CN115375123A - Resource scheduling method based on factory big data platform - Google Patents
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Abstract
The invention relates to a resource scheduling method based on a factory big data platform, which comprises the steps of constructing a scheduling structure, fusing a corresponding algorithm, selecting a staged selection strategy, adding a population rejection operator, fusing a simplified simulated annealing operation into a bee evolutionary genetic algorithm, and providing an improved bee evolutionary genetic algorithm fused with simulated annealing, so that the global search capability, the search precision and the search process stability of the traditional bee evolutionary algorithm are improved, and meanwhile, the inefficiency of the simulated annealing algorithm is avoided; the method can acquire information of the current transmission system processing equipment in real time while realizing on-line scheduling simulation, acquires scheduling related parameters from a physical space by adopting a twin model, establishes a virtual model based on the basic parameters and generates a scheduling scheme by utilizing a proper optimization algorithm, and carries out simulation synchronous with actual processing by the twin model, thereby providing guidance for physical space decision and avoiding blind trial and error in the actual transmission system.
Description
Technical Field
The invention belongs to the field of data processing, and particularly relates to a resource scheduling method based on a factory big data platform.
Background
Currently, research on smart manufacturing has become a major research direction in the industrial manufacturing field of various countries, which means that the driveline production process will become more intelligent. The production scheduling problem is one of the key research problems in the manufacturing industry, the scheduling problem should be developed towards intellectualization in a new production mode, and meanwhile, the scheduling process should have stronger anti-jamming capability and stability along with the improvement of the diversity degree of transmission system resources. Scheduling problems come from different areas such as computer technology, communication, logistics distribution, logistics management, etc. The scheduling problem has a common feature in these fields that it is difficult to find an effective algorithm to solve the problem in the scope of the constraint set. For a long time, genetic Algorithms (GA) have been widely used in solving scheduling problems due to their advantages such as simple principle and high fusion degree with other algorithms. However, in practical application, a simple genetic algorithm has the disadvantages of low efficiency, easy precocity and the like, which runs counter to the increasing requirements of intelligent production and the production efficiency of a transmission system, so that the academic world tries to improve the genetic algorithm all the time so as to optimize the performance of solving the scheduling problem, so that the performance index of the algorithm can meet the technical requirements of digital twin
With the continuous development of market economy, the production scale and the production complexity of modern enterprises are continuously improved. The scheduling capability in the production process of the transmission system marks the strength of the enterprise management capability and the production optimization capability of the manufacturing system. The efficient scheduling algorithm can fully utilize the production resources of the transmission system, and meanwhile, the efficient scheduling algorithm can enable the production system to maintain efficient and stable production order. The main purpose of the transmission system scheduling is to reasonably arrange the processing sequence under the condition of production constraint, thereby reducing the production time and realizing the optimization of the production target. In an actual part production process, the types of transmission system resources are many (for example, parts, machining equipment, personnel and the like), which causes that parameters related to production scheduling have diversity (for example, machining equipment performance, part machining processes, machining time of each process, equipment energy consumption and the like), and a system needs to be capable of accurately acquiring corresponding data in a current scheduling state in a scheduling process so as to realize transmission system scheduling. In addition, various scheduling parameters and objective constraints can be changed in real time during the production process of the transmission system (such as work order changes and equipment performance adjustment).
Various abnormal conditions can occur in the scheduling process, such as production equipment downtime, operator error, order change and the like, the deviation between the actual production process and the scheduling expectation scheme can be caused by the conditions, and the system can automatically make corresponding adjustment according to the change at the moment. If the physical entity can be modeled informationally, simulation optimization control is carried out on the information model, the model feeds a simulation result back to the field of the transmission system to guide the transmission system to process, the information-driven physical model is realized, and blind trial and error management and control on the field of the transmission system are not needed, so that the production efficiency can be improved to a great extent. The introduction of the digital twin concept in the driveline dispatch process can help us to solve such problems well. The scheduling process is divided into a physical part and a virtual part by fusing the production process and the idea of virtual-real evolution in the digital twin.
Due to the relative insufficiency of the simulation capability and the visualization degree, the capability of coping with dynamic abnormity in the production scheduling process and the decision-making capability of the system are low, and a user cannot intuitively acquire various hot spot information in the scheduling process and can only obtain a simple scheduling result.
Disclosure of Invention
Aiming at the defects faced by the current transmission system management system, the invention requests to protect a resource scheduling method based on a factory big data platform, which is characterized by comprising the following steps:
adopting an improved bee evolutionary genetic algorithm of fusion simulated annealing, setting a Hamming distance optimization initialization population, adopting a staged selection strategy in selection operation, adding a population rejection operator into the algorithm, and fusing the simplified simulated annealing operation into the bee evolutionary genetic algorithm;
constructing a digital twin transmission system scheduling management system architecture based on WEB development, and designing a transmission system scheduling management system by fusing a digital twin thought and an algorithm based on the architecture;
the method comprises the steps of developing and testing a core function module of the system, wherein the development and testing comprises management and maintenance of personnel information of the transmission system, storage of scheduling information parameters and generation of a scheduling scheme, management of equipment and sensor data, transmission system visual management based on digital twins and online scheduling simulation integrated with the digital twins idea.
Further, the above improved bee evolutionary genetic algorithm using fusion simulated annealing sets hamming distance optimization initialization population, adopts a staged selection strategy in selection operation, adds a population rejection operator to the algorithm, and fuses the simplified simulated annealing operation into the bee evolutionary genetic algorithm, further comprising:
constructing a JSP problem model, including the construction of a scheduling constraint condition and a scheduling digital model;
improving the bee evolution genetic algorithm, selecting and crossing, and crossing two parents according to a certain rule to generate two filial generations different from the parents;
mutation operation, namely, randomly selecting two pairs of genes, and exchanging the sequence of each pair of selected genes to form a new genotype;
discarding the population and simulating annealing operation to obtain a local optimal solution;
and selecting a target function and setting parameters by adopting a SABIBEGA algorithm, and verifying and simulating.
Further, the constructing of a digital twin transmission system scheduling management system architecture based on WEB development, and based on the architecture, designing a transmission system scheduling management system by fusing digital twin ideas and algorithms, further comprises:
the simple three-dimensional simulation of the transmission system is realized by building a twin body through the production information modeling and the light-weight 3D modeling of the transmission system, and the real-time hot data of the selected production equipment, including the running state of the machine, is displayed in a front-end interface in a chart form, so that the visual monitoring of the production process of the operation transmission system is realized;
providing a function of optimizing and scheduling according to constraints such as equipment capacity, order requirements and the like, giving a better production and processing sequence through the function, and guiding the subsequent production scheduling of the transmission system by a user according to feedback data so as to achieve the goal of production optimization of the transmission system;
for the three-dimensional virtual simulation of the scheduling process, a user can realize the visual management of the scheduling process through the three-dimensional simulation process and the scheduling information generated in the process;
scheduling simulations are performed for production scales where current drive trains do not exist, and the simulation results are used to guide future development of the drive trains.
Further, the developing and testing of the core function module of the system includes management and maintenance of personnel information of the transmission system, storage of scheduling information parameters and generation of scheduling schemes, management of equipment and sensor data, transmission system visualization management based on digital twin and online scheduling simulation integrated with digital twin thought, and also includes:
selecting a sensor according to the screening form, and displaying related data acquired by the selected sensor in an interface in a diagram form by the system;
personal basic information such as names, job numbers, job grades and the like of login users are displayed in a table form, and the personal basic information can be added, deleted, modified and checked according to actual conditions;
performing real-time simulation according to the real-time processing information and the historical information of the equipment, and performing timely correction or production verification on an abnormal result in the production process through a simulation result;
the method comprises the steps that light-weight 3D modeling is carried out through 3Dmax to achieve simple three-dimensional simulation of elements of a transmission system of the transmission system, information modeling is carried out through real-time production information collected by a sensor and equipment history information stored in a system background to construct twin models, one-to-one correspondence between physical equipment and the twin models is achieved, a data collection system feeds back collected real-time data of a production line to the twin models, the modules dynamically update the twin models based on the received real-time data, and visual display of the front ends of the three-dimensional models is achieved through three.
The improved bee evolution genetic algorithm fusing simulated annealing is provided, the global search capability, the search precision and the search process stability of the traditional bee evolution algorithm are improved, and meanwhile, the inefficiency of the simulated annealing algorithm is avoided; the method can acquire information of the current transmission system processing equipment in real time while realizing on-line scheduling simulation, acquires scheduling related parameters from a physical space by adopting a twin model, establishes a virtual model based on the basic parameters and generates a scheduling scheme by utilizing a proper optimization algorithm, and carries out simulation synchronous with actual processing by the twin model, thereby providing guidance for physical space decision and avoiding blind trial and error in the actual transmission system. And (4) modeling and predicting problems which may occur actually through deviation of actual production and prediction, and performing simulation control and adjustment.
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In order to more clearly illustrate the embodiments of the present invention 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, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flowchart of a resource scheduling method based on a factory big data platform according to the present invention;
fig. 2 is a flowchart of a first embodiment of a resource scheduling method based on a factory big data platform according to the present invention.
Detailed Description
The illustrative embodiments of the present application include, but are not limited to, a workflow diagram of a factory big data platform based resource scheduling method.
It is understood that, as used herein, the term; a module; a unit; may refer to or comprise an Application Specific Integrated Circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and/or memory that execute one or more software or firmware programs, a combinational logic circuit, and/or other suitable hardware components that provide the described functionality, or may be part of these hardware components.
It is to be appreciated that in various embodiments of the present application, the processor may be a microprocessor, a digital signal processor, a microcontroller, or the like, and/or any combination thereof. According to another aspect, the processor may be a single-core processor, a multi-core processor, the like, and/or any combination thereof.
It is to be appreciated that the workflow diagrams of a factory big data platform based resource scheduling method provided herein can be implemented on a variety of electronic devices, including but not limited to, a server, a distributed server cluster of multiple servers, a cell phone, a tablet computer, a laptop computer, a desktop computer, a wearable device, a head-mounted display, a mobile email device, a portable game console, a portable music player, a reader device, a personal digital assistant, a virtual reality or augmented reality device, a television with one or more processors embedded or coupled therein, and the like.
Referring to fig. 1, the present invention requests to protect a resource scheduling method based on a factory big data platform, which is characterized by comprising:
adopting an improved bee evolutionary genetic algorithm of fusion simulated annealing, setting a Hamming distance optimization initialization population, adopting a staged selection strategy in selection operation, adding a population rejection operator into the algorithm, and fusing the simplified simulated annealing operation into the bee evolutionary genetic algorithm;
constructing a digital twin transmission system scheduling management system architecture based on WEB development, and designing a transmission system scheduling management system by fusing a digital twin thought and an algorithm based on the architecture;
and developing and testing a core function module of the system, wherein the development and testing comprises management and maintenance of personnel information of the transmission system, storage of scheduling information parameters, generation of a scheduling scheme, management of equipment and sensor data, visual management of the transmission system based on digital twins and online scheduling simulation integrated with a digital twins idea.
Further, referring to fig. 2, the above improved bee evolutionary genetic algorithm using fusion simulated annealing sets hamming distance optimization to initialize populations, adopts a staged selection strategy in the selection operation, adds a population discarding operator to the algorithm, and fuses the simplified simulated annealing operation into the bee evolutionary genetic algorithm, which further includes:
constructing a JSP problem model, including the construction of a scheduling constraint condition and a scheduling digital model;
improving a bee evolution genetic algorithm, selecting and crossing, and crossing two parents according to a certain rule to generate two filial generations different from the parents;
mutation operation, namely, randomly selecting two pairs of genes, and exchanging the sequence of each pair of selected genes to form a new genotype;
discarding the population and simulating annealing operation to obtain a local optimal solution;
and selecting a target function and setting parameters by adopting a SABIBEGA algorithm, and verifying and simulating.
In the primary stage of the production system, the transmission system does not need to allocate production resources to meet production requirements because the production resources are in a sufficient state in this stage. The concept of scheduling is proposed after the advent of large-scale production systems, meaning that existing production resources are reasonably arranged to meet certain production goals, typically with the goals of shortest completion time, most balanced production line loads, or least consumption of production resources. According to different production methods, the traditional transmission system production scheduling problem is generally divided into two problems of job transmission system scheduling (JSP) and flow-transmission system scheduling (FSP), and in this document, we focus on the JSP problem, so that mathematical modeling needs to be performed on the JSP problem to meet basic conditions of intelligent scheduling. The conventional static JSP problem can be described as that for n workpieces to be machined, each workpiece contains k machining processes in total, m devices are used in the transmission system for machining the batch of workpieces, and certain constraint conditions exist in the machining process:
1) When the processing process is just started, any equipment has the possibility of being selected;
2) Each workpiece is machined at most once using each apparatus;
3) The process of each workpiece must be completed on a designated device;
4) One device can only carry out processing operation on one workpiece at a time;
5) The next procedure of the workpiece can be carried out only after the previous procedure is finished;
6) -the machining work cannot be interrupted once it has started;
7) When the task is completed, each process of all the workpieces must be completed;
8) No new operation is added in the processing process, and the existing operation processing flow can not be cancelled;
according to the constraint conditions, the problem to be researched is that on the premise that the constraint conditions are met, a scheduling algorithm provides a reasonable optimization scheme through continuous iteration, the processing sequence of each processing workpiece on each processing device is determined, and finally the optimal production time is obtained.
Selecting a strategy for adjusting the population scale in stages to realize selection operation, namely dividing the searching process of the algorithm into a plurality of stages, gradually increasing the Y value along with the evolution stage, setting an operation algebra in the algorithm as gen, setting a stage adjusting parameter as s, and initializing a random population scale parameter to enable a random population generated by the P generation to meet the following conditions:
a cross operator POX parent chromosome based on process coding is set as PI and P2, filial generations generated after POX operation are Childrenl and Children2, and the specific process is as follows:
1. the workpiece set is randomly divided into {1,2, 3.., 11} two non-empty subsets J1, J2.
2. Workpieces with P1 contained in J1 are copied to Childrenl, and workpieces with P2 contained in J2 are copied to Childrenl 2, while their positions are retained.
3. The artifacts that P1 contains in J2 are copied to Children2, and the artifacts that P2 contains in J1 are copied to Childrenl, while preserving their order.
In SABIBEGA, only P1 or P2 needs to be replaced by the optimal individual in each iteration.
Introduction of a population discard operator alpha in the SABIBEGA algorithm 0 After the selection, crossing and mutation operations are finished, the Hamming distance HD between the common male peak j and the Queen is calculated jQ If it satisfies formula HD jQ >α 0 The male peak is retained, otherwise it is discarded from the population and a new male peak is introduced in a randomly generated manner. The introduction of new bees further increases the biodiversity of the bee colony, so that the capability of the algorithm for breaking the local optimal dilemma is greatly improved.
The specific flow of the SABIBEGA algorithm comprises the following steps:
(1) The algorithm starts, an initial population P (0) with the scale of N is generated after initialization operation, and an evolution algebra g =0 is set;
and recording the optimal individuals in the initialized population as queens.
(2) And judging whether the stopping criterion is met, if so, outputting the current solution as the optimal solution, and otherwise, continuing. (3) let evolution algebra g = g + l.
(4) And (3) selecting, crossing, mutating, discarding the population and simulating annealing operation to generate a new population N (g). (5) And respectively calculating the individual fitness of N (g), and recording the optimal individual as a new bee. And if the fitness of the new queen bee is greater than that of the original queen bee, the new population N (g) is the g-th generation population P (g), otherwise, the original queen bee is used for replacing the worst individual in the new population to obtain P (g).
(6) And (3) turning to the step (2).
Further, the constructing a digital twin transmission system scheduling management system architecture based on WEB development, and designing a transmission system scheduling management system by fusing digital twin ideas and algorithms based on the architecture, further includes:
the simple three-dimensional simulation of the transmission system is realized by building a twin body through the production information modeling and the light-weight 3D modeling of the transmission system, and the real-time hot data of the selected production equipment, including the running state of the machine, is displayed in a front-end interface in a chart form, so that the visual monitoring of the production process of the operation transmission system is realized;
providing a function of carrying out optimized scheduling according to constraints such as equipment capacity, order requirements and the like, giving a better production and processing sequence through the function, and guiding the subsequent production scheduling of the transmission system by a user according to feedback data so as to achieve the goal of production optimization of the transmission system;
for the three-dimensional virtual simulation of the scheduling process, a user can realize the visual management of the scheduling process through the three-dimensional simulation process and the scheduling information generated in the process;
and performing scheduling simulation on the production scale where the current transmission system does not exist, and guiding the future development of the transmission system by using the simulation result.
The method comprises the steps of selecting a front-end and back-end separation technology, writing background system codes by using Java development language, and realizing the functions of persistence and service logic of the back end by using Springboot, springMVC and Mybatis (SSM) technologies. The back-end program is divided into an application layer, a logical layer and a data layer, the coding amount can be greatly reduced by the design, and meanwhile, the existence of the MVC design mode ensures the normative and the reusability of components, and the expansion of system functions is facilitated. The front-end interface design adopts a Vue framework to separate the front end from the back end, so that the relative independence of front-end codes and back-end codes is ensured, the system maintenance is facilitated, and the front-end and back-end interaction is realized by utilizing an axios library. The system is designed in a B/S mode, so that an operator can directly remotely access the system by using various browsers which are currently mainstream. Packaging of the database is achieved in Mybatis, real-time data are obtained through field sensing equipment of a transmission system, the real-time data are delivered to the database designed for the transmission system in a reasonable data transmission mode to achieve storage, and management functions of personnel, equipment and scheduling parameter information are achieved on the basis. And remote video monitoring of the transmission system on site is realized by combining a remote camera with WEB development. A digital twin functional module of the system realizes 3D lightweight modeling of the running state of a production transmission system by using a three.js framework under a WebGL protocol, and realizes real-time display of hot spot data in the production process by interconnection and intercommunication of an Echarts framework and a background database.
The acquisition function is realized by a large amount of sensor equipment arranged in a transmission system, most sensors are arranged in a punching machine at present in a manufacturing and molding transmission system, so that the acquisition function of real-time data of the equipment is realized by arranging a large amount of sensors in the punching equipment, and the data acquired by the sensors are finally stored by a data storage module. The current transmission strategy is to send sensor data at certain time intervals. The sensors deployed on the device mainly include a three-phase electric sensor, a temperature sensor, an air pressure sensor, and the like. In order to facilitate the expansion of the subsequent sensor types, the system adopts a JSON format to realize data transmission.
Further, the developing and testing of the core function module of the system includes management and maintenance of personnel information of the transmission system, storage of scheduling information parameters and generation of scheduling schemes, management of equipment and sensor data, transmission system visualization management based on digital twin and online scheduling simulation integrated with digital twin thought, and also includes:
selecting a sensor according to the screening form, and displaying related data acquired by the selected sensor in an interface by a system in a chart form;
personal basic information such as names, job numbers, job grades and the like of login users are displayed in a table form, and the personal basic information can be added, deleted, modified and checked according to actual conditions;
performing real-time simulation according to the real-time processing information and the historical information of the equipment, and performing timely correction or production verification on an abnormal result in the production process through a simulation result;
the method comprises the steps that light 3D modeling is carried out through 3Dmax to achieve simple three-dimensional simulation of elements of a transmission system of the transmission system, information modeling is carried out through real-time production information collected by a sensor and device history information stored in a system background to build a twin model, one-to-one correspondence between physical devices and the twin model is achieved, a data collection system feeds back collected real-time data of a production line to the twin model, the module dynamically updates the twin model based on the received real-time data, and front end visual display of the three-dimensional model is achieved through three.
The information modeling of the digital twin transmission system based on 3dmax and the loading of the model based on three. The information model of the digital twin transmission system mainly relates to transmission system information, processing equipment information, processing workpiece information, personnel information and the like of the transmission system, and finally, the mirror image relationship between the physical entities of the transmission system and the geometric attributes such as the shape, the size, the placement position and the like of the model is realized, so that each model is provided with corresponding codes so as to realize the association with the physical entities. The production line information modeling generally adopts three-dimensional visual modeling, the modeling mode of a product information model is relatively mature, a process information model is used as a data model, a geometric design part does not exist, the main purpose is to construct the data model through input and output data, a processing flow and the like of a production process, so that data support is provided for subsequent simulation analysis, scheduling analysis and the like, and the construction is generally realized through a system data layer through a plug-in of an information modeling tool.
The production line information modeling generally adopts three-dimensional visual modeling, and three-dimensional physical solid model mapping is also a technical standard of digital twinning. 3D modeling software commonly used in the past \23428comprisesSolidWorks, catia and the like, but model redundancy can be caused by the problems of modeling operation and resolution requirements of the software, so that 3Dmax is selected as modeling software. With the continuous progress and development of 3D visualization technology, complex 3D applications and models are being gradually applied to Web browsers that we use daily, which makes 3D visualization research 23428based on WebGL and html5 go deeper and deeper. WebGL is a JavaScript-based programming interface, which can realize the visualization of a 2D or 3D model in a Web browser supporting html5, but because of certain limitations, the difficulty of directly using a WebGL module to construct a three-dimensional scene is high and the realization process is complicated, so that three.js comes from now, the WebGL is a high-level open source program library for encapsulating the WebGL, the WebGL can create and plant and dye a three-dimensional scene in the Web browser through three main components (scene, camera, render), and the scene is essentially a three-dimensional space and is also a container of the model; the cameras have different types and camera parameters, and determine the presented scene; render operation is performed by render to map the three-dimensional object into the two-dimensional browser.
Monitoring abnormal events of the transmission system, wherein the function has the main significance of monitoring dynamic abnormal events occurring in the production process of the transmission system. The sensor is arranged on the site to acquire real-time data, the real-time data is compared with historical equipment operation information recorded by the system, if some indexes of the equipment are abnormal, the system can quickly monitor the abnormality and give related abnormal information, and a manager can timely feed the abnormal information back to the site transmission system after learning the abnormal conditions through the system to guide the current production decision change or the maintenance of workers. When the specific implementation form is that one abnormal condition monitoring button is arranged in a three-dimensional visual monitoring module, a log can be popped up by the system after the button is clicked, the type of the abnormal event, the specific condition description of the abnormal event, the time point of the occurrence of the abnormal event and whether the abnormality is processed or not are recorded in a tabular form, if the abnormality of the equipment is not processed, the implementation operation state displayed after the equipment is selected can be changed from normal state operation to abnormal state operation, and a manager can arrange the on-site abnormal processing work of the transmission system through the log.
It should be noted that, in the embodiments of the apparatuses in the present application, each unit/module is a logical unit/module, and physically, one logical unit/module may be one physical unit/module, or may be a part of one physical unit/module, and may also be implemented by a combination of multiple physical units/modules, where the physical implementation manner of the logical unit/module itself is not the most important, and the combination of the functions implemented by the logical unit/module is the key to solve the technical problem provided by the present application. Furthermore, in order to highlight the innovative part of the present application, the above-mentioned device embodiments of the present application do not introduce units/modules which are not so closely related to solve the technical problems presented in the present application, which does not indicate that no other units/modules exist in the above-mentioned device embodiments.
It is noted that, in the examples and descriptions of the present application, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the term; comprises the following steps of; comprises the following components; or any other variation thereof, is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, by a statement; comprises one; a defined element does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the defined element.
While the present application has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present application.
Claims (4)
1. A resource scheduling method based on a factory big data platform is characterized by comprising the following steps:
the improved bee evolutionary genetic algorithm of fusion simulated annealing is adopted, hamming distance optimization initialization population is set, a staged selection strategy is adopted in selection operation, a population rejection operator is added into the algorithm, and the simplified simulated annealing operation is fused into the bee evolutionary genetic algorithm;
constructing a digital twin transmission system scheduling management system architecture based on WEB development, and designing a transmission system scheduling management system by fusing a digital twin thought and an algorithm based on the architecture;
the method comprises the steps of developing and testing a core function module of the system, wherein the development and testing comprises management and maintenance of personnel information of the transmission system, storage of scheduling information parameters and generation of a scheduling scheme, management of equipment and sensor data, transmission system visual management based on digital twins and online scheduling simulation integrated with the digital twins idea.
2. The resource scheduling method based on the factory big data platform as claimed in claim 1, wherein the improved bee evolutionary genetic algorithm using fusion simulated annealing sets hamming distance optimization initialization population, adopts a staged selection strategy in the selection operation, adds population rejection operator to the algorithm, and fuses the simplified simulated annealing operation into the bee evolutionary genetic algorithm, further comprising:
constructing a JSP problem model, including the construction of a scheduling constraint condition and a scheduling digital model;
improving a bee evolution genetic algorithm, selecting and crossing, and crossing two parents according to a certain rule to generate two filial generations different from the parents;
mutation operation, namely, randomly selecting two pairs of genes, and exchanging the sequence of each pair of selected genes to form a new genotype;
discarding the population and simulating annealing operation to obtain a local optimal solution;
and selecting a target function and setting parameters by adopting a SABIBEGA algorithm, and verifying and simulating.
3. The method for scheduling resources based on a factory big data platform according to claim 1, wherein a digital twin transmission system scheduling management system architecture based on WEB development is constructed, and a transmission system scheduling management system is designed by fusing a digital twin thought and an algorithm based on the architecture, and further comprising:
the simple three-dimensional simulation of the transmission system is realized by building a twin body through the production information modeling and the light-weight 3D modeling of the transmission system, and the real-time hot data of the selected production equipment, including the running state of the machine, is displayed in a front-end interface in a chart form, so that the visual monitoring of the production process of the operation transmission system is realized;
providing a function of optimizing and scheduling according to constraints such as equipment capacity, order requirements and the like, giving a better production and processing sequence through the function, and guiding the subsequent production scheduling of the transmission system by a user according to feedback data so as to achieve the goal of production optimization of the transmission system; for the three-dimensional virtual simulation of the scheduling process, a user can realize the visual management of the scheduling process through the three-dimensional simulation process and the scheduling information generated in the process;
scheduling simulations are performed for production scales where current drive trains do not exist, and the simulation results are used to guide future development of the drive trains.
4. The resource scheduling method based on the factory big data platform as claimed in claim 1, wherein the developing test for the core function module of the system, including the management and maintenance of personnel information of the transmission system, the generation of the storage and scheduling scheme of the scheduling information parameters, the management of the equipment and sensor data, the visual management of the transmission system based on the digital twin and the online scheduling simulation integrated with the idea of the digital twin, further comprises:
selecting a sensor according to the screening form, and displaying related data acquired by the selected sensor in an interface by a system in a chart form;
personal basic information such as names, job numbers, job grades and the like of login users are displayed in a table form, and the personal basic information can be added, deleted, modified and checked according to actual conditions;
performing real-time simulation according to the real-time processing information and the historical information of the equipment, and performing timely correction or production verification on an abnormal result in the production process through a simulation result;
the method comprises the steps that light-weight 3D modeling is carried out through 3Dmax to achieve simple three-dimensional simulation of elements of a transmission system of the transmission system, information modeling is carried out through real-time production information collected by a sensor and equipment history information stored in a system background to construct twin models, one-to-one correspondence between physical equipment and the twin models is achieved, a data collection system feeds back collected real-time data of a production line to the twin models, the modules dynamically update the twin models based on the received real-time data, and visual display of the front ends of the three-dimensional models is achieved through three.
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| CN116703321B (en) * | 2023-06-09 | 2023-11-21 | 北京市永康药业有限公司 | Pharmaceutical factory management method and system based on green production |
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