CN114756595A

CN114756595A - Data processing method for database and related device

Info

Publication number: CN114756595A
Application number: CN202210665684.1A
Authority: CN
Inventors: 郭传亮
Original assignee: Hope Zhizhou Technology Shenzhen Co ltd
Current assignee: Hope Zhizhou Technology Shenzhen Co ltd
Priority date: 2022-06-14
Filing date: 2022-06-14
Publication date: 2022-07-15
Anticipated expiration: 2042-06-14
Also published as: CN114756595B

Abstract

The application provides a data processing method and a related device for a database, wherein the method is applied to a server and comprises the following steps: acquiring at least one production batch number corresponding to a target product, wherein the at least one production batch number comprises the target production batch number; updating the target database according to a target production batch data set corresponding to the target production batch number, wherein the target production batch data set is used for indicating various types of work data of at least one employee in the target production batch, and the various types of work data comprise at least one of the following types: resource consumption cost data, equipment efficiency data, product quality data, work order and work time data and staff attendance data; and determining the employee skill tag database according to the updated target database. Therefore, the server analyzes the working data of the staff in multiple dimensions through statistics and is based on intelligent and automatic processing procedures, so that the finally output evaluation result of the working capacity of the staff is more accurate, and the use experience of the user is improved.

Description

Data processing method for database and related device

Technical Field

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

Background

In the first-line production activity of a factory, a management layer generally needs to allocate tasks according to the working capacity of employees, but at present, the evaluation mode of the working capacity of the employees is generally based on subjective judgment of the management layer, or a server only analyzes the working capacity of the employees according to the working data of a single dimension of the employees, and a database reflecting the working capacity of the employees from multiple dimensions is lacked, so that the final output evaluation result is not accurate enough, and the user experience is influenced.

Disclosure of Invention

The application provides a data processing method and a related device for a database, aiming at improving the accuracy of employee work capacity evaluation results output by a server.

In a first aspect, an embodiment of the present application provides a data processing method for a database, which is applied to a server, and the method includes:

acquiring at least one production batch number corresponding to a target product, wherein the at least one production batch number comprises a target production batch number, the target production batch number corresponds to a target production batch one by one, and the target production batch corresponds to at least one employee;

Updating a target database according to a target production batch data set corresponding to the target production batch number, wherein the target production batch data set is used for indicating various types of work data of the at least one employee in the target production batch, and the various types of work data include at least one of the following: resource consumption cost data, equipment efficiency data, product quality data, work order and work time data and staff attendance data;

and determining an employee skill tag database according to the updated target database, wherein the employee skill tag database is used for indicating the working capacity and the busy/idle state of the at least one employee.

In a second aspect, an embodiment of the present application provides a data processing apparatus for a database, which is applied to a server, and the apparatus includes:

the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring at least one production batch number corresponding to a target product, the at least one production batch number comprises a target production batch number, the target production batch number corresponds to a target production batch one to one, and the target production batch corresponds to at least one employee; an updating unit, configured to update a target database according to a target production batch data set corresponding to the target production batch number, where the target production batch data set is used to indicate various types of work data of the at least one employee in the target production batch, and the various types of work data include at least one of: resource consumption cost data, equipment efficiency data, product quality data, work order and work time data and staff attendance data; and the determining unit is used for determining an employee skill tag database according to the updated target database, and the employee skill tag database is used for indicating the working capacity and the busy/idle state of the at least one employee.

In a third aspect, embodiments of the present application provide a server, 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, the programs including instructions for performing the steps in the first aspect of the embodiments of the present application.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium for storing a computer program for electronic data exchange, wherein the computer program enables a computer to perform some or all of the steps described in the first aspect 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.

It can be seen that, in the embodiment of the present application, a server firstly locks a target production batch through a production batch number, so as to obtain a production batch data set corresponding to the target production batch, where the production batch data set respectively counts working data of employees in the target production batch from multiple dimensions, such as resource consumption cost, equipment efficiency, product quality, work order man-hour, attendance, and the like, so as to update a target database according to the production batch data set, and finally determines an employee skill tag database according to the target database, where the employee skill tag database is used to indicate a working capacity and a busy/idle state of the at least one employee. Therefore, the server analyzes the working data of the staff in multiple dimensions through statistics and is based on intelligent and automatic processing procedures, so that the finally output evaluation result of the working capacity of the staff is more accurate, and the use experience of the user 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 description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a block diagram of a server according to an embodiment of the present disclosure;

fig. 2 is a schematic flowchart of a data processing method for a database according to an embodiment of the present application;

FIG. 3 is a diagram illustrating an example of a partial data set in a target production lot data set according to an embodiment of the present application;

FIG. 4 is an exemplary diagram of a resource consumption cost database provided by an embodiment of the present application;

FIG. 5 is an exemplary diagram of an apparatus efficiency database provided in an embodiment of the present application;

FIG. 6 is an exemplary diagram of a product quality database provided by an embodiment of the present application;

FIG. 7 is an exemplary diagram of a work order labor hour database provided by an embodiment of the present application;

fig. 8 is an exemplary diagram of an employee attendance database provided in an embodiment of the present application;

FIG. 9 is an exemplary diagram of an employee skill tag database provided by an embodiment of the present application;

fig. 10a is a block diagram of functional units of a data processing apparatus for a database according to an embodiment of the present application;

fig. 10b is a block diagram of functional units of another data processing apparatus for a database according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, 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 of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within 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 a non-exclusive inclusion. 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 can be combined with other embodiments.

The following description will first be made with respect to terms related to the present application.

And (3) production tasks: the method is characterized in that the method meets the work task of scheduling specific continuous production batches, and input materials, products and production lines produced under one production task are the same. For example, in the production task with the production task number of 20220001, the target product is an X product, the input material is a Y material, the production line number is 1, and the production type is a trial production.

Production batch: the input material is processed by at least one production device to obtain a product, wherein one process of the product is a production batch, and one production task corresponds to at least one production batch. For example, in the production task of the production task number 20220001, the target product is an X product, which corresponds to three production lots, namely, an a lot, a B lot, and a C lot, each production lot corresponds to at least one production equipment Pn, for example, the a lot corresponds to two production equipments P1 and P2, that is, in the a lot, the material Y is processed by P1 to obtain an intermediate material Z material, and the material Z is processed by P2 to generate the X product.

Work orders: one employee for each shift for example: the work order corresponds to the early, middle and late classes, is used for counting the working hours of front-line employees, and is convenient for the performance assessment at the end of the month. One production task comprises a plurality of work orders in different time periods, and the work order in one time period can also comprise one or more production batches in one or more production tasks, so that operators corresponding to the work orders can be traced when the production tasks are counted.

At present, when the working capacity of an employee is evaluated, a management layer usually performs subjective judgment according to own experience, or a server performs evaluation scoring only according to the working performance of the employee on a single dimension, a database which reflects the working capacity of the employee from multiple dimensions is lacked, and since the working data related to one-line production activity is a complex and multidimensional data set, the evaluation result obtained finally is not accurate enough when the method performs the working evaluation on the working capacity of the employee, and the management layer participates in the whole process, so that the cost of manual management is increased.

In order to solve the above problem, embodiments of the present application provide a data processing method for a database and a related apparatus, where the method may be applied to the field of manufacturing business. The server can lock the target production batch through the production batch number so as to obtain all data sets related to the production batch, namely the target production batch data set, the data sets respectively count the working data of the employee in the target production batch from multiple dimensions such as resource consumption cost, equipment efficiency, product quality, labor hour, attendance checking and the like, then update the target database according to the data sets, and finally determine the employee skill tag database according to the target database, so that the working capacity of the employee can be accurately evaluated based on the employee skill tag database. The application can be applied to various application scenarios requiring the evaluation of the working capacity of the employee, including but not limited to the application scenarios mentioned above.

Referring to fig. 1, fig. 1 is a block diagram of a server according to an embodiment of the present disclosure. As shown in FIG. 1, the server 10 may include one or more of the following components: a processor 11, a memory 12 coupled to the processor 11, wherein the memory 12 may store one or more computer programs, and the one or more computer programs may be configured to implement the methods described in the following embodiments when executed by the one or more processors 11. The server 10 may be a server, a server cluster composed of several servers, or a cloud computing service center.

Processor 11 may include one or more processing cores. The processor 11 connects various parts within the overall server 10 using various interfaces and lines, and performs various functions of the server 10 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 12, and calling data stored in the memory 12. Alternatively, the processor 11 may be implemented in hardware using at least one of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 11 may integrate one or a combination of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing display content; the modem is used to handle wireless communications. It is understood that the modem may be implemented by a communication chip without being integrated into the processor 11.

The Memory 12 may include a Random Access Memory (RAM) or a Read-Only Memory (ROM). The memory 12 may be used to store instructions, programs, code sets or instruction sets. The memory 12 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described above, and the like. The storage data area may also store data created by the server 10 in use, and the like.

It is understood that the server 10 may include more or less structural elements than those shown in the above structural block diagrams, including, for example, a power module, a physical key, a Wi-Fi module, a speaker, a bluetooth module, a sensor, etc., without limitation.

A data processing method for a database provided in an embodiment of the present application is described below.

Referring to fig. 2, fig. 2 is a schematic flowchart of a data processing method for a database according to an embodiment of the present application, where the data processing method for a database is applied to the server 10 shown in fig. 1, and as shown in fig. 2, the data processing method for a database includes:

Step 201, at least one production batch number corresponding to a target product is obtained, and the at least one production batch number includes the target production batch number.

The target production batch number corresponds to a target production batch one by one, and the target production batch corresponds to at least one employee. Illustratively, the target product is an X product, and the production task of the X product includes A, B, C three production batches, and the target production batch is an a batch, the production batch number of the a batch is 20220401, and the employees in charge of the a batch have four, namely zhang three, li four, wang five and zhao six.

Step 202, updating the target database according to the target production batch data set corresponding to the target production batch number.

Wherein the target production batch data set is used for indicating various types of work data of the at least one employee in the target production batch, and the various types of work data include at least one of the following: resource consumption cost data, equipment efficiency data, product quality data, work order work hour data and staff attendance data. Optionally, the target production batch data set may further include a product difficulty, a production condition, a production type, a production task number, and a production line number corresponding to the target product, where the production condition includes a production condition code and a condition complexity of the production condition. For example, referring to fig. 3, fig. 3 is an exemplary diagram of a partial data set in a target production lot data set according to an embodiment of the present application, where as shown in fig. 3, a target product is an X product, and a target production lot is an a lot, then a lot data set of the a lot corresponding to the X product includes: the production batch number is 20220401, the product difficulty is 2, the production type is trial production, the production task number is 20220001, the production line number is 1, the production working condition code is 11001100, and the working condition complexity of the production working condition is 2, wherein the product difficulty and the working condition complexity are divided into low, medium and high, and are respectively marked by 1, 2 and 3, that is, the product difficulty and the working condition complexity corresponding to the X product in the example are both in medium level.

It should be noted that the product difficulty and the working condition complexity are objective conditions used for representing products and working conditions in specific production, and are not used for representing the working capacity of employees, correspondingly, concepts used for representing the adaptation difficulty of employees to specific products and the working condition complexity are a product difficulty evaluation index and a working condition complexity evaluation index, wherein the product difficulty evaluation index and the working condition complexity evaluation index can also be divided into three grades of low, medium and high, and exemplarily, the three grades are respectively represented by 1, 2 and 3. If the product difficulty evaluation index of the employee is 3, the employee is indicated to be suitable for producing products with three difficulties, namely high difficulty, medium difficulty and low difficulty; if the product difficulty evaluation index of the employee is 2, the employee is only suitable for producing the products with medium and low difficulty, but not suitable for producing the products with high difficulty. Similarly, if the working condition complexity evaluation index of the employee is 3, the employee is indicated to be suitable for working conditions with high, medium and low complexities; if the evaluation index of the working condition complexity of the staff is 2, the staff is only suitable for working conditions with medium and low complexity but not suitable for working conditions with high complexity.

In one possible example, the target production lot corresponds to at least one production device, the target database comprises a resource consumption cost database, and the updating the target database according to the target production lot data set corresponding to the target production lot number comprises: acquiring the process starting time, the process ending time and the resource consumption corresponding to the at least one production device according to the target production batch number; and updating the resource consumption cost database according to the process starting time, the process ending time and the resource consumption corresponding to the at least one production device.

Wherein the resource consumption cost database is used to indicate the consumption of each cost resource in the target production lot. For example, with the batch a as the target production batch, the batch a may be divided into two time periods according to time dimension, where each time period corresponds to one production device Pn, for example, 7:00 to 15:00 corresponds to the production device P1, and 15:00 to 23:00 corresponds to the production device P2. Illustratively, the resource consumption required for producing the X product in the apparatus Pn includes water consumption Cn1, electricity consumption Cn2 and steam consumption Cn3, i.e., the water consumption in the apparatus P1 is denoted as C11, the electricity consumption is denoted as C12, the steam consumption is denoted as C13, and similarly, the water consumption, the electricity consumption and the steam consumption in the apparatus P2 are denoted as C21, C22 and C23, respectively. Optionally, the process start time and the process end time corresponding to the at least one production device are obtained by controlling the opening time of a feed valve and the closing time of a discharge valve of the production device Pn. Illustratively, taking P1 as an example, if the opening time of a feeding valve is controlled to be 2022/04/01/7:00, the starting time of a P1 process is 2022/04/01/7:00, the total water amount Q1, the electricity consumption Q2 and the total steam amount Q3 at the moment are recorded, the closing time of a discharging valve of a P1 device is 2022/04/01/15:00, the ending time of a P1 process is 2022/04/01/15:00, the total water amount Q1 ', the electricity consumption Q2' and the total steam amount Q3 'at the moment are recorded, the water consumption C11 of the P1 device is Q1' -Q1, the electricity consumption C12 is Q2 '-Q2, and the steam consumption C13 is Q3' -Q3. Similarly, the flow start time, the flow end time, and the resource consumption amount corresponding to the P2 device can be obtained. The data sets in the above example are synthesized, and the resource consumption cost database is updated, so as to obtain an example diagram of the resource consumption cost database shown in fig. 4.

Therefore, in this example, the server obtains the data set related to the resource consumption cost through the target production batch number, updates the resource consumption cost database based on the data set, provides a data base for subsequently evaluating the working capacity of the employee from the cost dimension, and improves the accuracy of the final evaluation of the working capacity of the employee.

In one possible example, the target database comprises a device efficiency database, and the updating the target database according to the target production lot data set corresponding to the target production lot number comprises: acquiring the charging time, the material reaction time and the discharging time corresponding to the at least one production device according to the target production batch number; and updating the equipment efficiency database according to the process starting time, the process ending time, the charging time, the material reaction time and the discharging time corresponding to the at least one piece of production equipment.

Wherein the equipment efficiency database is used to indicate the work efficiency of the at least one production equipment under the operation of the at least one employee. Illustratively, the target product is an X product, the target production batch is an a batch, the input material is a Y material, the intermediate material corresponding to the P1 equipment is a Z material, and the charging time, the material reaction time and the discharging time corresponding to the Pn equipment are respectively Tn1, Tn2 and Tn 3. Taking P1 equipment as an example, the charging start time T1, the charging end time T2, the material reaction start time T3, the material reaction end time T4, the discharging start time T5 and the discharging end time T6 corresponding to the P1 equipment can be respectively recorded by an equipment control system, so that the charging time T11 corresponding to the P1 equipment is T2-T1, the material reaction time T12 is T4-T3, and the discharging time T13 is T6-T5. In the same way, the charging time, the material reaction time and the discharging time corresponding to the P2 equipment can be obtained. The data sets in the above example are combined, and the device efficiency database is updated, so as to obtain an example diagram of the device efficiency database shown in fig. 5.

Therefore, in the example, the server obtains the data set related to the equipment efficiency through the target production batch number, updates the equipment efficiency database based on the data set, provides a data base for subsequent evaluation of the working capacity of the staff from the efficiency dimension, and improves the accuracy of final evaluation of the working capacity of the staff.

In one possible example, the target database comprises a product quality database, and the updating the target database according to the target production batch data set corresponding to the target production batch number comprises: acquiring an intermediate material index value and a product index value corresponding to the at least one production device according to the target production batch number; and updating the product quality database according to the process starting time, the process ending time, the intermediate material index value and the product index value corresponding to the at least one production device.

The product quality database is used for indicating quality parameter indexes of the target products in the target production batches, the intermediate material index values are used for indicating various index scores of intermediate materials, such as the hardness, the color or the purity of the intermediate materials, and the product index values are used for indicating various index scores of the target products, such as the hardness, the color or the purity of the target products. Illustratively, the target product is an X product, the target production batch is an A batch, the intermediate material is a Z material, index values of the Z material are respectively Z1, Z2 and Z3, and index values of the X product are respectively X1, X2 and X3. Optionally, a product management system is used for carrying out sampling detection on products of P1 equipment to obtain intermediate material index values Z1, Z2 and Z3; and performing sampling detection on products of the P2 equipment through a product management system to obtain the product index values X1, X2 and X3. Optionally, the server determines a product quality evaluation index of the target product according to the product index value of the target product, wherein the product quality evaluation index is used for representing the quality score of the target product, and the higher the evaluation index is, the better the quality of the produced target product is. Illustratively, specific values of the Z material index values Z1, Z2 and Z3 obtained through testing are a, b and c, specific values of the product index values X1, X2 and X3 of the X product are d, e and f, and a product quality evaluation index determined according to the product index values d, e and f of the X product is g, then the data set in the above example is integrated, and the product quality database is updated to obtain an illustration chart of the product quality database shown in fig. 6.

Therefore, in the example, the server acquires the data set related to the product quality through the target production batch number, updates the product quality database based on the data set, provides a data base for evaluating the working capacity of the staff from the product quality dimension in the follow-up process, and improves the accuracy of the final evaluation of the working capacity of the staff.

In one possible example, the target database comprises a work order time database, and the updating the target database according to the target production batch data set corresponding to the target production batch number comprises: acquiring at least one employee number according to the target production batch number, wherein the at least one employee number corresponds to the at least one employee one to one; acquiring at least one work order starting time and at least one work order ending time according to the at least one employee number; and updating the work order working hour database according to the corresponding flow starting time, flow ending time, the at least one work order starting time and the at least one work order ending time of the at least one production device.

The work order working hour database is used for indicating work order data corresponding to the target production batch, and each employee has a work order of the employee. Illustratively, the target product is an X product, the target production lot is batch a, and the employees responsible for batch a are zhang san, lie si, wang wu, and zhao liu, wherein zhang san and lie si are responsible for P1 devices, and wang wu and zhao liu are responsible for P2 devices; the employees have unique employee numbers, wherein the employee number of Zhang III is 108866, the employee number of Li IV is 108867, the employee number of Wang V is 108868, and the employee number of Zhao VI is 108869. In batch a, the work order of sheet three is the work order 1, the work order of plum four is the work order 2, the work order of king five is the work order 3, and the work order of Zhao six is the work order 4, so that the work order information of the part of the work order 1 corresponding to batch a includes: the start time of the work order is 2022/04/01/7:00, and the end time of the work order is 2022/04/01/11: 00; the work order information of the part of the work order 2 corresponding to the A batch comprises the following information: the starting time of the work order is 2022/04/01/11:00, and the finishing time of the work order is 2022/04/01/15: 00; the work order information of the part of the work order 3 corresponding to the batch A comprises the following information: the starting time of the work order is 2022/04/01/15:00, and the finishing time of the work order is 2022/04/01/19: 00; the work order information of the part of the work order 4 corresponding to the batch A comprises the following information: the work order start time is 2022/04/01/19:00, and the work order end time is 2022/04/01/23: 00. The work order labor hour database is updated by combining the data sets in the above example, resulting in an example diagram of the work order labor hour database as shown in fig. 7.

Therefore, in the example, the server acquires the data set related to the work order working hours through the target production batch number, updates the work order working hour database based on the data set, provides a data base for evaluating the working capacity of the staff from the work order working hour dimension in the following process, and improves the accuracy of evaluating the working capacity of the staff finally.

In one possible example, the target database comprises an employee attendance database, and updating the target database according to the target production lot data set corresponding to the target production lot number comprises: obtaining the name of the at least one employee, and a leave asking state and a production task state of the at least one employee within a preset time period according to the at least one employee number, wherein the leave asking state at least comprises one of the following states: the production task state comprises a locked state and an unlocked state; if the production task state of the at least one employee in the preset time period is the locking state, marking the scheduling state of the at least one employee in the preset time period as locked; if the production task state of the at least one employee in the preset time period is the unlocked state, marking the scheduling state of the at least one employee in the preset time period as unlocked; and updating the employee attendance database according to the name of the at least one employee, the leave-on state of the at least one employee within a preset time period and the scheduling state of the at least one employee within the preset time period.

The staff attendance database is used for indicating attendance data of the at least one staff, and the preset time period can be a certain production scheduling time period in the future date. For example, assuming that a certain scheduling time period is 2022/04/15/7:00 to 2022/04/15/15:00, acquiring the production task state and the leave-asking state of the employee in the time period, wherein the production task state comprises a locked state and an unlocked state, and when the production task state of the employee is the locked state, marking the scheduling state of the employee in the time period as locked, indicating that the employee is only responsible for the production task locked with the employee in the time period and cannot be assigned to perform other production tasks; when the production task state of a certain employee is an unlocked state, the shift scheduling state of the certain employee in the time period is marked as unlocked, which indicates that no certain production task must be completed by the employee in the time period, namely, the employee does not have a locked production task, so the shift scheduling state is marked as unlocked. Illustratively, the at least one employee may include zhang, li si, wang wu, zhao liu, huangqi (employee number 108870), liu ba (employee number 108871), wherein liu ba has production task status of locked status at a scheduling time period 2022/04/15/7:00 to 2022/04/15/15:00, production task number 20220003 for the locked production task, and none of the other five persons have production tasks locked during the time period, thereby marking the scheduling status of liu ba during the time period as locked and marking the production task number, and the scheduling status of the other five persons is marked as unlocked; in the time period, the leave asking state of the king five is vacation, the leave asking states of the Zhang three and the Li four are rest, and the leave asking states of the other three people are normal work. And integrating the data sets in the above examples, and updating the employee attendance database to obtain an example diagram of the employee attendance database shown in fig. 8.

Therefore, in the example, the server acquires the data set related to attendance through the target production batch number, updates the staff attendance database based on the data set, provides a data base for subsequently evaluating the working capacity of the staff from the attendance dimension, and improves the accuracy of the final evaluation of the working capacity of the staff.

And step 203, determining the employee skill tag database according to the updated target database.

Wherein the employee skill tag database is configured to indicate a work capacity and a busy-idle status of the at least one employee.

In one possible example, the determining the employee skill tag database from the updated target database includes: determining a cost score for the at least one employee based on the updated resource consumption cost database; determining the equipment operation score of the at least one employee according to the updated equipment efficiency database; determining a product quality score for the at least one employee based on the updated product quality database; determining the labor intensity evaluation index of the at least one employee according to the updated work order and work hour database; determining a busy-free state of the at least one employee within a preset time period according to the updated work order work time database and the updated employee attendance database, wherein the busy-free state comprises a busy state and an idle state; and determining the staff skill tag database according to the cost score, the equipment operation score, the product quality score, the labor intensity evaluation index and the busy/idle state of the at least one staff.

Wherein the cost score may include: the system comprises a cost standard rate, cost scores corresponding to high, medium and low difficulty products and a cost contribution score COP, wherein the cost scores are used for representing the working capacity of staff in cost dimension, and the cost contribution score COP is a comprehensive cost evaluation index obtained according to the cost scores of the products with different difficulties produced by the staff and corresponding weights; the device operation scoring may include: the method comprises the following steps of obtaining equipment operation evaluation indexes, material index yield rates corresponding to production equipment and equipment efficiency standard-reaching rates corresponding to the production equipment, wherein the equipment operation indexes are used for representing the working capacity of staff in equipment efficiency dimensionality and representing production equipment operation difficulty grades adapted to the staff; the product quality score may include: the method comprises the following steps of obtaining a product quality evaluation index, a working condition complexity evaluation index, a product quality evaluation index mean value corresponding to a high-difficulty product, a medium-difficulty product and a low-difficulty product, and a product quality evaluation index mean value under various working conditions, wherein the various working conditions comprise a non-standard working condition, a learning task working condition and a benchmarking working condition, and the product quality score is used for representing the working capacity of a staff in a product quality dimension; the labor intensity evaluation index is used for representing the labor intensity of the work of the staff. It should be noted that the data sets corresponding to the fields are all obtained through calculation and are pre-stored in the server, and the server only needs to perform data query according to the target database to obtain the pre-stored data sets.

Optionally, before the server queries the pre-stored data set, the method further includes: and respectively storing the pre-stored data sets in different blockchain nodes according to different dimensions, for example, storing the cost scores in a first blockchain node, storing the equipment operation scores in a second blockchain node, storing the product quality scores in a third blockchain node, and storing the labor intensity evaluation indexes in a fourth blockchain node. When the server queries the pre-stored data set according to the target database, the server needs to access the corresponding blockchain node according to the key to obtain the data set of the corresponding dimensionality, for example, when the cost score needs to be obtained, the server needs to access the first blockchain node by using the first key. Because the pre-stored data set is important production information of the plant and is related to the management and production of the plant, only the manager has the key for acquiring the data sets with different dimensions, namely, only the manager has the right to access the block chain node to acquire or call the pre-stored data set, thereby enhancing the confidentiality of data and the safety of a system.

The staff skill tag database further comprises busy and idle states of the at least one staff in the preset time period, and the busy and idle states comprise a busy state and an idle state. Illustratively, the busy state may be determined by: if the employee has a leave or rest state in the preset time period, or the shift scheduling state in the preset time period is locked, or the preset time period is less than 16 hours from the last work order ending time of the employee, the employee is marked as a busy state, and the busy state indicates that a work task cannot be allocated to the employee, wherein the time less than 16 hours from the last work order ending time indicates that the employee is in a rest state for leaving work; and if the employee is on duty normally in the leave-on state within the preset time period, the shift scheduling state within the preset time period is unlocked, and the preset time period is more than or equal to 16 hours from the last work order ending time of the employee, the employee is marked as an idle state, the idle state represents that a work task can be allocated to the employee, wherein the time period more than or equal to 16 hours from the last work order ending time indicates that the employee has finished resting.

Illustratively, taking Zhao Liu as an example, the employee number is 108869, the product quality evaluation index is h, the product difficulty evaluation index is 3, the product quality evaluation index mean values of high, medium and low difficulty products are h1, h2 and h3 respectively, the working condition complexity evaluation index is 2, the product quality evaluation index mean values under the non-standard working condition, the learning task working condition and the benchmarking working condition are h4, h5 and h6 respectively, the equipment operation evaluation index is 3, the material index yield corresponding to the Pn equipment is m, the equipment efficiency standard reaching rate is n, the cost standard reaching rate is z, the cost scores of the high, medium and low difficulty products are q1, q2 and q3 respectively, the cost contribution score is q4, the labor intensity evaluation index is r, the false request state in the scheduling time period 2022/04/15/7:00 to 2022/04/15/15:00 is normal on duty, and the scheduling state is unlocked, the last work order time completed was 17 hours, and therefore marked as idle. The data sets in the above example are combined to update the employee skill tag database, resulting in an example diagram of the employee skill tag database as shown in fig. 9.

As can be seen, in this example, the server determines, through the updated target database, a data set representing the working capacity of the employee from different dimensions, and updates the employee skill tag database based on the data set, thereby improving the accuracy of evaluating the working capacity of the employee. And moreover, the pre-stored data set is stored into the block chain nodes through the block chain technology, so that the data confidentiality and the system safety are enhanced.

In one possible example, the method further comprises: and if the busy-idle state of the at least one employee in the preset time period is an idle state, performing task allocation on the at least one employee according to the employee skill tag database.

Illustratively, in the case of Zhao Liu, which is marked as an idle state during the scheduling period 2022/04/15/7:00 through 2022/04/15/15:00, indicating that a work task may be assigned, the server may assign it with a task according to the employee skill tag database such that the assigned task difficulty is compatible with its work capacity. For example, if the operating condition complexity evaluation index of Zhao Liu is 2, the server will not assign the production task of the high complexity operating condition to it.

Therefore, in this example, task allocation is performed on the staff in the idle state through the staff skill tag database, so that production tasks adaptive to the working capacity of the staff can be intelligently allocated, and the production efficiency can be improved.

It can be seen that, in the embodiment of the present application, a server firstly locks a target production batch through a production batch number, so as to obtain a production batch data set corresponding to the target production batch, where the production batch data set respectively counts work data of employees in the target production batch from multiple dimensions, such as resource consumption cost, equipment efficiency, product quality, work order man-hour, attendance, and the like, so as to update a target database according to the production batch data set, and finally determines an employee skill tag database according to the target database, where the employee skill tag database is used to indicate a working capacity and a busy-idle state of the at least one employee. Therefore, the server analyzes the working data of the staff in multiple dimensions through statistics and is based on intelligent and automatic processing procedures, so that the finally output evaluation result of the working capacity of the staff is more accurate, and the use experience of the user is improved.

In accordance with the embodiment shown above, please refer to fig. 10a, fig. 10a is a block diagram of functional units of a data processing apparatus for a database according to an embodiment of the present application, the apparatus is applied to a server, and as shown in fig. 10a, the data processing apparatus 100 for a database includes: an obtaining unit 1001, configured to obtain at least one production batch number corresponding to a target product, where the at least one production batch number includes a target production batch number, the target production batch number corresponds to a target production batch one to one, and the target production batch corresponds to at least one employee; an updating unit 1002, configured to update a target database according to a target production batch data set corresponding to the target production batch number, where the target production batch data set is used to indicate various types of work data of the at least one employee in the target production batch, where the various types of work data include at least one of: resource consumption cost data, equipment efficiency data, product quality data, work order and work time data and staff attendance data; a determining unit 1003, configured to determine, according to the updated target database, an employee skill tag database, where the employee skill tag database is used to indicate the working capacity and the busy/idle state of the at least one employee.

In a possible example, the target production lot corresponds to at least one production device, the target database includes a resource consumption cost database, the resource consumption cost database is used for indicating the consumption amount of each cost resource in the target production lot, and in the updating of the target database according to the target production lot data set corresponding to the target production lot number, the updating unit 1002 is specifically configured to: acquiring the process starting time, the process ending time and the resource consumption corresponding to the at least one production device according to the target production batch number; and updating the resource consumption cost database according to the process starting time, the process ending time and the resource consumption corresponding to the at least one production device.

In a possible example, the target database includes a device efficiency database, the device efficiency database is used for indicating the work efficiency of the at least one production device under the operation of the at least one employee, and in the aspect of updating the target database according to the target production batch data set corresponding to the target production batch number, the updating unit 1002 is specifically configured to: acquiring the charging time, the material reaction time and the discharging time corresponding to the at least one production device according to the target production batch number; and updating the equipment efficiency database according to the process starting time, the process ending time, the charging time, the material reaction time and the discharging time corresponding to the at least one piece of production equipment.

In a possible example, the target database includes a product quality database, the product quality database is configured to indicate quality parameter indicators of the target product in the target production lot, and in the aspect of updating the target database according to the target production lot data set corresponding to the target production lot number, the updating unit 1002 is specifically configured to: acquiring an intermediate material index value and a product index value corresponding to the at least one production device according to the target production batch number; and updating the product quality database according to the process starting time, the process ending time, the intermediate material index value and the product index value corresponding to the at least one production device.

In a possible example, the target database includes a work order work-hour database, the work order work-hour database is used to indicate work order data corresponding to the target production lot, and in the aspect of updating the target database according to the target production lot data set corresponding to the target production lot number, the updating unit 1002 is specifically configured to: acquiring at least one employee number according to the target production batch number, wherein the at least one employee number corresponds to the at least one employee one by one; acquiring at least one work order starting time and at least one work order ending time according to the at least one employee number; and updating the work order working hour database according to the corresponding flow starting time, flow ending time, the at least one work order starting time and the at least one work order ending time of the at least one production device.

In one possible example, the target database includes an employee attendance database, the employee attendance database is configured to indicate attendance data of the at least one employee, and in terms of updating the target database according to the target production lot data set corresponding to the target production lot number, the updating unit 1002 is specifically configured to: obtaining the name of the at least one employee, and a leave asking state and a production task state of the at least one employee within a preset time period according to the at least one employee number, wherein the leave asking state at least comprises one of the following states: the production task state comprises a locked state and an unlocked state; if the production task state of the at least one employee in the preset time period is the locking state, marking the scheduling state of the at least one employee in the preset time period as locked; if the production task state of the at least one employee in the preset time period is the unlocked state, marking the scheduling state of the at least one employee in the preset time period as unlocked; and updating the employee attendance database according to the name of the at least one employee, the leave-on state of the at least one employee within a preset time period and the scheduling state of the at least one employee within the preset time period.

In one possible example, in terms of determining the employee skill tag database according to the updated target database, the determining unit 1003 is specifically configured to: determining a cost score for the at least one employee according to the updated resource consumption cost database; determining a device operation score of the at least one employee according to the updated device efficiency database; determining a product quality score for the at least one employee according to the updated product quality database; determining the labor intensity evaluation index of the at least one employee according to the updated work order and work hour database; determining a busy-free state of the at least one employee within a preset time period according to the updated work order work time database and the updated employee attendance database, wherein the busy-free state comprises a busy state and an idle state; and determining the staff skill tag database according to the cost score, the equipment operation score, the product quality score, the labor intensity evaluation index and the busy/idle state of the at least one staff.

In one possible example, the data processing apparatus 100 for a database is further configured to: and if the busy-idle state of the at least one employee in the preset time period is an idle state, performing task allocation on the at least one employee according to the employee skill tag database.

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. 10b, fig. 10b is a block diagram of a functional unit of another data processing apparatus for a database provided in an embodiment of the present application. In fig. 10b, the data processing apparatus 101 for a database includes: a processing module 1012 and a communication module 1011. The processing module 1012 is used for controlling and managing actions of the data processing apparatus with respect to the database, for example, performing the steps of the acquisition unit 1001, the updating unit 1002, and the determining unit 1003, and/or other processes for performing the techniques described herein. The communication module 1011 is used to support interaction between the data processing apparatus for the database and other devices. As shown in fig. 10b, the data processing apparatus for a database may further include a storage module 1013, and the storage module 1013 is used for storing program codes and data of the data processing apparatus for a database. The database-directed data processing apparatus 101 may be the aforementioned database-directed data processing apparatus 100.

The Processing module 1012 may be a Processor or a controller, 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 execute the various illustrative logical blocks, modules, and circuits described in connection with the disclosure herein. The processor may also be a combination of computing functions, e.g., comprising one or more microprocessors, DSPs, and microprocessors, and the like. The communication module 1011 may be a transceiver, an RF circuit or a communication interface, etc. The storage module 1013 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 101 for a database may perform the data processing method for a database shown in fig. 2.

The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. The procedures or functions according to the embodiments of the present application are wholly or partially generated when the computer instructions or the computer program are loaded or executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire or wirelessly. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more collections of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.

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

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.

It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

In the several embodiments provided in the present application, it should be understood that the disclosed method, apparatus and system may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative; for example, the division of the unit is only a logic function division, and there may be another division manner in actual implementation; for example, various elements or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical 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 invention may be integrated into one processing unit, or each unit may be physically included alone, or two or more units may be integrated into one unit. The integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.

The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: u disk, removable hard drive, diskette, optical disk, volatile memory or non-volatile memory. The non-volatile memory may be a read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an electrically Erasable EPROM (EEPROM), or a flash memory. Volatile memory can be Random Access Memory (RAM), which acts as external cache memory. By way of example and not limitation, many forms of Random Access Memory (RAM) are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), synchronous SDRAM (SLDRAM), and direct bus RAM (DR RAM) among various media that can store program code.

Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications can be easily made by those skilled in the art without departing from the spirit and scope of the present invention, and it is within the scope of the present invention to include different functions, combination of implementation steps, software and hardware implementations.

Claims

1. A data processing method for a database is applied to a server, and the method comprises the following steps:

obtaining at least one production batch number corresponding to a target product, wherein the at least one production batch number comprises a target production batch number, the target production batch number corresponds to a target production batch one by one, and the target production batch corresponds to at least one employee;

2. The method of claim 1, wherein the target production lot corresponds to at least one production device, the target database comprises a resource consumption cost database, the resource consumption cost database is used for indicating the consumption of each cost resource in the target production lot, and the updating the target database according to the target production lot data set corresponding to the target production lot number comprises:

acquiring the process starting time, the process ending time and the resource consumption corresponding to the at least one production device according to the target production batch number;

and updating the resource consumption cost database according to the process starting time, the process ending time and the resource consumption corresponding to the at least one production device.

3. The method of claim 2, wherein the target database comprises a device efficiency database for indicating the work efficiency of the at least one production device under the operation of the at least one employee, and wherein updating the target database according to the target production lot data set corresponding to the target production lot number comprises:

Acquiring the charging time, the material reaction time and the discharging time corresponding to the at least one production device according to the target production batch number;

and updating the equipment efficiency database according to the process starting time, the process ending time, the charging time, the material reaction time and the discharging time corresponding to the at least one piece of production equipment.

4. The method of claim 2, wherein the target database comprises a product quality database, the product quality database is used for indicating quality parameter indexes of the target product in the target production batch, and the updating of the target database according to the target production batch data set corresponding to the target production batch number comprises:

acquiring an intermediate material index value and a product index value corresponding to the at least one production device according to the target production batch number;

and updating the product quality database according to the process starting time, the process ending time, the intermediate material index value and the product index value corresponding to the at least one production device.

5. The method as claimed in claim 2, wherein the target database comprises a work order labor hour database, the work order labor hour database is used for indicating the work order data corresponding to the target production lot, and the updating the target database according to the target production lot data set corresponding to the target production lot number comprises:

Acquiring at least one employee number according to the target production batch number, wherein the at least one employee number corresponds to the at least one employee one to one;

acquiring at least one work order starting time and at least one work order ending time according to the at least one employee number;

and updating the work order working hour database according to the corresponding flow starting time, flow ending time, the at least one work order starting time and the at least one work order ending time of the at least one production device.

6. The method of claim 5, wherein the target database comprises an employee attendance database indicating attendance data for the at least one employee, and wherein updating the target database according to the target production lot data set corresponding to the target production lot number comprises:

obtaining the name of the at least one employee, and a leave asking state and a production task state of the at least one employee within a preset time period according to the at least one employee number, wherein the leave asking state at least comprises one of the following states: normally working, vacating and resting, wherein the production task state comprises a locked state and an unlocked state;

If the production task state of the at least one employee in the preset time period is the locking state, marking the scheduling state of the at least one employee in the preset time period as locked;

if the production task state of the at least one employee in the preset time period is the unlocked state, marking the scheduling state of the at least one employee in the preset time period as unlocked;

and updating the employee attendance database according to the name of the at least one employee, the leave-on state of the at least one employee in a preset time period and the scheduling state of the at least one employee in the preset time period.

7. A method according to any one of claims 2 to 6 wherein determining the employee skill tag database from the updated target database comprises:

determining a cost score for the at least one employee based on the updated resource consumption cost database;

determining the equipment operation score of the at least one employee according to the updated equipment efficiency database;

determining a product quality score for the at least one employee based on the updated product quality database;

Determining the labor intensity evaluation index of the at least one employee according to the updated work order and time database;

determining a busy-free state of the at least one employee within a preset time period according to the updated work order work time database and the updated employee attendance database, wherein the busy-free state comprises a busy state and an idle state;

and determining the staff skill tag database according to the cost score, the equipment operation score, the product quality score, the labor intensity evaluation index and the busy/idle state of the at least one staff.

8. The method of claim 7, further comprising:

and if the busy-idle state of the at least one employee in the preset time period is an idle state, performing task allocation on the at least one employee according to the employee skill tag database.

9. A data processing apparatus for a database, applied to a server, the apparatus comprising:

the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring at least one production batch number corresponding to a target product, the at least one production batch number comprises a target production batch number, the target production batch number corresponds to a target production batch one to one, and the target production batch corresponds to at least one employee;

An updating unit, configured to update a target database according to a target production batch data set corresponding to the target production batch number, where the target production batch data set is used to indicate various types of work data of the at least one employee in the target production batch, and the various types of work data include at least one of: resource consumption cost data, equipment efficiency data, product quality data, work order and work time data and staff attendance data;

and the determining unit is used for determining an employee skill tag database according to the updated target database, and the employee skill tag database is used for indicating the working capacity and the busy/idle state of the at least one employee.

10. A server, comprising a processor, memory, a communication interface, and one or more programs stored in the memory and configured to be executed by the processor, the programs including instructions for performing the steps in the method of any of claims 1-8.

11. 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 1-8.