CN116912027A - Auxiliary method and system for tobacco production - Google Patents

Abstract

The disclosure provides an auxiliary method and system for tobacco production, and relates to the technical field of tobacco production, wherein the method comprises the following steps: determining optimal parameters of process parameters adopted by the current process according to use data and a parameter recommendation model of the current process of tobacco production, and recommending the optimal parameters to a user, wherein the use data comprises a plurality of batch data, energy data and equipment data, the process parameters comprise at least one of environment parameters and material parameters, the parameter recommendation model is generated based on historical data of production data, and the production data comprises the use data and the process parameters; checking production data of the current process before the current process is executed; after the verification is passed, dispatching the production task of the current process according to the production data of the current process; and after the current process is finished, forming a production report of the current process according to the production data of the current process.

Description

Auxiliary method and system for tobacco production

Technical Field

The disclosure relates to the technical field of tobacco production, in particular to an auxiliary method and system for tobacco production.

Background

The industrial internet is a product of a fusion of information technology with industrial production. The information technology is applied to the field of industrial production, so that the yield and quality of products can be effectively improved. The tobacco production process can be monitored and analyzed by means of the industrial Internet platform to assist in tobacco production, and the method is greatly helpful for improving the yield and quality of tobacco.

Disclosure of Invention

The production data involved in the tobacco production process are various and wide in source, the existing industrial Internet platform lacks a unified and efficient data acquisition method, a data sharing method and a data display mechanism when being applied to the auxiliary of tobacco production, the production coordination among all production links is difficult to achieve, and the monitoring and analysis of the production conditions are difficult.

In order to solve the above problems, the embodiments of the present disclosure provide the following technical solutions.

According to an aspect of the embodiments of the present disclosure, there is provided a tobacco production assisting method including: determining optimal parameters of process parameters adopted by a current process of tobacco production according to use data and a parameter recommendation model of the current process, and recommending the optimal parameters to a user, wherein the use data comprises a plurality of batch data, energy data and equipment data, the process parameters comprise at least one of environment parameters and material parameters, the parameter recommendation model is generated based on historical data of production data, and the production data comprises the use data and the process parameters; checking the production data of the current process before the current process is executed; after the verification is passed, dispatching a production task of the current process according to the production data of the current process; and after the current process is finished, forming a production report of the current process according to the production data of the current process.

In some embodiments, the method further comprises: and in the current process, analyzing the production data according to a production plan and a production schedule, and sending out early warning information when the production data is abnormal.

In some embodiments, the analyzing the production data according to a production plan and a production schedule, and issuing the pre-warning information when the production data is abnormal comprises: obtaining attendance data through an attendance platform, wherein the attendance data comprises post information of staff; determining staff related to abnormal data in the production data according to the post information; and pushing the early warning information to staff related to the abnormal data through the attendance platform.

In some embodiments, the method further comprises: and controlling at least one production device related to the abnormal data in the current process according to the abnormal data in the production data.

In some embodiments, the production task includes an operation requiring personnel to perform during the current process, the method further comprising: and obtaining an execution result of the operation, wherein the execution result comprises one of on-time completion, overtime completion and unexecuted.

In some embodiments, the method further comprises: one or more of the energy data, the equipment data and the process parameters are obtained from an electronic control system for tobacco production via an object connection and embedding interface for process control connected to the electronic control system.

In some embodiments, said verifying said production data of said current process comprises: and verifying the production data of the current process by utilizing a data analysis model obtained by training the historical data based on the production data.

In some embodiments, the method further comprises: and sending the production report to a data display platform for display, wherein the production report comprises at least one of quality data, cost data and efficiency data.

In some embodiments, the method further comprises: acquiring alarm information of a video monitoring system for tobacco production; and alarming according to the alarm information.

In some embodiments, the method further comprises: and in the current process, analyzing the production data in real time by using an externally-hung data analysis tool to predict a production result so as to adjust the process parameters according to the production result.

According to a further aspect of embodiments of the present disclosure, there is provided a tobacco production assist system comprising: a recommendation module configured to determine optimal parameters of process parameters employed by a current process of tobacco production according to usage data of the current process and a parameter recommendation model, and recommend the optimal parameters to a user, wherein the usage data includes a plurality of batch data, energy data, and equipment data, the process parameters include at least one of environmental parameters and material parameters, the parameter recommendation model is generated based on historical data of production data, the production data includes the usage data and the process parameters; a verification module configured to verify the production data of the current process before the current process is performed; the dispatching module is configured to dispatch the production task of the current process according to the production data of the current process after the verification is passed; a forming module configured to form a production report of the current process from the production data of the current process after the current process is ended.

According to a further aspect of embodiments of the present disclosure, there is provided a tobacco production assist system comprising: a memory; and a processor coupled to the memory, the processor configured to perform the method of any of the embodiments described above based on instructions stored in the memory.

According to a further aspect of the disclosed embodiments, a computer readable storage medium is provided, comprising computer program instructions, wherein the computer program instructions, when executed by a processor, implement the method according to any of the embodiments described above.

According to a further aspect of the disclosed embodiments, a computer program product is provided, comprising a computer program, wherein the computer program, when executed by a processor, implements the method according to any of the above embodiments.

In the embodiment of the disclosure, the optimal parameters are recommended to the user, the current process is checked, the production task of the current process is distributed through the production data of the tobacco production process, and a production report is formed after the current process is finished. Through the full utilization of the production data, the comprehensive monitoring and analysis of the whole tobacco production process are realized, the production coordination among all production links of the tobacco production is realized in an auxiliary way, and the yield and quality of the tobacco are improved.

The technical scheme of the present disclosure is described in further detail below through the accompanying drawings and examples.

Drawings

In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of 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 disclosure, and other drawings may be obtained according to these drawings without inventive effort to a person of ordinary skill in the art.

FIG. 1 is a schematic flow diagram of a tobacco production assist method according to some embodiments of the present disclosure;

FIG. 2 is a schematic structural view of a tobacco production assist system according to some embodiments of the present disclosure;

FIG. 3 is a schematic illustration of a verification flow interface according to some embodiments of the present disclosure;

FIG. 4 is a schematic structural view of a tobacco production assist system according to further embodiments of the present disclosure;

fig. 5 is a schematic structural view of a tobacco production assist system according to further embodiments of the present disclosure.

Detailed Description

The following description of the technical solutions in the embodiments of the present disclosure will be made clearly and completely with reference to the accompanying drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments in this disclosure without inventive faculty, are intended to fall within the scope of this disclosure.

The relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless it is specifically stated otherwise.

Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.

Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any specific values should be construed as merely illustrative, and not a limitation. Thus, other examples of the exemplary embodiments may have different values.

It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.

Fig. 1 is a flow diagram of a tobacco production assist method according to some embodiments of the present disclosure. Fig. 2 is a schematic structural view of a tobacco production assist system according to some embodiments of the present disclosure. The following describes a tobacco production assistance method of some embodiments of the present disclosure with reference to fig. 1 and 2.

As shown in fig. 1, the auxiliary method of tobacco production includes steps 101 to 107.

In step 101, according to the usage data and the parameter recommendation model of the current process of tobacco production, determining the optimal parameters of the process parameters adopted by the current process, and recommending the optimal parameters to the user. The usage data includes a plurality of lot data, energy data, and equipment data. The process parameters include at least one of environmental parameters and material parameters. The parameter recommendation model is generated based on historical data of production data including usage data and process parameters.

In some embodiments, step 101 is performed by parameter recommendation module 201 in tobacco production assist system 200 as shown in fig. 2.

In some embodiments, there is at least one process in the tobacco production, each process being responsible for one step of the tobacco production. For example, in the tobacco production, there are unpacking, feeding, shredding, drying, flavoring, and the like.

In some embodiments, the tobacco production method is implemented based on an industrial internet platform. The production data is obtained through an industrial internet platform. Such as the thinworx platform.

In some embodiments, the batch data includes at least one of a batch number, a brand number, and a recipe.

In some embodiments, the energy data includes energy delivery from a process of tobacco production. For example, the steam pressure supply of the apparatus, etc.

In some embodiments, the equipment data includes the operation of the tobacco production equipment of the process of tobacco production, i.e., the tobacco production equipment involved in the corresponding procedure of the current process. For example, if the current process is a charging process, the equipment data includes: the leaf storage cabinet is in proportion, the state of a container where the material is located, the state of an electronic scale, the state of a moisture meter, the accumulated flow of the electronic scale, the state of a charging system and the like. The state of the container in which the material is located includes at least one of a high level state, a medium level state, and a low level state. The respective level states are detected by means of sensors mounted in fixed positions of the container.

In some embodiments, as shown in fig. 2, the tobacco production assistance system 200 accesses a database of at least one of the warehouse control system 270 (WMS, warehouse Control System), warehouse management system 280 (WCS, warehouse Management System), and production execution system 290 (MES, manufacturing Execution System) of tobacco production using a Java database connectivity (JDBC, java DataBase Connectivity) method to obtain production data in real time. The method can conveniently and rapidly acquire a large amount of data in real time, realizes data intercommunication among all systems, is beneficial to strengthening coordination and linkage of different systems, and further improves the quality and efficiency of tobacco production.

In some embodiments, the process parameter data is a parameter that can be controlled by a worker. For example, if the current process is a charging process, the process parameter data includes: the material flow, the circulating hot air temperature during operation, the feeding proportion, the frequency of a roller motor during operation, the opening of a tide-discharging air valve, the frequency of a hot air fan during operation, the opening of a steam applying valve and the like.

In some embodiments, the environmental parameter includes at least one, e.g., a plurality, of an ambient temperature and an ambient humidity. In some implementations, as shown in fig. 2, a tobacco production assist system 200 for performing a tobacco production assist method interfaces with an electronic control system 210 of tobacco production in real-time to obtain at least one of an ambient temperature and an ambient humidity of a current process.

In some embodiments, the electronic control system 210 includes a programmable logic controller (PLC, programmable Logic Controller) of the power plant responsible for powering the current process from which ambient temperature and humidity data for the current process is obtained.

In some embodiments, the parameter recommendation model is generated based on historical data of the production data. The step of generating a parameter recommendation model comprises: the use data in the history of the production data is used as input, and the process parameters actually adopted in the history of the production data are used as output training parameter recommendation models. And inputting the use data of the current process into a trained parameter recommendation model to obtain the optimal parameters of the process parameters.

After the optimal parameters are recommended to the user, the user may or may not adopt the recommended optimal parameters to execute the current process.

In some embodiments, as shown in fig. 2, a tobacco production assistance system 200 for performing a tobacco production assistance method obtains historical data through a centralized control system 220 of tobacco production. The centralized control system 220 is a centralized control system for tobacco production. In some embodiments, the centralized control system 220 is an upper computer layer of tobacco production. In some embodiments, the historical data is production data employed by previous batches. For example, where the current process is a charging process, the historical data refers to production data employed in the charging process for a previous batch of tobacco.

In some embodiments, the historical data is obtained through a linked database of structured query language (SQL, structured Query Language) servers. The mode can improve the efficiency of acquiring the historical data.

In some implementations, invalid data in the historical data is filtered to improve accuracy of the analysis results.

In some embodiments, the data in the history data when no material passes through the device is invalid data. For example, before tobacco production, the production equipment is started in advance to preheat, but no material enters the equipment to be processed at the moment, and the historical data generated at the stage is invalid data. For another example, the historical data generated when the production facility has not been shut down after the end of the current process is also invalid data.

In some embodiments, the parameter recommendation model is generated by an industrial internet platform using historical data of production data in combination with worker experience.

In some embodiments, the tobacco-assisted production method further comprises: during the current process, the production data is analyzed in real time by the plug-in data analysis tool 250 as shown in fig. 2 to predict the production results, so as to adjust the process parameters according to the production results. The predicted production result includes, for example, predicting, based on the current production data, a specific parameter of the material processed by the current process at the end of the current process, the specific parameter including a critical parameter of the current process. For example, the current process is a tobacco drying process, and the specific parameter is tobacco shred moisture at the outlet of the tobacco drying device. The specific parameters of the materials processed by the current process should be kept within certain preset ranges. The data analysis tool 250 is used for acquiring the predicted production result in real time, so that related workers can be assisted in adjusting the process parameters in time, and the process parameters can be adjusted, so that the materials processed by the current process meet the quality requirements, and the yield and quality of tobacco can be improved.

In some implementations, the tobacco production assistance system 200 inputs the production data into the data analysis tool 250 via an industrial internet to submit data to a server (POST) method.

In some implementations, the data analysis tool 250 is an xgboost (extreme gradient lifting, extreme gradient boosting) data analysis tool.

In step 103, the production data of the current process is verified before the current process is performed.

The automatic verification of the current technological process of tobacco production is realized by the mode, workers do not need to check all production equipment of the current technological process one by one, the labor cost is reduced, and the production efficiency is improved. The staff can quickly find out the abnormal problems by checking the checking result. Compared with manual verification, the verification result is more stable and reliable, and in addition, the production data which cannot be verified manually can be verified through the mode, so that the quality of tobacco production is improved.

In some embodiments, step 103 is performed by data analysis module 202 in tobacco production assist system 200 as shown in fig. 2.

FIG. 3 is a schematic diagram of a verification interface according to some embodiments of the present disclosure.

In some embodiments, as shown in fig. 3, verification of processes A, B and C is required. For example, the current process is process B, and when verifying production data of the current process, verification is performed separately according to each type of production data. For example, verification is performed separately according to batch data, energy data, equipment data, and process parameters.

In some embodiments, as shown in fig. 3, each type of production data includes one or more items. For example, the batch data includes 3 items, which are batch data 1, batch data 2, and batch data 3, respectively. The process parameters include 5 items, namely a process parameter 1, a process parameter 2, a process parameter 3, a process parameter 4 and a process parameter 5.

In some embodiments, the verification result of each production data includes one of normal, abnormal, and to-be-verified. Only when each production data is in a normal state, the production data of the current process is calculated and checked to pass.

In some embodiments, the current process may be started only if all production data of the current process passes verification, i.e. processing of the material by the current process is started.

In some embodiments, step 103 includes presenting the verification results for each item of data in each type of production data. For example, as shown in fig. 3, the process parameters 1 to 3 are checked to be normal, the process parameter 4 is checked to be abnormal, and the process parameter 5 is checked to be checked.

In some embodiments, step 103 further comprises displaying the proportion of each type of production data passing the verification in terms of percentages. For example, as shown in FIG. 3, the proportion of batch data passing verification is 100%, and the proportion of process parameters passing verification is 60%.

In other embodiments, the number of items that each type of production data passes the verification, the number of items that fail the verification, and the number of items to be verified are displayed. For example, as shown in FIG. 3, the process parameters include 3 pass checks, 1 pass unchecked and 1 pass to be checked.

In some embodiments, when verifying the production data of the current process, the plurality of types of production data are sequentially verified in a preset order. For example, as shown in fig. 3, the verification is sequentially performed in the direction indicated by the arrow, the batch data is verified first, then the energy data is verified, then the equipment data is verified, and finally the process parameters are verified.

In some embodiments, when checking the production data of the current process, if one of the production data fails the check, the current process of tobacco production cannot be started, i.e. the check fails. In this case, it is necessary to wait for the tobacco production system to fail automatically or for the staff to fail and to pass the verification before starting. For example, as shown in fig. 3, if the verification result of the process parameter 4 is abnormal and the verification is not passed, a process is required to make the process parameter 4 pass the verification so as to continue the production.

In step 105, after the verification is passed, the production task of the current process is dispatched according to the production data of the current process.

In some embodiments, the work order dispatch of the production task is automatically triggered after the verification is passed, so as to dispatch the production task to the corresponding production line.

In some embodiments, step 105 is performed by worksheet dispatching module 203 in tobacco production assist system 200 as shown in fig. 2.

In some embodiments, work order information is pushed to the relevant staff members based on the production task. For example, if a certain production task is dispatched to a corresponding production line, information such as the start time and the expected completion time of the production task is pushed to a worker on the production line, so as to remind the worker to start working.

In some implementations, the work order information is pushed through office software.

In some embodiments, the production task includes operations that require personnel to perform during the current process, and the auxiliary method for tobacco production further includes: and obtaining an execution result of the operation, wherein the execution result comprises one of on-time completion, overtime completion and unexecuted.

In some implementations, the operations that require the staff member to perform include requiring the staff member to reach the prescribed location at the prescribed time. And (3) acquiring whether the worker reaches the specified position or not through a sensor at the specified position, and feeding back the acquired point position signals.

In some embodiments, as shown in fig. 2, the work order dispatch module 203 identifies operations that require personnel to perform in the current process based on the SOP (standard job program, standard Operation Procedure) job file of the current process, and automatically dispatches production tasks according to the field environment.

In some embodiments, a reminder is triggered for a production task whose execution results are completed or not executed over time to ensure the execution efficiency of the production task. In some implementations, the reminder is made in the form of a push reminder message. In other implementations, the warning is provided by a warning light, e.g., different colored lights represent different levels of anomalies, and staff handles the anomalies according to the color of the lights. In other implementations, the alert is provided by an alert ring.

In step 107, after the end of the current process, a production report of the current process is formed from the production data of the current process. In some embodiments, each process of each batch forms a corresponding production report.

In some embodiments, step 107 is performed by reporting module 204 in tobacco production assist system 200 as shown in fig. 2.

In the embodiment of the disclosure, the optimal parameters are recommended to the user through the production data of the tobacco production process, the production data of the current process is checked, the production task of the current process is distributed, and a production report is formed after the current process is finished. Through the full utilization of the production data, the comprehensive monitoring and analysis of the whole tobacco production process are realized, the production coordination among all production links of the tobacco production is realized in an auxiliary way, and the yield and quality of the tobacco are improved.

In some embodiments, the tobacco production assistance method further comprises: in the current process, the production data of the current process is analyzed according to the production plan and the production schedule, and early warning information is sent when the production data is abnormal.

The method can ensure normal operation of the production link before the current process is started, can monitor production data in real time in the current process, reports abnormal states of the production data at any time, is convenient for staff to process the abnormality in time, and is beneficial to improving tobacco production efficiency.

In some embodiments, the production data of the current process is monitored in real time through an industrial internet platform, so that sensitive perception and visualization of the production data are realized.

In some embodiments, the production data of the current process is analyzed through a data analysis model, so that the monitoring and abnormality early warning of the current process are realized.

In some embodiments, analyzing the production data according to the production plan and the production schedule, and sending out the pre-warning information when the production data of the current process is abnormal comprises: acquiring attendance data through an attendance platform, wherein the attendance data comprises post information of staff; determining staff related to abnormal data in the production data of the current process according to the post information; and pushing early warning information to staff related to the abnormal data through the attendance platform. The mode can avoid the workers from missing the early warning information, can prevent other workers from being disturbed by the early warning information irrelevant to the working content of the workers, and is beneficial to further improving the tobacco production efficiency.

In some implementations, as shown in fig. 2, the tobacco production assistance system 200 obtains attendance data via an attendance platform 230.

In some implementations, the attendance platform 230 is, for example, an enterprise WeChat.

In some implementations, the early warning information is pushed through an API (application program interface, application Programming Interface). The pushing efficiency can be improved by the mode, and irrelevant people are prevented from being disturbed by early warning information.

In some embodiments, the tobacco production method further comprises: and controlling at least one production device related to the abnormal data in the current process according to the abnormal data in the production data of the current process. According to the mode, the fault of at least one production device can be automatically eliminated, the processing efficiency of the fault of the production device can be improved, and the production line can be enabled to quickly recover production, so that the tobacco production efficiency is improved.

In some embodiments, after the current process is completed, the process parameters of the current process are obtained, the process parameters are compared with the range of historical empirical data obtained according to experience, if the process parameters of the current process deviate from the range of the historical empirical data, the process parameters of the current process are abnormal, and related staff needs to be reminded. For example, counting the accumulated charge amount of the current process, comparing the accumulated charge amount with the accumulated charge amount in the historical experience data, and if the accumulated charge amount is more than the accumulated charge amount, reminding a worker related to the charging step to pay attention to troubleshoot the abnormality. The reminding information can also be pushed to related staff through the attendance platform according to a method similar to the alarm information pushing method.

In some embodiments, the tobacco production assistance method further comprises: and sending the production report to a data display platform for display. The production report includes at least one of quality data, cost data, and efficiency data. For example, the quality data includes quality check (QI, quality Inspection) data. As another example, the efficiency data includes one or more of equipment integrated efficiency (OEE, overall Equipment Effectiveness) data, and wire yield data. For another example, the cost data includes one or more of tobacco pest control data, and material consumption data.

The production result of the current process can be intuitively displayed through the data display platform, so that the analysis of the current process of tobacco production by workers is facilitated, main factors affecting production efficiency, quality or cost are determined, and the optimization of subsequent tobacco production by workers is facilitated.

In some implementations, as shown in fig. 2, the tobacco production assistance system 200 executing the tobacco production assistance method sends a production report to the data presentation platform 240.

In some implementations, the data presentation platform 240 is, for example, a QuickBI presentation platform.

In some embodiments, the historical production report is uploaded to the cloud database of the data display platform 240 through an interface provided by the web service of the industrial internet platform, and automatic uploading of data according to a preset period is achieved. For example, on a daily basis or on a weekly basis. The above-described manner may facilitate storage and analysis of production reports.

In some implementations, each interface is responsible for uploading different data in the production report. For example, interface 1 is responsible for uploading QI data, interface 2 is responsible for uploading OEE data, etc. The method is convenient for uploading the data, and errors are not easy to occur during uploading.

In some embodiments, the production report is generated at a preset reporting period. For example, if a preset report period is 1 day, a production report is generated every day.

In some embodiments, the tobacco production assistance method further comprises: acquiring alarm information of a video monitoring system for tobacco production; and alarming according to the alarm information. The video monitoring system for tobacco production can monitor the operation conditions of staff on each post in the current process. The mode is helpful for improving the tobacco production efficiency and quality.

In some embodiments, as shown in fig. 2, the tobacco production assistance system 200 for performing the tobacco production assistance method obtains the alarm information of the video monitoring system in the security system 260 through the API provided by the security system 260, and implements the alarm. In some embodiments, security system 260 is an ISC (integrated security management platform, isscure Center).

In some embodiments, the production report also includes pre-alarm events or alarm events in the current process and presents production tasks related to the events. The method can facilitate the staff to analyze the alarm event or the early warning event, and is beneficial to the staff to optimize the tobacco production.

In some embodiments, the tobacco production assistance method further comprises: one or more of the energy data, the equipment data and the process parameters are obtained from the electronic control system via an object connection and embedding (OPC, OLE for Process Control) interface for process control connected to the electronic control system for tobacco production. In some embodiments, the electronic control system is a PLC layer, which is the bottom control layer of tobacco production. The mode can directly establish connection with the bottom layer PLC, and the efficiency of acquiring production data is improved.

In some implementations, control of at least one production facility in the current process may also be achieved through an OPC interface.

In some implementations, the OPC interface is provided by an OPC server. In some embodiments, the OPC server is, for example, kepwire.

In some embodiments, the tobacco production assistance method further comprises: the camera is controlled to monitor a first scene of the current process in response to a user's monitoring demand for the first scene. The first scene comprises at least one of equipment startup check, before production and production overage in the current process. The production process refers to the situation that the material is before entering the production equipment of the current process, and the production process refers to the situation that the material enters the production equipment of the current process. The method is beneficial to the staff to monitor each production link of the current process in real time, and is convenient for the staff to find abnormal conditions in time.

In some embodiments, the above-described controlling of the camera to monitor the first scene is performed by the video monitoring module 205 in the tobacco production assist system 200 as shown in fig. 2.

In some embodiments, the position of the camera is adjustable. When the monitoring target of the staff member is changed from the first scene to the second scene, the camera is automatically transferred to the second scene position and shoots the second scene. The above manner can save resources.

In some implementations, there are multiple cameras, each monitoring a different preset location, and a worker can monitor multiple preset locations simultaneously.

In some embodiments, different positions are preset for multiple cameras for different scenes. For example, there are three cameras responsible for video surveillance of the current process. For scene 1, camera 1 is at position 1, camera 2 is at position 2, and camera 3 is at position 3, the three cameras cooperate to realize comprehensive monitoring of scene 1. For scene 2, camera 1 is at position 4, camera 2 is at position 5, and camera 3 is at position 6, the three cameras cooperate to achieve overall monitoring of scene 2. For scene 3, camera 1 is at position 7, camera 2 is at position 8, and camera 3 is at position 9. When the staff monitors scene 1, camera 1 is at position 1, camera 2 is at position 2, camera 3 is at position 3; when the monitoring target is adjusted to be a scene 2 by a worker, the camera 1 is automatically adjusted from the position 1 to the position 4, the camera 2 is adjusted from the position 2 to the position 5, and the camera 3 is adjusted from the position 3 to the position 6. The mode can improve the utilization rate of the camera and reduce the cost on the basis of realizing comprehensive monitoring.

In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For the device embodiments, since they basically correspond to the method embodiments, the description is relatively simple, and the relevant points are referred to in the description of the method embodiments.

Fig. 4 is a schematic structural view of a tobacco production assist system according to further embodiments of the present disclosure.

In some embodiments, as shown in fig. 4, the tobacco production assistance system includes a recommendation module 401, a verification module 402, a dispatch module 403, and a formation module 404.

The recommendation module 401 is configured to determine optimal parameters of the process parameters employed by the current process according to the usage data of the current process of tobacco production and the parameter recommendation model, and recommend the optimal parameters to the user. The usage data includes a plurality of lot data, energy data, and equipment data. The process parameters include at least one of environmental parameters and material parameters. The parameter recommendation model is generated based on historical data of production data including usage data and process parameters.

The verification module 402 is configured to verify production data of a current process prior to execution of the current process.

The dispatch module 403 is configured to dispatch the production task of the current process based on the production data of the current process after the verification is passed.

The forming module 404 is configured to form a production report of the current process from the production data of the current process after the current process is completed.

In some embodiments, the auxiliary device for tobacco production may also include other modules to perform the methods of other embodiments described above.

Fig. 5 is a schematic structural view of a tobacco production assist system according to further embodiments of the present disclosure.

As shown in fig. 5, the tobacco production assist system 500 includes a memory 501 and a processor 502 coupled to the memory 501, the processor 502 being configured to perform the method of any of the foregoing embodiments based on instructions stored in the memory 501.

Memory 501 may include, for example, system memory, fixed nonvolatile storage media, and the like. The system memory may store, for example, an operating system, application programs, boot Loader (Boot Loader), and other programs.

The tobacco production assist system 500 may also include an input-output interface 503, a network interface 504, a storage interface 505, and the like. The input/output interface 503, the network interface 504, the storage interface 505, and the memory 501 and the processor 502 may be connected via a bus 506, for example. The input output interface 503 provides a connection interface for input output devices such as a display, mouse, keyboard, touch screen, etc. Network interface 504 provides a connection interface for various networking devices. The storage interface 505 provides a connection interface for external storage devices such as SD cards, U discs, and the like.

The disclosed embodiments also provide a computer readable storage medium comprising computer program instructions which, when executed by a processor, implement the method of any of the above embodiments.

The disclosed embodiments also provide a computer program product comprising a computer program which, when executed by a processor, implements the method of any of the above embodiments.

Thus, various embodiments of the present disclosure have been described in detail. In order to avoid obscuring the concepts of the present disclosure, some details known in the art are not described. How to implement the solutions disclosed herein will be fully apparent to those skilled in the art from the above description.

It will be appreciated by those skilled in the art that embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable non-transitory storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that functions specified in one or more of the flowcharts and/or one or more of the blocks in the block diagrams may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present disclosure. It will be understood by those skilled in the art that the foregoing embodiments may be modified and equivalents substituted for elements thereof without departing from the scope and spirit of the disclosure. The scope of the present disclosure is defined by the appended claims.

Claims (13)

1. A tobacco production assist method, comprising:

determining optimal parameters of process parameters adopted by a current process of tobacco production according to use data and a parameter recommendation model of the current process, and recommending the optimal parameters to a user, wherein the use data comprises a plurality of batch data, energy data and equipment data, the process parameters comprise at least one of environment parameters and material parameters, the parameter recommendation model is generated based on historical data of production data, and the production data comprises the use data and the process parameters;

checking the production data of the current process before the current process is executed;

after the verification is passed, dispatching a production task of the current process according to the production data of the current process;

and after the current process is finished, forming a production report of the current process according to the production data of the current process.

2. The method of claim 1, further comprising:

and in the current process, analyzing the production data according to a production plan and a production schedule, and sending out early warning information when the production data is abnormal.

3. The method of claim 2, the analyzing the production data according to a production plan and a production schedule, and issuing early warning information when the production data is abnormal comprising:

obtaining attendance data through an attendance platform, wherein the attendance data comprises post information of staff;

determining staff related to abnormal data in the production data according to the post information;

and pushing the early warning information to staff related to the abnormal data through the attendance platform.

4. The method of claim 2, further comprising:

and controlling at least one production device related to the abnormal data in the current process according to the abnormal data in the production data.

5. The method of claim 1, wherein the production task includes an operation requiring personnel to perform during the current process, the method further comprising:

and obtaining an execution result of the operation, wherein the execution result comprises one of on-time completion, overtime completion and unexecuted.

6. The method of claim 1, further comprising:

one or more of the energy data, the equipment data and the process parameters are obtained from an electronic control system for tobacco production via an object connection and embedding interface for process control connected to the electronic control system.

7. The method of claim 1, wherein the verifying the production data of the current process comprises:

and verifying the production data of the current process by utilizing a data analysis model obtained by training the historical data based on the production data.

8. The method of claim 1, further comprising:

and sending the production report to a data display platform for display, wherein the production report comprises at least one of quality data, cost data and efficiency data.

9. The method of claim 1, further comprising:

acquiring alarm information of a video monitoring system for tobacco production;

and alarming according to the alarm information.

10. The method of claim 1, further comprising:

and in the current process, analyzing the production data in real time by using an externally-hung data analysis tool to predict a production result so as to adjust the process parameters according to the production result.

11. A tobacco production assist system, comprising:

a recommendation module configured to determine optimal parameters of process parameters employed by a current process of tobacco production according to usage data of the current process and a parameter recommendation model, and recommend the optimal parameters to a user, wherein the usage data includes a plurality of batch data, energy data, and equipment data, the process parameters include at least one of environmental parameters and material parameters, the parameter recommendation model is generated based on historical data of production data, the production data includes the usage data and the process parameters;

a verification module configured to verify the production data of the current process before the current process is performed;

the dispatching module is configured to dispatch the production task of the current process according to the production data of the current process after the verification is passed;

a forming module configured to form a production report of the current process from the production data of the current process after the current process is ended.

12. A tobacco production assist system, comprising:

a memory; and

a processor coupled to the memory and configured to perform the method of any of claims 1-10 based on instructions stored in the memory.

13. A computer readable storage medium comprising computer program instructions, wherein the computer program instructions, when executed by a processor, implement the method of any of claims 1-10.