CN115018471B

CN115018471B - Data processing method and related device

Info

Publication number: CN115018471B
Application number: CN202210845654.9A
Authority: CN
Inventors: 郭传亮
Original assignee: Hope Zhizhou Technology Shenzhen Co ltd
Current assignee: Hope Zhizhou Technology Shenzhen Co ltd
Priority date: 2022-07-19
Filing date: 2022-07-19
Publication date: 2022-12-09
Anticipated expiration: 2042-07-19
Also published as: CN115018471A; CN115879696A

Abstract

The embodiment of the application provides a data processing method and a related device, wherein the method comprises the following steps: acquiring production data of target employees; analyzing the production skills of the target staff according to the production data to obtain an analysis result; generating a production knowledge database aiming at the target employee according to the analysis result; generating a production knowledge training scheme aiming at the target staff according to the production knowledge database; acquiring training information for training production knowledge of the target staff according to the production knowledge training scheme; and updating the production knowledge database according to the training information, wherein the production knowledge database is used for indicating the production knowledge training condition of the target staff. Therefore, the production skill condition of each employee can be comprehensively and quickly mastered, the production skill training condition of each employee can be fully known, and the work order can be more reasonably distributed to each employee in the follow-up process.

Description

Data processing method and related device

Technical Field

The application belongs to the field of general data processing of the Internet industry, and particularly relates to a data processing method and a related device.

Background

At present, when managing the production condition of staff, can not meticulously accurate carry out categorised the obtaining to every staff's production condition for follow-up staff actual conditions can not laminate when distributing the work task for the staff. Moreover, because the production skills of the staff are not comprehensively known, targeted training cannot be provided for each staff, so that the production skills of the staff cannot be rapidly improved, and the production efficiency of a factory is reduced.

Disclosure of Invention

The embodiment of the application provides a data processing method and a related device, so that the production skill of each employee can be comprehensively and quickly known, and the production skill training condition of each employee can be managed in a targeted manner.

In a first aspect, an embodiment of the present application provides a data processing method, where the method includes:

acquiring production data of target employees;

analyzing the production skills of the target staff according to the production data to obtain an analysis result;

generating a production knowledge database aiming at the target staff according to the analysis result;

generating a production knowledge training scheme aiming at the target staff according to the production knowledge database;

acquiring training information for training production knowledge of the target staff according to the production knowledge training scheme;

and updating the production knowledge database according to the training information, wherein the production knowledge database is used for indicating the production knowledge training condition of the target staff.

In a second aspect, an embodiment of the present application provides a data processing apparatus, where the first obtaining unit is configured to obtain production data of a target employee; the analysis unit is used for analyzing the production skills of the target staff according to the production data to obtain an analysis result; the first production unit is used for generating a production knowledge database aiming at the target employee according to the analysis result; the second production unit is used for generating a production knowledge training scheme aiming at the target staff according to the production knowledge database; the second acquisition unit is used for acquiring training information for training the production knowledge of the target staff according to the production knowledge training scheme; and the updating unit is used for updating the production knowledge database according to the training information, and the production knowledge database is used for indicating the production knowledge training condition of the target staff.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, where the programs include instructions for performing the steps in the first aspect of the embodiment of the present application.

In a fourth aspect, embodiments of the present application provide a computer storage medium having stored thereon a computer program/instructions for execution by a processor to perform the steps of the method according to the first aspect of the embodiments of the present application.

In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.

In the embodiment of the application, firstly, production data of target employees are obtained, then, production skills of the target employees are analyzed according to the production data to obtain analysis results, then, a production knowledge database for the target employees is generated according to the analysis results, then, a production knowledge training scheme for the target employees is generated according to the production knowledge database, then, training information for training the production knowledge of the target employees according to the production knowledge training scheme is obtained, and finally, the production knowledge database is updated according to the training information, and is used for indicating the production knowledge training conditions of the target employees. Therefore, the production skill condition of each employee can be comprehensively and quickly mastered, the production skill training condition of the employee can be managed, the work order can be more reasonably distributed to each employee subsequently, and the production efficiency is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 is a schematic diagram of a data processing system provided by an embodiment of the present application;

fig. 2 is a schematic structural diagram of a server provided in an embodiment of the present application;

fig. 3 is a schematic flowchart of a data processing method according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a production skill situation of an employee according to an embodiment of the present application;

FIG. 5 is a schematic diagram of an employee training scenario provided by an embodiment of the present application;

FIG. 6 is a block diagram illustrating functional units of a data processing apparatus according to an embodiment of the present disclosure;

fig. 7 is a block diagram of functional units of another data processing apparatus according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein may be combined with other embodiments.

At present, when the production condition of the staff is managed, the production condition of each staff cannot be classified and acquired carefully and accurately, so that the actual condition of the staff cannot be fitted when the staff are assigned with work tasks subsequently. Moreover, because the production skills of the employees are not comprehensively known, the production skills of the employees cannot be trained in a targeted manner, so that the production skills of the employees cannot be quickly improved, the production efficiency of a factory is reduced, and the mode is low in training efficiency and wastes time of the employees.

In view of the foregoing problems, embodiments of the present application provide a data processing method and a related apparatus, and the following describes embodiments of the present application in detail with reference to the accompanying drawings.

Referring to fig. 1, fig. 1 is a schematic diagram of a data processing system according to an embodiment of the present disclosure. As shown in the figure, the data processing system 10 includes a server 110 and a plurality of electronic devices 111, where the server 110 and the plurality of electronic devices 111 are respectively connected in a communication manner, and the electronic devices 111 may correspond to employee devices or production devices. That is, the electronic device 111 may obtain production data of the employee. The electronic devices 111 upload the production data to the server 110, and the server processes the production data to determine the skill strength item, the skill normal item and the skill short board item corresponding to each production dimension of each employee, and determine the training scheme of each employee according to the skill strength item, the skill normal item and the skill short board item, so as to train the employees.

The server 110 is configured as shown in fig. 2, where the server 110 includes a processor 120, a memory 130, a communication interface 140, and one or more programs 131, where the one or more programs 131 are stored in the memory 130 and configured to be executed by the processor 120, and the one or more programs 131 include instructions for performing any of the steps of the method embodiments described below. In a specific implementation, the processor 120 is configured to perform any one of the steps performed by the server in the method embodiments described below, and when performing a data transmission operation such as receiving, optionally invokes the communication interface 140 to complete the corresponding operation.

Referring to fig. 3, fig. 3 is a schematic flowchart illustrating a data processing method according to an embodiment of the present disclosure. As shown in the figure, the data processing method includes the following steps.

S201, obtaining production data of target employees.

The production data includes, but is not limited to, work order information filled and uploaded in the production process of the staff, and information such as product quality corresponding to each device or each batch of products in the production process of the staff. The production data can be production data in a preset time period of the staff, and the preset time period can be customized by a user according to requirements, or can be determined according to the production time of the staff or the production seasons of a factory. For example, the production data of the employee is acquired once every certain time when the total production time of the employee is full.

And S202, analyzing the production skills of the target staff according to the production data to obtain an analysis result.

The production skill comprises a plurality of dimensions, namely a production product dimension, a production working condition dimension and a production equipment dimension. The analysis result corresponding to the product dimension is used for representing the quality condition of the product produced by the staff, so that the staff can be judged to be suitable for producing what product. The analysis result corresponding to the dimension of the production working condition is used for representing the quality of products produced by the staff under different working conditions, so that the staff can be judged under which working condition to produce, and the production working condition is used for representing the production condition jointly determined by information such as material form, production environment, equipment state and the like when the staff produces. The analysis result corresponding to the dimension of the production equipment is used for representing information such as product yield, production efficiency and production cost corresponding to the production of the staff on different equipment, and therefore the staff equipment can be judged to be produced on which equipment.

In specific implementation, the staff or the manager can check the obtained analysis result to know the specific production skill mastering condition of each staff in detail. As shown in fig. 4, fig. 4 is a schematic diagram of a production skill situation of an employee according to an embodiment of the present application. The table details the specific production skills of an employee, the production skills are divided into three production dimensions, namely a production product dimension, a production working condition dimension and a production equipment dimension, when the skill state corresponding to each production dimension is determined, the production dimensions are divided into different levels according to the difficulty, for example, it can be clearly and quickly known through a chart in fig. 4 that the employee has 4 products belonging to skill strength items in the production product dimension, wherein one product with a high difficulty level is a product 1. The difficulty level of the production working condition can be divided according to whether the production working condition is over-divided, namely the non-standard working condition which is not over-divided corresponds to high difficulty, the working condition which is over-trained is medium difficulty, and the standard working condition which is over-trained is low difficulty.

In specific implementation, after the analysis result is obtained, the obtained analysis result of the employee may be stored through the blockchain, each analysis result is encrypted, and the key corresponding to each analysis result is only sent to the corresponding employee and the superior administrator of the employee. The key can comprise a primary key and a superior key corresponding to the primary key, and one superior key can correspond to a plurality of primary keys, so that when a superior manager manages a plurality of persons at the same time, each person can only obtain the corresponding analysis result according to the key, the superior manager can simultaneously obtain the analysis results of the managed persons according to the superior key, and the analysis results of the persons not in the management range can not be obtained.

And S203, generating a production knowledge database aiming at the target employee according to the analysis result.

The skill state of each employee, including but not limited to production quality skill state, employee efficiency skill state, employee cost skill state, employee safety skill state, and the like, can be comprehensively known through the production knowledge database, and whether the knowledge skill of each skill state is normal or to be promoted or needs key training and the like can be determined according to the production knowledge database. And meanwhile, the training state of the employee can be known according to the production knowledge database, including training time, training score and training result of training corresponding to each skill state or production dimension, and the content of training data such as electronic test paper, training video and the like corresponding to each training progress. The production knowledge database can also comprise current training content and historical training information of the staff.

And S204, generating a production knowledge training scheme aiming at the target staff according to the production knowledge database.

The training scheme can comprise offline training and online training, and different training modes correspond to scores corresponding to all production dimensions in the analysis results of the employees or ranks of the employees.

S205, acquiring training information for training the production knowledge of the target staff according to the production knowledge training scheme;

in one possible example, the training information includes at least one of: training time, training score, training results and training data for each production skill dimension for the target user.

As shown in fig. 5, fig. 5 is a schematic diagram of an employee training situation provided in an embodiment of the present application. As can be seen from fig. 5, the employee a currently needs to train 4 items, and the training time, the training score, the training result, the training data, and the like of the employee for each training can be obtained in the production knowledge database. The training time may include the total time of training for each training and the training time currently being trained, e.g., the training for the product 4 divided into two parts in total, the current employee A has progressed to the second part, so it can be determined from the training time how long employee A has been trained in total, and where the second part has been trained. Or if the product 4 is for offline training, the training time may also be the training time for each training, for example, the employee may know that there is training at 5 pm tomorrow.

And S206, updating the production knowledge database according to the training information, wherein the production knowledge database is used for indicating the production knowledge training condition of the target staff.

As can be seen, in this example, production data of a target employee is first obtained, a production skill of the target employee is then analyzed according to the production data to obtain an analysis result, a production knowledge database for the target employee is then generated according to the analysis result, a production knowledge training plan for the target employee is then generated according to the production knowledge database, training information for performing production knowledge training on the target employee according to the production knowledge training plan is then obtained, and the production knowledge database is updated according to the training information, and is used to indicate a production knowledge training situation of the target employee. Therefore, the production skill condition of each employee can be comprehensively and quickly mastered, the production skill training condition of the employee can be managed, the work order can be more reasonably distributed for each employee subsequently, and the production efficiency is improved.

In one possible example, the analyzing the production skills of the target employees according to the production data to obtain an analysis result includes: acquiring a comprehensive quality evaluation index of each batch of products produced by the target staff according to the production data; and analyzing the production skills of the target staff in a preset production skill dimension according to the comprehensive quality evaluation index to obtain the skill short item, the skill normal item and the skill strong item of the target staff in the preset production skill dimension.

The comprehensive quality evaluation index is used for measuring the quality of the produced product, and the higher the comprehensive quality evaluation index is, the better the quality of the produced product is, and the better the product meets the requirements of users. The strong skill item corresponds to the production skill which is good for the staff, and the short skill item corresponds to the production skill which needs to be trained again for the staff. Therefore, the whole staff ranking of each skill in the skill strengths of the staff can be carried out according to the comprehensive quality evaluation index, the whole staff ranking of each skill strength of each staff is obtained, the skill standard soldier of each skill is determined according to the ranking, and the skill standard soldiers train other staff. For example, if the skill intensity item of employee a includes the production of product 1, determining the rank of the comprehensive quality evaluation index of employee a for producing product 1 among all employees for producing product 1, and if the rank is the first name, training employee a for other employees needing training, or generating an operation demonstration video according to the operation record of a and learning by other employees.

Therefore, in the example, the strong items and the short board items corresponding to each production skill in the production of the staff are determined according to the comprehensive quality evaluation index, the production skill of the staff can be accurately and comprehensively analyzed, a reasonable training scheme and a reasonable production task can be conveniently arranged for the staff, and the production efficiency and the training efficiency can be improved.

In one possible example, the preset production skill dimension includes a production product dimension, and the analyzing the production skill of the target employee in the preset production skill dimension according to the comprehensive quality evaluation index to obtain the skill short term, the skill normal term and the skill strong term of the target employee in the preset production skill dimension includes: obtaining the product type of each batch of products; determining a first average comprehensive evaluation index corresponding to each product type according to the comprehensive quality evaluation index of each batch of products; determining the product type of which the first average comprehensive quality evaluation index is positioned at a first preset threshold value as a first product type; determining that the product type of the first average comprehensive quality evaluation index at a second preset threshold is a second product type, wherein the maximum value of the second preset threshold is smaller than the minimum value of the first preset threshold; determining that the product type of the first average comprehensive quality evaluation index at a third preset threshold is a third product type, wherein the maximum value of the third preset threshold is smaller than the minimum value of the second preset threshold; determining that the target employee is a skill strong item of the target employee in producing the product of the first product type, the target employee is a skill normal item in producing the product of the second product type, and the target employee is a skill short item in producing the product of the third product type.

The average comprehensive quality evaluation index of the same type of products produced by an employee in a preset time period is determined according to the comprehensive quality evaluation index of each batch of products, so that the employee can determine which series or series of products is good in production quality, which series or series of products is normal in production quality, and which series or series of products is poor in production quality. In a specific implementation, after obtaining the evaluation of the production skill dimension of each employee, that is, whether each product type produced by the employee corresponds to a strong production item, a normal production item, or a short production item, the number of people who produce the short production item corresponding to each product type may also be determined, for example, if all the short production items of 10 employees include a product type m, a training scheme for the product type m may be generated for all the 10 employees. Or when the staff to be trained is determined, determining the sequence of the 10 staff according to the first average comprehensive quality evaluation index, and determining multiple staff with the inverse sequence as the staff to be trained, for example, 3 staff with the inverse sequence as the staff needing to be trained for the product type m. Or when training staff is determined, the working hours of the 10 staff members for producing the product type m are respectively determined, the staff members with the production working hours ranked first are determined as objects to be trained, and the production working hours ranked first mean that the staff members are mainly of the product type to be produced, so that the training is required preferentially. Particularly, if it is determined according to the foregoing method that the employee a needs to be trained both for the product type m and for the product type n, the training schemes of the two product types corresponding to the employee a may be determined first, and it is determined whether a time conflict occurs, and if the time conflict exists, the target product type is determined according to the current importance levels of the two product types, for example, the product production corresponding to the current product type m is important and the product type n, and it is determined that the employee a is currently trained only for the product type m.

Particularly, when the work tasks are distributed to the employees, the production tasks of the products corresponding to the strong skill items are preferentially distributed to the employees, before the production tasks of the products corresponding to the short skill items are distributed, whether the employees A have training schemes for the products needs to be checked, and if the employees A have the training schemes, whether the production tasks of the products are distributed to the employees is determined after comprehensive analysis according to the training schedule, the training results and the like.

Therefore, in the example, the production skill condition of the staff for the production of each type of product is determined according to the comprehensive quality evaluation index, the production skill of the staff can be accurately analyzed, a reasonable training scheme and a reasonable production task can be conveniently arranged for the staff, and the production efficiency and the training efficiency can be improved.

In a possible example, the preset production skill dimension includes a production condition dimension, and the analyzing the production skill of the target employee in the preset production skill dimension according to the comprehensive quality evaluation index to obtain the skill short term, the skill normal term and the skill strong term of the target employee in the preset production skill dimension includes: determining the production working condition of the target staff when producing each batch of products; determining a second average comprehensive quality evaluation index corresponding to each production working condition according to the comprehensive quality evaluation index of each batch of products; determining the production working condition that the second average comprehensive quality evaluation index is positioned at a first preset threshold value as a first production working condition; determining the production working condition that the second average comprehensive quality evaluation index is positioned at a second preset threshold as a second production working condition, wherein the maximum value of the second preset threshold is smaller than the minimum value of the first preset threshold; determining a production working condition that the second average comprehensive quality evaluation index is positioned at a third preset threshold as a third production working condition, wherein the maximum value of the third preset threshold is smaller than the minimum value of the second preset threshold; determining that the target employee is produced as the skill strong item of the target employee under the first production working condition, is produced as the skill normal item of the target employee under the second production working condition, and is produced as the skill short item of the target employee under the third production working condition.

Wherein, different production batches may correspond to different production working conditions and may correspond to the same production working condition. Therefore, the average comprehensive quality evaluation index of each production working condition can be determined according to the comprehensive quality evaluation index of each batch of produced products, and the evaluation comprehensive quality evaluation index can be used for measuring the working condition or working conditions suitable for production of employees. And distributing production tasks and determining a training scheme for the employees according to the skill intensity, the skill normal item and the skill short board item of the production working condition dimension corresponding to the employees. The method for determining the person needing to be trained is the same as the method for determining the person needing to be trained, and the content according to the product type is changed into the content according to the production working condition during the determination, so the description is omitted.

Therefore, in the example, the production skill condition of the staff in each working condition is determined according to the comprehensive quality evaluation index, the production skill of the staff can be accurately analyzed, a reasonable training scheme and a reasonable production task can be conveniently arranged for the staff, and the production efficiency and the training efficiency can be improved.

In one possible example, after determining that the target employee is producing a strong skill item for the target employee at the first production condition, is producing a normal skill item for the target employee at the second production condition, and is producing a short skill item for the target employee at the third production condition, the method further comprises: obtaining all production working condition types; determining the production batch number of the target staff aiming at each production working condition type in all the production working condition types according to the corresponding production working condition when the target staff produces each batch of products; determining the production working condition types of which the production batch number is less than the preset number as target production working condition types; and determining that the target employee is produced as the skill short board item of the target employee under the target production condition type.

When the total number of batches produced by the employee under a certain production condition is smaller than the preset number, it indicates that the employee is less in production or never encounters the production condition, and the production skill corresponding to the production condition of the employee can be determined as a skill short item. In this case, before the training plan of the employee is determined, the number of the staff to be trained corresponding to the same production working condition may be determined, and if the number is larger than the preset number, the training plan for the working condition is not generated for the employee, so that the training of other employees with lower comprehensive quality evaluation indexes is preferentially performed in limited resources. And when the work order is allocated to the employee, the work order corresponding to the production working condition under the condition can be preferentially allocated to the employee.

Therefore, in the example, the production skill condition of the staff in each working condition is determined according to the production batch number corresponding to each production working condition, the production skill of the staff can be accurately analyzed, a reasonable training scheme and a reasonable production task can be conveniently arranged for the staff, and the production efficiency and the training efficiency can be improved.

In one possible example, the analyzing the production skills of the target employees according to the production data to obtain an analysis result includes: determining a device output quality score, a device operation efficiency score and a device cost control score of each production device operated by the target staff according to the production data; and analyzing the production skill of the target user according to the equipment output quality score, the equipment operation efficiency score and/or the equipment cost control score to obtain a skill short item, a skill normal item and a skill strong item of the target user in the dimension of the production equipment.

The device output quality score may be determined according to a Process capability index (CPK) of a yield of a product output by each device, where the smaller the CPK is, the lower the corresponding device output quality score is. For example, if CPK is greater than K, it is determined that the output quality of the equipment is the best, the equipment performs production to obtain the skill strength of the employee, if CPK is greater than L and less than or equal to K, the equipment corresponds to the skill normal item of the employee, if CPK is less than or equal to L, the equipment corresponds to the skill short item of the employee, and K and L are positive integers respectively. When the skill state is determined according to the equipment operation efficiency score, the skill state of the staff can be determined according to the fact that the score is located in different intervals, namely the staff is in a skill short board item, a skill normal item or a skill strong item. And determining the skill state according to the equipment cost control score.

It should be noted that the skill state of the employee in the production through a certain device may be evaluated separately according to the device output quality score, the device operation efficiency score, and the device cost control score. Of course, the skill state of the employee for a device may also be determined from two or three of them simultaneously. When the skill state of the employee is determined according to the quality score generated by the equipment, the equipment operation efficiency score and the equipment cost control score, a weight can be determined for each skill score according to the requirement of the user, and the skill state of the user for a certain equipment is determined according to the weight corresponding to each skill score and the sum of the scores of the employee in the skill dimension. When setting the weight, the weight can be determined according to the production state of the staff or set according to the current factory requirement. For example, if the production status of the employee is that the equipment cost control scores of all employees in the current plant are relatively high, the weight corresponding to the equipment cost control dimension score can be determined to be a little lower.

The skill state of the employee in the production equipment dimension can be determined simultaneously from the equipment output quality score, the equipment operating efficiency score and the equipment cost control score, the method comprising: and respectively determining a device output quality score, a device operation efficiency score and a device cost control score for the same device, then respectively determining a plurality of preselected states for one device according to the scores, and determining a final skill state according to the preselected states. For example, if the device output quality score of the employee a on the device Q is greater than K, the first preselected state for the device is a skill strong item, and the device operation efficiency score on the device Q is in the second interval, the second preselected state for the device is a skill normal item, and if the device cost control score on the device Q is in the second interval, the third preselected state for the device is a skill normal item, so that the employee a may be determined to be the skill normal item for the device Q. When the final skill state is determined according to the plurality of preselected states, if at least two preselected states are skill intensity items aiming at the same equipment, the equipment is determined to be the skill intensity items of the staff, and the skill normal items and the skill short items are analogized. If the three preselected states are different, the ranking of the scores corresponding to the three preselected states in the whole staff can be respectively determined, and the preselected state corresponding to the score with the highest ranking is taken as the final state. For example, if the first preselected state is a skill normal item, the second preselected state is a skill short board item, the third preselected state is a skill strong item, the ranking of the score corresponding to the first preselected state is 5 th, the ranking of the score corresponding to the second preselected state is 10 th, and the ranking of the score corresponding to the third preselected state is 7 th, the skill state of the employee at the equipment is determined to be the skill normal item.

Therefore, in the embodiment, the production skill condition of the dimension of the production equipment is determined according to the equipment output quality score, the equipment operation efficiency score and/or the equipment cost control score, the production skill of the staff can be accurately analyzed, a reasonable training scheme and a reasonable production task can be conveniently arranged for the staff, and the production efficiency and the training efficiency can be favorably improved.

In accordance with the foregoing embodiments, please refer to fig. 6, and fig. 6 is a block diagram illustrating functional units of a data processing apparatus according to an embodiment of the present application. The data processing device 30 includes: a first obtaining unit 301, configured to obtain production data of a target employee; the analysis unit 302 is configured to analyze the production skills of the target employees according to the production data to obtain an analysis result; a first production unit 303, configured to generate a production knowledge database for the target employee according to the analysis result; a second production unit 304, configured to generate a production knowledge training plan for the target employee according to the production knowledge database; a second acquisition unit 305 configured to acquire training information for training production knowledge for the target employee according to the production knowledge training plan; an updating unit 306, configured to update the production knowledge database according to the training information, where the production knowledge database is used to indicate a training condition of the production knowledge of the target employee.

In a possible example, in terms of analyzing the production skills of the target employees according to the production data to obtain an analysis result, the analysis unit 302 is specifically configured to: acquiring a comprehensive quality evaluation index of each batch of products produced by the target staff according to the production data; and analyzing the production skills of the target staff in a preset production skill dimension according to the comprehensive quality evaluation index to obtain the skill short item, the skill normal item and the skill strong item of the target staff in the preset production skill dimension.

In a possible example, the preset production skill dimension includes a production product dimension, and in the aspect that the production skill of the target employee in the preset production skill dimension is analyzed according to the comprehensive quality evaluation index to obtain a skill short term, a skill normal term, and a skill strong term of the target employee in the preset production skill dimension, the analysis unit 302 is specifically configured to: obtaining the product type of each batch of products; determining a first average comprehensive evaluation index corresponding to each product type according to the comprehensive quality evaluation index of each batch of products; determining the product type of which the first average comprehensive quality evaluation index is positioned at a first preset threshold value as a first product type; determining that the product type of the first average comprehensive quality evaluation index at a second preset threshold is a second product type, wherein the maximum value of the second preset threshold is smaller than the minimum value of the first preset threshold; determining that the product type of the first average comprehensive quality evaluation index at a third preset threshold is a third product type, wherein the maximum value of the third preset threshold is smaller than the minimum value of the second preset threshold; determining that the target employee is a skill strong item of the target employee for producing the product of the first product type, the target employee is a skill normal item of the target employee for producing the product of the second product type, and the target employee is a skill short item of the target employee for producing the product of the third product type.

In a possible example, the preset production skill dimension includes a production condition dimension, and in the aspect that the production skill of the target employee in the preset production skill dimension is analyzed according to the comprehensive quality evaluation index to obtain a skill short term, a skill normal term, and a skill strong term of the target employee in the preset production skill dimension, the analysis unit 302 is specifically configured to: determining the production working condition of the target staff when producing each batch of products; determining a second average comprehensive quality evaluation index corresponding to each production working condition according to the comprehensive quality evaluation index of each batch of products; determining the production working condition of the second average comprehensive quality evaluation index at a first preset threshold value as a first production working condition; determining the production working condition that the second average comprehensive quality evaluation index is positioned at a second preset threshold as a second production working condition, wherein the maximum value of the second preset threshold is smaller than the minimum value of the first preset threshold; determining that the production working condition of the second average comprehensive quality evaluation index at a third preset threshold is a third production working condition, wherein the maximum value of the third preset threshold is smaller than the minimum value of the second preset threshold; and determining that the target employee is produced as the skill strong item of the target employee under the first production working condition, is produced as the skill normal item of the target employee under the second production working condition, and is produced as the skill short item of the target employee under the third production working condition.

In one possible example, after the determining that the target employee is produced as the skill strong item of the target employee in the first production condition, as the skill normal item of the target employee in the second production condition, and as the skill short item of the target employee in the third production condition, the analyzing unit 302 is further configured to: obtaining all production working condition types; determining the production batch number of the target staff aiming at each production working condition type in all the production working condition types according to the corresponding production working condition when the target staff produces each batch of products; determining the production working condition types of which the production batch number is less than the preset number as target production working condition types; and determining that the target employee is produced as the skill short board item of the target employee under the target production condition type.

In a possible example, in terms of analyzing the production skills of the target employees according to the production data to obtain an analysis result, the analysis unit 302 is specifically configured to: determining a device output quality score, a device operation efficiency score and a device cost control score of each production device operated by the target staff according to the production data; and analyzing the production skill of the target user according to the equipment output quality score, the equipment operation efficiency score and/or the equipment cost control score to obtain a skill short item, a skill normal item and a skill strong item of the target user in the dimension of the production equipment.

It can be understood that, since the method embodiment and the apparatus embodiment are different presentation forms of the same technical concept, the content of the method embodiment portion in the present application should be synchronously adapted to the apparatus embodiment portion, and is not described herein again.

In the case of using an integrated unit, as shown in fig. 7, fig. 7 is a block diagram of a functional unit of another data processing apparatus provided in an embodiment of the present application. In fig. 7, the data processing apparatus 400 includes: a processing module 412 and a communication module 411. The processing module 412 is used to control and manage actions of the condition-based machine learning progress management device, such as steps of the first obtaining unit 301, the analyzing unit 302, the first producing unit 303, the second producing unit 304, the second obtaining unit 305, and the updating unit 306, and/or other processes for performing the techniques described herein. The communication module 411 is used for interaction between the data processing apparatus and other devices. As shown in fig. 7, the data processing apparatus may further include a storage module 413, and the storage module 413 is used for storing program codes and data of the data processing apparatus.

The Processing module 412 may be a Processor or a controller, and may be, for example, a Central Processing Unit (CPU), a general-purpose Processor, a Digital Signal Processor (DSP), an ASIC, an FPGA or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors, among others. The communication module 411 may be a transceiver, an RF circuit or a communication interface, etc. The storage module 413 may be a memory.

All relevant contents of each scene related to the method embodiment may be referred to the functional description of the corresponding functional module, and are not described herein again. The data processing apparatus 400 may perform the data processing method shown in fig. 3.

The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the electronic device comprises corresponding hardware structures and software modules for performing the respective functions in order to realize the functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments provided herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed in hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiment of the present application, the electronic device may be divided into the functional units according to the method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that, in the embodiment of the present application, the division of the unit is schematic, and is only one logic function division, and when the actual implementation is realized, another division manner may be provided.

Embodiments of the present application further provide a chip, where the chip includes a processor, configured to call and run a computer program from a memory, so that a device in which the chip is installed performs some or all of the steps described in the electronic device in the above method embodiments.

Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.

Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art will recognize that the embodiments described in this specification are preferred embodiments and that acts or modules referred to are not necessarily required for this application.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.

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

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.

The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Those skilled in the art will appreciate that all or part of the steps of the methods of the above embodiments may be implemented by a program, which is stored in a computer-readable memory, the memory including: flash Memory disks, read-Only memories (ROMs), random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, the specific implementation manner and the application scope may be changed, and in summary, the content of the present specification should not be construed as a limitation to the present application.

Although the present invention is disclosed above, the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions without departing from the spirit and scope of the invention, and all changes and modifications can be made, including different combinations of functions, implementation steps, software and hardware implementations, all of which are included in the scope of the invention.

Claims

1. A method of data processing, the method comprising:

acquiring production data of target employees;

generating a production knowledge database aiming at the target employee according to the analysis result;

updating the production knowledge database according to the training information, wherein the production knowledge database is used for indicating the production knowledge training condition of the target staff;

analyzing the production skills of the target employees according to the production data to obtain an analysis result, wherein the analysis result comprises the following steps:

acquiring a comprehensive quality evaluation index of each batch of products produced by the target staff according to the production data;

analyzing the production skills of the target employees in a preset production skill dimension according to the comprehensive quality evaluation index to obtain skill short items, skill normal items and skill strong items of the target employees in the preset production skill dimension;

the preset production skill dimension comprises a production product dimension, the production skill of the target employee in the preset production skill dimension is analyzed according to the comprehensive quality evaluation index, and a skill short item, a skill normal item and a skill strong item of the target employee in the preset production skill dimension are obtained, and the method comprises the following steps:

obtaining the product type of each batch of products;

determining a first average comprehensive quality evaluation index corresponding to each product type according to the comprehensive quality evaluation index of each batch of products;

determining the product type of which the first average comprehensive quality evaluation index is positioned at a first preset threshold value as a first product type;

determining that the product type of the first average comprehensive quality evaluation index at a second preset threshold is a second product type, wherein the maximum value of the second preset threshold is smaller than the minimum value of the first preset threshold;

determining that the product type of the first average comprehensive quality evaluation index at a third preset threshold is a third product type, wherein the maximum value of the third preset threshold is smaller than the minimum value of the second preset threshold;

determining that the target employee is a skill strong item of the target employee for producing the product of the first product type, the target employee is a skill normal item of the target employee for producing the product of the second product type, and the target employee is a skill short item of the target employee for producing the product of the third product type;

the preset production skill dimension comprises a production working condition dimension, and the analysis of the production skill of the target employee in the preset production skill dimension according to the comprehensive quality evaluation index obtains a skill short item, a skill normal item and a skill strong item of the target employee in the preset production skill dimension, and comprises the following steps:

determining the production working condition of the target staff when producing each batch of products;

determining a second average comprehensive quality evaluation index corresponding to each production working condition according to the comprehensive quality evaluation index of each batch of products;

determining the production working condition of the second average comprehensive quality evaluation index at a first preset threshold value as a first production working condition;

determining the production working condition of the second average comprehensive quality evaluation index at a second preset threshold as a second production working condition, wherein the maximum value of the second preset threshold is smaller than the minimum value of the first preset threshold;

determining a production working condition that the second average comprehensive quality evaluation index is positioned at a third preset threshold as a third production working condition, wherein the maximum value of the third preset threshold is smaller than the minimum value of the second preset threshold;

determining that the target employee is produced as a skill strong item of the target employee under the first production working condition, is produced as a skill normal item of the target employee under the second production working condition, and is produced as a skill short item of the target employee under the third production working condition;

determining a device output quality score, a device operation efficiency score and a device cost control score of each production device operated by the target staff according to the production data;

and analyzing the production skill of the target staff according to the equipment output quality score, the equipment operation efficiency score and/or the equipment cost control score to obtain a skill short item, a skill normal item and a skill strong item of the target staff in the dimension of the production equipment.

2. The method of claim 1, wherein the determining that the target employee is producing a strong skill item for the target employee at the first production condition, a normal skill item for the target employee at the second production condition, and a short skill item for the target employee at the third production condition further comprises:

obtaining all production working condition types;

determining the production batch number of the target staff aiming at each production working condition type in all the production working condition types according to the corresponding production working condition when the target staff produces each batch of products;

determining the production working condition types of which the production batch number is less than the preset number as target production working condition types;

and determining that the target employee is produced as the skill short board item of the target employee under the target production working condition type.

3. The method of claim 1 or 2, wherein the training information comprises at least one of:

training time, training score, training results and training data of the target employee for each production skill dimension.

4. A data processing apparatus, characterized in that the apparatus comprises:

the first acquisition unit is used for acquiring production data of target employees;

the analysis unit is used for analyzing the production skills of the target staff according to the production data to obtain an analysis result;

the first production unit is used for generating a production knowledge database aiming at the target employee according to the analysis result;

the second production unit is used for generating a production knowledge training scheme aiming at the target staff according to the production knowledge database;

the second acquisition unit is used for acquiring training information for training the production knowledge of the target staff according to the production knowledge training scheme;

the updating unit is used for updating the production knowledge database according to the training information, and the production knowledge database is used for indicating the production knowledge training condition of the target staff;

in terms of analyzing the production skills of the target employees according to the production data to obtain an analysis result, the analysis unit is further configured to: acquiring a comprehensive quality evaluation index of each batch of products produced by the target staff according to the production data; the comprehensive quality evaluation index is used for analyzing the production skills of the target staff in a preset production skill dimension to obtain a skill short item, a skill normal item and a skill strong item of the target staff in the preset production skill dimension;

the preset production skill dimension comprises a production product dimension, and in the aspect of analyzing the production skill of the target employee in the preset production skill dimension according to the comprehensive quality evaluation index to obtain a skill short item, a skill normal item and a skill strong item of the target employee in the preset production skill dimension, the analyzing unit is further configured to: obtaining the product type of each batch of products; and the first average comprehensive quality evaluation index corresponding to each product type is determined according to the comprehensive quality evaluation index of each batch of products; and determining the product type of the first average comprehensive quality evaluation index at a first preset threshold value as a first product type; the product type of the first average comprehensive quality evaluation index at a first preset threshold is determined to be a first product type, and the maximum value of the first preset threshold is smaller than the minimum value of the first preset threshold; the product type used for determining that the first average comprehensive quality evaluation index is positioned at a third preset threshold value is a third product type, and the maximum value of the third preset threshold value is smaller than the minimum value of the second preset threshold value; and determining that the target employee is a skill strong item of the target employee in producing the product of the first product type, the target employee is a skill normal item in producing the product of the second product type, and the target employee is a skill short item in producing the product of the third product type;

the preset production skill dimension comprises a production working condition dimension, and in the aspect of analyzing the production skill of the target employee in the preset production skill dimension according to the comprehensive quality evaluation index to obtain a skill short item, a skill normal item and a skill strong item of the target employee in the preset production skill dimension, the analyzing unit is further configured to: determining the production working condition of the target staff when producing each batch of products; and the second average comprehensive quality evaluation index corresponding to each production working condition is determined according to the comprehensive quality evaluation index of each batch of products; the production working condition for determining that the second average comprehensive quality evaluation index is positioned at a first preset threshold value is a first production working condition; the production working condition for determining that the second average comprehensive quality evaluation index is positioned at a second preset threshold is a second production working condition, and the maximum value of the second preset threshold is smaller than the minimum value of the first preset threshold; the production working condition for determining that the second average comprehensive quality evaluation index is positioned at a third preset threshold is a third production working condition, and the maximum value of the third preset threshold is smaller than the minimum value of the second preset threshold; the system is used for determining that the target employee is produced as the skill strong item of the target employee under the first production working condition, is produced as the skill normal item of the target employee under the second production working condition and is produced as the skill short item of the target employee under the third production working condition;

in the aspect of analyzing the production skills of the target employees according to the production data to obtain an analysis result, the analysis unit is further configured to: determining a device output quality score, a device operation efficiency score and a device cost control score of each production device operated by the target staff according to the production data; and analyzing the production skill of the target staff according to the equipment output quality score, the equipment operation efficiency score and/or the equipment cost control score to obtain a skill short board item, a skill normal item and a skill strong item of the target staff in the production equipment dimension.

5. An electronic device comprising a processor, a memory, and one or more programs stored in the memory and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-3.

6. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any one of claims 1-3.