Three-flow fusion-based full-industry-chain manufacturing modeling method

Abstract

The application relates to a full-industry-chain manufacturing modeling method based on three-flow fusion, which comprises the following steps: step S10, acquiring a material flow model, an energy flow model and an information flow model of a device layer, constructing a ubiquitous controller and fusing the material flow model, the energy flow model and the information flow model into a production process flow model; step S20, acquiring an order information flow model, a material transfer flow model and the production process flow model of a factory layer, constructing a group intelligence network controller and a micro-control cloud platform, and fusing the order information flow model, the material transfer flow model and the production process flow model into a material collaborative transfer flow model; and step S30, acquiring a production process information flow model, an industry shared value flow model and the material collaborative transfer flow model of an industry layer, constructing an industry intelligence connection platform and completing planning, scheduling and control of an industry chain. The application can improve the effect of field operation efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent manufacturing, and in particular to a full-industry-chain manufacturing modeling method based on three-flow fusion. BACKGROUND

[0002] Intelligent manufacturing plays an important role in improving production efficiency, optimizing resource utilization, improving product quality, realizing personalized production, promoting innovation and technological progress, and enhancing competitiveness and sustainable development, so it is one of the key directions to promote the transformation and upgrading of modern manufacturing.

[0003] In the field of industrial internet today, enterprises generally lack modeling awareness to optimize the behavior and performance of manufacturing systems and their various components, helping enterprises better understand and manage complex production systems, improve production efficiency, quality and flexibility. Therefore, it is very necessary to propose a modeling method with strong practicability and universal applicability in the field of industrial internet.

[0004] The modeling method in the prior art is often low in efficiency, fuzzy in hierarchical awareness, and difficult to use in actual scenarios. SUMMARY

[0005] To solve the technical problems existing in the prior art, the purpose of the present application is to provide a full-industry-chain manufacturing modeling method based on three-flow fusion, which can deeply schedule to the micro level of production task execution, realize high efficiency in the modeling process, improve hierarchical awareness, realize the improvement of basic capabilities of each level, reduce unnecessary waiting, improve the effect of field operation efficiency, and is beneficial to actual scene application.

[0006] To achieve the above application purpose, the present application provides a full-industry-chain manufacturing modeling method based on three-flow fusion, comprising the following steps:

[0007] Step S10, obtaining a material flow model, an energy flow model and an information flow model of the equipment layer, constructing a ubiquitous controller, and fusing the material flow model, the energy flow model and the information flow model into a production process flow model;

[0008] Step S20, obtaining an order information flow model, a material transfer flow model and the production process flow model of the factory layer, constructing a group intelligence network controller and a micro control cloud platform, and fusing the order information flow model, the material transfer flow model and the production process flow model into a material collaborative transfer flow model;

[0009] Step S30, obtaining a production process information flow model, an industry shared value flow model and the material collaborative transfer flow model of the industry layer, constructing an industry intelligence platform, and completing the planning, scheduling and control of the industry chain.

[0010] According to one of the technical solutions of the present application, in the step S10, specifically comprising:

[0011] Step S101, obtaining the basic process of product production, and constructing a material flow model of product production;

[0012] Step S102, constructing an energy flow model of product production based on the process and process parameters;

[0013] Step S103, constructing an information flow model of product production based on equipment sensing data;

[0014] Step S104, constructing a ubiquitous controller, and fusing the material flow model, the energy flow model and the information flow model into a production process flow model.

[0015] According to one of the technical solutions of the present application, in the step S20, further comprising: the crowd intelligence network controller and the micro-control cloud platform fuse the order information flow model, the material transfer flow model and the production process flow model to complete the planning, scheduling and control of the factory layer.

[0016] According to one of the technical solutions of the present application, the planning of the factory layer comprises:

[0017] Step S201, obtaining enterprise sales orders based on the order information flow model, decomposing the enterprise sales orders into production orders, and simultaneously judging whether the production capacity of the enterprise itself can meet the order requirements to complete order planning;

[0018] Step S202, decomposing the production orders into production plan sheets of each workshop and production line based on the product production quantity and the delivery contract target to complete contract planning;

[0019] Step S203, matching the corresponding process path based on the order quality requirement and the cost constraint to generate a production work order, and completing process planning.

[0020] According to one of the technical solutions of the present application, taking the production work order obtained by the planning of the factory layer as input, the scheduling of the factory layer comprises:

[0021] Step S204, constructing a process tree containing a discrete manufacturing process of a product to obtain a scheduling model with a process as a core and a constraint condition as an attribute, and completing production process scheduling;

[0022] Step S205, constructing an overall scheduling scheme based on the complexity of the material transfer process;

[0023] Step S206, in each round of scheduling process, synchronizing and matching the order, material and process information at the current time, outputting the start and end time of each process for each machining task, obtaining a Gantt chart in the process dimension, and completing the scheduling of the production process.

[0024] According to one technical solution of the present application, the Gantt chart obtained by scheduling of the factory layer is taken as input, and the control of the factory layer comprises:

[0025] In step S207, field material scheduling is performed in real time according to field production state, inventory and raw material state, and production efficiency;

[0026] In step S208, when product specification is switched, corresponding core process parameters are dynamically batch-matched according to quality requirements and process parameters, and process parameter configuration is completed;

[0027] In step S209, real-time data in the production process is monitored, device availability prediction and real-time disturbance monitoring are performed, factors affecting device availability are respectively judged, and when abnormal conditions that cannot be solved by functions such as field material scheduling and process parameter configuration occur, it is judged by manual or controller whether the scheduling result needs to be adjusted.

[0028] According to one technical solution of the present application, in the step S30, the industry intelligence platform completes planning, scheduling and control of the industry layer based on a production process information flow model, a material collaborative transfer flow model and an industry shared value flow model.

[0029] According to one technical solution of the present application, the planning of the industry layer comprises:

[0030] In step S301, the matching degree between industrial production capacity and order requirements is preliminarily judged by the production process information flow model, and an order reply of accepting the order, partially accepting the order or refusing the order is made.

[0031] In step S302, the existing inventory state of the industry and the accessibility of materials are obtained based on the material collaborative transfer flow model, and a rough-granularity material demand plan is preliminarily matched by the material collaborative transfer flow model.

[0032] In step S303, the whole value of the industry is increased by sharing key production links.

[0033] In step S304, the production process information flow model, the material collaborative transfer flow model and the industry shared value flow model are fused to form an industry-level production process model, and decomposition from a series / batch order to an enterprise pre-sales order is completed.

[0034] According to one technical solution of the present application, the enterprise pre-sales order is taken as input, and the scheduling of the industry layer comprises:

[0035] In step S305, a group decision game model with enterprise benefits as the core is constructed based on the production process information flow model, the material collaborative transfer flow model and the industry shared value flow model.

[0036] Step S306, forming the group feedback opinions of negotiation based on the opinions of the multiple enterprises on the current order distribution;

[0037] Step S307, using the group decision model, coordinating and optimizing by means of the global information at the current time, and then forming the group decision result, and converting the decision result into a new enterprise pre-sale order pool.

[0038] According to one of the technical solutions of the present application, the control of the industry layer comprises:

[0039] When the abnormal situation occurs, the enterprise manager intervenes to handle the abnormal situation;

[0040] When the enterprise cannot solve the abnormal situation by itself, it can report to the industry intelligence platform, and based on the planning and scheduling of the industry layer, the enterprise sales order is re-distributed;

[0041] Among them, the abnormal situation includes:

[0042] The ordered enterprise has already exceeded the period or has a great possibility of exceeding the period in the production process;

[0043] The enterprise is unable to complete the scheduling of the required materials subjectively or objectively, and needs the help or re-distribution of the order of the whole industry;

[0044] The production quality of the enterprise changes obviously, resulting in that the product quality and value cannot reach the expectation;

[0045] The prices of raw materials and finished products fluctuate greatly, resulting in that the enterprise and the industry value are obviously affected.

[0046] According to one aspect of the present application, an electronic device is provided, comprising one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected with the memory, and the one or more computer programs are stored in the memory, and when the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes the three-flow fusion based whole industry chain manufacturing modeling method according to any one of the above technical solutions.

[0047] According to one aspect of the present application, a computer readable storage medium is provided for storing computer instructions, and when the computer instructions are executed by a processor, the three-flow fusion based whole industry chain manufacturing modeling method according to any one of the above technical solutions is realized.

[0048] Compared with the prior art, the present application has the following beneficial effects:

[0049] The application provides a full-industry-chain manufacturing modeling method based on three-flow fusion, which realizes the three-element control of robot controller data flow control, process control and motion control at the equipment layer, fuses a material flow model, an energy flow model and an information flow model in a production process to form an equipment-level production process flow model combined with industrial knowledge, fuses an order information flow model, a material transfer flow model and a production process flow model at the factory layer, forms a transparent factory-level material collaborative transfer flow model combined with the collaborative mechanism between industry knowledge and upstream and downstream processes, fuses a production process information flow model, an industry shared value flow model and the material collaborative transfer flow model at the industry layer, obtains an industry chain resource sharing model constructed based on distributed swarm intelligence, and forms a distributed industrial Internet architecture from bottom to top, which can be deep into the microscopic level of production task execution, realizes high efficiency in the modeling process, improves the hierarchical consciousness, realizes the improvement of the basic ability of each level, reduces unnecessary waiting, improves the effect of field operation efficiency, and is beneficial to practical scene application. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0051] Figure 1 A flow chart schematically showing a full-industry-chain manufacturing modeling method based on three-flow fusion provided in an embodiment of the present application;

[0052] Figure 2 A planning process schematically showing a three-flow fusion static perspective at the factory layer in the embodiment of the present application;

[0053] Figure 3 A planning process schematically showing a three-flow fusion dynamic perspective at the factory layer in the embodiment of the present application;

[0054] Figure 4 A manufacturing process schematically showing three products in the embodiment of the present application;

[0055] Figure 5 A process flow site layout view schematically showing the embodiment of the present application;

[0056] Figure 6 A factory layer control flow schematically showing the embodiment of the present application;

[0057] Figure 7Schematically represent the plant layer exception handling process in the embodiment of the application;

[0058] Figure 8 Schematically represent the plant layer three-flow fusion process in the embodiment of the application;

[0059] Figure 9 Schematically represent the industry layer planning process in the embodiment of the application;

[0060] Figure 10 Schematically represent the industry layer scheduling process in the embodiment of the application;

[0061] Figure 11 Schematically represent the industry layer control process in the embodiment of the application;

[0062] Figure 12 Schematically represent the industry layer three-flow fusion process in the embodiment of the application. DETAILED DESCRIPTION

[0063] The description of the embodiments of this specification should be combined with the corresponding drawings, which should be considered as part of the complete specification. In the drawings, the shape or thickness of the embodiments can be exaggerated and simplified or facilitated for illustration. Furthermore, parts of the structures in the drawings will be described separately, and it should be noted that the elements not shown or not described by text in the drawings are in the form known to those skilled in the art.

[0064] The description of the embodiments herein, any reference to direction and orientation, is only for the convenience of description, and cannot be understood as any limitation on the scope of protection of the application. The following description of the preferred embodiments will involve combinations of features, which can exist independently or in combination, and the application is not particularly limited to the preferred embodiments. The scope of the application is defined by the claims.

[0065] As shown in Figure 1 A three-flow fusion-based whole-industry-chain manufacturing modeling method of the application includes the following steps:

[0066] Step S10, acquire the material flow model, energy flow model and information flow model of the equipment layer, construct the ubiquitous controller, and fuse the material flow model, energy flow model and information flow model into a production process flow model;

[0067] Step S20, acquire the order information flow model, material transfer flow model and production process flow model of the plant layer, construct the swarm intelligence network controller and micro-control cloud platform, and fuse the order information flow model, material transfer flow model and production process flow model into a material collaborative transfer flow model;

[0068] Step S30, obtaining the production process information flow model, the industry shared value flow model and the material collaborative transfer flow model of the industry layer, constructing the industry intelligence platform, and completing the planning, scheduling and control of the industry chain.

[0069] By realizing the ternary control of the robot controller data flow control, process control and motion control in the equipment layer, and fusing the material flow model, energy flow model and information flow model in the production process, the equipment-level production process flow model combined with industrial knowledge is formed; by fusing the order information flow model, material transfer flow model and production process flow model in the factory layer, and combining the collaborative mechanism between the industry knowledge and upstream and downstream processes, the transparent factory-level material collaborative transfer flow model is formed; by fusing the production process information flow model, the industry shared value flow model and the material collaborative transfer flow model in the industry layer, the industry chain resource sharing model based on the distributed swarm intelligence is obtained, and the industrial models at each level constitute the core components of the distributed industrial PaaS layer, which provides favorable support for the distributed industrial SaaS layer, and then the distributed industrial internet architecture is formed from bottom to top, which can deeply schedule to the microscopic level of production task execution, realize high efficiency in the modeling process, improve the level consciousness, realize the improvement of the basic ability of each level, reduce unnecessary waiting, improve the effect of field operation efficiency, and is beneficial to actual scene application.

[0070] In an embodiment of the present application, preferably, in the step S10, specifically comprising:

[0071] Step S101, obtaining the basic process of product production, and constructing a material flow model of product production;

[0072] Step S102, constructing an energy flow model of product production based on the process and process parameters;

[0073] Step S103, constructing an information flow model of product production based on equipment perception data;

[0074] Step S104, constructing a ubiquitous controller, and fusing the material flow model, the energy flow model and the information flow model into a production process flow model.

[0075] Through the above technical solution, the ubiquitous controller carrying the basic carrier of the three-flow fusion in the control layer is obtained, the traditional motion control / logic control is changed into the ternary control of the data flow control, process control and motion control through the three-flow fusion, which is beneficial to implanting the process model into the bottom control closed loop, configuring the production process flow model in the control software architecture in the form of “plug-in” constraint solver, generating the control target in real time at the control closed loop level, and forming the multi-level real-time control with the production equipment itself independent controller, perfecting and optimizing the existing device control method, and improving the intelligent degree of the production equipment.

[0076] AsFigure 8 As shown, in one embodiment of the present application, preferably, in the step S20, the crowd intelligence network controller and the micro-control cloud platform further complete the planning, scheduling and control of the factory layer based on the order information flow model, the material transfer flow model and the production process flow model.

[0077] In this embodiment, the crowd intelligence network controller and the micro-control cloud are basic carriers for carrying out the three-flow fusion of the factory layer, aiming to realize the integration of the production process, and to complete the planning, scheduling and control of the factory layer. The planning refers to the process of generating production work orders from sales orders through order planning, contract planning and process planning, solving the problems of what to produce, how much to produce and in what time period to produce. The scheduling refers to the process of generating device-level executable production plans (Gantt chart) from production work orders, solving the problem of how to produce. The control refers to the process of on-site material scheduling, process parameter configuration and exception handling when production activities are carried out according to the production plan, solving the problem of on-site production.

[0078] In one embodiment of the present application, preferably, the planning of the factory layer includes:

[0079] Step S201, obtaining enterprise sales orders based on the order information flow model, and decomposing the enterprise sales orders into production orders, while judging whether the production capacity of the enterprise itself can meet the order requirements, to complete order planning;

[0080] Step S202, decomposing the production orders into production plan sheets of each workshop and production line based on product production quantity and delivery contract targets, to complete contract planning.

[0081] Step S203, matching corresponding process paths based on order quality requirements and cost constraints, to generate production work orders, and complete process planning.

[0082] In this embodiment, the planning of the factory layer is used to solve the problems of what to produce, how much to produce and in what time period to produce, and is divided into order planning, contract planning and process planning. The order planning refers to the process of decomposing enterprise sales orders into production orders, while judging whether the production capacity of the enterprise itself can meet the order requirements. The contract planning refers to the process of decomposing production orders into production plan sheets of each workshop and production line, considering product production quantity and delivery contract targets. The process planning refers to the process of matching corresponding process paths based on order quality requirements and cost constraints, to generate production work orders.

[0083] In the process of decomposing sales order, firstly, the problem of whether it can be produced is judged, that is, the enterprise production capacity is judged by referring to internal and external quality standards, production process parameters and process path. At the same time, considering the indexes such as material specification, material accessibility, inventory situation, etc., whether outsourcing production is needed is judged, and the overall material demand plan is generated. Finally, through the operation of splitting and combining orders, the production order set is formed. In summary, order planning is the process of generating master production plan (i.e. enterprise production order pool) from sales order, outsourcing order, and overall MRP.

[0084] In the process of decomposing the master production plan, according to the production capacity, production resources, etc. of each workshop and production line, the order delivery date, line-level process model, raw material and inventory situation, etc. are taken as constraints, and the target of balancing the production capacity of each process is achieved through production planning of each workshop and production line under the premise of ensuring the order delivery date. In summary, contract planning is the process of decomposing the master production plan (i.e. enterprise production order pool) into production plan sheets of each workshop and production line, while generating part of outsourcing orders and MRP of fine granularity (workshop and production line level).

[0085] According to the quality and process requirements in the production plan sheet, the production cost and production capacity are comprehensively considered, the process path for the specific production plan sheet is matched, and the production job list (JobList) facing the processing equipment is generated, such as the spinning and sizing in the textile industry, and the pouring and furnace plan in the steel industry. In summary, process planning is the process of matching the corresponding processing process from the production plan sheet, and then generating the production job list.

[0086] As shown in Figure 2 , firstly, from the static perspective, the planning processes are seen: (1) in the order planning process, the considered order information, material information, process information are sales order requirements, material accessibility and inventory status, enterprise process capacity; (2) in the contract planning process, the considered order information, material information, process information are product quantity and delivery date in the order, production raw material and inventory status, process capacity of workshop or production line; (3) in the process planning process, the considered order information, material information, process information are, material accessibility and inventory status, enterprise process capacity. Under the static perspective, as the sales order is gradually decomposed into production job list, order information, material transportation and production process are also decomposed and refined layer by layer.

[0087] As shown in Figure 3 , with the passage of time, sales orders continue to enter the system and the above planning behaviors occur, that is, sales orders are continuously decomposed into production job lists. In this process, order information, material transportation and production process also dynamically change, forming information flow, logistics and process flow respectively. It can be formally expressed as:

[0088] 1) Information flow = order information (t); 2) Material flow = material information (t); 3) Process flow = process information (t)

[0089] In the planning process of each round, the function that the planning model needs to achieve is to synchronize and match the order information, material transfer and production process at the current time. Thus, a three-flow fusion model of the chapter bee layer planning function is formed.

[0090] Under the action of the three-flow fusion-based planning model, the sales order forms outsourcing orders, material requirement plans MRP and production work orders of each workshop line through the planning function. The production work order is the input of the factory layer scheduling.

[0091] In an embodiment of the present application, preferably, the production work order obtained by the planning of the factory layer is taken as the input, and the factory layer scheduling includes:

[0092] Step S204, constructing a process tree of the discrete manufacturing process of the product to obtain a scheduling model with a process as the core and a constraint condition as the attribute, and completing the production process scheduling;

[0093] Step S205, constructing an overall scheduling scheme based on the complexity of the material transfer process;

[0094] Step S206, in the scheduling process of each round, synchronizing and matching the order, material and process information at the current time, outputting the start and end times of each process for each processing task, obtaining a Gantt chart in the process dimension, and completing the scheduling of the production process.

[0095] In this embodiment, the production work order is taken as the input for the factory layer scheduling, and the problem of how to produce is solved, that is, the process of arranging and combining the production work order and optimizing the production sequence and time.

[0096] First, an abstract description of the discrete manufacturing process of each product is provided: a process tree. The process tree is a tree data structure, which describes the upstream and downstream relationships of multiple process nodes in the manufacturing process and related process parameters. The edge connecting two nodes represents the material, information and process flow relationship between the two process nodes. The process tree can be extracted from the PLM system; for enterprises that do not deploy the PLM system, a graphical process tree configuration tool can be provided. It can be compared to an executable file of a software program, which provides a static description of the process.

[0097] The process tree is shown in Figure 4 The collected nodes usually represent that the node contains an assembly process. Similarly, the manufacturing processes of the three products also have a view superimposed on the factory site layout, as shown in Figure 5 Figure 5 ​The abstract tree diagram shows the flow of materials and information in the field device. Such an abstract tree diagram constitutes the core part of the production process model (PPM), that is, a scheduling model taking the process as the core and other constraints (such as capacity and processing time) as attributes. The process model is a concentrated embodiment of the scheduling layer process information.

[0098] There are two processing modes for logistics. When the logistics process itself is not complex, or the logistics scheduling detail information cannot be obtained, the logistics process itself can be abstracted as a process, which is homogenized with the generated process and is also reflected in the PPM model. When the logistics process itself is complex and important, for example, the scheduling of important buffer zones and the scheduling of AGVs in the field, a system can be independently designed to connect upstream and downstream processes through a system interface to form an overall scheduling scheme.

[0099] From the optimization point of view, in each round of scheduling process, the scheduling and dispatching model synchronizes and matches the current time order, material and process information, that is, constitutes the job shop scheduling problem (which can be divided into job shop, flow shop or open shop) and the like. The output result is the start and end time of each process for each processing task, that is, the Gantt chart of the process dimension. Taking the dynamic order information flow as the input, using the same logic as the planning layer, the logistics information and process information are added with the "time-varying part", so as to form a three-flow integration model of the scheduling function of the chapter bee layer.

[0100] Under the action of the three-flow integration scheduling model, the production order is finally formed into a device-level executable production plan Gantt chart through the scheduling and dispatching function, and serves as the input of the control layer.

[0101] As shown in Figure 6 In one embodiment of the present application, preferably, the Gantt chart obtained by scheduling of the factory layer is taken as the input, and the control of the factory layer comprises:

[0102] In step S207, the field material scheduling is performed in real time according to the field production state, the inventory and raw material state and the production efficiency.

[0103] In step S208, when the product specification is switched, the corresponding core process parameters are dynamically batch-matched according to the quality requirements and process parameters, and the process parameter configuration is completed.

[0104] In step S209, the real-time data in the production process is monitored, the device availability prediction and real-time disturbance monitoring are performed, the factors affecting the device availability are judged respectively, and when abnormal conditions that cannot be solved by the field material scheduling and process parameter configuration functions occur, it is judged by the human or the controller whether the scheduling result needs to be adjusted.

[0105] In this embodiment, the control at the factory level uses the production plan Gannt chart as input to solve problems such as material scheduling at the workshop and production line, batch configuration of order-driven process parameters, and how to adjust the production plan after abnormal situations occur during production.

[0106] The three core functions of control at the factory level focus on logistics control, process flow control, and information flow control, respectively. When abnormal situations on-site prevent the achievement of the production plan, a feedback loop is established to relay the abnormal information to the scheduling or planning layer, thereby adjusting the global production plan. Control can also be expressed as dynamic scheduling, which inherently possesses dynamic and real-time attributes.

[0107] For anomaly handling, real-time data from the production process can be monitored. Through equipment availability prediction and real-time disturbance monitoring, factors affecting equipment availability can be identified, such as remaining tool life, equipment operating status, and equipment processing capacity, as well as real-time disturbance factors like emergency order inquiries, material delays, and significant changes in processing time. When anomalies arise that cannot be resolved by on-site material scheduling or process parameter configuration functions, manual intervention or the controller determines whether adjustments to the scheduling results are necessary. If adjustments are deemed necessary, a fine-tuning mechanism is first attempted, such as shifting abnormal work orders to the right or rejecting order insertions, followed by evaluation of the fine-tuning. If the evaluation fails to meet scheduling requirements, a complete rescheduling is performed. This constitutes a dynamic, real-time adjustment feedback closed-loop control loop.

[0108] like Figure 7 As shown, the models of on-site material scheduling, process parameter configuration, and anomaly handling together form the three-flow fusion model of the Zhangfeng layer control function. Its fusion is reflected in real-time monitoring of on-site dynamics and determining whether there are abnormal situations that cannot be resolved by functions such as logistics scheduling and parameter configuration.

[0109] like Figure 12 As shown, in one embodiment of the present invention, preferably, in step S30, the industrial intelligent interconnection platform completes the planning, scheduling and control of the industrial layer based on the production process information flow model, the material collaborative transfer flow model and the industrial shared value flow model.

[0110] In this embodiment, the integration of the three flows at the industrial layer is an industrial value sharing system based on the information flow of the production process, the collaborative material transfer flow, and the shared value flow of the industry, with the industrial intelligent interconnection platform serving as the basic carrier for the integration of the three flows at the industrial layer;

[0111] (2) Technological path of transformation: Industrial value sharing system.

[0112] The industry value sharing system consists of three types of capabilities: industry-level planning, industry-level scheduling, and industry-level control.

[0113] The planning of the industry layer refers to a process of distributing the series orders and the bulk orders of an industry to the enterprises and shared factories that match the production capacity, and finally completing the decomposition from the series / bulk orders to the enterprise pre-sales orders; the scheduling of the industry layer takes the enterprise pre-sales orders as the input, and finally generates the enterprise sales orders through multiple negotiations and games among the enterprises; and the control of the industry layer refers to the dynamic processing of abnormal situations in the process of planning and producing the enterprise sales orders.

[0114] The industry value sharing system mainly enables two types of industrial structures: (1) an industrial aggregation zone form, that is, a collection of enterprises facing the same type of products, and the enterprises have cooperative and competitive relationships; and (2) a supply chain with a leading enterprise as the core, including the upstream and downstream supply chains thereof, and the cooperation among multiple large factories within the leading enterprise. For the leading enterprise, the cooperation among the multiple large factories within the leading enterprise is equivalent to a small “industrial aggregation zone”, and the planning, scheduling and control modes thereof are the same as those of the “industrial aggregation zone”, except for the difference in scale and granularity; for the cooperation of the upstream and downstream supply chains, it is equivalent to a “industrial aggregation zone” with closer relationships and stronger rules, and it mainly focuses on the cooperation of the upstream and downstream enterprises. Therefore, the planning, scheduling and control of the “industrial aggregation zone” structure are introduced below to embody the three-flow integration mechanism of the industry layer.

[0115] As shown in FIG. 1, in one embodiment of the present application, preferably, the planning of the industry layer comprises: Figure 9

[0116] Step S301: preliminarily judging the matching degree between the production capacity of the industry and the order requirements through the production process information flow model, and making a reply of accepting the order, partially accepting the order or refusing to accept the order;

[0117] Step S302: obtaining the existing inventory state of the industry and the accessibility of the materials based on the material collaborative transfer flow model, and preliminarily matching the coarse-grained material demand plan through the material collaborative transfer flow model;

[0118] Step S303: realizing the overall value growth of the industry by sharing the key production links;

[0119] Step S304: integrating the production process information flow model, the material collaborative transfer flow model and the industry shared value flow model to form an industry-level production process model, and completing the decomposition from the series / bulk orders to the enterprise pre-sales orders.

[0120] In the planning process of the industry layer, the production process information flow, the material collaborative transfer flow and the industry shared value flow are integrated to form an industry-level production process model PPM, and the pre-sales orders are distributed to the enterprises through the industry layer planning model.

[0121] ​The production process information flow contains important information in the industry set and batch order, including product, quantity, quality requirement, delivery date, etc. Meanwhile, it contains production capacity information of each enterprise (or core enterprise), including product type, product quality, enterprise history evaluation, production capacity, production cycle, etc. The material collaborative transfer flow contains the existing inventory state of the industry and the accessibility of the material. The inventory state can be obtained by aggregating the inventory quantity of each enterprise (or each core enterprise). The material accessibility is the coarse-grained material demand calculated according to the order information, and the material arrival time is estimated according to the inventory information, procurement cycle, etc. The industry shared value flow is the overall value growth process of the industry realized by sharing the key production link. In actual implementation, there are two feasible modes. One is to establish a shared factory for key common links, expand the production batch, unify the production mode, and utilize the industry advantage resources to achieve the effect of reducing the cost, improving the quality and increasing the efficiency of the key process, such as the finger joint plate material in furniture production. The second is that enterprises spontaneously share the surplus production capacity to achieve the overall production capacity balance of the industry. It should be noted that the spontaneous sharing of production capacity by enterprises usually needs to be combined with the "scheduling" function.

[0122] In addition, the meaning of the "flow" at the industry level is similar to that at the factory level, that is, the order / production capacity, material, and value information will dynamically change with the order access and time elapse, and have time sequence characteristics, which will not be repeated here.

[0123] The industry-level PPM model is similar to the factory-level PPM model, and can also be expressed by a tree structure, which is formed by the fusion of information in the three flows, that is, the three-flow fusion of the planning function at the industry level. After generating the industry-level production process model, the model can be iteratively optimized by a search method to decompose into pre-sales orders of each enterprise as the input of the scheduling layer.

[0124] As shown in FIG. 6, in one embodiment of the present application, preferably, the scheduling of the industry level includes: Figure 10

[0125] Step S305, based on the production process information flow model, the material collaborative transfer flow model, and the industry shared value flow model, a group decision game model with enterprise benefits as the core is constructed;

[0126] Step S306, based on the opinions of multiple enterprises on the current order distribution, a negotiated group feedback opinion is formed;

[0127] Step S307, using the group decision model, the global information at the current time is used for coordination and optimization, and then a group decision result is formed, and the decision result is converted into a new enterprise pre-sales order pool.

[0128] ​In this embodiment, the scheduling of the industry layer takes enterprise pre-sales orders as input, and through multiple negotiations and games among enterprises, enterprise sales orders that match the capacity are finally generated. In the scheduling process, by fusing the production process information flow model, the material collaborative transfer flow model, and the industry shared value flow model, a group decision game model is formed with enterprise benefits as the core, and the maximization of enterprise self-interest is taken as the "local interaction rule". Combined with the information sharing of the industry layer, a group wisdom decision mechanism is formed.

[0129] At the scheduling level, the production process information flow refers to important information in the enterprise pre-sales order, including product, quantity, quality requirements, delivery time, etc.; the material collaborative transfer flow refers to the inventory status of the industry and the enterprise; and the industry shared value flow refers to the goal of each negotiation and game, which is to maximize the self-interest under the current state. Here, the meaning of "flow" is the same as before, and the three-flow fusion of the scheduling function of the industry layer generates a group decision model, that is, in each negotiation process, each enterprise conducts game with the guidance of maximizing its own value, and then the industry optimizes the coordination based on the global shared information.

[0130] As shown in Figure 10 , in the scheduling process of the industry layer, multiple negotiations and feedbacks are needed based on the pre-sales order. In one negotiation process, the enterprise as an individual proposes opinions on the current order allocation (which can be between enterprises or between the enterprise and the industry), and finally forms an opinion pool to form the group feedback opinions of this negotiation; then through the three-flow fusion group decision model, the global information at the current time is used for coordination and optimization, and then the group decision result is formed; finally, the decision result is converted into a new enterprise pre-sales order pool through the industry scheduling model. After multiple feedback negotiations, a consensus path will finally appear, and according to the path, the enterprise sales order of each enterprise is formed.

[0131] As shown in Figure 11 , in one embodiment of the present application, preferably, the control of the industry layer comprises:

[0132] When an abnormal situation occurs, the enterprise manager intervenes to handle the abnormal situation;

[0133] When the enterprise cannot solve the abnormal situation by itself, it can report to the industry intelligence platform, and based on the planning and scheduling of the industry layer, the enterprise sales order is re-allocated;

[0134] Among them, the abnormal situation includes:

[0135] The ordered enterprise has already exceeded the period or has a great possibility of exceeding the period in the production process;

[0136] The enterprise cannot subjectively or objectively complete the scheduling of the materials required for production, and needs the overall industry to provide help or reallocate orders;

[0137] The production quality of the enterprise changes significantly, resulting in the product quality and value not meeting expectations;

[0138] The prices of raw materials and finished products fluctuate greatly, resulting in the value of the enterprise and the industry being significantly affected.

[0139] According to an aspect of the present application, an electronic device is provided, comprising one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected with the memory, and the one or more computer programs are stored in the memory, and when the electronic device is running, the processor executes the one or more computer programs stored in the memory, so that the electronic device executes a three-flow fusion-based whole-industry-chain manufacturing modeling method according to any of the above technical solutions.

[0140] The memory can be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device, in some embodiments. The memory can also be an external storage device of the electronic device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., in other embodiments. Further, the memory can include both the internal storage unit and the external storage device of the electronic device. The memory is used to store an operating system, application programs, a boot loader, data, and other programs, such as program codes of the computer programs, etc. The memory can also be used to temporarily store data that has been output or will be output.

[0141] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or can also be any conventional processor.

[0142] According to one aspect of the present application, a computer readable storage medium is provided for storing computer instructions which, when executed by a processor, implement a three-flow fusion based full industry chain manufacturing modeling method according to any of the above technical solutions.

[0143] The computer readable storage medium can include any medium capable of storing or transmitting information. Examples of the computer readable storage medium include electronic circuits, semiconductor memory systems, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, and the like. The code segments can be downloaded via a computer network such as the Internet, an intranet, or the like.

[0144] The three-flow fusion based full industry chain manufacturing modeling method according to the present application includes: step S10, obtaining a material flow model, an energy flow model and an information flow model of a device layer, constructing a ubiquitous controller, and fusing the material flow model, the energy flow model and the information flow model into a production process flow model; step S20, obtaining an order information flow model, a material transfer flow model and the production process flow model of a factory layer, constructing a swarm intelligence network controller and a micro control cloud platform, and fusing the order information flow model, the material transfer flow model and the production process flow model into a material collaborative transfer flow model; and step S30, obtaining a production process information flow model, an industry shared value flow model and the material collaborative transfer flow model of an industry layer, constructing an industry intelligence connection platform, and completing planning, scheduling and control of an industry chain. Through the ternary control of robot controller data flow control, process control and motion control at the device layer, the material flow model, the energy flow model and the information flow model in the production process are fused to form a device-level production process flow model combined with industrial knowledge. At the factory layer, the order information flow model, the material transfer flow model and the production process flow model are fused to form a transparent factory-level material collaborative transfer flow model combined with the collaborative mechanism between the industry knowledge and the upstream and downstream processes. At the industry layer, the production process information flow model, the industry shared value flow model and the material collaborative transfer flow model are fused to obtain an industry chain resource sharing model constructed based on distributed swarm intelligence. The industrial models at each level constitute the core components of the distributed industrial PaaS layer, provide favorable support for the distributed industrial SaaS layer, and then form a distributed industrial internet architecture from bottom to top. The scheduling can be deepened to the microscopic level of production task execution, high efficiency is achieved in the modeling process, the level consciousness is improved, the basic capabilities at each level are improved, unnecessary waiting is reduced, the efficiency of on-site operation is improved, and the actual scene application is facilitated.

[0145] Moreover, it is noted that the application can be provided as a method, an apparatus or a computer program product. Therefore, the application embodiments can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the application embodiments can take the form of a computer program product on one or more computer-usable storage media (including disks, diskettes, tapes, optical, solid storage, etc.) embodying computer-readable instructions.

[0146] The application embodiments are described with reference to the flowchart illustrations and / or block diagrams of the methods, terminal systems (systems), and computer program products according to the application embodiments. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing terminal system to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal system, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0147] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing terminal system to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0148] It is also noted that the term "comprising" or "including" or any other variant thereof is intended to cover non-exclusive inclusions, such that processes, methods, articles, or terminal systems that comprise a list of elements do not include only those elements in the list, but can also include other elements not expressly listed or inherent to such processes, methods, articles, or terminal systems. Without limitation, an element preceded by "comprises... a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or terminal system that includes the element.

[0149] Finally, it should be noted that the above description is of preferred embodiments of the application, and that although preferred embodiments of the application have been described, numerous changes and modifications can be made to the preferred embodiments without departing from the principles of the application, and that such changes and modifications are contemplated as falling within the scope of the application. Accordingly, the appended claims are intended to embrace all such changes and modifications.

Claims

1. A whole-industry chain manufacturing modeling method based on the integration of three flows (flow, information, and logistics), characterized in that, Includes the following steps: Step S10: Obtain the material flow model, energy flow model, and information flow model of the equipment layer, construct a ubiquitous controller, and integrate the material flow model, energy flow model, and information flow model into a production process flow model; Step S20: Obtain the order information flow model, material transfer flow model, and production process flow model at the factory level; construct a swarm intelligence network controller and a micro-control cloud platform; and integrate the order information flow model, material transfer flow model, and production process flow model into a material collaborative transfer flow model. Step S30: Obtain the production process information flow model, industry shared value flow model, and material collaborative transfer flow model of the industry layer, construct an industry intelligent interconnection platform, and complete the planning, scheduling, and control of the industrial chain; In step S30, the industrial intelligent interconnection platform completes the planning, scheduling, and control of the industrial layer based on the production process information flow model, the material collaborative transfer flow model, and the industrial shared value flow model. The planning for the industrial layer includes: Step S301: Use the production process information flow model to initially determine the degree of matching between the industry's production capacity and order requirements, and respond with "accept order," "partially accept order," or "reject order." Step S302: Obtain the current inventory status and material availability of the industry based on the material collaborative transfer flow model, and initially match the coarse-grained material demand plan through the material collaborative transfer flow model; Step S303: Achieve overall industrial value growth by sharing key production processes; Step S304: Integrate the production process information flow model, the material collaborative transfer flow model, and the industry shared value flow model to form an industry-level production process model, and complete the decomposition from kit / batch orders to enterprise pre-sale orders.

2. The whole-industry chain manufacturing modeling method based on the fusion of three flows as described in claim 1, characterized in that, Step S10 specifically includes: Step S101: Obtain the basic manufacturing process of the product and construct a material flow model for product manufacturing; Step S102: Based on the process and process parameters, construct an energy flow model for product manufacturing; Step S103: Based on the equipment sensing data, construct an information flow model for product production; Step S104: Construct a ubiquitous controller to integrate the material flow model, energy flow model, and information flow model into a production process flow model.

3. The full-industry chain manufacturing modeling method based on the fusion of three flows as described in claim 1, characterized in that, Step S20 further includes: the swarm intelligence network controller and the micro-control cloud platform integrate the order information flow model, the material transfer flow model and the production process flow model to complete the planning, scheduling and control of the factory layer.

4. The full-industry chain manufacturing modeling method based on the fusion of three flows as described in claim 3, characterized in that, The planning of the factory layer includes: Step S201: Obtain enterprise sales orders based on the order information flow model, decompose enterprise sales orders into production orders, and at the same time determine whether the enterprise's own production capacity can meet the order requirements to complete order planning; Step S202: Based on the product production volume and delivery contract targets, break down the production orders into production plans for each workshop and production line to complete the contract planning; Step S203: Based on the order quality requirements and cost constraints, match the corresponding process path, generate a production work order, and complete the process planning.

5. The full-industry chain manufacturing modeling method based on the fusion of three flows as described in claim 4, characterized in that, Using the production work orders obtained from the planning at the factory level as input, the scheduling at the factory level includes: Step S204: Construct a process tree containing the discrete manufacturing process of the product to obtain a scheduling model with the process as the core and the constraints as the attributes, and complete the production process scheduling. Step S205: Based on the complexity of the material transfer process, construct an overall scheduling scheme; Step S206: In each round of scheduling, synchronize and match the current order, material, and process information, output the start and end times of each process for each processing task, obtain the Gantt chart of the process dimension, and complete the scheduling of the production process.

6. The full-industry chain manufacturing modeling method based on the fusion of three flows as described in claim 5, characterized in that, Using the Gantt chart obtained from the scheduling of the factory layer as input, the control of the factory layer includes: Step S207: Based on the on-site production status, inventory and raw material status, and production efficiency, conduct on-site material scheduling in real time; Step S208: When product specifications are switched, the corresponding core process parameters are dynamically matched in batches according to quality requirements and process parameters to complete the process parameter configuration. Step S209: Monitor real-time data during the production process. Through equipment availability prediction and real-time disturbance monitoring, determine the factors affecting equipment availability. When abnormal situations occur that cannot be resolved by on-site material scheduling or process parameter configuration functions, determine manually or by the controller whether the scheduling results need to be adjusted.

7. The full-industry chain manufacturing modeling method based on the fusion of three flows as described in claim 1, characterized in that, Using enterprise pre-sale orders as input, the scheduling of the industry layer includes: Step S305: Based on the production process information flow model, material collaborative transfer flow model, and industry shared value flow model, construct a group decision-making game model with enterprise interests as the core. Step S306: Based on the opinions raised by multiple enterprises regarding the current order allocation, a collective feedback opinion is formed through consultation; Step S307: Utilize the group decision-making model, rely on the global information at the current moment to coordinate and optimize, thereby forming a group decision-making result, and transform the decision result into a new enterprise pre-sale order pool.

8. The full-industry chain manufacturing modeling method based on the fusion of three flows as described in claim 7, characterized in that, The control of the industrial layer includes: When an abnormal situation occurs, the company's management personnel intervene to handle the abnormal situation. When a company is unable to resolve an abnormal situation on its own, it reports to the Industry Intelligent Connectivity Platform, which then reallocates the company's sales orders based on industry-level planning and scheduling. The abnormal situations include: The order has been accepted by the company and is in the production process, and the deadline has already passed or there is a high probability that the deadline will pass. If a company is unable to schedule the materials needed for production, whether subjectively or objectively, it needs assistance from the industry as a whole or to reallocate orders. Significant changes in the quality of enterprise production have resulted in product quality and value failing to meet expectations; Significant fluctuations in the prices of raw materials and finished products have had a marked impact on the value of enterprises and industries.

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