CN116700189A - Control method, device, equipment and storage medium for butter kneader - Google Patents
Control method, device, equipment and storage medium for butter kneader Download PDFInfo
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- CN116700189A CN116700189A CN202310855034.8A CN202310855034A CN116700189A CN 116700189 A CN116700189 A CN 116700189A CN 202310855034 A CN202310855034 A CN 202310855034A CN 116700189 A CN116700189 A CN 116700189A
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- 235000014121 butter Nutrition 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000003860 storage Methods 0.000 title claims abstract description 13
- 239000003760 tallow Substances 0.000 claims abstract description 40
- 238000004519 manufacturing process Methods 0.000 claims abstract description 37
- 238000004886 process control Methods 0.000 claims abstract description 37
- 235000015278 beef Nutrition 0.000 claims abstract description 25
- 239000000463 material Substances 0.000 claims abstract description 21
- 238000004898 kneading Methods 0.000 claims abstract description 19
- 230000001105 regulatory effect Effects 0.000 claims description 25
- 238000012549 training Methods 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 14
- 238000013329 compounding Methods 0.000 claims 1
- 235000013305 food Nutrition 0.000 abstract description 9
- 230000000694 effects Effects 0.000 abstract description 7
- 239000004519 grease Substances 0.000 abstract description 4
- 239000003921 oil Substances 0.000 description 7
- 239000004615 ingredient Substances 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 238000007405 data analysis Methods 0.000 description 4
- 235000019197 fats Nutrition 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000001276 controlling effect Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000001125 extrusion Methods 0.000 description 1
- 235000012041 food component Nutrition 0.000 description 1
- 239000005417 food ingredient Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000003756 stirring Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by quality surveillance of production
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32368—Quality control
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The application relates to the technical field of intelligent control, in particular to a control method, a device, equipment and a storage medium for a butter kneader, wherein the control method for the butter kneader comprises the following steps: acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order; generating production process parameters according to the target product batching data and the target product demand data; obtaining kneader model data, splitting the production process parameters according to the kneader model data, and obtaining corresponding process control parameters; and after the material adding message is obtained, generating a beef tallow kneading instruction according to the process control parameters. The control method of the beef tallow kneader is optimized, so that the effect of the prepared grease food is improved.
Description
Technical Field
The application relates to the technical field of intelligent control, in particular to a control method, a device, equipment and a storage medium for a butter kneader.
Background
At present, when oil and fat foods such as beef tallow are produced, a beef tallow kneader is used for producing the oil and fat, and other food ingredients are put into the beef tallow kneader for producing the oil and fat foods.
When the existing butter kneader works, the added grease and other ingredients are continuously kneaded, stirred and compressed through the rotation and extrusion action in the machine, so that the intermolecular structure of the butter kneader is changed, and the effects of increasing the consistency and improving the taste are achieved.
The working state of the butter kneader during working has great influence on the effect of the prepared oil food, so that the control method of the butter kneader during working needs to be continuously optimized in order to continuously improve the effect of the prepared oil food.
Disclosure of Invention
In order to optimize the control method of the butter kneader so as to improve the effect of the prepared oil food, the application provides a control method, a device, equipment and a storage medium for the butter kneader.
The first object of the present application is achieved by the following technical solutions:
a control method for a tallow kneader, the control method for a tallow kneader comprising:
acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order;
generating production process parameters according to the target product batching data and the target product demand data;
obtaining kneader model data, splitting the production process parameters according to the kneader model data, and obtaining corresponding process control parameters;
and after the material adding message is obtained, generating a beef tallow kneading instruction according to the process control parameters.
According to the technical scheme, when the target product order is available, the target batching data and the corresponding target product demand data are obtained by analyzing the target product order, the kneader type data can be combined to be split into the corresponding process control parameters, the control parameters of the butter kneader during working can be automatically generated according to the data in the target order in the past in a mode of manually setting and inputting the corresponding control parameters according to the product order, the data analysis capability is utilized, the obtained process control parameters are more accurate, the quality of the product of the butter kneader is further improved, and when the production process parameters are generated, the customer demand of the target product order can be combined, namely, the target work product demand data are used for adjusting the basic process, so that the product passing through the butter kneader is more matched with the demand of the customer.
The present application may be further configured in a preferred example to: the generating production process parameters according to the target product batching data and the target product demand data specifically comprises the following steps:
generating reference product data according to the target batching data, and splitting the reference product data to obtain product reference types and product reference parameters corresponding to each product reference type;
inputting the target product requirement and the reference product data into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted;
and according to the type to be regulated, matching the corresponding product reference type, and regulating the product reference parameter of the reference to be regulated according to the parameter to be regulated to obtain the production process parameter.
By adopting the technical scheme, the reference product data are acquired, the corresponding product reference parameters of the product reference type pairs are obtained according to the split of the reference product data, basic control parameters meeting the quality requirements can be generated according to the current kneader model, and according to the basic control parameters, the parameters to be regulated generated by the parameter regulation model according to the target product requirements are combined, and the product reference parameters can be regulated according to the target product requirements, so that the quality of the finally obtained product can be met, and the requirements of customers can be met.
The present application may be further configured in a preferred example to: before the target product requirement and the reference product data are input into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted, the method for acquiring the parameter adjustment model comprises the following steps:
acquiring a historical product type, and acquiring corresponding historical finished product data according to the historical product type, wherein the historical finished product data comprises historical demand data and regulated parameter information;
and according to the types of the historical products, associating each piece of historical demand data with the adjusted parameter information, and training to obtain the parameter adjustment model corresponding to each type of the historical products.
By adopting the technical scheme, through analyzing the historical data, the correlation situation between the parameter adjustment and the historical demand data can be obtained through training and learning under the condition that the quality requirement of the product is met, and then the parameter adjustment model corresponding to each historical product type is obtained through training.
The present application may be further configured in a preferred example to: inputting the target product requirement and the reference product data into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted, wherein the method specifically comprises the following steps of:
obtaining product type information from the target product order, and obtaining the corresponding parameter adjustment model of the historical product type according to the product type information;
and identifying parameter index data in the target product demand, and inputting the parameter index data into the parameter adjustment model to obtain the type to be adjusted and the parameter to be adjusted.
Through adopting above-mentioned technical scheme, through matching corresponding parameter adjustment model to discern corresponding parameter index data in the target product demand, can quantify customer's demand, thereby be convenient for parameter adjustment model discerns and judges, and then make the product of making more can accord with customer's demand when guaranteeing the quality.
The present application may be further configured in a preferred example to: after the material adding message is obtained, generating a beef tallow kneading instruction according to the process control parameters, wherein the beef tallow kneading instruction specifically comprises the following steps:
acquiring Wen Jiedian information from the process control parameters, and generating node temperature control data corresponding to each temperature control node information according to the material adding information;
and generating the beef tallow kneading instruction according to the temperature control node information and the node temperature control data.
Through adopting above-mentioned technical scheme, according to the accuse Wen Jiedian information that obtains to according to material adds the information generation corresponding node accuse temperature data, can combine the kind and the quantity of actual input material, accurately carry out the accuse temperature, thereby promoted the quality of the product of making.
The second object of the present application is achieved by the following technical solutions:
a control device for a tallow kneader, the control device for a tallow kneader comprising:
the order acquisition module is used for acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order;
the parameter generation module is used for generating production process parameters according to the target product batching data and the target product demand data;
the parameter splitting module is used for acquiring model data of the kneader, splitting the production process parameters according to the model data of the kneader, and obtaining corresponding process control parameters;
and the instruction generation module is used for generating a beef tallow kneading instruction according to the process control parameters after the material adding message is acquired.
According to the technical scheme, when the target product order is available, the target batching data and the corresponding target product demand data are obtained by analyzing the target product order, the kneader type data can be combined to be split into the corresponding process control parameters, the control parameters of the butter kneader during working can be automatically generated according to the data in the target order in the past in a mode of manually setting and inputting the corresponding control parameters according to the product order, the data analysis capability is utilized, the obtained process control parameters are more accurate, the quality of the product of the butter kneader is further improved, and when the production process parameters are generated, the customer demand of the target product order can be combined, namely, the target work product demand data are used for adjusting the basic process, so that the product passing through the butter kneader is more matched with the demand of the customer.
The third object of the present application is achieved by the following technical solutions:
a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the control method for a tallow kneader as described above when the computer program is executed.
The fourth object of the present application is achieved by the following technical solutions:
a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the control method for a tallow kneader described above.
In summary, the present application includes at least one of the following beneficial technical effects:
1. when a target product order exists, target batching data and corresponding target product demand data are obtained by analyzing the target product order, the kneader model data can be combined to be split into corresponding process control parameters, the control parameters of the butter kneader during operation can be automatically generated according to the data in the target order in a mode of manually setting and inputting the corresponding control parameters in the past, the data analysis capability is utilized, the obtained process control parameters are more accurate, the quality of products manufactured by the butter kneader is further improved, and when the production process parameters are generated, the basic process can be adjusted according to the client demands of the target product order, namely the target work product demand data, so that the products manufactured by the butter kneader are more matched with the demands of clients;
2. obtaining reference product data, splitting the reference product data to obtain corresponding product reference parameters of product reference types, generating basic control parameters meeting quality requirements according to the current kneader model, and according to the basic control parameters, combining parameters to be adjusted generated by a parameter adjustment model according to target product requirements, and adjusting the product reference parameters according to the target product requirements, so that the quality of the finally obtained product can be met, and the requirements of customers can be met;
3. by analyzing the historical data, the correlation situation between the parameter adjustment and the historical demand data can be obtained through training and learning under the condition that the quality requirement of the product is met, and then the parameter adjustment model corresponding to each historical product type is obtained through training.
Drawings
FIG. 1 is a flow chart of a control method for a butter kneader in an embodiment of the present application;
FIG. 2 is a flowchart showing the implementation of step S20 in the control method for a butter kneader according to an embodiment of the present application;
FIG. 3 is a flowchart of another implementation in a control method for a butter kneader in an embodiment of the present application;
FIG. 4 is a flowchart showing the implementation of step S23 in the control method for a butter kneader according to an embodiment of the present application;
FIG. 5 is a flowchart showing the implementation of step S40 in the control method for a butter kneader according to an embodiment of the present application;
FIG. 6 is a schematic block diagram of a control apparatus for a butter kneader in accordance with an embodiment of the present application;
fig. 7 is a schematic diagram of an apparatus in an embodiment of the application.
Detailed Description
The present application will be described in further detail with reference to the accompanying drawings.
In one embodiment, as shown in fig. 1, the application discloses a control method for a butter kneader, which specifically comprises the following steps:
s10: and acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order.
In this embodiment, the target product order refers to data of an order for the grease-like food to be produced. The target product demand data refers to additional demands made by customers based on standard-based products.
Specifically, after the type and quantity of the oil and fat food are determined by the customer, the target product demand data, for example, the demand of viscosity, taste change, and other changes in effect, is set according to the self demand, and then the target product demand data is used to generate the target product order.
Further, after the target product order is obtained, a corresponding product type is identified from the target product order, and preset formula data is obtained according to the product type to serve as the target product batching data and the target product demand data of the client.
S20: and generating production process parameters according to the target product batching data and the target product demand data.
Specifically, after the target product batching data is obtained, generating parameters of a basic production process based on the target product batching data and the product type, and adjusting the parameters of the basic production process according to the target product demand data to obtain the production process parameters for controlling the butter kneader to manufacture the target order.
S30: and obtaining kneader model data, and splitting production process parameters according to the kneader model data to obtain corresponding process control parameters.
In the present embodiment, the kneader model data refers to a specific model of the beef tallow kneader for completion of the order for the target product. The process control parameters refer to parameters executed by the equipment corresponding to each node when the specific beef tallow kneader specifically makes the target order.
Specifically, because different butter kneaders have different control logics when manufacturing the same product, a pre-trained parameter splitting model is obtained according to the model of the butter kneader, namely the model data of the kneader, of which the target product is specifically manufactured, and production process parameters are input into the parameter splitting model to obtain the process control parameters.
S40: and after the material adding message is obtained, generating a butter kneading instruction according to the process control parameters.
Specifically, after a worker obtains other automatic feeding equipment to add corresponding ingredients into the kneader according to target ingredient data, the material adding message is triggered, and a beef tallow kneading instruction is generated according to the split process control parameters.
In this embodiment, when there is a target product order, the target ingredient data and the corresponding target product demand data are obtained by analyzing the target product order, which can be split into corresponding process control parameters in combination with the kneader model data, and the control parameters for the butter kneader during operation can be automatically generated according to the data in the target order in the past by manually setting and inputting the corresponding control parameters, so that the obtained process control parameters are more accurate by utilizing the data analysis capability, thereby being beneficial to improving the quality of the product manufactured by the butter kneader, and when the production process parameters are generated, the basic process can be adjusted by combining the client demand of the target product order, namely, the target product demand data, so that the product manufactured by the butter kneader is more matched with the client demand.
In one embodiment, as shown in fig. 2, in step S20, production process parameters are generated according to the target product batching data and the target product demand data, which specifically includes:
s21: and generating reference product data according to the target batching data, and splitting the reference product data to obtain product reference types and product reference parameters corresponding to each product reference type.
In this embodiment, the reference product data refers to parameters of a product corresponding to a reference type of the completed target product.
Specifically, the reference product data is generated according to the target ingredient data and the product type in the target product order, namely, a standard product corresponding to the product type is simulated, corresponding product attributes are obtained from the standard product, and in order to achieve the product attributes, control parameters corresponding to the butter kneader are used as the reference product data.
Further, the included data dimension is obtained from the reference product data, the type of each data dimension is used as the product reference type, and the data corresponding to each product reference type is obtained as the product reference parameter.
S22: and inputting the target product requirement and the reference product data into a preset parameter adjustment model to obtain the type to be adjusted and the corresponding parameter to be adjusted.
Specifically, the target product requirement and the reference product data are input into a preset parameter adjustment model, the parameter adjustment model is based on the historical product type and data for adjusting the actually produced product in combination with the customer requirement, the reference product data are judged, and the data dimension required to be adjusted is judged to be used as the type to be adjusted and the corresponding parameter to be adjusted.
S23: and matching corresponding product reference types according to the types to be regulated, and regulating product reference parameters of the references to be regulated according to the parameters to be regulated to obtain production process parameters.
Specifically, a product reference type matched with the type to be regulated is obtained and used as the reference type to be regulated, and the production process parameter is obtained after the product reference parameter corresponding to the reference type to be regulated is replaced by the parameter to be regulated.
In one embodiment, as shown in fig. 3, before step S22, the method for obtaining the parameter adjustment model includes:
s2201: and acquiring the type of the historical product, and acquiring corresponding historical finished product data according to the type of the historical product, wherein the historical finished product data comprises historical demand data and regulated parameter information.
Specifically, each time a grease food is produced by a butter kneader, a corresponding product category is counted as data of the history product category and attributes of actually produced products corresponding to each history product category as the history product data.
The historical product data comprises the requirements of corresponding clients as historical requirement data, and data for adjusting the parameters to meet the requirements of the clients and the quality of the products, wherein the data comprises temperature, heating time, stirring rotating speed and the like, and the data is used as adjusted parameter information.
S2202: and according to the types of the historical products, associating each piece of historical demand data with the adjusted parameter information, and training to obtain a parameter adjustment model corresponding to each type of the historical products.
Specifically, training the historical demand data and the regulated parameter information class by class according to the type of the historical product to obtain the parameter adjustment model, associating the historical demand data with the regulated parameter information regulated to meet the historical demand data before training, performing training learning, and training according to the association between the demand data and the regulated parameter to obtain the parameter adjustment model.
In one embodiment, as shown in fig. 4, in step S22, target product requirements and reference product data are input into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted, which specifically includes:
s221: and obtaining product type information from the target product order, and obtaining a corresponding parameter adjustment model of the historical product type according to the product type information.
Specifically, from the target product order, the type of the product that the customer needs to acquire is acquired as the product type information. Further, because each historical product type has a corresponding parameter adjustment model to improve the accuracy of model identification, the matched historical product type is obtained according to the product type information, and the corresponding parameter adjustment model is obtained according to the matched historical product type.
S222: and identifying parameter index data in the demand of the target product, and inputting the parameter index data into a parameter adjustment model to obtain the type to be adjusted and the parameter to be adjusted.
Specifically, by means of character recognition, the attribute which is required to be additionally and newly added in the demand of the target product is recognized as compared with the reference product, so that the demand of the target product is quantized in numerical value and used as parameter index data, and the parameter index data are input into a parameter adjustment model to obtain the type to be adjusted and the parameter to be adjusted.
In one embodiment, as shown in fig. 5, in step S40, that is, after the material adding message is obtained, a beef tallow kneading command is generated according to the process control parameters, which specifically includes:
s41: and acquiring Wen Jiedian information from the process control parameters, and generating node temperature control data corresponding to each temperature control node information according to the material adding information.
Specifically, in the process control parameters, corresponding processing steps are acquired, and nodes which need to control the temperature of grease in the processing steps are used as temperature control node information. Further, according to the material adding information, the mass of each ingredient actually put into the kneader is obtained, and temperature data which are corresponding to each temperature control node and need to be controlled are generated.
S42: and generating a butter kneading instruction according to the temperature control node information and the node temperature control data.
Specifically, a beef tallow kneading command is generated according to the temperature control node information and the node temperature control data, so that each node needing heating and temperature control kneads materials according to the corresponding node temperature control data.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.
In one embodiment, a control device for a tallow kneader is provided, which corresponds one-to-one to the control method for a tallow kneader in the above-described embodiment. As shown in fig. 6, the control device for the beef tallow kneader comprises an order acquisition module, a parameter generation module, a parameter splitting module and an instruction generation module. The functional modules are described in detail as follows:
the order acquisition module is used for acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order;
the parameter generation module is used for generating production process parameters according to the target product batching data and the target product demand data;
the parameter splitting module is used for acquiring model data of the kneader, splitting production process parameters according to the model data of the kneader, and obtaining corresponding process control parameters;
and the instruction generation module is used for generating a beef tallow kneading instruction according to the process control parameters after the material adding message is acquired.
Optionally, the parameter generating module includes:
the reference data acquisition sub-module is used for generating reference product data according to the target batching data, and splitting the reference product data to obtain product reference types and product reference parameters corresponding to each product reference type;
the model identification sub-module is used for inputting the target product requirement and the reference product data into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted;
and the parameter adjusting sub-module is used for matching corresponding product reference types according to the types to be adjusted, and obtaining production process parameters after adjusting the product reference parameters of the references to be adjusted according to the parameters to be adjusted as the reference types to be adjusted.
Optionally, the control device of the beef tallow kneader further comprises:
the historical data association module is used for acquiring the types of the historical products and acquiring corresponding historical finished product data according to the types of the historical products, wherein the historical finished product data comprises historical demand data and adjusted parameter information;
and the model training module is used for associating each historical demand data with the adjusted parameter information according to the types of the historical products, and training to obtain a parameter adjustment model corresponding to each type of the historical products.
Optionally, the model identification submodule includes:
the demand quantification sub-module is used for acquiring product type information from the target product order and acquiring a corresponding parameter adjustment model of the historical product type according to the product type information;
the model identification sub-module is used for identifying parameter index data in the requirements of the target product, and inputting the parameter index data into the parameter adjustment model to obtain the type to be adjusted and the parameter to be adjusted.
Optionally, the instruction generating module includes:
the temperature control data generation sub-module is used for acquiring Wen Jiedian information from the process control parameters and generating node temperature control data corresponding to each temperature control node information according to the material adding information;
the instruction generation sub-module is used for generating a butter kneading instruction according to the temperature control node information and the node temperature control data.
The specific limitations regarding the control device for the butter kneader may be found in the above description of the control method for the butter kneader, and will not be described in detail herein. The respective modules in the control device for the beef tallow kneader described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements a control method for a butter kneader.
In one embodiment, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order;
generating production process parameters according to the target product batching data and the target product demand data;
obtaining kneader model data, splitting production process parameters according to the kneader model data, and obtaining corresponding process control parameters;
and after the material adding message is obtained, generating a butter kneading instruction according to the process control parameters.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order;
generating production process parameters according to the target product batching data and the target product demand data;
obtaining kneader model data, splitting production process parameters according to the kneader model data, and obtaining corresponding process control parameters;
and after the material adding message is obtained, generating a butter kneading instruction according to the process control parameters.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (10)
1. A control method for a tallow kneader, characterized in that the control method for a tallow kneader comprises:
acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order;
generating production process parameters according to the target product batching data and the target product demand data;
obtaining kneader model data, splitting the production process parameters according to the kneader model data, and obtaining corresponding process control parameters;
and after the material adding message is obtained, generating a beef tallow kneading instruction according to the process control parameters.
2. The control method for a beef tallow kneader according to claim 1, wherein the generating production process parameters according to the target product compounding data and the target product demand data specifically includes:
generating reference product data according to the target batching data, and splitting the reference product data to obtain product reference types and product reference parameters corresponding to each product reference type;
inputting the target product requirement and the reference product data into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted;
and according to the type to be regulated, matching the corresponding product reference type, and regulating the product reference parameter of the reference to be regulated according to the parameter to be regulated to obtain the production process parameter.
3. The control method for a beef tallow kneader according to claim 2, characterized in that the method for acquiring the parameter adjustment model before the target product requirement and the reference product data are inputted into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted comprises:
acquiring a historical product type, and acquiring corresponding historical finished product data according to the historical product type, wherein the historical finished product data comprises historical demand data and regulated parameter information;
and according to the types of the historical products, associating each piece of historical demand data with the adjusted parameter information, and training to obtain the parameter adjustment model corresponding to each type of the historical products.
4. The control method for a butter kneader according to claim 3, characterized in that the inputting the target product requirement and the reference product data into a preset parameter adjustment model, obtaining a type to be adjusted and a corresponding parameter to be adjusted, specifically includes:
obtaining product type information from the target product order, and obtaining the corresponding parameter adjustment model of the historical product type according to the product type information;
and identifying parameter index data in the target product demand, and inputting the parameter index data into the parameter adjustment model to obtain the type to be adjusted and the parameter to be adjusted.
5. The control method for a butter kneader according to claim 1, characterized in that said generating a butter kneading instruction according to said process control parameters after the acquisition of the material addition message, specifically comprises:
acquiring Wen Jiedian information from the process control parameters, and generating node temperature control data corresponding to each temperature control node information according to the material adding information;
and generating the beef tallow kneading instruction according to the temperature control node information and the node temperature control data.
6. A control device for a tallow kneader, characterized in that the control device for a tallow kneader comprises:
the order acquisition module is used for acquiring a target product order, and acquiring target product batching data and target product demand data from the target product order;
the parameter generation module is used for generating production process parameters according to the target product batching data and the target product demand data;
the parameter splitting module is used for acquiring model data of the kneader, splitting the production process parameters according to the model data of the kneader, and obtaining corresponding process control parameters;
and the instruction generation module is used for generating a beef tallow kneading instruction according to the process control parameters after the material adding message is acquired.
7. The control device for a beef tallow kneader according to claim 6, wherein the parameter generation module includes:
the reference data acquisition sub-module is used for generating reference product data according to the target batching data, and splitting the reference product data to obtain product reference types and product reference parameters corresponding to each product reference type;
the model identification sub-module is used for inputting the target product requirement and the reference product data into a preset parameter adjustment model to obtain a type to be adjusted and a corresponding parameter to be adjusted;
and the parameter adjusting sub-module is used for matching the corresponding product reference type according to the type to be adjusted, and obtaining the production process parameter after adjusting the product reference parameter of the reference to be adjusted according to the parameter to be adjusted as the reference type to be adjusted.
8. The control device for a tallow kneader according to claim 7, characterized in that the control device for a tallow kneader further comprises:
the historical data association module is used for acquiring a historical product type, and acquiring corresponding historical finished product data according to the historical product type, wherein the historical finished product data comprises historical demand data and adjusted parameter information;
and the model training module is used for associating each historical demand data with the adjusted parameter information according to the type of the historical product, and training to obtain the parameter adjustment model corresponding to each type of the historical product.
9. Computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, realizes the steps of the control method for a tallow kneader according to any of claims 1 to 5.
10. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, realizes the steps of the control method for a butter kneader according to any one of claims 1 to 5.
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