CN112528502A - Management and control method and system for production workshop and related devices - Google Patents
Management and control method and system for production workshop and related devices Download PDFInfo
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Abstract
The application relates to the field of production workshop management, and discloses a production workshop management and control method, a production workshop management and control system and a relevant device. The method comprises the following steps: acquiring production data of a production workshop; simulating on the virtual model based on the production data to obtain a simulation result; the virtual model is obtained according to equipment and environment mapping of a production workshop; and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop. By the mode, the management level and the production efficiency of a production workshop are improved, and the production cost is reduced.
Description
Technical Field
The present disclosure relates to the field of manufacturing shop management, and in particular, to a method, a system and a related device for managing and controlling a manufacturing shop.
Background
The injection molding industry belongs to the typical discrete flow industry, and has the particularity and complexity that: the production mode of multiple varieties, small batch and even single piece leads the development of new products to be frequent; the manufacturing process is complex, and the relevance of each manufacturing process in production is strong; the probability of plan change in the production process is very high, the production environment is complex and changeable, the problems of temporary bill insertion, material shortage and the like in the production process occur occasionally, and the production period of a product is greatly influenced by the production period of key equipment. The realization of the injection molding process often requires production equipment such as an injection molding machine, a mold, a hot runner temperature control device, a mold temperature controller, a feeding device, a manipulator and the like. Meanwhile, a large amount of data is often processed in the injection molding process, such as product data, inventory data, material quota data, production planning data, processing information, process information, labor hour information, cost accounting information, and the like.
In the production management process of the injection molding workshop, because the production equipment relates to multiple types, brands and models, the equipment interfaces are often not uniform and difficult to interconnect and intercommunicate, the production condition of the injection molding workshop cannot be mastered in real time, and the real-time interaction, dynamic optimization and automatic adjustment of the injection molding production process are difficult to realize.
The related injection molding process control system can realize the functions of production plan scheduling, process statistics and the like of injection molding orders, but is difficult to monitor the production process in real time, and cannot carry out dynamic interaction and optimization adjustment on the injection molding production process, so that the problems of low production efficiency, high production cost and the like are caused.
Disclosure of Invention
The technical problem mainly solved by the application is to provide a management and control method, a management and control system and a related device for a production workshop, so that the management level and the production efficiency of the production workshop can be improved, and the production cost can be reduced.
The technical scheme adopted by the application is to provide a production workshop management and control method, which comprises the following steps: acquiring production data of a production workshop; simulating on the virtual model based on the production data to obtain a simulation result; the virtual model is obtained according to equipment and environment mapping of a production workshop; and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop.
Wherein, carry out the simulation on the virtual model based on the production data to obtain the simulation result, include: acquiring production element data and production tasks; inputting the production tasks and the production element data into a virtual model for simulation, and configuring the production tasks by using the production element data to obtain configuration data; generating a control instruction according to the simulation result so as to control equipment or environment of the production workshop, wherein the control instruction comprises the following steps: and generating a control command according to the configuration data so as to allocate the production elements of the production workshop.
The method for simulating the production task by the virtual model includes the following steps: acquiring historical production element data; inputting the production task and historical production element data into a virtual model for simulation, and carrying out initial configuration on the production task by using the historical production element data to obtain first configuration data; acquiring current production element data; and inputting the current production element data into the virtual model for simulation, and correcting the first configuration data by using the current production element data to obtain second configuration data.
Wherein, carry out the simulation on the virtual model based on the production data to obtain the simulation result, include: acquiring historical simulation data and a predicted production plan; inputting the historical simulation data, the predicted production plan and the production data into a virtual model for simulation, and adjusting the production plan by using the historical simulation data and the production data to obtain a target production plan; generating a control instruction according to the simulation result so as to control equipment or environment of the production workshop, wherein the control instruction comprises the following steps: and generating a control instruction according to the target production plan so as to carry out production plan scheduling on equipment in the production workshop.
Wherein, carry out the simulation on the virtual model based on the production data to obtain the simulation result, include: when the abnormal data are obtained, inputting the abnormal data and the production data into the virtual model for simulation to obtain a simulation result; generating a control instruction according to the simulation result so as to control equipment or environment of the production workshop, wherein the control instruction comprises the following steps: and generating a scheduling instruction based on the simulation result, and scheduling the equipment in the production workshop according to the scheduling instruction.
The method for generating the scheduling instruction based on the simulation result and scheduling the equipment in the production workshop according to the scheduling instruction comprises the following steps: acquiring historical production data; and generating a scheduling instruction according to the historical production data, the simulation result and the production data, and scheduling equipment in the production workshop according to the scheduling instruction.
Wherein, carry out the simulation on the virtual model based on the production data to obtain the simulation result, include: inputting production data into the virtual model for simulation to obtain a fault prediction result and/or a capacity prediction result of the production workshop; generating a control instruction according to the simulation result so as to control equipment or environment of the production workshop, wherein the control instruction comprises the following steps: and generating a control instruction according to the fault prediction result and/or the productivity prediction result so as to monitor the fault or the productivity of the equipment in the production workshop.
Another technical solution adopted by the present application is to provide a management terminal for a production workshop, where the management terminal includes a processor and a memory coupled to the processor; wherein the memory is used for storing program data and the processor is used for executing the program data to realize the method provided by the above technical scheme.
Another technical solution adopted by the present application is to provide a computer-readable storage medium for storing program data, which when executed by a processor, is used for implementing the method provided in the above technical solution.
Another technical scheme that this application adopted provides a management and control system in workshop, and this management and control system includes: the data acquisition device is arranged in the production workshop and is used for acquiring production data of the production workshop; and the management terminal is connected with the data acquisition device and is provided by the technical scheme.
Wherein, management and control system still includes: and the network equipment is connected with the data acquisition device and is used for acquiring the production data and transmitting and storing the production data.
The data acquisition device comprises at least one of an RFID device, a mold sensor and an equipment controller; the RFID device is connected with the network equipment, is arranged at a preset station of the production workshop and is used for collecting personnel data of the production workshop; the mould sensor is connected with the network equipment and is used for acquiring the operation data of the mould; the equipment controller is connected with the network equipment, arranged on the equipment in the production workshop and used for controlling the equipment and sending the running data of the equipment to the network equipment.
The virtual model is formed by mapping personnel data, position information of preset stations, raw materials, die accessories, the space position of a cutter, the stock state, design data of a die, the three-dimensional size of equipment and the environment of a production workshop.
The beneficial effect of this application is: different from the situation of the prior art, the management and control method for the production workshop comprises the following steps: acquiring production data of a production workshop; simulating on the virtual model based on the production data to obtain a simulation result; the virtual model is obtained according to equipment and environment mapping of a production workshop; and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop. Through the mode, the virtual model simulates production of the production workshop by utilizing production data of the production workshop, interactive mapping and iterative optimization of the production workshop and the virtual model are realized, real-time production management and control and process dynamic optimization adjustment are carried out on the production workshop, and therefore the production process is optimized, the production efficiency is improved, and the production cost is reduced.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts. Wherein:
FIG. 1 is a schematic flow chart illustrating an embodiment of a method for managing and controlling a production shop provided by the present application;
FIG. 2 is a schematic structural diagram of an embodiment of a management terminal of a production plant provided in the present application;
FIG. 3 is a schematic flow chart of another embodiment of a method for managing and controlling a production plant provided by the present application;
FIG. 4 is a schematic flow chart diagram illustrating the step 32 of FIG. 3 provided herein;
FIG. 5 is a schematic flow chart of another embodiment of a method for managing and controlling a production plant provided by the present application;
FIG. 6 is a schematic flow chart of another embodiment of a method for managing and controlling a production plant provided by the present application;
FIG. 7 is a schematic structural diagram of another embodiment of a management terminal of a production plant provided in the present application;
FIG. 8 is a schematic block diagram of one embodiment of a computer-readable storage medium provided herein;
FIG. 9 is a schematic structural diagram of an embodiment of a management and control system of a production plant provided in the present application;
fig. 10 is a schematic structural diagram of another embodiment of a management and control system of a production plant provided by the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, fig. 1 is a schematic flow chart of an embodiment of a method for managing and controlling a production shop provided by the present application. The method comprises the following steps:
step 11: and acquiring production data of the production workshop.
In some embodiments, the production data may be different for different production plants, such as a stamping plant, which may include multiple stamping devices, such as stamping machines, robots, test terminals, and the like. The production data may be the brand, specification, model, elapsed time, stamping speed, accuracy, and status information of the stamping device.
In some embodiments, the production data may be collected by a data collection device. For example, the data acquisition device is connected with equipment in a production workshop and is used for acquiring production data of the equipment. In an application scenario, the data acquisition device comprises a data acquisition controller and at least one acquisition terminal. The acquisition terminal is connected with the production equipment and used for acquiring production data of the production equipment. The data acquisition controller is connected with the acquisition terminal and the network equipment and is used for sending the production data acquired by the acquisition terminal to the network equipment. The production data of the production equipment collected by the collecting terminal can be collected in real time, and can also be collected at regular time, such as once every 1 minute, once every 5 minutes, once every 10 minutes and the like. Step 11 may specifically be to acquire production data of the production shop from the network device.
It is understood that the data collection controller and the network device may be connected wirelessly or through wires. For example, the data acquisition controller may be connected to the network device through a wireless lan, or the data acquisition controller may be provided with a network cable port connected to the network device through a network cable.
In some embodiments, the data acquisition device is connected with the management terminal, and the production data acquired by the data acquisition device is directly transmitted to the management terminal.
In some embodiments, production data for the production plant may be acquired in real-time.
Step 12: simulating on the virtual model based on the production data to obtain a simulation result; wherein the virtual model is obtained according to equipment and environment mapping of the production workshop.
In some embodiments, the virtual model is derived from a device and environment map of the production plant. The environmental number may include, among other things, the temperature, humidity, noise, personnel, etc. of the production plant. For example, the data is mapped by using personnel data of a production workshop, position information of preset stations, raw materials, mould accessories, the spatial position of a cutter, the stock state, design data of a mould, the three-dimensional size of equipment and the environment of the production workshop. The three-dimensional size of the equipment can establish corresponding virtual equipment in a virtual model, the design data of the mould can establish corresponding virtual mould in the virtual model, the personnel data and the position information of the preset station can establish corresponding virtual personnel and virtual station in the virtual model, and the spatial positions and the inventory state of raw materials, mould accessories and cutters can establish corresponding virtual raw materials, virtual mould accessories and virtual cutters in the virtual model.
In some embodiments, when a new order requirement is obtained, production data is obtained and input to the virtual model for simulation, so as to determine production equipment suitable for production, and a control instruction is generated based on the production equipment.
In some embodiments, the production equipment is scheduled for maintenance according to the set production time or production batch according to the production data, and a production control instruction is generated to perform maintenance reminding.
In some embodiments, the production data is input to the virtual model for simulation, the use requirement of the material can be obtained through simulation, and then the control instruction is generated according to the use requirement.
Step 13: and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop.
In some embodiments, the simulation result is configuration information of the production element, and then a control instruction can be generated according to the configuration information to control the equipment or environment of the production plant. For example, the configuration information may be settings for production plant temperature, material, personnel number, and process flow.
In some embodiments, the simulation result is a production plan, and control instructions are generated according to the target production plan to schedule production plans for equipment in the production plant.
In some embodiments, the control instruction may be a reminder of a suggestion to be presented via a display interface. For example, the monitored and managed data is sent to the mobile terminal and the computer terminal through the network, so that people with different identities in the production workshop can check the data.
In an application scenario, the method is applied to a management terminal. Referring to fig. 2, fig. 2 is a schematic structural diagram of an embodiment of a management terminal of a production workshop according to the present application. The management terminal 20 includes a virtual model module 21, a twin data module 22, and an interactive system module 23. The virtual model module 21 is obtained by mapping the equipment and environment of the production workshop. The twin data module 22 includes collected production data of the production plant and configuration data of the virtual model module 21. The interactive system module 23 performs simulation in the virtual model module 21 by analyzing and processing the industrial production process data of the twin data module 22; and evaluating and predicting twin data such as simulation results, real-time production data, historical production data and the like, and generating a real-time monitoring instruction so as to perform feedback control on equipment and the like of the production workshop, thereby realizing interactive mapping between the virtual model module 21 and the production workshop.
In the embodiment, production data of a production workshop is obtained; simulating on the virtual model based on the production data to obtain a simulation result; the virtual model is obtained according to equipment and environment mapping of a production workshop; and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop. The production of the production workshop is simulated by utilizing the production data of the production workshop through the virtual model, and the interactive mapping and iterative optimization of the production workshop and the virtual model are realized, so that the production workshop is subjected to real-time production management and control and process dynamic optimization and adjustment, the production process is optimized, the production efficiency is improved, and the production cost is reduced.
Referring to fig. 3, fig. 3 is a schematic flow chart of another embodiment of the management and control method for a manufacturing shop provided by the present application. The method comprises the following steps:
step 31: and acquiring production element data and production tasks.
In some examples, the production task may be a production order. The production element data can be the number of personnel in a production workshop, production equipment, materials, process flows, environmental data and the like.
Step 32: and inputting the production tasks and the production element data into the virtual model for simulation so as to configure the production tasks by using the production element data to obtain configuration data.
In some embodiments, the production plant is an injection molding production plant, and is described with reference to fig. 2: when the production task is obtained, the interactive system module 23 obtains historical production element data from the twin data module 22, and performs simulation in the virtual model module 21 according to the current production task and the historical production element data to obtain initial configuration data; meanwhile, real-time data of production element data of personnel, molds, injection molding machines, materials and the like in a production workshop are obtained, the states of the production element data are analyzed, evaluated and predicted, an initial configuration scheme is optimized, an order regulation and control instruction is generated, and the production element data are guided to be allocated in the production workshop.
Specifically, referring to fig. 4, step 32 may be the following process:
step 321: and acquiring historical production element data.
In some embodiments, the historical production element data corresponds to the historical production task of the workshop, and can represent the production element configuration data of the historical production task.
Step 322: and inputting the production task and the historical production element data into the virtual model for simulation, and performing initial configuration on the production task by using the historical production element data to obtain first configuration data.
Step 323: and acquiring current production element data.
Step 324: and inputting the current production element data into the virtual model for simulation, and correcting the first configuration data by using the current production element data to obtain second configuration data.
It can be understood that the current production element data is more reflective of the actual situation of the production shop, and therefore the first configuration data needs to be corrected in combination with the current production element data.
Step 33: and generating a control command according to the configuration data so as to allocate the production elements of the production workshop.
In some embodiments, the above steps are performed in real time, and during the production process of the production shop, by performing optimization in real time, different time periods of the production shop may be optimized correspondingly, so that the production shop obtains the optimal production element configuration.
In this embodiment, the virtual model simulates the production of the production workshop by using the production element data and the production task to obtain the optimal configuration information of the production element data, and allocates the production element data of the production workshop according to the configuration information, so as to perform real-time production management and control and process dynamic optimization and adjustment on the production workshop, thereby optimizing the production process, improving the production efficiency and reducing the production cost.
Referring to fig. 5, fig. 5 is a schematic flow chart of another embodiment of the management and control method for a production shop provided by the present application. The method comprises the following steps:
step 51: historical simulation data and a projected production plan are acquired.
In the above embodiment, after the production task is obtained and the production element configuration information is obtained, the corresponding production plan is produced.
Step 52: and inputting the historical simulation data, the predicted production plan and the production data into the virtual model for simulation, and adjusting the production plan by using the historical simulation data and the production data to obtain a target production plan.
Step 53: and generating a control instruction according to the target production plan so as to carry out production plan scheduling on equipment in the production workshop.
The description is made with reference to fig. 2: after the virtual model module 21 receives the predicted production plan, historical simulation data and real-time production data are obtained from the twin data module 22, the schedule of the predicted production plan is simulated and optimized based on the logic, rule model and algorithm with optimal injection production time and lowest cost, and the simulation result is fed back to the twin data module 22. The interactive system module 23 performs optimization simulation according to the fed-back simulation result, transmits the result to the virtual model module 21, and performs iterative optimization until an optimal scheme of production plan scheduling and a production operation instruction based on the scheme are obtained, and drives and controls equipment in the production workshop to schedule the production plan.
In this embodiment, the virtual model simulates the production in the production shop by using the historical simulation data and the predicted production plan to obtain the optimal production plan, and performs production plan scheduling on the equipment in the production shop according to the optimal production plan, so as to perform real-time production control and process dynamic optimization adjustment on the production shop, thereby optimizing the production process, improving the production efficiency and reducing the production cost.
Referring to fig. 6, fig. 6 is a schematic flow chart of another embodiment of the management and control method for a production shop provided by the present application. The method comprises the following steps:
step 61: and acquiring production data of the production workshop.
Step 62: and when the abnormal data are obtained, inputting the abnormal data and the production data into the virtual model for simulation to obtain a simulation result.
And step 63: and generating a scheduling instruction based on the simulation result, and scheduling the equipment in the production workshop according to the scheduling instruction.
In an application scenario, the production plant is an injection molding plant, which includes 10 injection molding machines. Of these 8 stations are in normal operation and 2 are in idle state. And when the two injection molding machines which normally work are abnormal, simulating in the virtual model according to the abnormal data and the production data to obtain a simulation result. And (4) the simulation result shows that the two abnormal injection molding machines can not complete the task within the specified time, and then the idle injection molding machine is recommended to be used for replacing the work. And performing production scheduling according to the simulation result, and enabling the idle injection molding machine to work to complete the production task, wherein the scheduling instruction comprises scheduling of materials and personnel.
In this embodiment, the virtual model is used to realize the optimal production scheduling during an anomaly, and solve the problem of reduction of production efficiency caused by the anomaly, so that real-time production management and control and process dynamic optimization and adjustment are performed on a production workshop, and therefore, the production process is optimized, the production efficiency is improved, and the production cost is reduced.
In other embodiments, production data is input into the virtual model for simulation to obtain a fault prediction result of the production workshop; and generating a control instruction according to the fault prediction result so as to monitor the fault of the equipment in the production workshop. The description is made with reference to fig. 2: in the production process, production data are collected in real time and transmitted to the twin data module 22 in real time, the virtual model module 21 performs fault prediction, diagnosis simulation, capacity prediction and the like based on the real-time data in the production process, the interactive system module 23 performs evaluation and prediction according to the simulation result, the real-time production data, historical production data and other twin data, and generates a real-time monitoring instruction to drive a physical space to realize the functions of equipment maintenance and maintenance, capacity prediction and evaluation and the like until the order is produced.
In other embodiments, the production data is input into the virtual model for simulation to obtain a productivity prediction result of the production workshop; and generating a control instruction according to the productivity prediction result so as to monitor the productivity of the equipment in the production workshop. For example, the production data is input into the virtual model for simulation, so as to obtain the productivity prediction result of the production workshop as 1000/day. And generating a control command based on the productivity prediction result, and monitoring the productivity of the equipment in the production workshop every day to see whether the achievement and the productivity prediction result can be achieved. And the simulation can be carried out in the virtual model according to the actual capacity, and the optimization of the capacity prediction result is carried out again to obtain the optimal capacity prediction result.
In this embodiment, the virtual model is used to realize capacity prediction and use historical simulation data and a predicted production plan, so as to simulate the production in the production workshop to obtain an optimal production plan, and perform production plan scheduling on the equipment in the production workshop according to the optimal production plan, thereby performing real-time production management and control and process dynamic optimization and adjustment on the production workshop, thereby optimizing the production process, improving the production efficiency and reducing the production cost.
Referring to fig. 7, fig. 7 is a schematic structural diagram of another embodiment of a management terminal of a production workshop according to the present application. The management terminal 70 includes a processor 71 and a memory 72 coupled to the processor 71; wherein the memory 72 is used for storing program data and the processor 71 is used for executing the program data to realize the following method:
acquiring production data of a production workshop; simulating on the virtual model based on the production data to obtain a simulation result; the virtual model is obtained according to equipment and environment mapping of a production workshop; and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop.
It is understood that the processor 71 in this embodiment may also implement any method in the foregoing embodiments, which is not described herein again.
By implementing the method, the management terminal 70 of this embodiment simulates the production of the production workshop by using the production data of the production workshop through the virtual model, and realizes interactive mapping and iterative optimization of the production workshop and the virtual model, thereby performing real-time production management and control and process dynamic optimization adjustment on the production workshop, optimizing the production process, improving the production efficiency and reducing the production cost.
Referring to fig. 8, fig. 8 is a schematic structural diagram of an embodiment of a computer-readable storage medium provided in the present application. The computer readable storage medium 80 is for storing program data 81, the program data 81, when executed by a processor, being for implementing the method of:
acquiring production data of a production workshop; simulating on the virtual model based on the production data to obtain a simulation result; the virtual model is obtained according to equipment and environment mapping of a production workshop; and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop.
It is understood that the computer-readable storage medium 80 in this embodiment may also implement any method in the above-described embodiments, which is not described herein again.
When the computer-readable storage medium 80 of this embodiment is applied to the above-mentioned management terminal, the virtual model simulates the production in the production workshop by using the production data in the production workshop, and realizes the interactive mapping and iterative optimization between the production workshop and the virtual model, so as to perform real-time production management and control and process dynamic optimization adjustment on the production workshop, thereby optimizing the production process, improving the production efficiency, and reducing the production cost.
Referring to fig. 9, fig. 9 is a schematic structural diagram of an embodiment of a management and control system of a production workshop according to the present application. The management and control system 90 includes a data acquisition device 91 and a management terminal 92. Wherein, the data acquisition device 91 is arranged in a production workshop and used for acquiring production data of the production workshop. The management terminal 92 is connected to the data acquisition device 91, and the management terminal 92 is the management terminal in the above-described embodiment.
Further, referring to fig. 10, the management and control system 90 further includes a network device 93, in addition to the data acquisition device 91 and the management terminal 92, connected to the data acquisition device 91, for acquiring the production data, transmitting the production data, and storing the production data.
Specifically, the network device 93 may be communicatively connected to the data acquisition device 91 and the management terminal 92 by a field bus or an industrial ethernet. Network devices 93 may include routers, switches, edge computing servers, vehicle database servers, cloud servers, and like network devices.
The data acquisition device 91 includes at least one of an RFID device, a mold sensor, and a device controller. The RFID device is connected with the network equipment 93, arranged at a preset station of the production workshop and used for collecting personnel data of the production workshop. The mold sensors are connected to a network device 93 for collecting operational data of the mold. The device controller is connected to the network device 93, is disposed on a device in the production workshop, and is configured to control the device and send operation data of the device to the network device 93.
The virtual model in the management terminal 92 is mapped by using personnel data, position information of a preset station, raw materials, mold accessories, a space position of a cutter, a stock state, design data of a mold, a three-dimensional size of equipment and an environment of a production workshop.
In some embodiments, the production workshop is an injection molding workshop, and data such as personnel, materials, equipment and the like are involved in the production process of the injection molding workshop, wherein a large number of devices of different types, brands and models exist in the production workshop, interface protocols and the like of the devices are different, and a uniform standardized communication framework and a protocol need to be established for realizing heterogeneous device-oriented data acquisition. Since OPC UA (OLE for Process Control Unified Architecture) supports complex data built-in, cross-platform operation, provides Unified address space and services, and most of the above devices support OPC UA protocol, a communication Architecture of an injection molding production Process based on OPC UA protocol is adopted. The data of the injection molding production process in the production workshop is acquired through the RFID, the data acquisition unit, the mold sensor, the injection molding machine controller and the like, and is transmitted to the data server in real time through a field bus or an industrial Ethernet based on the OPC UA protocol.
In some embodiments, the virtual model module in the management terminal 92 can accurately map the equipment and environment of the production plant with high fidelity, multiple time scales and multiple spatial dimensions. The virtual model can be obtained by digital modeling using a three-dimensional CAD (Computer Aided Design) system such as unity3d, 3Dmax, Maya, and the like. Specifically, the virtual model module comprises a personnel virtual model, a material virtual model, a mold virtual model, an equipment virtual model and an environment virtual model.
The virtual personnel model is mainly embodied in personnel actions and the space position in a production workshop, a human body structure is mapped through the three-dimensional structure model, the identity and the position are positioned by adopting RFID or fingerprint image recognition, and the personnel position and the identity are controlled in the virtual model module.
The material virtual model mainly includes spatial positions and stock states of plastic raw materials, mold accessories, cutters and the like, and data information is acquired through a warehouse material management system or an ERP (Enterprise Resource Planning) system.
The virtual mold model is mainly CAD/CAM (Computer Aided Manufacturing)/CAE (Computer Aided Engineering)/CAPP (Computer Aided Process Planning) Data of the mold, and can be directly obtained through a PDM (Product Data Management) system or a CAX system. CAX is a comprehensive name for CAD, CAM, CAE, CAPP, etc., since all abbreviations begin with CA and X represents all. CAX actually integrates diversified computer-aided technologies to compound and coordinate work, except for the work of design departments during product design, other departments can intervene in advance without waiting for the completion of the previous operation to start the next operation, and the development time is shortened; meanwhile, various factors of the life cycle of the product can be well considered in the early stage of product design, errors and errors in design can be found in advance, correction can be carried out in time, and various design schemes which can be compared can be continuously provided according to market requirements in the design process, so that the optimized design achievement and benefit can be obtained.
The virtual model of the equipment is the most critical and complex, and specifically comprises an injection molding machine, an industrial robot, a mold temperature controller, a loading and unloading device and the like. In order to complete the real mapping of the twin model to the physical entity, the model must first ensure that the three-dimensional size and behavior are highly consistent with the physical entities of the devices, a virtual-real communication control interface needs to be established to acquire data in real time, and related virtual services need to be defined to complete the action behavior of the devices.
The environment virtual model is mainly a mapping of the production workshop environment, such as temperature, humidity, noise, etc.
In an application scene, an injection molding workshop is taken as an example for explanation, and data acquisition of an industrial production process of the injection molding workshop is carried out. The method comprises the steps of collecting data of key generating elements such as equipment, personnel, materials, environment and the like in an injection molding workshop in real time through an RFID (radio frequency identification device), a data collector, a mold sensor and an injection molding machine controller, and transmitting the data to a server in real time through a field bus or an industrial Ethernet based on an OPC UA (optical proximity correction) protocol to form a twin database.
And establishing a virtual model of the injection molding workshop. Through the analysis of the physical entity elements of the injection molding workshop, a virtual model of production elements such as an injection molding machine, a mold, personnel, materials, an environment and the like can be established by adopting a three-dimensional CAD system such as unity3d, 3Dmax, Maya and the like.
And a data interface is provided in the twin database, and the virtual model of the injection molding workshop can acquire real-time industrial data of the injection molding workshop and display the real-time states of equipment and the environment of the injection molding workshop in real time.
And the interactive system generates an interactive instruction according to the optimization result in the twin database for dynamic control optimization of the physical space of the injection workshop, so that interactive mapping between the physical space of the injection workshop and the virtual model is realized.
According to the embodiment, innovative fusion application based on digital twinning and injection molding production processes is adopted, a virtual model corresponding to an injection molding workshop is established firstly, twinning data is established through real-time acquisition of production data of the injection molding workshop, and interactive mapping and iterative optimization of physical space and model space are realized by combining analysis processing of industrial data, so that real-time production management and control and process dynamic optimization adjustment of the injection molding workshop are realized, the production process is optimized, the production efficiency is improved, and the production cost is reduced.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other manners. For example, the above-described device embodiments are merely illustrative, and for example, the division of the above modules or units is only one logical functional division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated units in the other embodiments described above may be stored in a computer-readable storage medium if they are implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the purpose of illustrating embodiments of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application or are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (13)
1. A management and control method for a production workshop is characterized by comprising the following steps:
acquiring production data of a production workshop;
simulating on a virtual model based on the production data, and obtaining a simulation result; wherein the virtual model is obtained according to equipment and environment mapping of the production workshop;
and generating a control instruction according to the simulation result so as to control the equipment or the environment of the production workshop.
2. The method of claim 1,
the simulating on the virtual model based on the production data and obtaining a simulation result comprises:
acquiring production element data and production tasks;
inputting the production task and the production element data into the virtual model for simulation, and configuring the production task by using the production element data to obtain configuration data;
the generating of the control instruction according to the simulation result to control the equipment or the environment of the production workshop comprises:
and generating a control instruction according to the configuration data so as to allocate the production elements of the production workshop.
3. The method of claim 2,
the inputting the production task and the production element data into the virtual model for simulation so as to configure the production task by using the production element data to obtain configuration data includes:
acquiring historical production element data;
inputting the production task and the historical production element data into the virtual model for simulation, and performing initial configuration on the production task by using the historical production element data to obtain first configuration data;
acquiring current production element data;
and inputting the current production element data into the virtual model for simulation, and correcting the first configuration data by using the current production element data to obtain second configuration data.
4. The method of claim 1,
the simulating on the virtual model based on the production data and obtaining a simulation result comprises:
acquiring historical simulation data and a predicted production plan;
inputting the historical simulation data, the predicted production plan and the production data into the virtual model for simulation, and adjusting the production plan by using the historical simulation data and the production data to obtain a target production plan;
the generating of the control instruction according to the simulation result to control the equipment or the environment of the production workshop comprises:
and generating a control instruction according to the target production plan so as to carry out production plan scheduling on equipment in the production workshop.
5. The method of claim 1,
the simulating on the virtual model based on the production data and obtaining a simulation result comprises:
when abnormal data are obtained, inputting the abnormal data and the production data into the virtual model for simulation to obtain a simulation result;
the generating of the control instruction according to the simulation result to control the equipment or the environment of the production workshop comprises:
and generating a scheduling instruction based on the simulation result, and scheduling the equipment of the production workshop according to the scheduling instruction.
6. The method of claim 5,
the generating a scheduling instruction based on the simulation result, and scheduling the equipment of the production workshop according to the scheduling instruction comprises:
acquiring historical production data;
and generating a scheduling instruction according to the historical production data, the simulation result and the production data, and scheduling the equipment in the production workshop according to the scheduling instruction.
7. The method of claim 1,
the simulating on the virtual model based on the production data and obtaining a simulation result comprises:
inputting the production data into the virtual model for simulation to obtain a fault prediction result and/or a capacity prediction result of the production workshop;
the generating of the control instruction according to the simulation result to control the equipment or the environment of the production workshop comprises:
and generating a control instruction according to the fault prediction result and/or the capacity prediction result so as to monitor the fault or the capacity of the equipment in the production workshop.
8. A management terminal for a production plant, characterized in that it comprises a processor and a memory coupled to said processor;
wherein the memory is for storing program data and the processor is for executing the program data to implement the method of any one of claims 1-7.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium is used for storing program data, which, when being executed by a processor, is used for carrying out the method according to any one of claims 1-7.
10. A management and control system for a production workshop, characterized in that the management and control system comprises:
the data acquisition device is arranged in the production workshop and is used for acquiring production data of the production workshop;
a management terminal connected to the data acquisition device, the management terminal being the management terminal according to claim 8.
11. The management and control system according to claim 10, further comprising:
and the network equipment is connected with the data acquisition device and used for acquiring the production data and transmitting and storing the production data.
12. The management and control system according to claim 11,
the data acquisition device comprises at least one of an RFID device, a mold sensor and an equipment controller;
the RFID device is connected with the network equipment, is arranged at a preset station of the production workshop and is used for collecting personnel data of the production workshop;
the mould sensor is connected with the network equipment and is used for acquiring the operation data of the mould;
the equipment controller is connected with the network equipment, arranged on the equipment of the production workshop and used for controlling the equipment and sending the running data of the equipment to the network equipment.
13. The management and control system according to claim 10,
the virtual model is formed by mapping the personnel data, the position information of the preset station, the raw materials, the die fittings, the space position of the cutter, the stock state, the design data of the die, the three-dimensional size of the equipment and the environment of the production workshop.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113485280A (en) * | 2021-08-23 | 2021-10-08 | 东北大学 | New energy stamping workshop scheduling system and method based on information physical model conversion |
| CN113505953A (en) * | 2021-04-06 | 2021-10-15 | 汕头经济特区超艺螺丝工业有限公司 | Fastener supply chain management system and control method thereof |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110196575A (en) * | 2019-03-08 | 2019-09-03 | 上海大学 | It is a kind of that system and method is produced and processed based on the twin intelligent workshop with machine learning techniques of number |
| CN110765589A (en) * | 2019-09-10 | 2020-02-07 | 上海大学 | Intelligent workshop virtual and real synchronous monitoring system and method based on digital twins |
| US20200249663A1 (en) * | 2017-10-17 | 2020-08-06 | Guangdong University Of Technology | Method and system for quick customized-design of intelligent workshop |
| CN111722603A (en) * | 2020-05-25 | 2020-09-29 | 深圳先进技术研究院 | Management and control system and management and control method for production workshop |
| CN111857065A (en) * | 2020-06-08 | 2020-10-30 | 北京邮电大学 | Intelligent production system and method based on edge calculation and digital twinning |
-
2020
- 2020-12-11 CN CN202011459771.9A patent/CN112528502A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20200249663A1 (en) * | 2017-10-17 | 2020-08-06 | Guangdong University Of Technology | Method and system for quick customized-design of intelligent workshop |
| CN110196575A (en) * | 2019-03-08 | 2019-09-03 | 上海大学 | It is a kind of that system and method is produced and processed based on the twin intelligent workshop with machine learning techniques of number |
| CN110765589A (en) * | 2019-09-10 | 2020-02-07 | 上海大学 | Intelligent workshop virtual and real synchronous monitoring system and method based on digital twins |
| CN111722603A (en) * | 2020-05-25 | 2020-09-29 | 深圳先进技术研究院 | Management and control system and management and control method for production workshop |
| CN111857065A (en) * | 2020-06-08 | 2020-10-30 | 北京邮电大学 | Intelligent production system and method based on edge calculation and digital twinning |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113505953A (en) * | 2021-04-06 | 2021-10-15 | 汕头经济特区超艺螺丝工业有限公司 | Fastener supply chain management system and control method thereof |
| CN113505953B (en) * | 2021-04-06 | 2024-02-02 | 汕头经济特区超艺螺丝工业有限公司 | Fastener supply chain management system and control method thereof |
| CN113485280A (en) * | 2021-08-23 | 2021-10-08 | 东北大学 | New energy stamping workshop scheduling system and method based on information physical model conversion |
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