CN111814113A

CN111814113A - Early warning method and system for product manufacturing, electronic equipment and storage medium

Info

Publication number: CN111814113A
Application number: CN202010519605.7A
Authority: CN
Inventors: 王超; 宣晓敏; 刘鹏; 韩松; 熊丽琼
Original assignee: Accelink Technologies Co Ltd
Current assignee: Accelink Technologies Co Ltd
Priority date: 2020-06-09
Filing date: 2020-06-09
Publication date: 2020-10-23

Abstract

The technical scheme of the application provides an early warning method for product manufacturing, which comprises the following steps: determining whether the detection target is qualified; counting the statistic value of the detection target within a preset time length; and when determining that the abnormal phenomenon corresponding to the early warning line occurs in the detection target according to the statistical value, early warning for product manufacture is carried out. The scheme realizes automatic early warning of product manufacture in the product manufacture process.

Description

Early warning method and system for product manufacturing, electronic equipment and storage medium

Technical Field

The present invention relates to the field of product manufacturing, and in particular, to a method and a system for early warning of product manufacturing, an electronic device, and a storage medium.

Background

With the development of the manufacturing industry and the continuous change of the market demand, each manufacturing enterprise faces more difficult challenges and more pressure, in order to improve the product competitiveness, the attention of each manufacturing enterprise on the product quality is higher and higher, and the quality of the product quality is closely related to the cost and the profit of the enterprise. Many manufacturing enterprises have adopted automatic production lines to produce products, and data acquisition related to the products in various production devices in the production process is monitored in real time, but the early warning on the product quality in the product manufacturing process is not enough.

Disclosure of Invention

The embodiment of the invention provides an early warning method and system for product manufacturing, electronic equipment and a storage medium.

The technical scheme of the invention is realized as follows:

an early warning method for product manufacturing comprises the following steps: determining whether the detection target is qualified; counting the statistic value of the detection target within a preset time length; and when determining that the abnormal phenomenon corresponding to the early warning line occurs in the detection target according to the statistical value, early warning for product manufacture is carried out.

In one embodiment, the method further comprises:

determining an early warning type for early warning the product manufacture according to the process parameters of the detection target; wherein the early warning types include: the method comprises the following steps of carrying out first-class early warning according to general early warning configuration and carrying out second-class early warning according to special early warning configuration; the special early warning configuration is used for early warning of the detection target within a preset range; and the general early warning configuration is used for early warning of the detection target outside the preset range.

In one embodiment, the determining the type of the early warning for early warning of the product manufacturing according to the process parameter of the detection target includes at least one of: determining the early warning type as the second type of early warning when determining that the material used by the product to be manufactured is within a preset material group range according to the material parameters of the detection target; determining the work order of the detection target as follows according to the work order of the detection target: when one of a test order, a rework order or a retest order is selected, determining that the early warning type is the second type of early warning; determining that the early warning type is the second type of early warning according to the condition that a product to be manufactured corresponding to the detection target has a material number of a prior early warning product; and determining the early warning type as the second type of early warning according to the condition that the product to be manufactured corresponding to the detection target has a priority early warning defect.

In one embodiment, the statistics include a yield, and the statistics of the detected target within a preset time period includes: counting the qualification rate of the detection target within the preset time; when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the statistical value, early warning is carried out on product manufacture, and the method comprises the following steps: and when the qualification rate is determined to be reduced to an early warning qualification rate threshold corresponding to an early warning line according to the qualification rate, early warning is carried out on the product manufacture according to the general early warning configuration.

In one embodiment, the statistical value includes the number of abnormal parts, and the counting the statistical value of the detection target within a preset time period includes: counting the number of abnormal pieces of the detection target in the preset time length; when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the statistical value, early warning is carried out on product manufacture, and the method comprises the following steps: and when the number of the abnormal parts is determined to reach an early warning abnormal number threshold corresponding to an early warning line, early warning is carried out on the manufacture of the product according to the special early warning configuration.

In one embodiment, the statistical values are: counting the detection target by taking a working section as a counting unit to obtain the qualification rate or the number of abnormal parts; or, the statistical value is: counting the qualification rate or the number of abnormal parts obtained by taking the work order as a counting unit; or, the statistical value is: and taking key working sections in the work order as a statistical unit, and counting the detection target to obtain the qualification rate or the number of abnormal parts.

In one embodiment, the counting the statistical value of the detection target within the preset time period includes one of: taking a working section as a statistical unit, and obtaining the qualification rate of the detection target in the target working section according to the ratio of the qualified number and the input number of the detection target in the target working section within the preset time; taking a work order as a statistical unit, and obtaining the qualification rate of the detection target in the target work order according to the ratio of the input number and the qualified number of the detection target in the target work order within the preset time length; taking key work sections in the work order as a statistical unit, and obtaining the qualification rate of the detection target on the key work sections in the target work order according to the ratio of the input number of the detection target in the target work order within the preset time and the qualified number of the key work sections in the target work order; taking a working section as a statistical unit, and according to the number of abnormal pieces produced by the detection target in the target working section within the preset time length; taking the work order as a statistical unit, and according to the number of abnormal pieces produced by the detection target when the product of the target work order is manufactured within the preset time length; and taking key work sections in the work order as a statistical unit, and according to the number of abnormal pieces output by the detection target in the target work order within the preset time length.

In one embodiment, the method further comprises: acquiring an early warning processing mode determined according to the severity of early warning for manufacturing products, wherein the early warning processing mode comprises the following steps: continuing production, pausing production and stopping production; and controlling the product manufacture according to the acquired early warning processing mode.

In one embodiment, the obtaining of the early warning processing mode determined according to the severity of the early warning for the manufacturing of the product includes: sending the early warning to a first processing end; and receiving an early warning processing mode returned by the first processing terminal based on the early warning severity.

In one embodiment, the receiving of the warning processing mode that the first processing end returns based on the severity of the warning includes: and receiving the early warning processing mode which is provided by the first processing terminal according to the severity and passes the audit of the second processing terminal.

In one embodiment, the method further comprises: and sending notification information for generating early warning for the production of the product to a third processing terminal when the early warning processing mode is not received, wherein the notification information is used for prompting the processing of the early warning.

In one embodiment, the method further comprises: and closing the early warning and generating an early warning record table.

An early warning system for product manufacturing, comprising:

the determining module is used for determining whether the detection target is qualified;

the statistic module is used for counting the statistic value of the detection target within the preset time length;

and the early warning module is used for early warning the product manufacture when determining that the abnormal phenomenon corresponding to the early warning line occurs in the detection target according to the statistical value.

An electronic device, comprising:

a processor;

a memory storing program instructions that, when executed by the processor, cause the electronic device to perform any of the methods described above.

A storage medium storing a program which, when executed by a processor, performs any of the methods described above.

The technical scheme of the embodiment of the invention determines whether the detection target is qualified or not by detecting whether the detection target is qualified or not, and then counts the statistical value of the detection target in the preset time length according to the determination result of whether the detection target is qualified or not, wherein the statistical value can comprise the qualification rate of the detection target or the number of abnormal pieces and the like. And finally, when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the obtained statistic value of the detection target, the product is automatically early warned without human intervention. According to the scheme, the early warning can be carried out on the product manufacture when the qualification condition of the detection target is abnormal in the product manufacture process, the early warning production manufacture can be further detected, the probability of the product abnormity of manufacture caused by continuing to carry out the product manufacture when the qualification condition of the detection target is abnormal is reduced, and therefore the quality of the manufactured product can be improved.

Drawings

Fig. 1 is a schematic flow chart of an early warning method for manufacturing a product according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of an early warning method for manufacturing another product according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of an early warning system for manufacturing a product according to an embodiment of the present invention;

fig. 4 is a schematic flow chart of another early warning method for manufacturing a product according to an embodiment of the present invention;

fig. 5 is a schematic flow chart of another early warning method for manufacturing a product according to an embodiment of the present invention;

fig. 6 is a schematic diagram illustrating a corresponding relationship between an early warning type and a statistic of a detected target according to an embodiment of the present invention;

fig. 7 is a schematic flowchart of a priority early warning method for manufacturing a product according to an embodiment of the present invention;

FIG. 8 is a schematic diagram of a product manufacturing process according to an embodiment of the present invention;

fig. 9 is a schematic diagram of determining an early warning type according to an embodiment of the present invention;

fig. 10 is a schematic diagram of an early warning record table according to an embodiment of the present invention.

Detailed Description

The technical solution of the present invention is further described in detail with reference to the drawings and the specific embodiments of the specification.

The early warning of the product quality in the process of manufacturing the product also has many defects, for example, the early warning of the product quality in the process of manufacturing the product needs to be completed in a manual monitoring mode, and the product quality is fed back and processed after the problem is found. The mode of carrying out the early warning through the manual work is wasted time and energy to efficiency is lower. The existing early warning system has single function, cannot effectively consider all processes, all sections, various products and various defects in a production line, cannot control and monitor all production processes, and is easy to generate various omissions. And serious loss caused by continuous product manufacturing when a large number of unqualified products are generated due to failure of timely early warning can also occur.

The technical scheme of the application provides the early warning method for the product manufacturing, and early warning of the product manufacturing can be achieved according to the qualification condition of the detection target and the early warning line in the product manufacturing process.

Referring to fig. 1, a schematic flow chart of an early warning method for manufacturing a product according to the present application is shown, where the method mainly includes the following steps:

step S100, determining whether the detection target is qualified. The method comprises the steps of storing a product manufacturing object in the product manufacturing process, carrying out early warning on the product manufacturing according to the product manufacturing object in the product manufacturing process, taking the product manufacturing object in the product manufacturing process as a detection target according to business needs, detecting the detection target in the product manufacturing process, and determining whether the detection target is qualified.

And determining whether the detection target is qualified or not can be carried out according to the actual service requirement. For example, the inspection target may be determined as defective in a certain process, step or work order, and the inspection target may be determined as defective when the defect is present, or may be determined as defective when one or more of the defects are present. The defects may be defects set in advance (each defect may be represented by a code or a code), may be defect a, defect B, and/or defect C, and the like, and the defects corresponding to different detection targets may be different, so that the defect a, defect B, and/or defect C specifically represents which kind of defect may be set according to the detection target, and is not limited here.

The detection target comprises a processing object in the product manufacturing process, namely an object processed from the first working section or working procedure to the last working section or working procedure in the automatic production line. For example, it may be a single finished product, a single semi-finished product, or a single material from which a product is made, etc., involved in the product making process.

Step S200, counting the statistic value of the detection target in the preset time length. And setting detection time in advance according to actual service requirements, wherein the detection time is equivalent to preset time. For example, the preset time duration is a preset time duration in units of "hour" or the like, such as a preset time duration conforming to the actual service demand in a half hour, 1 hour or 3 hours, and is not limited herein.

And counting the statistical value of the detection target according to the preset time length, acquiring a result of whether the determined detection target is qualified or not during counting, and counting the statistical value according to the result. The statistical value of the detection target is counted in the preset time length, the statistical value is a statistical value reflecting whether the detection target is qualified, namely the statistical value reflects whether the detection target is qualified in the preset time length, and the statistical value can be a qualified rate, and can also be the quantity of abnormal pieces (unqualified quantity) or the quantity of normal pieces (qualified quantity).

In the statistical process, the process may be taken as a statistical unit, the work section may be taken as a statistical unit, the work order may be taken as a statistical unit, and the like. The specific statistical method is not particularly limited, and the qualification conditions of the detection target in a preset time length in a certain statistical unit can be collected, and the statistical value of the detection target is determined according to the qualification conditions of the detection target in the preset time length in the certain statistical unit.

And S300, when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the statistical value, early warning is carried out on the product manufacture. And determining whether the abnormal phenomenon corresponding to the early warning line occurs in the detected target or not according to the statistical value of the detected target within the statistical preset duration, and when the abnormal phenomenon corresponding to the early warning line occurs in the detected target, early warning the product manufacture.

The early warning line can be the early warning line that finishes for having set up, including early warning qualification rate and abnormal component quantity etc. that the early warning line corresponds, and this early warning line can set up through the mode of setting up of difference. For example, the setting is performed through a port such as a web page side or an Application Program Interface (API).

The abnormal phenomena corresponding to the early warning lines can include: and the statistic value of the detection target exceeds the early warning abnormal quantity threshold value corresponding to the early warning line or is lower than the early warning qualification rate threshold value corresponding to the early warning line, and the like. For example, when the statistical value of the detection target is the yield, whether the abnormal phenomenon corresponding to the early warning line occurs is determined according to the magnitude relation between the actually detected yield and the early warning yield threshold corresponding to the early warning line. And when the statistic value of the detected target is lower than the early warning qualification rate threshold, indicating that the detected target has an abnormal phenomenon corresponding to an early warning line, and early warning the product manufacture. And when the statistic value of the detection target is the number of abnormal parts, determining whether the abnormal phenomenon corresponding to the early warning line exists or not according to the size relation between the number of the actually detected abnormal parts and the early warning abnormal number threshold value corresponding to the early warning line. When the statistic value of the detected target exceeds the early warning abnormal quantity threshold value, the abnormal phenomenon corresponding to the early warning line of the detected target is shown, and early warning is carried out on the product manufacture.

The method for early warning the product manufacture can be determined according to the actual service requirement or application scene. Different early warnings can be expressed through different early warning modes, including different detection targets can be early warned through different early warning modes, different detection positions can be early warned through different early warning modes, and/or different defects can be early warned through different early warning modes, and the like.

The early warning mode can be light early warning, can also be sound early warning, can also be light and sound early warning simultaneously, can also be the mode that sends the bullet window to the control end that has control relation with the production line of product production and carry out the early warning, can also be other various modes that can carry out the early warning certainly. For example, when the detected target is a material of a certain type, the early warning is carried out in a red light early warning mode.

Whether the detection target is qualified or not is determined by detecting whether the detection target is qualified or not, and then a statistical value of the detection target in a preset time length is counted according to a determination result of whether the detection target is qualified or not, wherein the statistical value can comprise the qualification rate of the detection target or the number of abnormal parts and the like. And finally, when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the obtained statistic value of the detection target, early warning is carried out on the product manufacture.

The scheme realizes automatic statistics and automatic early warning of product manufacture in the product manufacture process, reduces the cost of manual statistics by automatic statistics, and simultaneously reduces the occurrence of inaccurate statistics caused by manual reasons. The product manufacturing can be warned when the qualification condition of the detection target is abnormal, the production manufacturing of the warning can be further detected, the probability of the manufactured product abnormity caused by the fact that the product manufacturing is continuously performed when the qualification condition of the detection target is abnormal is reduced, and therefore the quality of the manufactured product is improved.

In another embodiment, in step S200, the statistical value in the statistical values of the detection target in the preset time period may be a yield or the number of abnormal parts obtained by counting the detection target with the working section as a statistical unit. The detection target can be counted by taking the work order as a statistical unit to obtain the qualification rate or the number of abnormal pieces. And the qualification rate or the number of abnormal parts obtained by counting the detection target can be obtained by taking the key working sections in the work order as a statistical unit. This example is illustrated by taking the above three statistical approaches as examples.

The first statistical method is as follows:

when the qualification rate or the number of abnormal parts obtained by counting the detection targets by taking the working sections as a counting unit is counted, counting the counting value of the detection targets within the preset time length, wherein the counting value comprises the following steps:

and obtaining the qualification rate of the detection target in the target working section according to the ratio of the qualified number and the input number of the detection target in the target working section within the preset time, wherein the qualification rate is the statistic value of the detection target within the preset time. Taking a certain working section as a target working section, counting the statistical value of the detection target in the target working section within the preset time, counting the ratio of the qualified number and the input number of the detection target in the target working section within the preset time when the statistical value is the qualified rate, and taking the ratio as the qualified rate of the detection target in the target working section. The input number is the number of the detection targets entering the target workshop section within the preset time, and the qualified number is the number of the qualified detection targets in the detection targets entering the target workshop section within the preset time.

Counting the quantity of abnormal pieces produced by the detection target in the target working section within the preset time, wherein the quantity of the abnormal pieces is the statistical value of the detection target in the target working section within the preset time. Taking a certain working section as a target working section, counting the number of abnormal objects, namely the number of detection objects with problems, of a detection object in the target working section within a preset time length when the counting value is the qualified rate, and taking the number of the abnormal objects as the counting value of the detection object within the preset time length.

The abnormal part in this embodiment refers to an inspection target with at least one defect, and may also be understood as an unqualified inspection target, and the defect may be any defect or defects that may occur in the current product manufacturing process. The number of the abnormal parts is the number of unqualified detection targets produced in a statistical unit in a preset time length. In the current product manufacturing process, a work order is taken as a statistical unit, whether a detection target is qualified or not is further determined by determining whether the detection target has preset defects matched with the current product manufacturing, so that whether the detection target is an abnormal piece or not is obtained, and the number of the abnormal pieces is obtained.

For example, a certain type of mobile phone screen targeted as a material is detected, whether the mobile phone screen is qualified or not is determined according to whether at least one defect exists in the mobile phone film, the defect is a defect (which can be expressed as defect 001 and the like), and the unqualified mobile phone screen is regarded as an abnormal piece. And counting the number of the mobile phone screens with defects in the current working section within a preset time period by taking the working section as a counting unit, wherein the number is the number of abnormal parts. The defect may also be a specification inconsistency, which is regarded as an abnormal piece when it is determined that the specification of the inspection target is inconsistent. Of course, other defects may also exist, and the detection target with the defects is regarded as an unqualified detection target, i.e. an abnormal part.

The specification also provides a specific application scenario example of the first statistical method:

processing the mobile phone screen to be used as a product manufacture, using a working section as a statistical unit, using the mobile phone screen as a detection target, using the defect of the defect and/or the crack of the mobile phone screen as a defect, and counting the qualification rate of the mobile phone screen in the working section. And when the mobile phone screen is incomplete and/or cracked, determining the mobile phone screen as an unqualified mobile phone screen, and determining the mobile phone screen without the incomplete and/or cracked mobile phone screen as a qualified mobile phone screen. Then, the input number and the qualified number of the mobile phone screen in the working section are counted in the time period of 1 hour, and the ratio of the qualified number and the input number of the mobile phone screen is used as the qualified rate. The mode reflects the qualified condition of the mobile phone screen at a certain working section aiming at various defects.

For example, if the number of inputs of the mobile phone screen is 1000 and the number of qualified products is 950, the yield is 95%. The quality condition of the mobile phone screen in the working section is reflected by counting the qualification rate of the mobile phone screen in the working section, and whether the quality of the mobile phone screen in the working section is pre-warned can be determined according to the qualification rate so as to ensure the quality of the mobile phone screen.

The number of the abnormal parts can be used as a determining factor for reflecting the quality condition of the mobile phone screen at the working section. For example, when the number of the mobile phone screen failures determined in the working section is 100 within a preset time period, the number of abnormal parts caused by the defect of crack is 100. The number of the abnormal pieces is used as a reference, the input number of the workshop section within the preset time length does not need to be considered, no matter how many the input numbers are, early warning can be carried out when the number of the abnormal pieces reaches the threshold value of the early warning abnormal number, the quality condition of the mobile phone screen at the workshop section can be reflected more strictly, and the method is favorable for engineers to timely process and adjust equipment through defect phenomena and know the production condition of the equipment.

And a second statistical mode:

when the qualification rate or the number of abnormal parts obtained by counting the detection target by taking the work order as a counting unit is counted, counting the counting value of the detection target within the preset time length, wherein the counting value comprises the following steps:

and obtaining the qualification rate of the detection target in the target work order according to the ratio of the input number and the qualified number of the detection target in the preset time length when the product of the target work order is manufactured, wherein the qualification rate is the statistic value of the detection target in the preset time length. And taking a certain work order as a target work order, and taking the ratio of the qualified number and the input number of the target work order as the qualification rate of the detected target in the target work order within the preset time length.

And counting the quantity of abnormal pieces produced by the detection target in the preset time length when the product of the target work order is manufactured, and taking the quantity of the abnormal pieces as a statistical value of the detection target in the preset time length. For the abnormal components and the number thereof in this method, please refer to the abnormal components and the number thereof in the first statistical method.

The specification also provides a specific application scenario example of the statistical method two:

processing the mobile phone screen to be used as a product manufacture, using the work order as a statistical unit, using the mobile phone screen as a detection target, using the defect of the defect and/or the crack of the mobile phone screen as a defect, and counting the qualification rate of the mobile phone screen in the work order. And when the mobile phone screen is incomplete and/or cracked, determining the mobile phone screen as an unqualified mobile phone screen, and determining the mobile phone screen without the incomplete and/or cracked mobile phone screen as a qualified mobile phone screen. Then, the input number and the qualified number of the mobile phone screen in the work order are counted in the time duration of 1 hour, and the ratio of the qualified number and the input number of the mobile phone screen is taken as the qualified condition of the mobile phone screen in the work order.

The qualified number of the mobile phone screen in the work order can be obtained by starting calculation from the first working section or working procedure in the work order and sequentially accumulating the qualified numbers in the subsequent working sections or working procedures. The statistical mode reflects the qualification condition of the mobile phone screen in the work order aiming at various defects.

For example, if the number of inputs of the mobile phone screen is 1000 and the number of qualified products is 900, the yield is 90%. The quality condition of the mobile phone screen in the work order is reflected by counting the qualification rate of the mobile phone screen in the work order, and whether the quality of the mobile phone screen is pre-warned in the work order or not can be determined according to the qualification rate so as to ensure the quality of the mobile phone screen. The mode reflects the qualified condition of the mobile phone screen in a wider range of work orders.

The number of abnormal parts can be used as a determining factor for reflecting the quality condition of the mobile phone screen on the work order. For example, when the number of the unqualified mobile phone screens determined in the work order is 50 within the preset time, the number of abnormal parts caused by the defect of the crack is 50. The number of abnormal pieces is used as a reference, the input number of the work order in a preset time length does not need to be considered, and the quality condition of the mobile phone screen produced by using the equipment in the work order can be reflected more strictly when the number of the abnormal pieces reaches the threshold value of the early warning abnormal number no matter how many the input numbers are.

A third statistical mode:

when the key workshop section in the work order is taken as a statistical unit, and the qualification rate or the number of abnormal parts obtained by counting the detection target is counted, the statistical value of the detection target in the preset time duration is counted, and the statistical value comprises the following steps:

and detecting the ratio of the input number of the target in the target work order to the qualified number of the key work sections in the target work order within the preset time. The method specifically comprises the step of taking the ratio of the qualified number of a detected target in a key working section in a target work order within a preset time length to the input number of the detected target in the target work order within the preset time length as the qualified rate of the detected target in the key working section in the target work order, wherein the qualified rate is the statistical value of the detected target within the preset time length.

And according to the quantity of abnormal pieces produced by the detection target in the target work order within the preset time length, taking the quantity of the abnormal pieces as a statistic value of the detection target within the preset time length. For the abnormal components and the number thereof in this method, please refer to the abnormal components and the number thereof in the first statistical method.

The specification also provides a specific application scenario example of the statistical method three:

processing the mobile phone screen to be used as product manufacturing, taking a key workshop section in the work order as a statistical unit, taking the mobile phone screen as a detection target, taking the defect of the mobile phone screen as a defect, and counting the qualification rate of the mobile phone screen in the key workshop section in the work order. And when the defect phenomenon of the mobile phone screen occurs, determining the mobile phone screen as an unqualified mobile phone screen, and determining the mobile phone screen without the defect as a qualified mobile phone screen. Then, counting the input number of the work order and the qualified number of the key work sections within the time of 1 hour, and taking the ratio of the qualified number of the mobile phone screen in the key work sections to the input number of the mobile phone screen in the work order as the qualified condition of the mobile phone screen in the key work sections of the work order.

For example, if the input number of mobile phone screens in a work order is 1000, and the qualified number of key sections is 800, the yield is 80%. The quality condition of the mobile phone screen in the key workshop section of the work order is reflected by counting the qualification rate of the mobile phone screen in the key workshop section of the work order, and whether the quality of the mobile phone screen is pre-warned in the key workshop section of the work order can be determined according to the qualification rate so as to ensure the quality of the mobile phone screen. The mode reflects the qualified condition of a certain working section of the mobile phone screen in the work order aiming at a certain defect.

The number of abnormal parts can be used as a determining factor for reflecting the quality condition of the mobile phone screen in the key working section of the work order. For example, when the number of unqualified mobile phone screens determined in the key work section of the work order is 10 within the preset time, the number of abnormal parts is 10, and early warning can be performed on product manufacturing according to the number of the abnormal parts.

Referring to fig. 2, in another embodiment, before step S300, the method further includes:

step A, determining an early warning type for early warning the product manufacture according to the process parameters of the detection target, and after determining the early warning type, early warning the determined early warning type for the product manufacture. The early warning types comprise a first type of early warning for early warning according to the general early warning configuration and a second type of early warning for early warning according to the special early warning configuration. The special early warning configuration is used for early warning of the detection target within the preset range, and the general early warning configuration is used for early warning of the detection target outside the preset range.

And determining whether the early warning for the product manufacturing is the early warning of the detection target within the preset range or the early warning of the detection target outside the preset range according to the process parameters of the detection target. After the process parameters of the detection target are determined, the early warning type for early warning the product manufacture is determined according to the process parameters of the detection target.

The preset range can be a range determined according to actual requirements and comprises a determined material group range, a preset work order type, a priority early warning product material number, a priority early warning defect and the like. The process parameters of the detection target are parameters related to early warning for product manufacturing or parameters reflecting self attributes in the product manufacturing process. Such as type, model, work order number, product specification, material parameters, work order type, product material number, and/or pre-warning defects, etc.

The application range of the first type of early warning is larger than that of the second type of early warning. The second type of early warning has a limiting condition, the targeted detection target is more finely divided, and the degree of division of the targeted detection target of the first type of early warning is smaller than that of the second type of early warning. For example, the first type of early warning can be used in a translation mode among the same products, the second type of early warning cannot be used in a translation mode among the same products, and the like.

The method comprises the following steps of determining an early warning type for early warning product manufacture according to process parameters of a detection target, wherein the early warning type at least comprises one of the following modes:

the determination method is as follows: and when the materials used by the product to be manufactured are determined to be within the range of the preset material group according to the material parameters of the detection target, determining that the early warning type is the second type of early warning. The preset material group range is a preset range, the material group range is a set composed of preset materials with different material parameters, and the material parameters of the detection target are used as the process parameters of the detection target. When the materials used by the products to be manufactured are determined to be within the range of the preset material group according to the material parameters of the detection target, the second type of early warning for early warning is performed according to the special early warning configuration to manufacture the products, and the early warning line of the second type of early warning is determined according to the materials within the range of the preset material group. And when the materials used by the product to be manufactured are determined not to be in the range of the preset material group according to the material parameters of the detection target, the detection target outside the preset range of the detection target position is indicated, and the early warning type is determined to be the first type of early warning.

Determining a second mode: determining the work order of the detection target according to the work order of the detection target as follows: and when one of the test order, the rework order or the retest order is selected, determining the early warning type as a second early warning. The preset range is that the work order where the detection target is located is a test order, a rework order or a retest order, and the work order occupied by the detection target is used as a process parameter of the detection target. And when the work order where the detection target is located is one of the test order, the rework order or the retest order, the detection target is a detection target in a preset range, and the early warning type is determined to be the second type of early warning. All the detection targets have work orders, and the type of the work order where the detection target is located can be obtained and known. And when the work order where the detection target is located is determined not to be within the preset range according to the work order where the detection target is located, namely the work order where the detection target is located is out of the preset range, determining that the early warning type is the first type of early warning.

Determining a third mode: and determining the early warning type as a second early warning type when the product to be manufactured corresponding to the detection target has the material number of the prior early warning product. The product to be manufactured has a priority early warning product material number which is a preset range, and the product material number to be manufactured corresponding to the detection target is used as a process parameter of the detection target. And when the product to be manufactured corresponding to the detection target has the material number of the prior early warning product, the detection target is indicated to be the detection target within a preset range, and the early warning type is determined to be the second type of early warning. And determining that the early warning type is the first type of early warning according to the fact that the detection target is a detection target outside a preset range when the product to be manufactured corresponding to the detection target does not have the material number of the prior early warning product.

Determining a mode four: and determining the early warning type as a second early warning type according to the condition that the product to be manufactured corresponding to the detection target has the priority early warning defect. The product to be manufactured corresponding to the detection target has the priority early warning defect in the preset range, and the defect of the product to be manufactured corresponding to the detection target is used as the process parameter of the detection target. When the product to be manufactured corresponding to the detection target has the priority early warning defect, the detection target is indicated to the detection target in the preset range, the early warning type is determined to be the second type early warning, and otherwise, the early warning type is determined to be the first type early warning.

Of course, other process parameters and preset ranges of the inspection target are also included, which are not illustrated here.

In another embodiment, when the statistical value of the detection target within the preset duration counted in step S200 includes the yield, then the statistical value of the detection target within the preset duration includes the yield of the detection target within the preset duration. The yield in this embodiment may be that the work section is taken as a statistical unit, the work order is taken as a statistical unit, or a key work section in the work order is taken as a statistical unit, and the like.

Step S300, when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the statistical value, early warning is carried out on the product manufacture, and the method comprises the following steps: and when the qualification rate is determined to be reduced to the early warning qualification rate threshold corresponding to the early warning line according to the qualification rate, early warning is carried out on the product manufacture according to the general early warning configuration. When the qualification rate of the detection target counted in the step S200 is reduced to the early warning qualification rate threshold corresponding to the early warning line, it is described that an abnormal phenomenon corresponding to the early warning line occurs in the detection target, and then the product manufacturing is early warned, where the early warning is performed on the product manufacturing according to the general early warning configuration. The early warning qualified rate threshold corresponding to the early warning line in this embodiment may be an early warning qualified rate threshold determined in a percentage form, for example, 90%.

In another embodiment, when the statistical value of the detection target within the preset duration counted in step S200 includes the number of abnormal pieces, the statistical value of the detection target within the preset duration includes counting the number of abnormal pieces of the detection target within the preset duration. The number of abnormal units in this embodiment may be the number of working sections as a statistical unit, the number of work orders as a statistical unit, the number of key working sections in a work order as a statistical unit, or the like.

Step S300, when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the statistical value, early warning is carried out on the product manufacture, and the method comprises the following steps: and determining whether the counted number of the abnormal parts reaches the early warning abnormal number threshold according to the number of the abnormal parts and the early warning abnormal number threshold corresponding to the early warning line, when the counted number of the abnormal parts reaches the early warning abnormal number threshold corresponding to the early warning line, indicating that the abnormal phenomenon corresponding to the early warning line occurs in the detection target, and then early warning for product manufacturing according to special early warning configuration. The threshold for the number of early warning anomalies in this embodiment may be an integer number in a non-percentage form such as 30 or 50.

Referring to fig. 2, in another embodiment, after the early warning of the production, the method further includes:

step S400, acquiring an early warning processing mode determined according to the severity of early warning on the product, wherein the early warning processing mode determined according to the severity of early warning on the product manufacturing can be an operation performed by a processing terminal. The processing end is used for determining a processing mode of the early warning according to the severity of the early warning, and the severity of the early warning can be determined according to the statistical value of the statistical detection target and the threshold of the early warning qualification rate or the threshold of the number of the early warning abnormal parts. The warning processing mode may include continuing production, suspending production, terminating production, and the like, and may also be other warning processing modes, which are not illustrated here.

Determining the early warning processing mode according to the severity may include: and when the number of the abnormal pieces of the detection target is greater than the threshold value of the number of the early warning abnormal pieces and the greater number does not exceed a first numerical value, determining the early warning degree as continuous production. And when the number of abnormal pieces of the detection target is larger than the threshold value of the number of early warning abnormal pieces and the larger number does not exceed a second numerical value, determining the early warning degree as the production suspension. And when the number of abnormal pieces of the detection target is greater than the threshold value of the number of early warning abnormal pieces and the greater number exceeds a second numerical value, determining the early warning degree as terminating the production, wherein the first numerical value is smaller than the second numerical value.

And S500, controlling the product manufacture according to the acquired early warning processing mode so as to carry out further processing. For example, when the acquired early warning processing mode is to continue production, the production of the product is continued, and when the acquired early warning processing mode is to suspend production, the production of the product is temporarily stopped, and the production of the product can be continued after waiting for further processing. And when the acquired early warning processing mode is to terminate production, terminating the production of the product and not resuming the production.

Further, the obtained early warning processing mode determined according to the severity of early warning for manufacturing the product may be an early warning processing mode determined by the processing end according to the severity of the early warning, and specifically may include:

the early warning of the product making is sent to the first processing end, and specifically, the early warning can be sent in a mode of mail or notification message and the like, so that the first processing end is reminded to early warn the product making, and the first processing end is required to process the early warning within a preset time limit. The first processing end is configured to determine an early warning processing mode according to the early warning, specifically, the early warning processing mode may be determined according to the severity of the early warning, and certainly, the early warning processing mode may also be determined according to other factors of the early warning. The first processing terminal returns the determined early warning processing mode after determining the early warning processing mode, and the first processing terminal can be any processing terminal which can determine the early warning processing mode according to the severity of the early warning.

And after the first processing terminal returns the determined early warning processing mode, receiving the early warning processing mode returned by the first processing terminal based on the early warning severity, wherein the step specifically comprises receiving the early warning processing mode which is provided by the first processing terminal according to the early warning severity and passes the audit by the second processing terminal. That is to say, the first processing terminal determines the pre-warning processing mode according to the severity of the pre-warning within a predetermined time limit, and then the second processing terminal further needs to check the pre-warning processing mode determined by the first processing terminal within the predetermined time limit, which is equivalent to the second processing terminal performing secondary confirmation on the determination result of the first processing terminal within the predetermined time limit. And when the second processing terminal passes the audit within the preset period, the first processing terminal returns the determined early warning processing mode, and then receives the early warning processing mode returned by the first processing terminal. The predetermined time limit of the first processing end and the predetermined time limit of the second processing end can be the same or different, and is determined according to actual requirements.

In another embodiment, the first processing end may also be in a situation that the early warning is not processed within a predetermined time limit, or the second processing end may be in a situation that the early warning processing manner determined by the first processing end is not audited within a predetermined time limit, so that the first processing end cannot return to the early warning processing manner.

And when the early warning processing mode returned by the first processing end is not received after expiration, sending notification information for generating early warning for product manufacturing to a third processing end, wherein the notification information is used for prompting the processing of the early warning. That is, the early warning processing mode returned by the first processing end is not received within the preset time limit, which indicates that the first processing end does not determine the early warning processing mode according to the severity of the early warning, or the second processing end does not audit the early warning processing mode determined by the first processing end. In this case, the third processing end is prompted to process the early warning by sending notification information of the early warning generated by the product manufacturing to the third processing end.

The processing priority of the first processing end is higher than that of the second processing end, and the processing priority of the second processing end is higher than that of the third processing end. The processing authority of the third processing end is greater than the processing authority of the first processing end and the second processing end, and the processing authority of the second processing end is greater than the processing authority of the first processing end. If the second processing end does not pass the audit when the second processing end audits the processing mode determined by the first processing end, the second processing end can determine the processing mode according to the audit result of the second processing end. When the first processing end and the second processing end do not perform corresponding processing at corresponding time, the third processing end can determine the processing mode of the early warning.

For example, if the early warning processing mode returned by the first processing end is not received within 24 hours after the early warning is generated in the product manufacturing, it indicates that the early warning is not processed within 24 hours after the early warning is generated in the product manufacturing by the first processing end or the second processing end, and the early warning generated in the product manufacturing is sent to the third processing end. And prompting that the first processing end or the second processing end of the third processing end does not process the early warning within 24 hours after the early warning is generated in the product manufacturing process, and requiring the third processing end to process the early warning or informing the first processing end or the second processing end to process the early warning. The mode can be processed through the third processing end when the first processing end or the second processing end does not process in time, so that the processing efficiency of early warning can be improved, and the risk of processing omission is reduced.

In another embodiment, after controlling the production of the product according to the acquired early warning processing mode, the method further comprises:

and after the product is controlled to be manufactured according to the acquired early warning processing mode, closing early warning on the product manufacture so as to prevent the product from being manufactured and early warning. The control method is characterized in that an early warning record table is generated according to early warning of product manufacture after the control product is manufactured, so that operations such as query and analysis of early warning are performed in the future, and the product manufacture is managed better. The early warning record table can comprise early warning types, early warning time, early warning sections, early warning materials, the qualification rate of detected targets, the number of abnormal parts and the like.

In another embodiment, after the early warning is performed on the product manufacturing, the early warning is processed, and the early warning processing mode comprises three conditions of continuing production, suspending production and stopping production. The three situations can be processed through the three processing ends, after the early warning is carried out, the first processing end processes the early warning within a preset time limit, the second processing end also determines or audits the processing result of the first processing end within the preset time limit, and then the first processing end returns the processing result, wherein the result is the result of processing the early warning. And when the first processing end or the second processing end does not perform relevant processing within the respective preset time limit, the early warning is sent to the third processing end for processing. And (4) stopping the early warning after the early warning is processed through the three-level processing response, and producing an early warning record table so as to perform operations such as inquiry and the like in the following.

Through the technical scheme provided by the specification, automatic early warning of product quality in the production process is realized, quality problems in the batch production process are effectively reduced, and loss caused by continuous production is avoided after certain unqualified products appear. The method can be used for each procedure or working section or work order in the product manufacturing process, can feed back the abnormity in the product manufacturing process, and the manufactured product can continue to flow to the next step after the conditions of production and manufacturing are met, so that the quality of the produced product is improved, and the abnormal product and the existing defects can be inquired, so that the reason of the problem can be inquired. The early warning data in the product manufacturing process can be subjected to statistical analysis through the early warning record table.

Referring to fig. 3, the present specification further provides an early warning system for manufacturing a product, which can solve the same technical problems of the above methods and achieve the same technical effects. This early warning system includes:

and the determining module is used for determining whether the detection target is qualified.

And the statistic module is used for counting the statistic value of the detection target within the preset time length.

In another embodiment, the warning system further comprises:

the early warning type determining module is used for determining an early warning type for early warning the product manufacture according to the process parameters of the detection target; wherein, the early warning type includes: the method comprises the following steps of carrying out first-class early warning according to general early warning configuration and carrying out second-class early warning according to special early warning configuration; the special early warning configuration is used for early warning of a detection target within a preset range; and the general early warning configuration is used for early warning of the detection target outside the preset range.

The early warning processing module is used for acquiring an early warning processing mode determined according to the severity of early warning for manufacturing products, wherein the early warning processing mode comprises the following steps: continuing production, pausing production and stopping production. And controlling the product manufacture according to the acquired early warning processing mode.

And the early warning record table generating module is used for closing the early warning and generating an early warning record table.

The early warning type determining module is specifically used for determining an early warning type for early warning the product manufacture according to the process parameters of the detection target, and comprises at least one of the following components:

and when the materials used by the product to be manufactured are determined to be within the range of a preset material group according to the material parameters of the detection target, determining the early warning type as the second type of early warning.

Determining the work order of the detection target according to the work order of the detection target as follows: and when one of the test order, the rework order or the retest order is selected, determining the early warning type as the second early warning.

And determining the early warning type as a second early warning type when the product to be manufactured corresponding to the detection target has the material number of the prior early warning product.

And determining the early warning type as a second early warning type according to the condition that the product to be manufactured corresponding to the detection target has the priority early warning defect.

The early warning module comprises a first early warning submodule and a second early warning submodule. And the first early warning submodule is used for early warning the manufacture of the product according to the general early warning configuration when the qualification rate is determined to be reduced to an early warning qualification rate threshold value corresponding to an early warning line according to the qualification rate.

And the second early warning submodule is used for early warning the manufacture of the product according to the special early warning configuration when the number of the abnormal parts reaches the early warning abnormal number threshold corresponding to the early warning line.

The statistic module is specifically used for one of the following:

taking a working section as a statistical unit, and obtaining the qualification rate of the detection target in the target working section according to the ratio of the qualified number and the input number of the detection target in the target working section within the preset time;

taking a work order as a statistical unit, and obtaining the qualification rate of the detection target in the target work order according to the ratio of the input number and the qualified number of the detection target in the target work order within the preset time length;

taking key work sections in the work order as a statistical unit, and obtaining the qualification rate of the detection target on the key work sections in the target work order according to the ratio of the input number of the detection target in the target work order within the preset time and the qualified number of the key work sections in the target work order;

taking a working section as a statistical unit, and according to the number of abnormal pieces produced by the detection target in the target working section within the preset time length;

taking the work order as a statistical unit, and according to the number of abnormal pieces produced by the detection target when the product of the target work order is manufactured within the preset time length;

and taking key work sections in the work order as a statistical unit, and according to the number of abnormal pieces output by the detection target in the target work order within the preset time length.

The early warning processing module comprises a first early warning processing unit, a second early warning processing unit and a third early warning processing unit. Wherein the content of the first and second substances,

and the first early warning processing unit is used for sending the early warning to a first processing end and receiving an early warning processing mode returned by the first processing end based on the severity of the early warning.

And the second early warning processing unit is used for receiving the early warning processing mode which is provided by the first processing end according to the severity and passes the audit of the second processing end.

And the third early warning processing unit is used for sending notification information for generating early warning for product manufacturing to a third processing terminal when the early warning processing mode is not expected to be received, wherein the notification information is used for prompting the processing of the early warning.

The technical scheme of this application still provides an electronic equipment, includes:

a processor;

a memory storing program instructions that, when executed by the processor, cause the electronic device to perform the method of any of the embodiments described above.

The technical solution of the present application further provides a storage medium storing a program, and when the program is executed by a processor, the method in any one of the embodiments described above is performed. The storage medium comprises a non-transitory storage medium.

The present specification also provides another embodiment, which provides an early warning method for product manufacturing.

Referring to fig. 4, the warning method includes:

and early warning configuration, namely determining an early warning line according to actual service requirements, wherein different services are matched with different early warning lines. For example, the setting may be performed through a port such as a web page port or an API. The data acquisition is equivalent to counting the statistic value of the detection target, and after the statistic value of the detection target is counted, when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the statistic value of the detection target, namely when the statistic value of the detection target triggers the early warning line, the early warning is carried out on the product manufacture.

And early warning processing, namely processing the early warning after the early warning is made on the product. And determining a corresponding early warning processing mode according to the early warning. Specifically, after the early warning is performed on the product manufacturing, the early warning is processed within a predetermined period, and the processing manner of the early warning processing includes continuing the production, suspending the production (which may be referred to as temporary storage), terminating the production, and the like. The processing may be performed by the first processing side.

And (4) early warning auditing, namely auditing the early warning processing mode determined in the early warning processing. Specifically, the determined early warning processing mode is audited within a preset time limit, and the early warning processing mode which is audited is determined as the early warning processing mode after the audit is passed. During auditing, the determined early warning processing mode can be modified, determined, default setting can be selected and the like. The processing may be performed by the second processing side.

And when the early warning processing and/or the early warning auditing are carried out corresponding operations within a preset time limit, the early warning is determined to be overdue processing, and the early warning degree is upgraded. In this case, the warning may be sent to the third processing end for processing in the form of mail or the like.

And the early warning closing notification is used for closing the early warning after the early warning is processed. The early warning can be performed in a form of sending mails and the like, and a closed loop from early warning to early warning closing is formed.

Referring to fig. 5, in another embodiment, another early warning method for product manufacturing is provided, the method comprising:

step S10, counting the statistics of the detection targets within a preset time period, wherein the process can be a statistical unit to count the statistics of the detection targets, and the key process or process in the process can be a statistical unit to count the statistics of the detection targets.

For example, it is determined whether the detected target is qualified, and then statistics of the detected target within a preset time period is counted. The step can be called as a data acquisition step, and the data acquisition is carried out by taking a working section or a working procedure or a working order as an acquisition unit.

And step 20, determining an early warning line, wherein the early warning line comprises an early warning qualification rate threshold or an early warning abnormal quantity threshold. And in the process of manufacturing the product, determining the early warning index of the early warning line according to the requirement so as to carry out early warning on the manufacturing of the product according to the statistic value of the detection target and the determined early warning line. The early warning line comprises an early warning line for the first type of early warning and an early warning line for the second type of early warning. The first type of early warning comprises section early warning, material early warning, defect early warning and the like, and the second type of early warning comprises priority early warning and the like.

And step 30, processing the early warning after the early warning is carried out on the product manufacture. After the early warning, the early warning can be sent to the early warning processing end in a notification sending mode, and the corresponding processing end is prompted to process.

In step S40, the processing end may include a plurality of processing ends with different processing priorities, where the processing priorities of the processing ends with different priorities are different and the processing permissions are different. The processing priority of the low-level processing end is higher, but the processing authority is lower; the processing priority of the high-level processing end is lower, but the processing authority is higher. For example, the first processing end, the second processing end and the third processing end are sequentially reduced in level, the first processing end preferentially determines the early warning processing mode within a preset time limit, then the second processing end audits the early warning processing mode determined by the first processing end within the preset time limit, and the processing mode passing the audit is determined as the early warning processing mode. And if the first processing end and/or the second processing end do not perform corresponding processing within the preset time limit, the third processing end informs the third processing end to perform processing. In practical applications, the first processing end may be a processing end of a field technician, the second processing end may be a processing end of an engineer, and the third processing end may be a processing end of a manager.

And step S50, processing the early warning according to the determined early warning processing mode, wherein the processing comprises the steps of continuing production, suspending production, stopping production and the like, and normal production can be resumed after the problem corresponding to the early warning is solved.

And step S60, establishing an early warning record table according to the processing process of the early warning.

In another embodiment, a corresponding relationship between the early warning type and the statistic of the detected target is provided, refer to fig. 6.

The first type of early warning comprises material early warning, workshop section (process) early warning and defect early warning. Wherein the content of the first and second substances,

in the early warning of the workshop section, when the workshop section is taken as a statistical unit to count the qualification rate or the number of abnormal parts of the detection target, the statistical value of the detection target in the preset time is counted. The warning by this statistical method is referred to herein as a process warning. The statistical method comprises the following steps:

In the material early warning, when the qualification rate or the number of abnormal parts obtained by counting the detection target by taking a work order as a counting unit, counting the counting value of the detection target within the preset time length. The warning by this statistical method is referred to herein as a material warning. The statistical method comprises the following steps:

And counting the quantity of abnormal pieces produced by the detection target in the preset time length when the product of the target work order is manufactured, and taking the quantity of the abnormal pieces as a statistical value of the detection target in the preset time length.

The statistical method is used for counting the detection target according to the research and development of products and quality indexes required by customers, the ratio of the output number of the current workshop section (or working procedure) to the input number of work orders is an early warning line, meanwhile, early warning can be performed on unqualified quantity of special products, and the requirement is stricter.

In the defect early warning, a key working section in a work order is taken as a statistical unit, and when the qualification rate or the number of abnormal parts obtained by counting the detection target aiming at a certain defect is obtained, the statistical value of the detection target within the preset time is counted. The warning by such statistical method is referred to herein as a defect warning. The statistical method comprises the following steps:

and detecting the ratio of the input number of the target work order to the qualified number of the key work sections in the target work order aiming at a certain defect within preset time. The method specifically comprises the step of taking the ratio of the qualified number of a detected target in a key working section in a target work order within a preset time length to the input number of the detected target in the target work order within the preset time length as the qualified rate of the detected target in the key working section in the target work order, wherein the qualified rate is the statistical value of the detected target within the preset time length.

And according to the quantity of abnormal pieces produced by the detection target in the target work order within the preset time length, taking the quantity of the abnormal pieces as a statistic value of the detection target within the preset time length. The early warning mode carries out early warning according to the number of abnormal parts of a specific defect of a product or the proportion of the number of the abnormal parts. And carrying out specific defect statistics on a detection target in a certain section of the work order. And meanwhile, early warning is carried out by combining the product type of the detection target. When the product type is not limited, the method is applicable to all product types.

Further, the defect early warning also comprises comprehensive defect early warning, wherein the comprehensive defect early warning aims at a specified product, is used for counting two or more defects, and is used for comprehensively counting the percentage of the sum of the number of abnormal parts of various defects existing in a detection target in the input number of the work orders.

For example: aiming at the defect a, the early warning line of a detection target in a work order appointing a work section is 2 percent; aiming at the defect b, the early warning line of the detection target in the designated work section in the work order is 2 percent; and aiming at the defect c, the early warning line of the detection target at the designated workshop section in the work order is 3 percent. When the input number of the detection targets in the work order is 1000 within the preset time length, the number of the detection targets with the defects a is 10, the number of the detection targets with the defects b is 10, and the number of the detection targets with the defects c is 20, at this time, for the detection targets, the number of any one of the three defects does not exceed the standard.

However, when the early warning line Q of the comprehensive defect early warning is set to be 3% by the statistical mode of the comprehensive defect early warning, the statistics is performed by a formula Q ═ 100% (the number of a defects, the number of b defects, and the number of c defects), and when the early warning line Q is 3%, the number of the detected comprehensive defects exceeds the early warning line of the comprehensive defect early warning. The method is used for further optimizing or supplementing the defect early warning, and the early warning degree is more accurate.

Referring to fig. 7, the second type of warning includes a priority warning, and the priority warning further includes the following conditions:

and when the materials used by the product to be manufactured are determined to be within the range of the preset material group according to the material parameters of the detection target, determining that the early warning type is the second type of early warning. It can also be called material group early warning here, and a material group is a collection of material numbers with some specific rules.

Determining the work order of the detection target according to the work order of the detection target as follows: and when one of the test order, the rework order or the retest order is selected, determining the early warning type as a second early warning. And early warning is carried out on the product manufacture according to the work order, or the product manufacture can be early warned according to the initial two-digit number and the material group of the order in the work order where the detection target is located.

And determining the early warning type as a second early warning type when the product to be manufactured corresponding to the detection target has the material number of the prior early warning product. The method aims at early warning of product manufacturing of products with special product material numbers. For example, the statistical value of the product is counted in the form of the number of abnormal parts, and the product is early warned when the number of the abnormal parts reaches an early warning line. And second-class early warning of the order beginning and the product material number can be carried out when the product to be manufactured corresponding to the detection target is matched with the beginning two bits of the order and the combination of the product material number.

And determining the early warning type as a second early warning type according to the condition that the product to be manufactured corresponding to the detection target has the priority early warning defect. Because a lot of unpredictable factors exist in the batch production process, specific defects of a certain product cannot be avoided, the method can count the types of detection targets, and early warning is carried out when the product has priority early warning defects.

And when a single product is produced in a small batch, material early warning and/or defect early warning can be carried out. For large-scale automatic production, the early warning of the working sections (working procedures) can be carried out aiming at key working procedures or working sections. When the product number or the defect has special requirements, prior early warning can be carried out.

Referring to fig. 8, the defect warning is one of the first type of warnings, and is directed to warning a detection target at a specific defect. For the detected target, statistics of the detected target is performed from a point, and then the product manufacturing is early-warned according to the statistics of the statistics and the corresponding early-warning line. The material early warning and the workshop section early warning can be understood as counting the statistic value of a detection target from a line and a plane, and then early warning is carried out on the product manufacturing according to the statistic value of the statistics and the corresponding early warning line.

The second type of early warning comprises a priority early warning which is further supplementary and optimized to the first type of early warning.

As shown in fig. 9, a schematic diagram of determining the warning type is shown, where the diagram includes information such as the warning type, the form of statistics, the specific warning manner, the warning code information, the warning line, the corresponding product manufacturing department, the operating user, and other relevant descriptions, and is stored through the storage button. The type of warning may be a first type warning or a second type warning. The statistical values may be in the form of yield and number of anomalies. The specific early warning mode can be workshop section early warning, material early warning, defect early warning or priority early warning and the like. The early warning code information can be code information of a workshop section where the detection target is located, code information of a defect corresponding to the detection target, and/or material code information and the like. The precaution line may be in the form of a yield or in the form of an exception.

Referring to fig. 10, a schematic diagram of the warning record table is shown, and the information included in the warning record table refers to the contents shown in fig. 10, and may be summarized, and the like according to these contents. In the later stage, quality analysis can be performed through the product type, product number, key workshop section, process, work order and/or defect code early warning quantity and the like in a certain time period, so that strict management and control on people, machines, materials, methods and rings in the production process are facilitated, and the description is omitted.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, all the functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may be separately used as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

In some cases, any two of the above technical features may be combined into a new method solution without conflict.

In some cases, any two of the above technical features may be combined into a new device solution without conflict.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: various media capable of storing program codes, such as a removable Memory device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, and an optical disk.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims

1. An early warning method for product manufacturing, comprising:

determining whether the detection target is qualified;

counting the statistic value of the detection target within a preset time length;

and when determining that the abnormal phenomenon corresponding to the early warning line occurs in the detection target according to the statistical value, early warning for product manufacture is carried out.

2. The warning method of claim 1, further comprising:

3. The warning method as claimed in claim 2, wherein the determining the type of warning for warning of the product manufacturing according to the process parameter of the detection target includes at least one of:

determining the early warning type as the second type of early warning when determining that the material used by the product to be manufactured is within a preset material group range according to the material parameters of the detection target;

determining the work order of the detection target as follows according to the work order of the detection target: when one of a test order, a rework order or a retest order is selected, determining that the early warning type is the second type of early warning;

determining that the early warning type is the second type of early warning according to the condition that a product to be manufactured corresponding to the detection target has a material number of a prior early warning product;

and determining the early warning type as the second type of early warning according to the condition that the product to be manufactured corresponding to the detection target has a priority early warning defect.

4. The warning method as claimed in claim 2 or 3, wherein the statistical value includes a qualification rate, and the statistical value of the detection target within a preset time period includes:

counting the qualification rate of the detection target within the preset time;

when the abnormal phenomenon corresponding to the early warning line of the detection target is determined according to the statistical value, early warning is carried out on product manufacture, and the method comprises the following steps:

and when the qualification rate is determined to be reduced to an early warning qualification rate threshold corresponding to an early warning line according to the qualification rate, early warning is carried out on the product manufacture according to the general early warning configuration.

5. The warning method as claimed in claim 2 or 3, wherein the statistical value includes the number of abnormal parts, and the statistical value of the detection target in the preset time period includes:

counting the number of abnormal pieces of the detection target in the preset time length;

and when the number of the abnormal parts is determined to reach an early warning abnormal number threshold corresponding to an early warning line, early warning is carried out on the manufacture of the product according to the special early warning configuration.

6. The warning method according to claim 1,

the statistical values are: counting the detection target by taking a working section as a counting unit to obtain the qualification rate or the number of abnormal parts;

alternatively, the first and second electrodes may be,

the statistical values are: counting the qualification rate or the number of abnormal parts obtained by taking the work order as a counting unit;

alternatively, the first and second electrodes may be,

the statistical values are: and taking key working sections in the work order as a statistical unit, and counting the detection target to obtain the qualification rate or the number of abnormal parts.

7. The warning method as claimed in claim 6, wherein the counting of the statistical value of the detected target within the preset time period includes one of:

8. An early warning system for product manufacturing, comprising:

9. An electronic device, comprising:

a processor;

a memory storing program instructions that, when executed by the processor, cause the electronic device to perform the method of any of claims 1-7.

10. A storage medium storing a program which, when executed by a processor, performs the method of any one of claims 1 to 7.