Intelligent equipment operation method and system based on industrial Internet of Things cloud edge collaboration

Abstract

The invention relates to the technical field of industrial Internet of Things intelligent production control, and discloses an industrial Internet of Things cloud edge collaboration-based equipment intelligent operation method and system, and the method comprises the steps: extracting production flow information and production demands in each product industrial production order, analyzing the elastic production flow related information of the product industrial production order, and carrying out the cloud edge collaboration of the product industrial production order; querying artificial production resources and industrial production auxiliary equipment resources, solving a product industrial production order allocation sub-strategy and an industrial production auxiliary equipment configuration sub-strategy, and issuing the sub-strategies to each production line production edge management terminal and each production line production edge execution terminal; and a production executor is driven to control the production processing equipment to execute the production operation of independent manual production or equipment-assisted production. According to the invention, seamless application and connection of the production auxiliary equipment under the industrial Internet of Things intelligent production control system are realized, and the overall energy efficiency of industrial production is improved while the distribution rationality and scientificity of the production processing orders and the production auxiliary equipment are improved.

Description

Technical Field

[0001] The present invention relates to the field of industrial Internet of Things intelligent production control technology, and in particular to a method and system for intelligent equipment operation based on industrial Internet of Things cloud-edge collaboration. Background Art

[0002] Industrial IoT intelligent production control refers to the intelligent management and control of the entire production process using IoT technology. By integrating core elements such as production equipment, personnel, and data, a real-time, interconnected, and dynamically coordinated production system is constructed. Data drives production decisions, enabling precise allocation of production resources, efficient coordination of production processes, and continuous optimization of production efficiency. The application of cloud-edge collaborative technology in the context of Industrial IoT intelligent production control can enable intelligent operation of production and processing equipment through Industrial IoT cloud-edge collaborative technology, based on order data processing and task dispatching in the industrial production intelligent cloud and production operations executed by production line edge execution terminals, thereby enhancing the intelligence and automation of Industrial IoT intelligent production control.

[0003] In actual applications, intelligent production control of the Industrial Internet of Things involves the application of production auxiliary equipment (such as head-mounted AR display devices, which can provide production execution personnel with guidance information for each operation action through image recognition and intelligent positioning). Production auxiliary equipment can significantly improve the production speed of production execution personnel, but there are still significant limitations and defects when applying production auxiliary equipment to this system: First, due to high costs, it is difficult to fully equip production auxiliary equipment for all employees, and it is impossible for all production execution personnel to enjoy the same technological empowerment; second, when equipment is allocated to different personnel in different production cycles, due to the different operating habits and processing product types of different production execution personnel, the production auxiliary model needs to be re-trained and reconfigured, which makes the production execution personnel "no output in the early stage and high efficiency in the later stage". The phased characteristics of production affect the continuity of the production process and increase the difficulty of efficiency-driven management; thirdly, when production execution personnel constantly change the type of processed products, the difference in operating actions will reduce the product yield or increase the scrap rate of raw materials. The application of production auxiliary equipment can well solve the impact of product output caused by the difference in operating actions; fourthly, different personnel have different processing speeds for different operating action groups, and orders are diverse due to different processing types, quantities, and time requirements. This brings great difficulties to the reasonable allocation of production and processing orders and production auxiliary equipment among multiple production lines, restricting the maximization of equipment efficiency.

[0004] Therefore, how to achieve seamless application and connection of production auxiliary equipment under the intelligent production control system of the Industrial Internet of Things, while improving the rationality and scientificity of the allocation of production and processing orders and production auxiliary equipment among multiple production lines, alleviate the limitations of low product yield or high pigment scrap rate caused by differences in operating actions for different types of processed products, and improve the overall energy efficiency of industrial production, is a technical problem that needs to be solved urgently. Summary of the Invention

[0005] The main purpose of the present invention is to provide an intelligent equipment operation method and system based on industrial Internet of Things cloud-edge collaboration, aiming to solve at least one of the above-mentioned technical problems.

[0006] To achieve the above objectives, the present invention provides a method for intelligent operation of equipment based on industrial Internet of Things cloud-edge collaboration, which is used in industrial production intelligent cloud. The method includes the following steps: Receive product industrial production requests continuously uploaded by several request terminals, and generate product industrial production tasks for each industrial production cycle before each industrial production cycle; Extracting several product industrial production orders from the product industrial production task, and constructing a product industrial production demand list for the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order; Analyze the production process information of each industrial product production type in the product industrial production demand list, and generate the flexible production process association information corresponding to each industrial product production type; Query industrial production resource information, consider the production demand and flexible production process association information of each industrial product type in the product industrial production demand list, and solve the industrial production intelligent operation strategy for the industrial production cycle; wherein, the industrial production intelligent operation strategy includes the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy; Send the product industrial production order allocation sub-strategy to each production line production edge management terminal in the industrial production area, driving each industrial production line to execute the corresponding product industrial production order; The industrial production auxiliary equipment configuration sub-strategy is sent to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform independent manual production or equipment-assisted production operations.

[0007] Optionally, receiving product industrial production requests continuously uploaded by a plurality of request terminals, generating product industrial production task steps of the industrial production cycle before each industrial production cycle, specifically including: Receive product industrial production requests continuously uploaded by a plurality of request terminals, and extract product industrial production orders from each product industrial production request; wherein the product industrial production order records the industrial product production quantity, industrial product production type, and industrial product production period; Before each industrial production cycle, the industrial production orders of the products whose production time segments are included in the industrial production cycle are summarized to generate industrial production tasks for the products.

[0008] Optionally, extracting several product industrial production orders from the product industrial production task and constructing a product industrial production demand list for the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order specifically includes: Extracting several product industrial production orders from the product industrial production task, extracting the order content of the product industrial production orders, and obtaining production process information and production requirements for each industrial product production type; wherein the production process information includes production operation data, and the production requirements include industrial product production quantity and industrial product production time period; The production operation data contained in each product industrial production order is associated with the industrial product production quantity and industrial product production period in the product industrial production demand list of the constructed industrial production cycle and stored with the order identifier corresponding to the product industrial production order.

[0009] Optionally, the steps of parsing the production process information of each industrial product production type in the product industrial production demand list and generating the flexible production process association information corresponding to each industrial product production type include: Parsing the production process information of each industrial product production type in the product industrial production demand list, extracting the production operation action group and the number of standard guidance images for industrial production auxiliary equipment for several production operation actions from the production operation data of the production process information; Flexible production process association information is generated based on the production operation action group in the production operation data and the number of standard guidance images for industrial production auxiliary equipment for several production operation actions.

[0010] Optionally, query industrial production resource information, consider the production demand and flexible production process association information of each industrial product production type in the product industrial production demand list, and solve the industrial production intelligent operation strategy steps of the industrial production cycle, including: Querying industrial production resource information, and extracting manual production resources and industrial production auxiliary equipment resources from the industrial production resource information; Considering the production demand and flexible production process association information for each industrial product type in the product industrial production demand list, an optimization solution model is constructed, which uses the production efficiency determined by independent manual production and equipment-assisted production within the production period as a constraint condition, and takes the lowest quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle as the optimization goal. An optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy; Based on the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy, an industrial production intelligent operation strategy for the industrial production cycle is generated.

[0011] Optionally, the step of querying industrial production resource information and extracting manual production resources and industrial production auxiliary equipment resources from the industrial production resource information specifically includes: Query industrial production resource information, extract the personnel identifications of several production executives of each industrial production line, and use the personnel identifications to index data in an independent manual production history database or an equipment-assisted production history database; The first historical product industrial production data indexed to each production executive is extracted as a manual production resource, and the second historical product industrial production data on the industrial production auxiliary equipment that each production executive relies on is extracted as an industrial production auxiliary equipment resource.

[0012] Optionally, considering the production demand and flexible production process association information of each industrial product production type in the product industrial production demand list, an optimization solution model is constructed with the production efficiency jointly determined by independent manual production and equipment-assisted production within the production period as a constraint condition, and with the lowest quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle as the optimization goal. The optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy steps, specifically including: Considering the industrial product production quantity of each industrial product production type in the product industrial production demand list and the industrial product production period and the production operation action group in the production operation data and the number of standard guidance images for several production operation actions for industrial production auxiliary equipment; Allocating each product industrial production order and each industrial production auxiliary equipment to a number of production execution personnel of the corresponding industrial production line is used as the allocation principle to solve the optimal allocation; The constraint condition is that the sum of the independent manual production efficiency determined during the industrial product production period by the production executors who are not equipped with industrial production auxiliary equipment and assigned to each product industrial production order and the equipment-assisted production efficiency determined during the industrial product production period by the production executors who are equipped with industrial production auxiliary equipment is greater than the production quantity of the industrial products corresponding to the industrial production order of the product. The optimization goal is to minimize the sum of the proportions of different production operation actions in the production operation action group when all production executors who are not equipped with industrial production auxiliary equipment execute every two adjacent product industrial production orders within the industrial production cycle, which is the lowest quantitative value of the production learning cost. The independent manual production efficiency is calculated by multiplying the first production processing speed of the same production operation action group by the first duration of the industrial product production period by the production execution personnel assigned to each product industrial production order who are not equipped with industrial production auxiliary equipment in the first historical product industrial production data to obtain the independent manual production efficiency; The equipment-assisted production efficiency is calculated by multiplying the second production processing speed of the same production operation action group in the second historical product industrial production data by the production execution personnel assigned to each product industrial production order equipped with industrial production auxiliary equipment and the second duration of the auxiliary production period in the industrial product production period to obtain the equipment-assisted production efficiency; The auxiliary production period is configured as a period of time in which the industrial product production period excludes the non-auxiliary production period, and the duration of the non-auxiliary production period is obtained by matching the number of standard guidance images for industrial production auxiliary equipment for several production operation actions in the product industrial production order with a pre-configured mapping comparison table of the number of standard guidance images and the time consumption of equipment auxiliary model training; An optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy.

[0013] Optionally, a pre-configured mapping comparison table between the number of standard guidance images and the equipment-assisted model training time is extracted and mapped and stored by calculating the average of all equipment-assisted model training times for different numbers of standard guidance images in the historical equipment-assisted model training records.

[0014] Optionally, the industrial production auxiliary equipment configuration sub-strategy is distributed to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform production operation steps of independent manual production or equipment-assisted production, specifically including: Sending the industrial production auxiliary equipment configuration sub-strategy to several production line production edge execution terminals corresponding to each industrial production line; Driving the production execution personnel configured with the production edge execution terminal of the production line to use the production assistance model of the production assistance equipment to realize equipment-assisted production during the auxiliary production period of the industrial product production period; wherein, the production assistance equipment imports the production assistance model completed by the auxiliary production support personnel during the non-auxiliary production period through standard guidance image acquisition, sample construction and model training; Drive production execution personnel who are not equipped with the production line production edge execution terminal to achieve independent manual production when performing each production operation.

[0015] In addition, to achieve the above objectives, the present invention also provides an intelligent equipment operation system based on industrial Internet of Things cloud-edge collaboration, which includes the following modules: A receiving module is used to receive product industrial production requests continuously uploaded by a number of request terminals, and generate product industrial production tasks for each industrial production cycle before each industrial production cycle; A construction module is used to extract a plurality of product industrial production orders from the product industrial production task, and to construct a product industrial production demand list of the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order; A parsing module is used to parse the production process information of each industrial product production type in the product industrial production demand list and generate flexible production process association information corresponding to each industrial product production type; A query module is used to query industrial production resource information, consider the production requirements and flexible production process association information of each industrial product type in the product industrial production requirement list, and solve the industrial production intelligent operation strategy for the industrial production cycle; wherein the industrial production intelligent operation strategy includes a product industrial production order allocation sub-strategy and an industrial production auxiliary equipment configuration sub-strategy; A sending module is used to send the product industrial production order allocation sub-strategy to each production line production edge management terminal in the industrial production area, driving each industrial production line to execute the corresponding product industrial production order; The execution module is used to send the industrial production auxiliary equipment configuration sub-strategy to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform independent manual production or equipment-assisted production operations.

[0016] The beneficial effects of the present invention are: a method and system for intelligent equipment operation based on industrial Internet of Things cloud-edge collaboration is proposed, which extracts the production process information and production requirements in each product industrial production order, analyzes the elastic production process association information of each product industrial production order, queries the manual production resources and industrial production auxiliary equipment resources of the industrial production resource information, solves the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy, and sends them to each production line production edge management terminal and production line production edge execution terminal, driving the production execution personnel to control the production and processing equipment to perform independent manual production or equipment-assisted production production operations. The present invention improves the overall energy efficiency of industrial production by realizing the seamless application and connection of production auxiliary equipment under the intelligent production control system of the Industrial Internet of Things, while improving the rationality and scientificity of the allocation of production and processing orders and production auxiliary equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of the device intelligent operation method based on industrial Internet of Things cloud-edge collaboration of the present invention; Figure 2 This is a structural diagram of the equipment intelligent operation system based on industrial Internet of Things cloud-edge collaboration of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] The embodiment of the present invention provides a device intelligent operation method based on industrial Internet of Things cloud-edge collaboration, referring to Figure 1 , Figure 1 This is a flow chart of an embodiment of the method for intelligent operation of equipment based on industrial Internet of Things cloud-edge collaboration of the present invention.

[0020] In this embodiment, a method for intelligent operation of equipment based on industrial Internet of Things cloud-edge collaboration is used in an industrial production intelligent cloud. The method includes the following steps: S1: Receive product industrial production requests continuously uploaded by several request terminals, and generate product industrial production tasks for each industrial production cycle before each industrial production cycle; S2: extracting several product industrial production orders from the product industrial production task, and constructing a product industrial production demand list for the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order; S3: Analyze the production process information of each industrial product production type in the product industrial production demand list, and generate the flexible production process association information corresponding to each industrial product production type; S4: Querying industrial production resource information, considering the production demand and flexible production process association information of each industrial product type in the product industrial production demand list, and solving the industrial production intelligent operation strategy for the industrial production cycle; wherein the industrial production intelligent operation strategy includes a product industrial production order allocation sub-strategy and an industrial production auxiliary equipment configuration sub-strategy; S5: Send the product industrial production order allocation sub-strategy to each production line production edge management terminal in the industrial production area, driving each industrial production line to execute the corresponding product industrial production order; S6: Send the industrial production auxiliary equipment configuration sub-strategy to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform independent manual production or equipment-assisted production operations.

[0021] It should be noted that in actual applications, the intelligent production control of the Industrial Internet of Things will involve the application of production auxiliary equipment (such as head-mounted AR display devices, which can provide production execution personnel with guidance information for each operation action through image recognition and intelligent positioning). Production auxiliary equipment can significantly improve the production speed of production execution personnel, but when production auxiliary equipment is applied to this system, there are still significant limitations and defects: First, due to high costs, it is difficult to fully equip production auxiliary equipment, and it is impossible for all production execution personnel to enjoy the same technological empowerment; second, when equipment is assigned to different personnel in different production cycles, due to the different operating habits and processing product types of different production execution personnel, the production auxiliary model needs to be retrained. training and configuration, which makes production execution personnel present the stage characteristics of "no output in the early stage and high efficiency in the later stage", affecting the continuity of the production process and increasing the difficulty of efficiency-driven management; thirdly, when production execution personnel constantly change the type of processed products, the difference in operating actions will reduce the product yield or increase the scrap rate of raw materials, and the application of production auxiliary equipment can well solve the impact of product output caused by differences in operating actions; fourthly, different personnel have different processing speeds for different operating action groups, and orders are diverse due to different processing types, quantities, and time requirements. This brings great difficulties to the reasonable allocation of production and processing orders and production auxiliary equipment among multiple production lines, restricting the maximization of equipment efficiency.

[0022] In order to solve the above problems, this embodiment extracts the production process information and production requirements from each product industrial production order, analyzes the flexible production process association information of each product industrial production order, queries the manual production resources and industrial production auxiliary equipment resources of the industrial production resource information, solves the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy, and sends them to each production line production edge management terminal and production line production edge execution terminal, driving the production execution personnel to control the production and processing equipment to perform independent manual production or equipment-assisted production operations. The present invention improves the overall energy efficiency of industrial production by realizing the seamless application and connection of production auxiliary equipment under the intelligent production control system of the Industrial Internet of Things, while improving the rationality and scientificity of the allocation of production and processing orders and production auxiliary equipment.

[0023] In a preferred embodiment, product industrial production requests continuously uploaded by a plurality of request terminals are received, and before each industrial production cycle, product industrial production task steps of the industrial production cycle are generated, specifically including: S11: receiving product industrial production requests continuously uploaded by a plurality of requesting terminals, and extracting a product industrial production order from each product industrial production request; wherein the product industrial production order records the industrial product production quantity, industrial product production type, and industrial product production period; S12: Before each industrial production cycle, industrial production orders for products whose production time periods are included in the industrial production cycle are summarized to generate industrial production tasks for the products.

[0024] In this embodiment, by continuously accepting product industrial production requests from request terminals on the industrial production intelligent cloud, the product industrial production orders in the product industrial production requests are extracted, so as to obtain the industrial product production quantity, industrial product production type and industrial product production time period corresponding to each product industrial production request, and then based on the time period relationship between the industrial product production time period and the industrial production cycle, a product industrial production task containing all product industrial production orders of the industrial production cycle is generated.

[0025] In a preferred embodiment, the steps of extracting several product industrial production orders from the product industrial production task and constructing a product industrial production demand list for the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order specifically include: S21: extracting several product industrial production orders from the product industrial production task, extracting the order content of the product industrial production orders, and obtaining production process information and production requirements for each industrial product production type; wherein the production process information includes production operation data, and the production requirements include industrial product production quantity and industrial product production time period; S22: The production operation data included in each product industrial production order is associated with the industrial product production quantity and the industrial product production period in the product industrial production demand list of the constructed industrial production cycle and stored with the order identifier corresponding to the product industrial production order.

[0026] In this embodiment, by extracting the order content from the product industrial production order, the production process information is clarified with the industrial product production quantity and industrial product production period, and the order identifier corresponding to the product industrial production order is associated and stored in the product industrial production demand list of the constructed industrial production cycle, providing data support for the subsequent generation of flexible production process association information.

[0027] In a preferred embodiment, the steps of parsing the production process information of each industrial product production type in the product industrial production demand list and generating the flexible production process association information corresponding to each industrial product production type specifically include: S31: parsing the production process information of each industrial product production type in the product industrial production demand list, extracting the production operation action group and the number of standard guidance images for industrial production auxiliary equipment for several production operation actions from the production operation data of the production process information; S32: Generate flexible production process association information based on the production operation action group in the production operation data and the number of standard guidance images for the industrial production auxiliary equipment for the plurality of production operation actions.

[0028] In this embodiment, by parsing the product industrial production process information, the production operation action group corresponding to each industrial product production type and the number of standard guidance images for industrial production auxiliary equipment for several production operation actions are extracted (the number of standard guidance images is adapted to the number of production operation actions, that is, one standard guidance image corresponds to one production operation action, and the standard guidance image is defined as a standard posture image for industrial production auxiliary equipment to perform image recognition and intelligent positioning for the corresponding production operation action. The production auxiliary equipment collects processed images that meet the standard posture image, and provides visual guidance to production execution personnel through image recognition and intelligent positioning), which facilitates the subsequent solution of the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy.

[0029] In a preferred embodiment, the steps of querying industrial production resource information, considering the production demand and flexible production process association information of each industrial product production type in the product industrial production demand list, and solving the industrial production intelligent operation strategy of the industrial production cycle specifically include: S41: Querying industrial production resource information, extracting manual production resources and industrial production auxiliary equipment resources from the industrial production resource information; S42: Considering the production demand and flexible production process association information of each industrial product production type in the product industrial production demand list, an optimization solution model is constructed with the production efficiency jointly determined by independent manual production and equipment-assisted production within the production period as a constraint condition, and the minimum quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle as the optimization goal. The optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy; S43: Generate an industrial production intelligent operation strategy for the industrial production cycle based on the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy.

[0030] In this embodiment, by generating product industrial production tasks for each industrial production cycle, extracting the production process information and production requirements in each product industrial production order, constructing a product industrial production requirement list, and then parsing the flexible production process association information of each product industrial production order, and then querying the manual production resources and industrial production auxiliary equipment resources in the industrial production resource information, constructing an optimization solution model with the production efficiency determined by independent manual production and equipment-assisted production within the production period as a constraint condition, and the lowest quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle as the optimization goal, and using the optimization algorithm to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy.

[0031] In a preferred embodiment, the step of querying industrial production resource information and extracting manual production resources and industrial production auxiliary equipment resources from the industrial production resource information specifically includes: S411: Query industrial production resource information, extract personnel identifications of several production executives of each industrial production line, and use the personnel identifications to index data in an independent manual production history database or an equipment-assisted production history database; S412: extracting the first historical product industrial production data indexed to each production executive as manual production resources, and extracting the second historical product industrial production data of each production executive that relies on industrial production auxiliary equipment as industrial production auxiliary equipment resources.

[0032] In this embodiment, by querying industrial production resource information, the first historical product industrial production data in the independent manual production history database and the second historical product industrial production data in the equipment-assisted production history database of each production executor can be indexed. The acquisition of the first historical product industrial production data and the second historical product industrial production data is used to measure the production efficiency of each production executor in independent production and equipment-assisted production in different production operations.

[0033] In a preferred embodiment, the production demand and flexible production process association information of each industrial product production type in the product industrial production demand list are considered, and an optimization solution model is constructed with the production efficiency jointly determined by independent manual production and equipment-assisted production within the production period as a constraint condition, and the minimum quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle as the optimization goal. The optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy steps, specifically including: S421: Considering the industrial product production quantity and industrial product production period of each industrial product production type in the product industrial production demand list, the production operation action group in the production operation data, and the number of standard guidance images for several production operation actions for industrial production auxiliary equipment; S422: Allocating each product industrial production order and each industrial production auxiliary equipment to a number of production execution personnel of the corresponding industrial production line as an allocation principle to perform optimal allocation solution; S423: The constraint condition is that the sum of the independent manual production efficiency determined during the industrial product production period by the production executor assigned to each product industrial production order who is not equipped with industrial production auxiliary equipment and the equipment-assisted production efficiency determined during the industrial product production period by the production executor assigned to each product industrial production order who is equipped with industrial production auxiliary equipment is greater than the production quantity of the industrial products corresponding to the industrial production order of the product. The optimization objective is to minimize the sum of the proportions of different production operation actions in the production operation action group when all production executors who are not equipped with industrial production auxiliary equipment execute every two adjacent product industrial production orders within the industrial production cycle, as the minimum quantitative value of the production learning cost. The independent manual production efficiency is calculated by multiplying the first production processing speed of the same production operation action group by the first duration of the industrial product production period by the production execution personnel assigned to each product industrial production order who are not equipped with industrial production auxiliary equipment in the first historical product industrial production data to obtain the independent manual production efficiency; The equipment-assisted production efficiency is calculated by multiplying the second production processing speed of the same production operation action group in the second historical product industrial production data by the production execution personnel assigned to each product industrial production order equipped with industrial production auxiliary equipment and the second duration of the auxiliary production period in the industrial product production period to obtain the equipment-assisted production efficiency; The auxiliary production period is configured as a period of time in which the industrial product production period excludes the non-auxiliary production period, and the duration of the non-auxiliary production period is obtained by matching the number of standard guidance images for industrial production auxiliary equipment for several production operation actions in the product industrial production order with a pre-configured mapping comparison table of the number of standard guidance images and the time consumption of equipment auxiliary model training; S424: Using an optimization algorithm to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy.

[0034] In this embodiment, by realizing the seamless application and connection of production auxiliary equipment under the intelligent production control system of the Industrial Internet of Things, the production energy efficiency of each production execution personnel for the production operation action group corresponding to different production and processing types when adopting independent production or auxiliary production is evaluated, the production demand of industrial production orders of different products and the capacity gap due to model training and deployment in the early stage of auxiliary production and the efficient output of auxiliary production in the later stage are taken into consideration. While improving the rationality and scientificity of the allocation of production and processing orders and production auxiliary equipment among multiple production lines, it also effectively eliminates the problem that the application of production auxiliary equipment has the characteristics of "no output in the early stage and high efficiency in the later stage". The impact of the phased characteristics of the production process on the continuity and efficiency-driven management, on this basis, through reasonable scheduling and allocation of product industrial production orders, ensure that the quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle is the lowest (that is, the production execution personnel who perform independent manual production should assign production tasks with more similar production operation action groups as much as possible, while the production execution personnel who perform equipment-assisted production should assign production tasks with greater differences in production operation action groups, and use the intelligent and high-precision characteristics of production auxiliary equipment to compensate for the impact of differences in the generation of operation action groups), which can alleviate the limitations of low product yield or high pigment scrap rate caused by differences in operation actions of different processed product types, and improve the overall energy efficiency of industrial production.

[0035] In a preferred embodiment, a mapping comparison table of the pre-configured number of standard guidance images and the equipment-assisted model training time is extracted and mapped and stored by calculating the average value of all equipment-assisted model training times for different numbers of standard guidance images in the historical equipment-assisted model training records.

[0036] In this embodiment, because production support equipment is assigned to different production executives during different production cycles, and their operating habits and product types vary, retraining and reconfiguration of the production support model is required. This training and configuration period is defined as the non-assisted production period, and the period after training and configuration is completed is defined as the assisted production period. The duration of the non-assisted production period can be calculated by calculating the average training time for all equipment-assisted models with the same number of standard guidance images in historical equipment-assisted model training records. For example, for an industrial production order with a product processing type involving five production operations, the production support equipment needs to be configured with a production support model that recognizes and locates standard guidance images captured in five different poses and generates production guidance information. This production support model generation requires labeling, training, and verification of sample images (e.g., 50,000 images) captured or enhanced in these five different poses. Based on the average training time for all equipment-assisted models with the same number of standard guidance images in historical equipment-assisted model training records, the non-assisted production period lasts for eight hours. The production executive produces no output during the first eight hours, but after eight hours, relying on production guidance information can achieve significantly higher efficiency than independent manual production.

[0037] In a preferred embodiment, the industrial production auxiliary equipment configuration sub-strategy is distributed to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform production operation steps for independent manual production or equipment-assisted production, specifically including: S61: Sending the industrial production auxiliary equipment configuration sub-strategy to several production line production edge execution terminals corresponding to each industrial production line; S62: driving the production execution personnel configured with the production edge execution terminal of the production line to use the production assistance model of the production assistance equipment to implement equipment-assisted production during the auxiliary production period of the industrial product production period; wherein the production assistance equipment imports the production assistance model completed by the auxiliary production support personnel during the non-auxiliary production period through standard guidance image acquisition, sample construction, and model training; S63: Driving the production execution personnel who are not equipped with the production line production edge execution terminal to achieve independent manual production when performing each production operation action.

[0038] In this embodiment, by issuing industrial production order allocation sub-strategies to the production edge management terminal of each production line, each industrial production line is driven to execute the corresponding product industrial production order. By issuing industrial production auxiliary equipment configuration sub-strategies to the production edge execution terminal of the production line, production execution personnel are driven to control production and processing equipment to perform independent manual production or equipment-assisted production operations, thereby realizing the seamless application and connection of production auxiliary equipment under the intelligent production control system of the Industrial Internet of Things, and improving the rationality and scientificity of the allocation of production and processing orders and production auxiliary equipment while improving the overall energy efficiency of industrial production.

[0039] Reference Figure 2 , Figure 2 This is a structural block diagram of an embodiment of the equipment intelligent operation system based on industrial Internet of Things cloud-edge collaboration of the present invention.

[0040] like Figure 2 As shown, the intelligent equipment operation system based on industrial Internet of Things cloud-edge collaboration proposed in an embodiment of the present invention includes: The receiving module 10 is used to receive product industrial production requests continuously uploaded by a number of request terminals, and generate product industrial production tasks for each industrial production cycle before each industrial production cycle; A construction module 20 is configured to extract a plurality of product industrial production orders from the product industrial production task, and construct a product industrial production demand list for the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order; The parsing module 30 is used to parse the production process information of each industrial product production type in the product industrial production demand list and generate flexible production process association information corresponding to each industrial product production type; Query module 40 is used to query industrial production resource information, consider the production requirements and flexible production process association information of each industrial product production type in the product industrial production requirement list, and solve the industrial production intelligent operation strategy for the industrial production cycle; wherein the industrial production intelligent operation strategy includes a product industrial production order allocation sub-strategy and an industrial production auxiliary equipment configuration sub-strategy; The issuing module 50 is used to issue the product industrial production order allocation sub-strategy to each production line production edge management terminal in the industrial production area, driving each industrial production line to execute the corresponding product industrial production order; The execution module 60 is used to send the industrial production auxiliary equipment configuration sub-strategy to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform independent manual production or equipment-assisted production operations.

[0041] Other embodiments or specific implementation methods of the intelligent operation system of equipment based on industrial Internet of Things cloud-edge collaboration of the present invention can refer to the above-mentioned method embodiments and will not be repeated here.

[0042] It should be understood that, in the description of this specification, reference to terms such as "one embodiment," "another embodiment," "other embodiments," or "first to Nth embodiments" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any appropriate manner in any one or more embodiments or examples.

[0043] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0044] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A device intelligent operation method based on industrial Internet of Things cloud-edge collaboration, characterized in that: For industrial production intelligent cloud, the method includes the following steps: Receive product industrial production requests continuously uploaded by several request terminals, and generate product industrial production tasks for each industrial production cycle before each industrial production cycle; Extracting several product industrial production orders from the product industrial production task, and constructing a product industrial production demand list for the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order; Analyze the production process information of each industrial product production type in the product industrial production demand list, and generate the flexible production process association information corresponding to each industrial product production type; Query industrial production resource information, consider the production demand and flexible production process association information of each industrial product type in the product industrial production demand list, and solve the industrial production intelligent operation strategy for the industrial production cycle; wherein, the industrial production intelligent operation strategy includes the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy; Send the product industrial production order allocation sub-strategy to each production line production edge management terminal in the industrial production area, driving each industrial production line to execute the corresponding product industrial production order; The industrial production auxiliary equipment configuration sub-strategy is sent to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform independent manual production or equipment-assisted production operations.

2. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 1 is characterized in that: Receive product industrial production requests continuously uploaded by several request terminals, and generate product industrial production task steps for the industrial production cycle before each industrial production cycle, specifically including: Receive product industrial production requests continuously uploaded by a plurality of request terminals, and extract product industrial production orders from each product industrial production request; wherein the product industrial production order records the industrial product production quantity, industrial product production type, and industrial product production period; Before each industrial production cycle, the industrial production orders of the products whose production time segments are included in the industrial production cycle are summarized to generate industrial production tasks for the products.

3. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 1 is characterized in that: Extracting several product industrial production orders from the product industrial production task, and constructing a product industrial production demand list for the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order, specifically including: Extracting several product industrial production orders from the product industrial production task, extracting the order content of the product industrial production orders, and obtaining production process information and production requirements for each industrial product production type; wherein the production process information includes production operation data, and the production requirements include industrial product production quantity and industrial product production time period; The production operation data contained in each product industrial production order is associated with the industrial product production quantity and industrial product production period in the product industrial production demand list of the constructed industrial production cycle and stored with the order identifier corresponding to the product industrial production order.

4. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 1 is characterized in that: The steps for parsing the production process information of each industrial product production type in the product industrial production demand list and generating the corresponding flexible production process association information for each industrial product production type include: Parsing the production process information of each industrial product production type in the product industrial production demand list, extracting the production operation action group and the number of standard guidance images for industrial production auxiliary equipment for several production operation actions from the production operation data of the production process information; Flexible production process association information is generated based on the production operation action group in the production operation data and the number of standard guidance images for industrial production auxiliary equipment for several production operation actions.

5. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 1 is characterized in that: Query industrial production resource information, consider the production demand and flexible production process association information of each industrial product type in the product industrial production demand list, and solve the industrial production intelligent operation strategy steps of the industrial production cycle, including: Querying industrial production resource information, and extracting manual production resources and industrial production auxiliary equipment resources from the industrial production resource information; Considering the production demand and flexible production process association information for each industrial product type in the product industrial production demand list, an optimization solution model is constructed, which uses the production efficiency determined by independent manual production and equipment-assisted production within the production period as a constraint condition, and takes the lowest quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle as the optimization goal. An optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy; Based on the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy, an industrial production intelligent operation strategy for the industrial production cycle is generated.

6. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 5 is characterized in that: The steps of querying industrial production resource information and extracting manual production resources and industrial production auxiliary equipment resources from the industrial production resource information specifically include: Query industrial production resource information, extract the personnel identifications of several production executives of each industrial production line, and use the personnel identifications to index data in an independent manual production history database or an equipment-assisted production history database; The first historical product industrial production data indexed to each production executive is extracted as a manual production resource, and the second historical product industrial production data on the industrial production auxiliary equipment that each production executive relies on is extracted as an industrial production auxiliary equipment resource.

7. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 6 is characterized in that: Considering the production demand and flexible production process association information of each industrial product production type in the product industrial production demand list, an optimization solution model is constructed with the production efficiency determined by independent manual production and equipment-assisted production within the production period as a constraint condition, and the minimum quantitative value of the production learning cost of independent manual production for different industrial product production types of product industrial production orders within the industrial production cycle as the optimization goal. The optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy steps, which include: Considering the industrial product production quantity of each industrial product production type in the product industrial production demand list and the industrial product production period and the production operation action group in the production operation data and the number of standard guidance images for several production operation actions for industrial production auxiliary equipment; Allocating each product industrial production order and each industrial production auxiliary equipment to a number of production execution personnel of the corresponding industrial production line is used as the allocation principle to solve the optimal allocation; The constraint condition is that the sum of the independent manual production efficiency determined during the industrial product production period by the production executors who are not equipped with industrial production auxiliary equipment and assigned to each product industrial production order and the equipment-assisted production efficiency determined during the industrial product production period by the production executors who are equipped with industrial production auxiliary equipment is greater than the production quantity of the industrial products corresponding to the industrial production order of the product. The optimization goal is to minimize the sum of the proportions of different production operation actions in the production operation action group when all production executors who are not equipped with industrial production auxiliary equipment execute every two adjacent product industrial production orders within the industrial production cycle, which is the lowest quantitative value of the production learning cost. The independent manual production efficiency is calculated by multiplying the first production processing speed of the same production operation action group by the first duration of the industrial product production period by the production execution personnel assigned to each product industrial production order who are not equipped with industrial production auxiliary equipment in the first historical product industrial production data to obtain the independent manual production efficiency; The equipment-assisted production efficiency is calculated by multiplying the second production processing speed of the same production operation action group in the second historical product industrial production data by the production execution personnel assigned to each product industrial production order equipped with industrial production auxiliary equipment and the second duration of the auxiliary production period in the industrial product production period to obtain the equipment-assisted production efficiency; The auxiliary production period is configured as a period of time in which the industrial product production period excludes the non-auxiliary production period, and the duration of the non-auxiliary production period is obtained by matching the number of standard guidance images for industrial production auxiliary equipment for several production operation actions in the product industrial production order with a pre-configured mapping comparison table of the number of standard guidance images and the time consumption of equipment auxiliary model training; An optimization algorithm is used to solve the product industrial production order allocation sub-strategy and the industrial production auxiliary equipment configuration sub-strategy.

8. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 7 is characterized in that: A mapping comparison table between the number of pre-configured standard guidance images and the training time of the device-assisted model is extracted and mapped and stored by calculating the average of all device-assisted model training times for different numbers of standard guidance images in the historical device-assisted model training records.

9. The device intelligent operation method based on industrial Internet of Things cloud-edge collaboration according to claim 1 is characterized in that: The industrial production auxiliary equipment configuration sub-strategy is distributed to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform production operation steps for independent manual production or equipment-assisted production, specifically including: Sending the industrial production auxiliary equipment configuration sub-strategy to several production line production edge execution terminals corresponding to each industrial production line; Driving the production execution personnel configured with the production edge execution terminal of the production line to use the production assistance model of the production assistance equipment to realize equipment-assisted production during the auxiliary production period of the industrial product production period; wherein, the production assistance equipment imports the production assistance model completed by the auxiliary production support personnel during the non-auxiliary production period through standard guidance image acquisition, sample construction and model training; Drive production execution personnel who are not equipped with the production line production edge execution terminal to achieve independent manual production when performing each production operation.

10. An intelligent equipment operation system based on industrial Internet of Things cloud-edge collaboration, characterized by: The system includes the following modules: A receiving module is used to receive product industrial production requests continuously uploaded by a number of request terminals, and generate product industrial production tasks for each industrial production cycle before each industrial production cycle; A construction module is used to extract a plurality of product industrial production orders from the product industrial production task, and to construct a product industrial production demand list of the industrial production cycle based on the production process information and production demand of each industrial product production type in each product industrial production order; A parsing module is used to parse the production process information of each industrial product production type in the product industrial production demand list and generate flexible production process association information corresponding to each industrial product production type; A query module is used to query industrial production resource information, consider the production requirements and flexible production process association information of each industrial product type in the product industrial production requirement list, and solve the industrial production intelligent operation strategy for the industrial production cycle; wherein the industrial production intelligent operation strategy includes a product industrial production order allocation sub-strategy and an industrial production auxiliary equipment configuration sub-strategy; A sending module is used to send the product industrial production order allocation sub-strategy to each production line production edge management terminal in the industrial production area, driving each industrial production line to execute the corresponding product industrial production order; The execution module is used to send the industrial production auxiliary equipment configuration sub-strategy to several production line production edge execution terminals corresponding to each industrial production line, driving the production execution personnel who configure the production line production edge execution terminals to perform independent manual production or equipment-assisted production operations.

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