CN111832931A - Intelligent factory personnel flow detection method based on big data - Google Patents
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Abstract
The invention discloses a big data-based intelligent factory personnel flow detection system, which comprises a fingerprint card punching device, a detection device, a timer, a total database and a display, wherein the total database is respectively connected with a personal database, a data processing module and a device recording module, the personal data module is connected with a data input module and the fingerprint card punching device, the data processing module is connected with the display and an order input module, the display and the timer are both connected with a fingerprint switch module, and the fingerprint switch module and the device recording module are both connected with the detection device. The overall production efficiency of the factory is improved.
Description
Technical Field
The invention relates to the technical field of intelligent factories, in particular to a method for detecting the flow of intelligent factory personnel based on big data.
Background
The intelligent factory is a new stage of modern factory informatization development, and is based on a digital factory, information management and service are enhanced by using the technology of the Internet of things and the equipment monitoring technology, the production and marketing process is clearly mastered, the controllability of the production process is improved, manual intervention on a production line is reduced, production line data is timely and correctly acquired, and reasonable production planning and production progress are realized;
but at present because of the wisdom factory personnel of big data flow in detecting, do not set up the convenient record analysis module to personal data, do not know personnel's behavior, thereby lead to the production efficiency of how influence mill of reasonable accuracy not enough of personnel's distribution.
Disclosure of Invention
The invention provides a smart factory personnel flow detection method based on big data, which can effectively solve the problem that the production efficiency of a factory is influenced because personnel allocation is not reasonable and accurate because no recording and analyzing module convenient for personal data is arranged and the working condition of personnel is not known in the conventional smart factory personnel flow detection based on big data in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a big data-based intelligent factory personnel flow detection system comprises fingerprint card punching equipment, detection equipment, a timer, a total database and a display, wherein the total database is respectively connected with a personal database, a data processing module and an equipment recording module, the personal data module is connected with a data entry module and the fingerprint card punching equipment, the data processing module is connected with the display and an order input module, the display and the timer are both connected with a fingerprint switch module, and the fingerprint switch module and the equipment recording module are both connected with the detection equipment;
the fingerprint input module, the newly-built data module and the data retrieval module are arranged in the personal database;
the display displays the detection production line, the name of the inspector and the opening time of the equipment.
Preferably, after the fingerprint of the employee is scanned by a fingerprint input module in the fingerprint card punching equipment, the fingerprints are compared, and after a personal database with the same fingerprint is detected, the information of the personal database is called to a total database through a data calling module;
and the fingerprint input module receives the fingerprint input for the first time and establishes a new database through the newly-built data module.
Preferably, the order input module receives the order information of the current day, the data received by the called personal database, the equipment recording module and the order input module in the total database simultaneously enter the data processing module, the data are analyzed and processed by the data processing module to perform allocation operation on the personnel, the fingerprint switch module receives the fingerprint of the personnel entering the detection workshop, the detection equipment is started, the timer starts to time, and the name of the personnel, the detection production line and the equipment starting time are displayed on the display.
Preferably, after the detection device completes the detection task, the detection device sends the detection data to the device recording module, the device recording module sends the detection data to the total database, the detection device is periodically detected and maintained, and the device damage condition is conveyed to the device recording module.
Preferably, the detection step of the product by the detection device is as follows:
s1, a new employee is programmed into a C-level inspector to enter a first-level detection, and a product sequentially passes through B, A and the C-level inspector;
s2, classifying products detected by a class B inspector, checking by the class A inspector, and evaluating the detection result of the class B inspector;
s3, checking and comparing the products after the second-level detection by a C-level inspector;
s4, classifying the qualified products and the unqualified products in the first-stage detection, and entering the secondary detection;
s5, after the second-stage detection, dividing the four groups into a third-stage detection;
and S6, dividing the products after the third-level detection into three groups, namely, to-be-packaged, repaired and reported to be damaged.
Preferably, the first-level detection is appearance detection, the second-level detection is label detection, and the third-level detection is performance detection;
the total detection time length of the A-level inspector is larger than 480h, the total detection time length of the B-level inspector is 240h-480h, and the total detection time length of the C-level inspector is 0-240 h.
Preferably, promotion standard in the second-level detection is the same as that of the first-level detection, the second-level detection is started when the total detection time of the A-level inspector in the first-level detection is longer than 920h, the detection is started from the position of the C-level inspector in the second-level detection, and the third-level detection is started until the A-level inspector in the second-level detection is promoted and the total detection time reaches 920 h.
Preferably, when the A-level inspector in the secondary detection enters the third-level detection, the C-level inspector is programmed into the third-level detection, the total detection time length is upgraded to the B-level inspector after reaching 480h, and the total detection time length is upgraded to the A-level inspector after reaching 960 h.
Preferably, the inspection quantity and the inspection effect of the inspectors of the B level and the C level are manually input by the inspectors of the A level in the first level inspection and the second level inspection through a data input module;
and the A-level inspector in the third-level detection inputs the detection number and the detection effect of the B-level inspector, the C-level inspector and the A-level inspector in the rest two-level detection through the data input module.
Preferably, in S4, the products after the first-stage detection are divided into two groups, namely products that are qualified in the first-stage detection and products that are not qualified in the first-stage detection;
in the step S5, products after the second-stage detection are divided into four groups of products qualified by two-stage detection, products unqualified by only the first-stage detection, products unqualified by only the second-stage detection and products unqualified by two-stage detection;
in the step S6, the products after the third-level detection are divided into three groups, namely, a product to be packaged, a repair product and a damage reporting product, the product to be packaged is a product which is qualified after the third-level detection, the damage reporting product is an unqualified product after the third-level detection, and the sum of the product to be packaged, the repair product and the damage reporting product is equal to the total product quantity;
and the repaired products enter a first-level detection and a second-level detection after being repaired, the repaired products are directly classified into a product group to be packaged after being qualified, and the rest products are subjected to price reduction sale processing.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the personal database and the data entry module are arranged to record the personal data, so that the personal data can be conveniently allocated, and the flow distribution is carried out on the detection personnel by combining the order production task and the equipment operation condition, so that the production can be reasonably planned, and the overall production efficiency of a factory is improved;
through reasonable distribution of the employees and manual input of detection conditions, the detection conditions of inspectors can be conveniently known, a reasonable promotion system is clear, the actual detection capability of the employees can be known through promotion grades of the employees, and promotion and management of the employees are facilitated;
through the classification detection of the appearance, the label and the performance of the product, the qualified product to be packaged is detected, the unqualified damage reporting product is removed, the product with the good performance is recovered and repaired, the product which can be normally sold after being repaired is packaged, and the product which can not be normally sold is subjected to price reduction treatment, so that the defective rate of the product is reduced, and the production loss of a factory is reduced.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a schematic diagram of the system architecture of the present invention;
FIG. 2 is a flow chart of the detection of the present invention;
FIG. 3 is a schematic view of the product testing of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1: as shown in fig. 1, the present invention provides a technical solution, a smart factory personnel flow detection system based on big data, which includes a fingerprint card punching device, a detection device, a timer, a total database and a display, wherein the total database is respectively connected with a personal database, a data processing module and a device recording module, the personal data module is connected with a data entry module and the fingerprint card punching device, the data processing module is connected with the display and an order input module, the display and the timer are both connected with a fingerprint switch module, and the fingerprint switch module and the device recording module are both connected with the detection device;
a fingerprint input module, a newly-built data module and a data retrieval module in the personal database;
the display displays the detection production line, the name of the inspector and the opening time of the equipment.
After a fingerprint input module in the fingerprint card punching equipment scans the fingerprints of the employees, the fingerprints are compared, and after a personal database with the same fingerprint is detected, the information of the personal database is called to a total database through a data calling module;
the fingerprint input module receives the fingerprint input for the first time and establishes a new database through the new data building module.
The order input module receives the order information of the current day, the data received by the called personal database, the equipment recording module and the order input module in the total database simultaneously enter the data processing module, the data are analyzed and processed by the data processing module to carry out allocation operation on the staff, the fingerprint switch module receives the fingerprint of the staff entering the detection workshop, the detection equipment is started, the timer starts to time, and the staff name, the detection production line and the equipment starting time are displayed on the display.
After the detection equipment completes the detection task, the detection equipment sends the detection data to the equipment recording module, the equipment recording module sends the detection data to a total database, the detection equipment is detected and maintained every month, and the equipment damage condition is conveyed to the equipment recording module.
Example 2: as shown in fig. 2-3, the present invention provides a technical solution, wherein the detection steps of the product by the detection device are as follows:
s1, a new employee is programmed into a C-level inspector to enter a first-level detection, and a product sequentially passes through B, A and the C-level inspector;
s2, classifying products detected by a class B inspector, checking by the class A inspector, and evaluating the detection result of the class B inspector;
s3, checking and comparing the products after the second-level detection by a C-level inspector;
s4, classifying the qualified products and the unqualified products in the first-stage detection, and entering the secondary detection;
s5, after the second-stage detection, dividing the four groups into a third-stage detection;
and S6, dividing the products after the third-level detection into three groups, namely, to-be-packaged, repaired and reported to be damaged.
The first-level detection is appearance detection, the second-level detection is label detection, and the third-level detection is performance detection;
the total detection time of the A-level inspectors is larger than 480h, the total detection time of the B-level inspectors is 240h-480h, and the total detection time of the C-level inspectors is 0-240 h.
Promotion standard in the second-level detection is the same as that of the first-level detection, the second-level detection is started when the total detection time of A-level inspectors in the first-level detection is longer than 920h, the detection is started from the post of C-level inspectors in the second-level detection, and the third-level detection is started until the A-level inspectors in the second-level detection are upgraded and the total detection time reaches 920 h.
When the A-level inspector in the secondary detection enters the third-level detection, the C-level inspector is programmed in the third-level detection, the total detection time length is upgraded to the B-level inspector after reaching 480h, and the total detection time length is upgraded to the A-level inspector after reaching 960 h.
The A-level inspectors in the first-level detection and the second-level detection manually input the detection number and the detection effect of the B-level inspectors and the C-level inspectors through a data input module;
and the A-level inspector in the third-level detection inputs the detection number and the detection effect of the B-level inspector, the C-level inspector and the A-level inspector in the rest two-level detection through the data input module.
In S4, products after the first-stage detection are divided into two groups of products which are qualified in the first-stage detection and unqualified in the first-stage detection;
in S5, products after the second-stage detection are divided into four groups of products qualified by the two-stage detection, products unqualified by the first-stage detection only, products unqualified by the second-stage detection only and products unqualified by the two-stage detection;
in S6, products after the third-level detection are divided into three groups, namely products to be packaged, repair products and damage reporting products, the products to be packaged are qualified products after the third-level detection, the damage reporting products are unqualified products after the third-level detection, and the sum of the products to be packaged, the repair products and the damage reporting products is equal to the total product quantity;
and (4) the repaired product enters a first-stage detection and a second-stage detection after being repaired, the repaired product is directly classified into a product group to be packaged after being qualified, and the rest products are subjected to price reduction sale treatment.
The working principle and the using process of the invention are as follows: after a fingerprint input module in the fingerprint card printing equipment scans fingerprints of employees, the fingerprints are compared, after personal databases with the same fingerprints are detected, information of the personal databases is called to a total database through a data calling module, the fingerprint input module receives the fingerprints which are firstly input, a new database is established through a newly-built data module, an order input module receives order information on the day, data received by the called personal databases, an equipment recording module and the order input module in the total database simultaneously enter a data processing module, the data are analyzed and processed through the data processing module to distribute the employees, when the fingerprint switch module receives the fingerprints when the employees enter a detection workshop, detection equipment is started, a timer starts to time, and employee names, detection production lines and equipment starting time are displayed on a display;
after the detection device completes the detection task, the detection device sends the detection data to the device recording module, the device recording module sends the detection data to a general database, the detection device is detected and maintained every month, and the device damage condition is conveyed to the device recording module;
the product after the appearance of the product is detected by the first-level detection is divided into two groups of products which are qualified by the first-level detection and unqualified by the first-level detection, the product enters the second-level detection, the product after the label detection by the second-level detection is divided into four groups of products which are qualified by two-time detection, products which are unqualified by only the first-level detection, products which are unqualified by only the second-level detection and unqualified by two-time detection, the product enters the third-level detection, the products which are qualified by the third-level detection are divided into three groups of products to be packaged, repair products and damage reporting products, the repair products enter the first-level detection and the second-level detection after being repaired.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides an wisdom factory personnel flow detecting system based on big data which characterized in that: the system comprises fingerprint card punching equipment, detection equipment, a timer, a total database and a display, wherein the total database is respectively connected with a personal database, a data processing module and an equipment recording module, the personal data module is connected with a data input module and the fingerprint card punching equipment, the data processing module is connected with the display and an order input module, the display and the timer are both connected with a fingerprint switch module, and the fingerprint switch module and the equipment recording module are both connected with the detection equipment;
the fingerprint input module, the newly-built data module and the data retrieval module are arranged in the personal database;
the display displays the detection production line, the name of the inspector and the opening time of the equipment.
2. The intelligent factory personnel flow detection system based on big data as claimed in claim 1, wherein after a fingerprint entry module in the fingerprint card punching equipment scans the fingerprints of employees, the fingerprints are compared, and after a personal database with the same fingerprint is detected, the information of the personal database is called to a total database through a data calling module;
and the fingerprint input module receives the fingerprint input for the first time and establishes a new database through the newly-built data module.
3. The intelligent factory personnel flow detection system based on big data as claimed in claim 1, wherein the order input module receives the order information of the day, the data received by the called personal database, the equipment recording module and the order input module in the total database simultaneously enter the data processing module, the data processing module analyzes and processes the data to perform distribution operation on personnel, the fingerprint switch module receives the fingerprint of the personnel entering the detection workshop, the detection equipment is started, the timer starts to time, and the name of the personnel, the detection production line and the equipment starting time are displayed on the display.
4. The intelligent factory staff flow detection system based on big data as claimed in claim 1, wherein after the detection device completes the detection task, the detection device sends the detection data to the device recording module, the device recording module sends the detection data to the general database, the detection device is periodically detected and maintained, and the device damage condition is sent to the device recording module.
5. The method for detecting the intelligent factory personnel flow detection system based on big data as claimed in claims 1-4, wherein the detection steps of the detection device for the product are as follows:
s1, a new employee is programmed into a C-level inspector to enter a first-level detection, and a product sequentially passes through B, A and the C-level inspector;
s2, classifying products detected by a class B inspector, checking by the class A inspector, and evaluating the detection result of the class B inspector;
s3, checking and comparing the products after the second-level detection by a C-level inspector;
s4, classifying the qualified products and the unqualified products in the first-stage detection, and entering the secondary detection;
s5, after the second-stage detection, dividing the four groups into a third-stage detection;
and S6, dividing the products after the third-level detection into three groups, namely, to-be-packaged, repaired and reported to be damaged.
6. The big-data based intelligent factory personnel flow detection method as claimed in claim 5, wherein the first level detection is appearance detection, the second level detection is label detection, and the third level detection is performance detection;
the total detection time length of the A-level inspector is larger than 480h, the total detection time length of the B-level inspector is 240h-480h, and the total detection time length of the C-level inspector is 0-240 h.
7. The method as claimed in claim 5, wherein the promotion standard in the second level test is the same as that of the first level test, the second level test is performed when the total test time of the A-level inspectors in the first level test is longer than 920h, the test is performed from the C-level inspectors in the second level test until the third level test is performed after the A-level inspectors in the second level test are promoted and the total test time is up to 920 h.
8. The intelligent factory personnel flow detection method based on big data as claimed in claim 5, wherein when the class A inspector in the secondary inspection enters the third inspection, the class C inspector programmed in the third inspection is upgraded to the class B inspector after the total detection time reaches 480h, and the class A inspector after the total detection time reaches 960 h.
9. The intelligent factory personnel flow detection method based on big data as claimed in claim 5, wherein the class A inspectors in the first-class detection and the second-class detection manually enter the detection number and detection effect of class B and class C inspectors through a data entry module;
and the A-level inspector in the third-level detection inputs the detection number and the detection effect of the B-level inspector, the C-level inspector and the A-level inspector in the rest two-level detection through the data input module.
10. The method as claimed in claim 5, wherein in step S4, the products after the first-stage inspection are classified into two groups, i.e. qualified products and unqualified products;
in the step S5, products after the second-stage detection are divided into four groups of products qualified by two-stage detection, products unqualified by only the first-stage detection, products unqualified by only the second-stage detection and products unqualified by two-stage detection;
in the step S6, the products after the third-level detection are divided into three groups, namely, a product to be packaged, a repair product and a damage reporting product, the product to be packaged is a product which is qualified after the third-level detection, the damage reporting product is an unqualified product after the third-level detection, and the sum of the product to be packaged, the repair product and the damage reporting product is equal to the total product quantity;
and the repaired products enter a first-level detection and a second-level detection after being repaired, the repaired products are directly classified into a product group to be packaged after being qualified, and the rest products are subjected to price reduction sale processing.
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| CN202010655537.7A CN111832931A (en) | 2020-07-09 | 2020-07-09 | Intelligent factory personnel flow detection method based on big data |
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| CN202010655537.7A CN111832931A (en) | 2020-07-09 | 2020-07-09 | Intelligent factory personnel flow detection method based on big data |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114707847A (en) * | 2022-03-30 | 2022-07-05 | 南昌菱形信息技术有限公司 | Intelligent factory personnel flow detection method and system based on 5G technology |
| CN116384682A (en) * | 2023-04-04 | 2023-07-04 | 江苏智慧工场技术研究院有限公司 | Intelligent factory personnel flow detection system and detection method thereof |
-
2020
- 2020-07-09 CN CN202010655537.7A patent/CN111832931A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114707847A (en) * | 2022-03-30 | 2022-07-05 | 南昌菱形信息技术有限公司 | Intelligent factory personnel flow detection method and system based on 5G technology |
| CN114707847B (en) * | 2022-03-30 | 2023-05-26 | 南昌菱形信息技术有限公司 | Intelligent factory personnel flow detection method and system based on 5G technology |
| CN116384682A (en) * | 2023-04-04 | 2023-07-04 | 江苏智慧工场技术研究院有限公司 | Intelligent factory personnel flow detection system and detection method thereof |
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Application publication date: 20201027 |