1. the hub detection results of a plurality of factories are sent to a system for manual secondary evaluation in an online centralized evaluation mode, and once a set of hub photos are evaluated by an evaluation staff, the evaluation staff automatically distribute the next set of hub photos; conditional limits of dispatch are also increased: the hub defect classification, defect type and time sequence are distributed, and the same reviewer only reviews the defects of the same type, so that the review quality and efficiency are ensured;
2. the result of the artificial secondary evaluation is automatically fed back to the algorithm model to be used as a training and tuning basis, so that the evaluation accuracy of the algorithm model is improved;
3. the leadership decision-making layer can visually and effectively master the hub production operation conditions of a plurality of factories through the automatic statistics of the system, and make scientific and reasonable decisions.
Drawings
FIG. 1 is a system architecture diagram of the present invention;
FIG. 2 is a functional block diagram of the hub online centralized quality analysis review platform of the present invention;
FIG. 3 is a flow chart of the present invention for performing a manual secondary review.
Detailed Description
The invention is further described below with reference to the following figures and specific examples.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments.
As shown in fig. 1, the present invention provides an online centralized quality analysis decision system based on a hub detection review framework, comprising: the system comprises hub defect detection equipment, a distributed file storage unit, a hub defect detection algorithm model, a message middleware, a hub online centralized quality analysis review platform, a message queue, a database and data display application;
the hub defect detection equipment is used for acquiring an original picture of hub defects and storing the original picture in the distributed file storage unit; the hub defect algorithm model acquires original pictures of hub defects from the distributed file storage unit for preliminary review, and sends the preliminary review results to the message middleware, the message middleware sends the preliminary review results of the hub defects to the hub online centralized quality analysis review platform, the hub online centralized quality analysis review platform caches the preliminary review results needing manual secondary review in a message queue for gradual manual secondary review according to the sequence, the hub online centralized quality analysis review platform transmits the manual secondary review results to the message middleware, the message middleware sends the manual secondary review results to the hub defect detection algorithm model and the database, and the data display is used for displaying relevant data of the preliminary review results and the manual secondary review results;
the hub online centralized quality analysis review platform distributes the primary review result to review personnel for manual secondary review, and distributes step by step according to the priority of the review task distribution strategy, the review task distribution strategy sets three priorities, and distributes step by step according to the sequence of the first, second and third levels:
a first stage: reviewers in an idle state in the same hub defect field;
and a second stage: when a plurality of idle reviewers exist in the first level, preferentially distributing to the reviewers with higher efficiency;
and a third stage: when a plurality of reviewers are in the second level of priority at the same time, the reviewers are firstly allocated to the reviewers with higher default priority;
wherein, higher efficiency means: the average value of the evaluation time of a single task in the historical evaluation tasks is shorter than that of other evaluation personnel at the same level;
the default priority level refers to: setting according to the total amount of tasks processed in the past, wherein the priority level is higher when the total amount of the processed tasks is more, and the tasks can be received preferentially;
the field of hub defects is as follows: and dividing the review tasks with the same hub defect grade and hub defect type into the same hub defect field, and dividing and distributing the review tasks by the reviewers according to the hub defect field.
The hub defect detecting apparatus includes: an ultrasonic detector, an eddy current detector and an X-ray machine;
the hub defect detection device is used for acquiring an original picture of hub defect detection and information of a hub, and storing the original picture of hub defect detection, the information of the hub and the information of the hub defect detection device into the distributed file storage unit;
the hub own information includes: the hub brand, the hub number, and the number of the mold used for producing the hub;
the information of the hub defect detection equipment comprises: equipment name, equipment number, position sensor data, valve status data.
The hub defect algorithm model acquires an original picture of hub defect detection, hub self-information and hub defect detection equipment self-information from the distributed file storage unit, performs preliminary review to obtain a preliminary review result of hub defects, and then transmits the preliminary review result, the original picture of hub defect detection, the hub self-information and the hub defect detection equipment self-information to a message middleware;
the hub defect algorithm model stores the initial evaluation result and the information of the hub to a database;
the hub defect algorithm model adopts a fast-RCNN model;
the hub information itself includes: wheel hub brand, wheel hub serial number, the serial number of the used mould of production wheel hub.
The hub online centralized quality analysis review platform acquires a primary review result, an original picture of hub defect detection, hub self-information and hub defect detection equipment self-information from a message middleware, caches the primary review result to a message queue according to the time sequence, and is used for performing manual secondary review on the primary review result and obtaining a secondary review result;
and the hub online centralized quality analysis review platform stores the information of the reviewers into a database.
The message queue is used for temporarily caching the primary review result transmitted by the message middleware;
the message queue distributes the primary evaluation result to the logged corresponding examiners in the idle state for manual secondary evaluation according to the defect grade, the defect type and the time sequence;
and the message queue lists the overtime unviewed primary evaluation results into an abnormal alarm data queue according to the time sequence, and the primary evaluation results in the abnormal alarm data queue are distributed prior to the overtime unviewed primary evaluation results.
The message middleware transmits the primary review result transmitted by the hub defect algorithm model, the original picture of the hub defect detection, the information of the hub and the information of the hub defect detection equipment to the hub online centralized quality analysis review platform, transmits the manual secondary review result transmitted by the hub online centralized quality analysis review platform to the hub defect algorithm model, and simultaneously stores the manual secondary review result to the database.
The data display application is used for displaying the data transmitted by the hub online centralized quality analysis review platform;
the types of the data presentation application include: WEB, APP, or H5;
the data displayed by the data display application comprises: the method comprises the steps of obtaining queue data of preliminary review results to be reviewed, original pictures of hub defect detection, hub self information, hub defect detection equipment self information, overall hub qualification rate of manual secondary review, hub quantity detected by the hub defect detection equipment, hub quantity of the preliminary review of a hub defect algorithm model, and quantity and qualification rate of the manual secondary review.
As shown in fig. 2, the hub online centralized quality analysis review platform comprises: the system comprises a user management module, a decision center module, a review center module, an X-ray machine state module and a statistical analysis module;
the user management module is used for managing the account number of the reviewer, and specifically comprises the following steps: adding, modifying, deleting and configuring authority;
the decision center module is used for counting, analyzing and predicting relevant data of hub production information, hub defect detection information, hub defect distribution information and manual review information;
the evaluation center module is used for manually rechecking the primary evaluation result of the hub defect algorithm model after the evaluation personnel log in;
the hub defect detection equipment state module is used for displaying the equipment state of the hub defect detection equipment in real time, so that a reviewer can conveniently judge whether the hub defect detection equipment is in a normal working state;
and the statistical analysis module is used for further performing statistics and analysis on the hub defect data subjected to the manual secondary review.
As shown in fig. 3, the step of manual secondary review includes:
the hub online centralized quality analysis review platform is logged in by the reviewers;
entering a review center module, then entering a review function page,
carrying out manual secondary evaluation on the automatically distributed primary evaluation result to be evaluated;
and the statistical analysis module further performs statistics and analysis on the manual secondary evaluation result.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
1. the hub detection results of a plurality of factories are sent to a system for manual secondary evaluation in an online centralized evaluation mode, and once a set of hub photos are evaluated by an evaluation staff, the evaluation staff automatically distribute the next set of hub photos; conditional limits of dispatch are also increased: the hub defect classification, defect type and time sequence are distributed, and the same reviewer only reviews the defects of the same type, so that the review quality and efficiency are ensured;
2. the result of the artificial secondary evaluation is automatically fed back to the algorithm model to be used as a training and tuning basis, so that the evaluation accuracy of the algorithm model is improved;
3. the leadership decision-making layer can visually and effectively master the hub production operation conditions of a plurality of factories through the automatic statistics of the system, and make scientific and reasonable decisions.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (4)
1. An online centralized quality analysis decision system based on a hub detection review framework, comprising: the system comprises hub defect detection equipment, a distributed file storage unit, a hub defect detection algorithm model, a message middleware, a hub online centralized quality analysis review platform, a message queue, a database and data display application;
the hub defect detection equipment is used for acquiring an original picture of hub defects and storing the original picture in the distributed file storage unit; the hub defect algorithm model acquires original pictures of hub defects from the distributed file storage unit for preliminary review, and sends the preliminary review results to the message middleware, the message middleware sends the preliminary review results of the hub defects to the hub online centralized quality analysis review platform, the hub online centralized quality analysis review platform caches the preliminary review results needing manual secondary review in a message queue, the hub online centralized quality analysis review platform carries out step-by-step manual secondary review according to the sequence, the hub online centralized quality analysis review platform transmits the manual secondary review results to the message middleware, the message middleware sends the manual secondary review results to the hub defect detection algorithm model and the database, and the data display is used for displaying relevant data of the preliminary review results and the manual secondary review results;
the hub online centralized quality analysis review platform distributes the primary review result to the reviewers for manual secondary review, and distributes step by step according to the priority of the review task distribution strategy, the review task distribution strategy sets three priorities, and distributes step by step according to the sequence of the first, second and third levels:
a first stage: reviewers in an idle state in the same hub defect field;
and a second stage: when a plurality of idle reviewers exist in the first level, preferentially distributing to the reviewers with higher efficiency;
and a third stage: when a plurality of reviewers are in the second level of priority at the same time, the reviewers are firstly allocated to the reviewers with higher default priority;
wherein, higher efficiency means: the average value of the evaluation time of a single task in the historical evaluation tasks is shorter than that of other evaluation personnel at the same level;
the default priority level refers to: setting according to the total amount of tasks processed in the past, wherein the priority level is higher when the total amount of the processed tasks is more, and the tasks can be received preferentially;
the field of hub defects is as follows: dividing review tasks with the same hub defect grade and hub defect type into the same hub defect field, and dividing and distributing the review tasks by review personnel according to the hub defect field;
the hub defect detecting apparatus includes: an ultrasonic detector, an eddy current detector and an X-ray machine;
the hub defect detection device is used for acquiring an original picture of hub defect detection and information of a hub, and storing the original picture of hub defect detection, the information of the hub and the information of the hub defect detection device into the distributed file storage unit;
the hub own information includes: the hub brand, the hub number, and the number of the mold used for producing the hub;
the information of the hub defect detection equipment comprises: equipment name, equipment number, position sensor data and valve state data;
the hub defect algorithm model acquires an original picture of hub defect detection, hub self-information and hub defect detection equipment self-information from the distributed file storage unit, performs preliminary review to obtain a preliminary review result of hub defects, and then transmits the preliminary review result, the original picture of hub defect detection, the hub self-information and the hub defect detection equipment self-information to a message middleware;
the hub defect algorithm model stores the initial review result and the information of the hub to a database;
the hub defect algorithm model adopts a fast-RCNN model;
the hub online centralized quality analysis review platform acquires a primary review result, an original picture of hub defect detection, hub self-information and hub defect detection equipment self-information from a message middleware, caches the primary review result to a message queue according to the time sequence, and is used for performing manual secondary review on the primary review result and obtaining a secondary review result;
the hub online centralized quality analysis review platform stores the information of the reviewers into a database;
the hub online centralized quality analysis review platform comprises: the system comprises a user management module, a decision center module, a review center module, an X-ray machine state module and a statistical analysis module;
the user management module is used for managing the account number of the reviewer, and specifically comprises the following steps: adding, modifying, deleting and configuring authority;
the decision center module is used for counting, analyzing and predicting relevant data of hub production information, hub defect detection information, hub defect distribution information and manual review information;
the evaluation center module is used for manually rechecking the primary evaluation result of the hub defect algorithm model after the evaluation personnel log in;
the hub defect detection equipment state module is used for displaying the equipment state of the hub defect detection equipment in real time, so that a reviewer can conveniently judge whether the hub defect detection equipment is in a normal working state;
and the statistical analysis module is used for further performing statistics and analysis on the hub defect data subjected to the manual secondary review.
2. The hub detection review framework based online centralized quality analysis decision making system according to claim 1, wherein the message queue is used for temporarily caching the preliminary review results transmitted by the message middleware;
the message queue distributes the primary evaluation result to the logged corresponding examiners in the idle state for manual secondary evaluation according to the defect grade, the defect type and the time sequence;
and the message queue lists the overtime unviewed primary evaluation results into an abnormal alarm data queue according to the time sequence, and the primary evaluation results in the abnormal alarm data queue are distributed prior to the overtime unviewed primary evaluation results.
3. The on-line centralized quality analysis and decision-making system based on the hub detection and review framework as claimed in claim 1, wherein the message middleware transfers the primary review result transmitted by the hub defect algorithm model, the original picture of the hub defect detection, the information of the hub itself and the information of the hub defect detection device itself to the hub on-line centralized quality analysis and review platform, and transfers the manually performed secondary review result transmitted by the hub on-line centralized quality analysis and review platform to the hub defect algorithm model, and simultaneously saves the manually performed secondary review result to a database.
4. The hub detection and review framework based online centralized quality analysis decision making system according to claim 1, wherein the data presentation application is configured to present data transmitted from the hub online centralized quality analysis review platform;
the types of the data presentation application include: WEB, APP, or H5;
the data displayed by the data display application comprises: the method comprises the steps of obtaining queue data of preliminary review results to be reviewed, original pictures of hub defect detection, hub self information, hub defect detection equipment self information, overall hub qualification rate of manual secondary review, hub quantity detected by the hub defect detection equipment, hub quantity of the preliminary review of a hub defect algorithm model, and quantity and qualification rate of the manual secondary review.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104899143A (en) * | 2015-06-15 | 2015-09-09 | 中国航空无线电电子研究所 | Software peer review system realizing device for providing DM (Data Mining) |
| CN112308241A (en) * | 2020-09-28 | 2021-02-02 | 深圳优地科技有限公司 | Robot production management system, method, device and storage medium |
| WO2021120186A1 (en) * | 2019-12-20 | 2021-06-24 | 京东方科技集团股份有限公司 | Distributed product defect analysis system and method, and computer-readable storage medium |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110376220A (en) * | 2019-08-02 | 2019-10-25 | 中电九天智能科技有限公司 | Realize the device and method of real-time judgment glass panel defect |
| CN113112216A (en) * | 2021-03-03 | 2021-07-13 | 广东电网有限责任公司 | Prejudgment analysis method for equipment defects |
| CN113567446B (en) * | 2021-07-06 | 2022-07-19 | 北京东方国信科技股份有限公司 | Method and system for grading component defect detection quality |
| CN113470018B (en) * | 2021-09-01 | 2021-12-21 | 深圳市信润富联数字科技有限公司 | Hub defect identification method, electronic device, device and readable storage medium |
-
2022
- 2022-01-21 CN CN202210071260.2A patent/CN114118878B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104899143A (en) * | 2015-06-15 | 2015-09-09 | 中国航空无线电电子研究所 | Software peer review system realizing device for providing DM (Data Mining) |
| WO2021120186A1 (en) * | 2019-12-20 | 2021-06-24 | 京东方科技集团股份有限公司 | Distributed product defect analysis system and method, and computer-readable storage medium |
| CN112308241A (en) * | 2020-09-28 | 2021-02-02 | 深圳优地科技有限公司 | Robot production management system, method, device and storage medium |
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