CN111814113B

CN111814113B - Early warning method, system, electronic equipment and storage medium for product manufacturing

Info

Publication number: CN111814113B
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: 2024-08-23
Anticipated expiration: 2040-06-09
Also published as: CN111814113A

Abstract

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

Description

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

Technical Field

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

Background

With the development of manufacturing industry and the continuous change of market demands, each manufacturing enterprise faces more difficult challenges and more pressures, so as 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 profit of the enterprise. An automatic production line is adopted by many manufacturing enterprises to produce products, and data acquisition related to the products in various production equipment in the production process is monitored in real time, but the early warning of the product quality in the process of producing the products is insufficient.

Disclosure of Invention

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

The technical scheme of the invention is realized as follows:

An early warning method for product manufacture, comprising: determining whether the detection target is qualified; counting the statistic value of the detection target within a preset time period; and when the abnormal phenomenon corresponding to the early warning line appears in the detection target according to the statistic value, early warning is carried out on the production of the product.

In one embodiment, the method further comprises:

Determining an early warning type for early warning of product manufacture according to the process parameters of the detection target; wherein, early warning type includes: a first type of early warning according to the general early warning configuration and a second type of early warning according to the special early warning configuration; the special early warning configuration is used for early warning of the detection target in a preset range; 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 the product manufacturing according to the process parameters of the detection target includes at least one of the following: when the material used by the product to be manufactured is determined to be in the range of the preset material group according to the material parameters of the detection target, determining the early warning type as the second type early warning; determining the worksheet of the detection target according to the worksheet of the detection target as follows: determining the early warning type as the second type early warning when one of a test sheet, a reworking sheet or a retest sheet is adopted; when the product to be manufactured corresponding to the detection target has a priority early warning product material number, determining that the early warning type is the second type early warning; and determining the early warning type as the second type early warning when the product to be manufactured corresponding to the detection target has the priority early warning defect.

In one embodiment, the statistics include qualification rate, and the statistics of the detection targets within the statistical preset time period include: counting the qualification rate of the detection target within the preset time period; when determining that the abnormal phenomenon corresponding to the early warning line occurs to the detection target according to the statistic value, early warning is carried out on the production of the product, 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 production of the product according to the general early warning configuration.

In one embodiment, the statistics include the number of abnormal pieces, and the statistics of the detection targets within the preset time period include: counting the number of abnormal parts of the detection target in the preset time period; when determining that the abnormal phenomenon corresponding to the early warning line occurs to the detection target according to the statistic value, early warning is carried out on the production of the product, and the method comprises the following steps: and when the abnormal quantity reaches the early warning abnormal quantity threshold corresponding to the early warning line, early warning is carried out on the production of the product according to the special early warning configuration.

In one embodiment, the statistics are: counting the detection targets by taking the working sections as a counting unit to obtain the qualification rate or the abnormal part number; or the statistics are: counting the detection targets by taking the worksheets as a counting unit to obtain the qualification rate or the number of abnormal parts; or the statistics are: and counting the detection targets by taking the key working sections in the work order as a counting unit to obtain the qualification rate or the abnormal part number.

In one embodiment, the statistics of the detection targets within the statistical preset time period includes 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 qualification number and the input number of the detection target in the target working section within the preset time length; 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 qualification number of the detection target in the target work order within the preset time; taking a key working section in a work order as a statistical unit, and obtaining the qualification rate of the detection target on the key working section in the target work order according to the ratio of the input number of the detection target in the target work order to the qualification number of the key working section in the target work order in the preset time period; taking a working section as a statistical unit, and according to the number of abnormal parts 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 quantity of abnormal pieces produced by the detection target in the preset time period when the detection target is used for manufacturing the product of the target work order; and taking a key working section in the work order as a statistical unit, and according to the number of abnormal parts produced by the detection target in the target work order within the preset time.

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

In one embodiment, the obtaining the early warning processing mode determined according to the severity of early warning on the production of the product includes: the early warning is sent to a first processing end; and receiving an early warning processing mode returned by the first processing end based on the severity degree of the early warning.

In one embodiment, the receiving the early warning processing manner returned by the first processing end based on the severity of the early warning includes: and receiving the early warning processing mode provided by the first processing end according to the severity and checked and passed by the second processing end.

In one embodiment, the method further comprises: and sending notification information for generating early warning on the production of the product to a third processing end in anticipation of not receiving the early warning processing mode, 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 list.

An early warning system for product manufacturing, comprising:

The determining module is used for determining whether the detection target is qualified or not;

the statistics module is used for counting the statistics value of the detection target in a preset time period;

and the early warning module is used for carrying out early warning on the production of the product when determining that the abnormal phenomenon corresponding to the early warning line occurs to the detection target according to the statistic value.

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 the preceding claims.

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

According to the technical scheme, whether the detection target is qualified or not is determined through whether the detection target is qualified or not, and then the statistical value of the detection target within a preset time period is counted according to the determination result of whether the detection target is qualified or not, wherein the statistical value can comprise the qualification rate or the abnormal part number of the detection target and the like. Finally, when the abnormal phenomenon corresponding to the early warning line appears in the detection target according to the obtained statistical value of the detection target, the product production is automatically early warned without human intervention. According to the technical scheme, early warning can be carried out on the product when the qualified condition of the detection target is abnormal in the process of producing the product, early warning production and production can be further detected, the probability of abnormal produced products caused by continuous production of the product when the qualified condition of the detection target is abnormal is reduced, and therefore the quality of produced products can be improved.

Drawings

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

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

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

fig. 6 is a schematic diagram of a correspondence between a pre-warning type and a statistic value of a detection target according to an embodiment of the present invention;

Fig. 7 is a schematic flow chart of a method for giving priority to early warning for product manufacture according to an embodiment of the present invention;

FIG. 8 is a generalized schematic of a product making provided by 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 scheme of the invention is further elaborated below by referring to the drawings in the specification and the specific embodiments.

The early warning of the product quality in the process of manufacturing the product has a plurality of 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 feedback and processing are performed after the product quality problem is found. The mode of early warning is carried out through the manual work and is wasted time and energy to efficiency is lower. The existing early warning system has single function, cannot effectively consider various procedures, various working sections, various products and various defects in the production line, cannot control and monitor all production processes, and is easy to generate various omission. And the situation that serious loss is caused when the production is continued when a large amount of products are unqualified due to the fact that early warning is not performed in time can also occur.

The technical scheme of the application provides a product manufacturing early warning method, which can realize early warning of product manufacturing according to the qualification condition of a detection target and an early warning line in the process of product manufacturing.

Referring to fig. 1, a flow chart of an early warning method for product manufacturing provided by the application mainly comprises the following steps:

Step S100, determining whether the detection target is qualified. The product manufacturing process has the product manufacturing object, the product manufacturing early warning is carried out according to the product manufacturing object in the product manufacturing process, the product manufacturing object in the product manufacturing process is taken as a detection target according to business requirements, the detection target is detected in the product manufacturing process, and whether the detection target is qualified or not is determined.

Determining whether the detection target is qualified or not can be performed according to actual service requirements. For example, it is determined whether or not a certain defect exists in a certain section, process or work order, and the detection target is determined to be failed when such a defect exists, or may be a plurality of defects, and the detection target is determined to be failed when one or more of the plurality of defects exist. The defects may be defects (each defect may be represented by a code or a code number) set in advance, may be a defect a, a defect B, a defect C, and the like, and the defects corresponding to different detection targets may be different, so that the defect a, the defect B, and/or the defect C specifically indicate which defect may be set according to the detection target, and are not limited herein.

The detection target comprises a processing object in the production process of the product, namely, an object processed from a first working section or working procedure to a last working section or working procedure in an 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 production process of the product.

Step S200, statistics of detection targets in a preset time period are counted. The detection time is set in advance according to the actual service demand, which is equivalent to the preset time length. For example, the preset time period is a preset time period in units of "hour" or the like, such as a preset time period corresponding to an actual service demand of half an hour, 1 hour, 3 hours, or the like, and is not limited herein.

And counting the statistic value of the detection target according to the preset duration, acquiring the result of whether the determined detection target is qualified or not during counting, and counting the statistic value according to the result. And counting the statistic value of the detection target within the preset time, wherein the statistic value is a statistic value reflecting whether the detection target is qualified or not, namely, the statistic value reflects whether the detection target is qualified or not within the preset time, and the statistic value can be qualification rate, abnormal part quantity (unqualified quantity) or normal part quantity (qualified quantity) and the like.

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

And step S300, when the abnormal phenomenon corresponding to the early warning line appears in the detection target according to the statistical value, early warning is carried out on the production of the product. And determining whether the detection target has abnormal phenomena corresponding to the early warning line or not according to the statistical value of the detection target in the statistical preset time period, and carrying out early warning on the production of the product when determining that the detection target has abnormal phenomena corresponding to the early warning line.

The early warning line can be an early warning line which is already arranged, and comprises early warning qualification rate, abnormal part number and the like corresponding to the early warning line, and the early warning line can be arranged in different arrangement modes. For example, the setting is performed through a port such as a web page end or an Application Program Interface (API).

The abnormal phenomenon corresponding to the early warning line may include: 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. For example, when the statistical value of the detection target is the qualification rate, determining whether an abnormal phenomenon corresponding to the early warning line occurs according to the magnitude relation between the actually detected qualification rate and the early warning qualification rate threshold corresponding to the early warning line. When the statistical value of the detection target is lower than the early warning qualification rate threshold value, the abnormal phenomenon corresponding to the early warning line appears on the detection target, and early warning is carried out on the production of the product. 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 magnitude relation between the actually detected number of abnormal parts and the early warning abnormal number threshold value corresponding to the early warning line. When the statistic value of the detection target exceeds the threshold value of the early warning abnormal quantity, the abnormal phenomenon corresponding to the early warning line appears on the detection target, and early warning is carried out on the production of the product.

The method for early warning of the production can be determined according to actual business requirements or application scenes. Different early warning can be represented through different early warning modes, including that 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, sound early warning, light and sound simultaneous early warning, and early warning can be carried out by sending a popup window to a control end with a control relation with a production line of product production, and can be various other modes capable of carrying out early warning. For example, when the detection target is a material of a certain model, 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 the statistical value of the detection target within a preset time period is counted according to the determination result of whether the detection target is qualified or not, wherein the statistical value can comprise the qualification rate or the abnormal part number of the detection target and the like. And finally, when the abnormal phenomenon corresponding to the early warning line appears in the detection target according to the obtained statistical value of the detection target, early warning is carried out on the product manufacture.

According to the scheme, automatic statistics and automatic early warning of product manufacture in the product manufacture process are realized, the automatic statistics reduces the cost of manual statistics, and meanwhile, the occurrence of inaccurate statistics caused by manual reasons is also reduced. The method has the advantages that the product manufacture can be early-warned when the qualified condition of the detection target is abnormal, the early-warned production manufacture can be further detected, the probability of abnormal manufactured products caused by continuing to manufacture the product when the qualified condition of the detection target is abnormal is reduced, and therefore the quality of manufactured products is improved.

In another embodiment, in step S200, the statistical value in the statistical value of the detection target in the preset time period may be a qualification rate or the number of abnormal parts obtained by counting the detection target with the workshop section as a statistical unit. And the qualification rate or the abnormal part number obtained by counting the detection targets by taking the worksheets as a statistical unit can also be obtained. And the qualification rate or the abnormal part number obtained by counting the detection targets can also be counted by taking the key working sections in the work order as a counting unit. This embodiment is described by taking the above three statistical methods as examples.

Statistical mode one:

when the qualification rate or the abnormal part number obtained by counting the detection targets by taking the working section as a statistical unit, counting the statistical value of the detection targets in a preset time length, wherein the statistical 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 qualification number and the input number of the detection target in the target working section in the preset time, wherein the qualification rate is the statistical value of the detection target in the preset time. Taking a certain working section as a target working section, counting the statistic value of the detection target in the target working section within a preset time period, counting the ratio of the qualification number and the input number of the detection target in the target working section within the preset time period when the statistic value is the qualification rate, and taking the ratio as the qualification rate of the detection target in the target working section. The input number is the number of detection targets entering the target working section within a preset time period, and the qualification number is the number of qualified detection targets in the detection targets entering the target working section within the preset time period.

Counting the number of abnormal pieces produced by the detection target in the target working section within a preset time period, wherein the number of abnormal pieces is the statistical value of the detection target in the target working section within the preset time period. And taking a certain working section as a target working section, counting the number of abnormal parts of the detection target in the target working section within a preset time period when the statistical value is the qualification rate, namely the number of problematic detection targets, and taking the number of abnormal parts as the statistical value of the detection target within the preset time period.

An anomaly in this embodiment refers to a detection target that has at least one defect, which may be any defect or defects that may occur during the current manufacturing process of the product, and may be understood as a failed detection target. The number of abnormal parts is the number of unqualified detection targets produced in the statistical unit within a preset time period. In the current product manufacturing process, a work order is used as a statistical unit, whether the detection target is qualified 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 part or not and the number of the abnormal parts are obtained.

For example, a mobile phone screen with a certain model is detected as a material, 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 incomplete (can be expressed as defect 001 and the like), and the unqualified mobile phone screen is regarded as an abnormal part. And counting the number of defective mobile phone screens in the current working section in 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 specification inconsistency, and the detection target is regarded as an abnormal piece when it is determined that the specification of the detection target is inconsistent. Of course, other defects may be present, and the detection targets with defects may be regarded as unqualified detection targets, i.e. abnormal pieces.

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

Processing the mobile phone screen as a product manufacture, taking a working section as a statistics unit, taking the mobile phone screen as a detection target, taking the mobile phone screen as a defect, and counting the qualification rate of the mobile phone screen in the working section. When the mobile phone screen is incomplete and/or cracked, the mobile phone screen is determined to be an unqualified mobile phone screen, and the mobile phone screen which is not incomplete and/or cracked is determined to be an unqualified mobile phone screen. And then counting the input number and the qualification number of the mobile phone screen in the working section in the duration of 1 hour, and taking the ratio of the qualification number and the input number of the mobile phone screen as the qualification rate. The method reflects the qualification condition of the mobile phone screen at a certain working section aiming at various defects.

For example, the number of inputs of the mobile phone screen is 1000, and the number of pass is 950, and the pass rate 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 is pre-warned in the working section or not can be determined according to the qualification rate so as to ensure the quality of the mobile phone screen.

The number of abnormal parts can also be used as a determining factor for reflecting the quality condition of the mobile phone screen in the working section. For example, when the number of failures of the cell phone screen determined in the section is 100 in a preset period of time, the number of abnormal pieces due to such defects as cracks is 100. Taking the number of abnormal parts as a reference, the input number of the working section in the preset time period is not needed to be considered, no matter how many the input number is, the early warning can be carried out when the number of abnormal parts reaches the threshold value of the early warning abnormal number, the quality condition of the mobile phone screen in the working section can be more strictly reflected, and the method is beneficial for engineers to timely process and adjust equipment through defect phenomena so as to know the production condition of the equipment.

And a second statistical mode:

When the work order is taken as a statistics unit to count the qualification rate or the abnormal part number of the detection targets, counting the statistic value of the detection targets in a preset time length, wherein the method comprises the following steps:

and obtaining the qualification rate of the detection targets in the target worksheet according to the ratio of the input number and the qualification number of the detection targets in the production of the target worksheet in the preset time, wherein the qualification rate is the statistical value of the detection targets in the preset time. And taking a certain work order as a target work order, and taking the ratio of the qualification number and the investment number of the target work order as the qualification rate of the target in the target work order in a preset time.

Counting the number of abnormal pieces produced by the detection target in the preset time period when the product of the target work order is manufactured, and taking the number of abnormal pieces as the counting value of the detection target in the preset time period. The number of abnormal parts in the first mode refers to the number of abnormal parts in the first statistical mode.

The specification also provides a specific application scenario example of the second statistical mode:

Processing the mobile phone screen as a product manufacture, taking a work order as a statistics unit, taking the mobile phone screen as a detection target, taking the mobile phone screen as a defect, and counting the qualification rate of the mobile phone screen in the work order. When the mobile phone screen is incomplete and/or cracked, the mobile phone screen is determined to be an unqualified mobile phone screen, and the mobile phone screen which is not incomplete and/or cracked is determined to be an unqualified mobile phone screen. And then counting the input number and the qualification number of the mobile phone screen in the work order in the time length of 1 hour, and taking the ratio of the qualification number and the input number of the mobile phone screen as the qualification condition of the mobile phone screen in the work order.

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

For example, the number of inputs of the mobile phone screen is 1000, and the qualification rate is 900, and the qualification rate is 90%. The qualification rate of the mobile phone screen in the work order is counted, the quality condition of the mobile phone screen in the work order is reflected, 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 that the quality of the mobile phone screen is guaranteed. The method reflects the qualification status of the mobile phone screen in a wider range of worksheets.

The number of abnormal parts can also 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 failures of the mobile phone screen determined in the work order within the preset time period is 50, the number of abnormal parts caused by the defect of the crack is 50. The number of the abnormal parts is used as a reference, the input number of the work order in the preset time period is not needed to be considered, no matter how many the input number is, the number of the abnormal parts reaches the threshold value of the early warning abnormal number, and the quality condition that the mobile phone screen is produced by using the equipment on the work order can be more strictly reflected.

And a third statistical mode:

when the key working section in the work order is used as a statistical unit and the qualification rate or the number of abnormal parts obtained by counting the detection targets are counted, counting the statistical value of the detection targets in a preset time length, wherein the method comprises the following steps:

And detecting the ratio of the input number of the target in the target work order to the qualification number of the key working section in the target work order according to the preset time length. The method specifically comprises the steps of taking the ratio of the qualification number of the detection targets in the preset time period in the key working section in the target work order to the input number of the detection targets in the preset time period in the target work order as the qualification rate of the detection targets in the key working section in the target work order, wherein the qualification rate is the statistical value of the detection targets in the preset time period.

And taking the number of the abnormal parts as the statistic value of the detection target in the preset time according to the number of the abnormal parts generated by the detection target in the target work order in the preset time. The number of abnormal parts in the first mode refers to the number of abnormal parts in the first statistical mode.

The specification also provides a specific application scenario example of the third statistical mode:

Processing the mobile phone screen as a product manufacture, taking a key working section in a work order as a statistics 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 key working section in the work order. When the mobile phone screen is in incomplete phenomenon, determining the mobile phone screen as an unqualified mobile phone screen, and determining the mobile phone screen without incomplete mobile phone screen as a qualified mobile phone screen. And then counting the qualification number of the mobile phone screen in the key working section and the qualification number of the mobile phone screen in the key working section in the time length of 1 hour, and taking the ratio of the qualification number of the mobile phone screen in the key working section and the qualification number of the mobile phone screen in the key working section as the qualification condition of the mobile phone screen in the key working section of the work sheet.

For example, the input number of mobile phone screens in a work order is 1000, the qualification number of key working sections is 800, and the qualification rate is 80%. The quality condition of the mobile phone screen in the key working section of the work order is reflected by counting the qualification rate of the mobile phone screen in the key working section of the work order, and whether the quality of the mobile phone screen is pre-warned in the key working 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 method reflects the qualification condition of a mobile phone screen in a certain working section in a work order aiming at a certain defect.

The number of abnormal parts can also 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 products determined by the mobile phone screen in the key working section of the work order in the preset time period is 10, the number of abnormal parts is 10, and early warning can be carried out on product production according to the number of abnormal parts.

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

And step A, determining an early warning type for early warning of the production according to the process parameters of the detection target, and after determining the early warning type, early warning the early warning type for determining the production. The early warning types comprise a first type of early warning according to a general early warning configuration and a second type of early warning according to a special early warning configuration. The special early warning configuration is used for early warning of the detection target in 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 of the product manufacture is the early warning of the detection target in a 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 targets are determined, the early warning type for early warning the production of the product is determined according to the process parameters of the detection targets.

The predetermined range may be a range determined according to actual requirements, including a determined material group range, a predetermined work order type, a priority early warning product material number, and/or a priority early warning defect, etc. The process parameters of the detection targets are parameters related to early warning of the production of the product or parameters reflecting the attribute of the product in the production process of the product. Such as type, model number, work order number, product specification, material parameters, work order type, product material number, and/or pre-alarm defects, etc.

The application range of the first type early warning is larger than that of the second type early warning. The second type of early warning has a limiting condition, the division of the aimed detection targets is finer, and the division degree of the aimed detection targets of the first type of early warning is smaller than that of the second type of early warning. For example, a first type of early warning may be used in translation between like products, a second type of early warning may not be used in translation between like products, and so on.

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

Determining a first mode: and when the material used by the product to be manufactured is determined to be in the range of the preset material group according to the material parameters of the detection target, determining the early warning type as the second type early warning. The preset material group range is a preset range, namely a set formed by materials with different preset material parameters, and the material parameters of the detection target are used as the process parameters of the detection target. When the material used by the product to be manufactured is determined to be in the range of the preset material group according to the material parameters of the detection target, the product is manufactured and pre-warned according to a second type of pre-warning which is performed by special pre-warning configuration, and the pre-warning line of the second type of pre-warning is a pre-warning line determined according to the material in the range of the preset material group. When the material used by the product to be manufactured is determined to be not positioned in the range of the preset material group according to the material parameters of the detection targets, the detection targets outside the preset range of the detection targets are indicated, and the early warning type is determined to be the first early warning type.

And a second determination mode: determining the work order in which the detection target is located according to the work order in which the detection target is located as follows: and determining the early warning type as the second type early warning when one of the test sheet, the reworking sheet or the repeated test sheet is adopted. The preset range is that the work order in which the detection target is located is a test order, a reworking order or a retest order, and the work order occupied by the detection target is used as the processing parameter of the detection target. When the work order in which the detection target is located is one of a test order, a reworking order or a retest order, the detection target is indicated to be the detection target in a preset range, and the early warning type is determined to be the second type early warning. The work orders of the detection targets are all available, and the type of the work orders of the detection targets can be obtained and known. When the work order in which the detection target is located is determined to be not in the preset range according to the work order in which the detection target is located, namely, when the work order in which the detection target is located is out of the preset range, the early warning type is determined to be the first early warning type.

And determining a third mode: and determining the early warning type as the second type early warning when the product to be manufactured corresponding to the detection target has the priority early warning product material number. 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 processing parameter of the detection target. When the product to be manufactured corresponding to the detection target has the priority early warning product material number, the detection target is the detection target in the preset range, and the early warning type is determined to be the second type early warning. And when the product to be manufactured corresponding to the detection target does not have the priority early warning product material number, the detection target is the detection target outside the preset range, and the early warning type is determined to be the first type early warning.

And determining a fourth mode: and determining the early warning type as the second type early warning when 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 defects with priority early warning as a preset range, and the defects of the product to be manufactured corresponding to the detection target are used as the processing parameters 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 be opposite to the detection target in the preset range, the early warning type is determined to be the second type early warning, otherwise, the early warning type is determined to be the first type early warning.

Of course, other process parameters and predetermined ranges of the target are also included, which are not exemplified herein.

In another embodiment, when the statistical value of the detection target in the preset time period counted in step S200 includes the qualification rate, the statistical value of the detection target in the preset time period includes the qualification rate of the detection target in the preset time period. The qualification rate in this embodiment may be in a unit of statistics for the work section, a unit of statistics for the work order, a unit of statistics for the key work section in the work order, and so on.

Step S300, when determining that the detection target has abnormal phenomena corresponding to the early warning line according to the statistical value, early warning is carried out on the production of the product, 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 production of the product according to the general early warning configuration. When the qualification rate of the detection target counted in the step S200 is reduced to the pre-warning qualification rate threshold corresponding to the pre-warning line, the abnormal phenomenon corresponding to the pre-warning line appears in the detection target, and then the product manufacture is pre-warned, wherein the pre-warning is performed on the product manufacture according to the general pre-warning configuration. The pre-warning qualification rate threshold corresponding to the pre-warning line in this embodiment may be a pre-warning qualification rate threshold determined in a percentage form, such as 90%.

In another embodiment, when the statistical value of the detection target in the preset time period counted in step S200 includes the number of abnormal pieces, the statistical value of the detection target in the preset time period includes the number of abnormal pieces of the detection target in the preset time period. The number of abnormal parts in the embodiment can be counted by taking the working section as a statistic unit, the work order as a statistic unit, the key working section in the work order as a statistic unit and the like.

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

Referring to fig. 2, in another embodiment, after the product making is pre-warned, the method further includes:

Step S400, obtaining an early warning processing mode determined according to the severity of early warning on the product, where the early warning processing mode determined according to the severity of early warning on the product manufacturing may be an operation performed by the processing end. The processing end is used for determining the 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 early warning qualification rate threshold or the early warning abnormal part quantity threshold. The early warning processing mode can comprise continuous production, suspension of production, termination of production and the like, and can be other early warning processing modes, which are not exemplified here.

The determining the early warning processing mode according to the severity degree can comprise the following steps: and when the number of abnormal parts of the detection target is larger than the threshold value of the number of abnormal parts of the early warning and the number of abnormal parts is larger than the first value, determining the early warning degree as continuous production. And determining the early warning degree as production suspension when the number of abnormal parts of the detection target is larger than the early warning abnormal part number threshold value and the number larger than the early warning abnormal part number threshold value is not larger than a second value. And when the number of abnormal parts of the detection target is larger than the threshold value of the number of abnormal parts of the early warning and the larger number exceeds a second numerical value, determining the early warning degree as stopping production, wherein the first numerical value is smaller than the second numerical value.

And S500, controlling the production of the product 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 continuous production, the production of the product is continuous, and when the acquired early warning processing mode is pause production, the production of the product is temporarily stopped, and the production of the product can be continued after waiting for further processing. When the acquired early warning processing mode is to terminate production, the product is manufactured and is not restored.

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

The early warning of the product production is sent to the first processing end, and the early warning can be sent in a mail or notification message mode and the like, so that the first processing end is reminded of carrying out early warning on the product production, and the first processing end is required to process the early warning within a preset period. The first processing end is used for determining an early warning processing mode according to the early warning, specifically, the early warning processing mode can be determined according to the severity of the early warning, and the early warning processing mode can be determined according to other factors of the early warning. The first processing end returns the determined early warning processing mode after determining the early warning processing mode, and the first processing end can be any processing terminal capable of determining the early warning processing mode according to the severity of early warning.

After the first processing end returns to the determined early warning processing mode, the early warning processing mode of the first processing end returned based on the severity of the early warning is received, and the step specifically can include receiving the early warning processing mode provided by the first processing end according to the severity of the early warning and checked to pass by the second processing end. That is, the first processing end determines the early warning processing mode according to the severity of the early warning within a predetermined period, and then the second processing end also needs to audit the early warning processing mode determined by the first processing end within the predetermined period, which is equivalent to the second processing end performing a secondary confirmation on the determination result of the first processing terminal within the predetermined period. And after the second processing end passes the examination within a preset period, the first processing end returns the determined early warning processing mode and then receives the early warning processing mode returned by the first processing end. The predetermined period of the first processing end and the predetermined period of the second processing end can be the same or different, and are determined according to actual requirements.

In another embodiment, the first processing end may also perform no processing on the early warning within a predetermined period, or the second processing end may perform no auditing on the early warning processing mode determined by the first processing end within the predetermined period, so that the first processing end cannot return to the early warning processing mode.

And when the early warning processing mode returned by the first processing end is not received after overdue, sending notification information for generating early warning on the production of the product to the 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 a preset period, which indicates that the first processing end does not determine the early warning processing mode according to the severity of 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 notification information of the early warning generated by the product production is sent to the third processing end, and the third processing end is prompted to process the early warning.

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 larger than that of the first processing end and the second processing end, and the processing authority of the second processing end is larger than that of the first processing end. If the second processing end examines the processing mode determined by the first processing end, the second processing end examines the processing mode not passed, and the second processing end determines the processing mode according to the examination 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 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 production of the product, which means that the first processing end or the second processing end does not process the early warning within 24 hours after the early warning is generated in the production of the product, the early warning generated in the production of the product is sent to the third processing end. The first processing end or the second processing end of the third processing end is prompted to process the early warning within 24 hours after the early warning is generated in the production of the product, and the third processing end is required to process the early warning or inform the first processing end or the second processing end of processing the early warning. According to the method, when the first processing end or the second processing end does not process in time, the first processing end or the second processing end processes the information through the third processing end, so that the processing efficiency of early warning can be improved, and the risk of missing processing is reduced.

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

And after the product manufacture is controlled according to the acquired early warning processing mode, the early warning on the product manufacture is closed, so that the early warning on the product manufacture is not performed any more. And after the product is controlled to be manufactured, an early warning record list is generated according to early warning performed on the product so as to perform operations such as early warning inquiry and analysis in the future, and the product manufacturing is convenient to manage better. The early warning record table can comprise early warning types, early warning time, early warning sections, early warning materials, qualification rate of detection targets, abnormal part number and the like.

In another embodiment, after the product is made, the early warning is processed, and the early warning processing mode includes three conditions of continuous production, suspension of production and termination of production. The three conditions 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 period, the second processing end also determines or audits the processing result of the first processing end within the preset period, and then the first processing end returns the processing result which is the result of processing the early warning. 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 closing the early warning after the early warning is processed through the three-stage processing response, and producing an early warning record list so as to facilitate subsequent operations such as inquiry.

Through the technical scheme provided by the specification, automatic early warning of the product quality in the production process is realized, the quality problem in the mass production process is effectively reduced, and the loss caused by continuous production after certain disqualification of the product occurs. The method can be used for various procedures or working sections or work orders in the production process, can feed back the abnormality in the production process, and after the conditions of production and production are met, the produced product can continue to flow to the next step, so that the quality of the produced product is improved, the abnormal product and the defects can be inquired, and the cause of the problem can be inquired. The data of the early warning in the production process can be statistically analyzed through the early warning record table.

Referring to fig. 3, the present disclosure further provides an early warning system for product manufacture, which can solve the same technical problems as the above method and achieve the same technical effects. The early warning system comprises:

And the determining module is used for determining whether the detection target is qualified or not.

The statistics module is used for counting the statistics value of the detection target in the preset time.

In another embodiment, the early warning system further comprises:

the early warning type determining module is used for determining the early warning type for early warning of the production according to the process parameters of the detection target; the early warning types comprise: a first type of early warning according to the general early warning configuration and a second type of early warning according to the special early warning configuration; the special early warning configuration is used for early warning of a detection target in a preset range; and the universal early warning configuration is used for early warning of the detection target outside a preset range.

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

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

The early warning type determining module is specifically configured to determine an early warning type for early warning of product manufacturing according to a process parameter of a detection target, and includes at least one of the following:

And when the material used by the product to be manufactured is determined to be in the range of the preset material group according to the material parameters of the detection target, determining the early warning type as the second type early warning.

Determining the work order in which the detection target is located according to the work order in which the detection target is located as follows: and determining the early warning type as the second type early warning when one of the test sheet, the reworking sheet or the repeated test sheet is adopted.

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

And determining the early warning type as the second type early warning when 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 sub-module and a second early warning sub-module. And the first early warning sub-module is used for carrying out early warning on the production of the product according to the general early warning configuration 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.

And the second early warning sub-module is used for carrying out early warning on the production of the product according to the special early warning configuration when the abnormal number reaches the early warning abnormal number threshold corresponding to the early warning line.

The statistics 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 qualification number and the input number of the detection target in the target working section within the preset time length;

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 qualification number of the detection target in the target work order within the preset time;

Taking a key working section in a work order as a statistical unit, and obtaining the qualification rate of the detection target on the key working section in the target work order according to the ratio of the input number of the detection target in the target work order to the qualification number of the key working section in the target work order in the preset time period;

taking a working section as a statistical unit, and according to the number of abnormal parts 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 quantity of abnormal pieces produced by the detection target in the preset time period when the detection target is used for manufacturing the product of the target work order;

And taking a key working section in the work order as a statistical unit, and according to the number of abnormal parts produced by the detection target in the target work order within the preset time.

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 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.

The second early warning processing unit is used for receiving the early warning processing mode provided by the first processing end according to the severity and checked and passed by the second processing end.

And the third early warning processing unit is used for sending notification information for generating early warning on the production of the product to a third processing end 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 the application also provides electronic equipment, which comprises:

A processor;

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

The technical solution of the present application also provides a storage medium storing a program, which when executed by a processor, performs the method of any one of the above embodiments. The storage medium includes a non-transitory storage medium.

The specification also provides another embodiment, and the embodiment provides a product manufacturing early warning method.

Referring to fig. 4, the early warning method includes:

The early warning configuration is equivalent to determining early warning lines according to actual service requirements, and different services are matched with different early warning lines. For example, the setting may be performed through a port such as a web page end or an API. The data collection is equivalent to statistics of detection targets, and after statistics of the detection targets, when abnormal phenomena corresponding to the early warning lines appear on the detection targets, namely when the statistics of the detection targets trigger the early warning lines, product production is early warned.

And (3) early warning processing, wherein after the product is subjected to early warning, the early warning needs to be processed. And determining a corresponding early warning processing mode according to the early warning. Specifically, after the product is made and pre-warned, the pre-warning is processed within a preset period, and the processing mode of the pre-warning processing includes continuous production, suspension of production (which can be called temporary storage), termination of production and the like. The processing may be performed by the first processing side.

And (5) 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 period, 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 selected and other operations. The processing may be performed by the second processing side.

And when the early warning processing and/or the early warning auditing are/is to perform corresponding operation within a preset period, determining the early warning as overdue processing, and upgrading the early warning degree. In this case, the pre-warning may be sent to the third processing end for processing by mail or the like.

And closing the early warning notification, and closing the early warning after the early warning is processed. The method can be specifically carried out in a form of sending mails and the like, and a closed loop from early warning to closing early warning is formed.

Referring to fig. 5, in another embodiment, another method for pre-warning of product fabrication is provided, the method comprising:

Step S10, counting the statistic value of the detection target in the preset duration, wherein the statistic value of the detection target can be counted by taking a working section as a statistic unit, the statistic value of the detection target can be counted by taking a working procedure as a statistic unit, the statistic value of the detection target can be counted by taking a working unit statistic unit, and the statistic value of the detection target can be counted by taking a key working section or working procedure in the working order as a statistic unit.

For example, whether the detection target is qualified is determined, and then the statistics of the detection target in a preset time period are counted. This step may be referred to as a data acquisition step, where data is acquired in units of sections or procedures or work orders.

And 20, determining an early warning line, wherein the early warning line comprises an early warning qualification rate threshold value or an early warning abnormal quantity threshold value of the early warning line. In the process of manufacturing the product, the early warning index of the early warning line is determined according to the requirement, so that the early warning of the product manufacturing is performed according to the statistic value of the detection target and the determined early warning line. The early warning line comprises an early warning line of the first type of early warning and an early warning line of 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, after the product is manufactured and pre-warned, processing the pre-warning. 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 priority levels, where the processing ends with different levels have different processing priorities and different processing rights. 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 with sequentially reduced levels, the first processing end preferentially determines the early warning processing mode within a preset period, and then the second processing end examines the early warning processing mode determined by the first processing end within the preset period, and the processing mode passing the examination is determined as the early warning processing mode. If the first processing end and/or the second processing end do not perform corresponding processing within a preset period, the third processing end notifies the third processing end to perform processing. In practical application, 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, including continuing production, suspending production, stopping production and the like, and recovering normal production after the corresponding problem of the early warning is solved.

Step S60, an early warning record table is established according to the early warning processing process.

In another embodiment, a correspondence between the pre-warning type and the statistics of the detection targets is provided, refer to fig. 6.

The first type of early warning comprises material early warning, working section (working procedure) early warning and defect early warning. Wherein,

In the early warning of the working section, when the working section is used as a statistical unit to count the detection targets to obtain the qualification rate or the number of abnormal parts, counting the statistical value of the detection targets in a preset time period. The early warning by such statistical methods is referred to herein as a section early warning. The statistical method comprises the following steps:

In the material early warning, when the qualification rate or the abnormal part number obtained by counting the detection targets by taking a work order as a statistical unit, counting the statistical value of the detection targets in a preset time period. The pre-warning by this statistical method is referred to herein as a material pre-warning. The statistical method comprises the following steps:

Counting the number of abnormal pieces produced by the detection target in the preset time period when the product of the target work order is manufactured, and taking the number of abnormal pieces as the counting value of the detection target in the preset time period.

According to the statistical method, the detection targets are counted according to the research and development of the products and the quality index required by the clients, the ratio of the output number of the current working section (or working procedure) to the input number of the work order is an early warning line, and meanwhile, early warning can be carried out on the unqualified number of the special products, so that the requirements are more strict.

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

And detecting the ratio of the input number of the target work order to the qualification number of the key working section in the target work order according to a certain defect in a preset time. The method specifically comprises the steps of taking the ratio of the qualification number of the detection targets in the preset time period in the key working section in the target work order to the input number of the detection targets in the preset time period in the target work order as the qualification rate of the detection targets in the key working section in the target work order, wherein the qualification rate is the statistical value of the detection targets in the preset time period.

And taking the number of the abnormal parts as the statistic value of the detection target in the preset time according to the number of the abnormal parts generated by the detection target in the target work order in the preset time. The early warning mode carries out early warning according to the number of abnormal parts or the proportion of the number of the abnormal parts of a specific defect of the product. The detection targets in one section of the work order are used for carrying out specific defect statistics. And meanwhile, early warning is carried out by combining the product type of the detection target. When the product type is not defined, it is applicable to all the product types.

Further, the defect early warning further comprises comprehensive defect early warning, wherein the comprehensive defect early warning aims at a specified product, statistics is carried out on two or more defects, and comprehensive statistics is carried out on the percentage of the number of work orders, which is occupied by the sum of the number of abnormal parts of the defects existing in the detection target.

For example: aiming at the defect a, the detection target designates an early warning line of a section as 2% in a work order; aiming at the defect b, the detection target designates an early warning line of a working section as 2% in a work order; aiming at the defect c, the detection target designates the early warning line of the working section as 3% in the work order. When the input number of the detection targets in the work order is 1000 within the preset time, the number of the detection targets with the a defects is 10, the number of the detection targets with the b defects is 10, and the number of the detection targets with the c defects is 20, at this time, the situation that the number of any one of the three defects exceeds the standard is not caused.

However, when the early warning line Q of the comprehensive defect early warning is set to 3% in a statistical manner, statistics is performed by a formula q= (the number of defects a+the number of defects b+the number of defects c)/the number of work order inputs is 100%, and when the early warning line Q is 3%, the number of comprehensive defects existing in the detection target exceeds the early warning line of the comprehensive defect early warning. The method is further optimized or supplemented for defect early warning, and the early warning degree is more accurate.

Referring to fig. 7, the second type of early warning includes priority early warning, which further includes the following cases:

and when the material used by the product to be manufactured is determined to be in the range of the preset material group according to the material parameters of the detection target, determining the early warning type as the second type early warning. The method can also be called material group early warning, wherein a material group is a collection of material numbers with specific rules.

Determining the work order in which the detection target is located according to the work order in which the detection target is located as follows: and determining the early warning type as the second type early warning when one of the test sheet, the reworking sheet or the repeated test sheet is adopted. The product manufacture is pre-warned according to the work order, or in the work order where the detection target is located, the product manufacture is pre-warned according to the first two digits of the order and the material group.

And determining the early warning type as the second type early warning when the product to be manufactured corresponding to the detection target has the priority early warning product material number. The method is to pre-warn the production of products with special product numbers. For example, statistics values of the products are counted in the form of the number of abnormal parts, and early warning is carried out after the number of abnormal parts of the products reaches an early warning line. And the second type early warning of the first two orders and the second type early warning of the second two orders can be carried out when the first two orders of the products to be manufactured corresponding to the detection targets are matched with the combination of the first two orders and the second product numbers.

And determining the early warning type as the second type early warning when the product to be manufactured corresponding to the detection target has the priority early warning defect. Because a certain specific defect of a certain product cannot be avoided due to a plurality of unpredictable factors in the mass production process, the method can be used for counting the detection targets, and early warning is carried out when the product has the prior early warning defect.

And when single products are produced in small batches, material early warning and/or defect early warning can be carried out. For mass automatic production, the working procedure (working procedure) early warning can be carried out aiming at key working procedures or working procedures. When special requirements are met on the product number or the defect, the priority early warning can be carried out.

Referring to fig. 8, defect early warning is one of the first type of early warning, and aims at early warning of a detection target in a specific defect. For the detection target, it can be understood that statistics of statistics values are performed on the detection target from the point, and then early warning is performed on product production according to the statistics values of the statistics and corresponding early warning lines. The material early warning and the section early warning can be understood as counting the statistics value of the detection target from the line and the plane, and then early warning is carried out on the production of the product according to the counted statistics value and the corresponding early warning line.

The second type of early warning includes priority early warning which is further supplemented and optimized to the first type of early warning.

As shown in fig. 9, in order to determine the pre-warning type, the form of statistics, the specific pre-warning mode, the pre-warning code information, the pre-warning line, the corresponding product making department, the operation user, other related description and other information are stored through a storage button. The type of pre-warning may be a first type of pre-warning or a second type of pre-warning. The statistics may be in the form of yield and number of anomalies. The specific early warning mode can be section early warning, material early warning, defect early warning or priority early warning and the like. The early warning code information can be the section code information of the section where the detection target is located, the code information of the defect corresponding to the detection target, the material code information and/or the like. The warning line may be in the form of a yield or in the form of an anomaly.

Referring to fig. 10, for a schematic diagram of the early warning record table, the information included in the early warning record table refers to the contents shown in fig. 10, and operations such as generalization and summarization can be performed according to the contents. The later stage can carry out quality analysis through the product type, the product number, the key working section, the working procedure, the work order, the defect code early warning quantity and the like of a certain time period so as to strictly control people, machines, materials, methods and rings in the production process, and the explanation is omitted here.

In the several embodiments provided by 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 only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.

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

In addition, each functional unit in each embodiment of the present invention may be integrated in one processing module, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.

In some cases, the two technical features do not conflict, and a new method technical scheme can be combined.

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

Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or a optical disk, or the like, which can store program codes.

The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. The early warning method for manufacturing the product is characterized by comprising the following steps of:

determining whether the detection target is qualified;

Counting the statistic value of the detection target within a preset time period;

When the abnormal phenomenon corresponding to the early warning line appears in the detection target according to the statistic value, early warning is carried out on the production of the product;

the method further comprises the steps of: determining an early warning type for early warning of product manufacture according to the process parameters of the detection target; wherein, early warning type includes: a first type of early warning according to the general early warning configuration and a second type of early warning according to the special early warning configuration; the special early warning configuration is used for early warning of the detection target in a preset range; the general early warning configuration is used for early warning of the detection target outside the preset range;

Wherein the predetermined range includes at least one of: the determined material group range, the predetermined work order type, the priority early warning product material number and/or the priority early warning defect; the process parameters of the detection target comprise at least one of the following: type, model, worksheet number, product specification, material parameters, worksheet type, product material number and/or pre-warning defects;

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

When the material used by the product to be manufactured is determined to be in the range of the preset material group according to the material parameters of the detection target, determining the early warning type as the second type early warning;

determining the worksheet of the detection target according to the worksheet of the detection target as follows: determining the early warning type as the second type early warning when one of a test sheet, a reworking sheet or a retest sheet is adopted;

When the product to be manufactured corresponding to the detection target has a priority early warning product material number, determining that the early warning type is the second type early warning;

2. The method according to claim 1, wherein the statistics include a qualification rate, and the statistics of the detection targets within the preset time period include:

Counting the qualification rate of the detection target within the preset time period;

when determining that the abnormal phenomenon corresponding to the early warning line occurs to the detection target according to the statistic value, early warning is carried out on the production of the product, 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 production of the product according to the general early warning configuration.

3. The method according to claim 1, wherein the statistics include a number of abnormal pieces, and the statistics of the detection targets within the preset time period include:

Counting the number of abnormal parts of the detection target in the preset time period;

And when the abnormal quantity reaches the early warning abnormal quantity threshold corresponding to the early warning line, early warning is carried out on the production of the product according to the special early warning configuration.

4. The method of claim 1, wherein,

The statistical value is: counting the detection targets by taking the working sections as a counting unit to obtain the qualification rate or the abnormal part number;

Or alternatively

The statistical value is: counting the detection targets by taking the worksheets as a counting unit to obtain the qualification rate or the number of abnormal parts;

Or alternatively

The statistical value is: and counting the detection targets by taking the key working sections in the work order as a counting unit to obtain the qualification rate or the abnormal part number.

5. The method according to claim 4, wherein the counting the statistics of the detection targets within the preset time period includes one of:

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

The early warning module is used for carrying out early warning on the production of the product when determining that the abnormal phenomenon corresponding to the early warning line occurs to the detection target according to the statistic value;

The early warning system further comprises: the early warning type determining module is used for determining the early warning type for early warning of the production according to the process parameters of the detection target; wherein, early warning type includes: a first type of early warning according to the general early warning configuration and a second type of early warning according to the special early warning configuration; the special early warning configuration is used for early warning of the detection target in a preset range; the general early warning configuration is used for early warning of the detection target outside the preset range;

The early warning type determining module is specifically configured to determine an early warning type for early warning of product production according to a process parameter of a detection target, and includes at least one of the following: when the material used by the product to be manufactured is determined to be in the range of the preset material group according to the material parameters of the detection target, determining the early warning type as the second type early warning; determining the work order in which the detection target is located according to the work order in which the detection target is located as follows: determining the early warning type as the second type early warning when one of the test sheet, the reworking sheet or the retest sheet; when the product to be manufactured corresponding to the detection target has a priority early warning product material number, determining that the early warning type is a second type early warning; and determining the early warning type as the second type early warning when the product to be manufactured corresponding to the detection target has the priority early warning defect.

7. 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 one of claims 1-5.

8. A storage medium storing a program which, when executed by a processor, performs the method of any one of claims 1 to 5.