Generation of a programming system, programming method, apparatus, system, device, and medium

Abstract

The application discloses a generation method of an automatic programming system of flexible manufacturing based on an industrial language, an automatic programming method of flexible manufacturing based on an industrial language, a device, a system, equipment and a medium, and belongs to the field of intelligent manufacturing. Through the preset industrial language specification, an industrial language system model is constructed according to the demand information of flexible manufacturing, an analysis result is obtained by analyzing the industrial language system model, and the automatic programming system of flexible manufacturing is automatically generated based on the analysis result, thereby realizing efficient and standardized conversion from flexible manufacturing demand to the automatic programming system, replacing the traditional industrial software waterfall development mode which depends on manual work, greatly shortening the development cycle of the flexible manufacturing related programming software, reducing the difficulty of customized development, improving the adaptation ability and expansion ability of the generated programming system to different flexible manufacturing scenes, and better meeting the real-time and personalized development needs of the flexible manufacturing scenes of small batches, multiple batches and variable varieties.

Description

Technical Field

[0001] This application belongs to the field of intelligent manufacturing, specifically relating to a method for generating an automated programming system for flexible manufacturing based on industrial language, an automated programming method for flexible manufacturing based on industrial language, a device for generating an automated programming system for flexible manufacturing based on industrial language, an automated programming system for flexible manufacturing based on industrial language, an electronic device, and a readable storage medium. Background Technology

[0002] In the fields of intelligent manufacturing and industrial software technology, small-batch, multi-batch flexible manufacturing has become the mainstream production mode in the manufacturing industry, placing higher demands on the development and application of industrial software for flexible manufacturing scenarios. Currently, the development of industrial software, especially process programming software for flexible manufacturing scenarios, generally adopts the traditional waterfall development process. This process is characterized by phase division and relies on manual implementation step by step. Specifically, it includes multiple sequential steps such as requirements analysis, architecture design, detailed design, coding, testing and delivery, and requires manual iteration and requirements adaptation throughout the entire process.

[0003] Current mainstream offline programming software in the industry, such as RobotStudio and Mastercam, all rely on the aforementioned traditional development models to build their operating systems, revealing many inherent defects in practical applications. This type of software is developed based on a fixed program framework, resulting in a rigid and closed program structure that is difficult to flexibly reconstruct and adjust according to on-site production line layout, equipment models, and processing technologies. Faced with the flexible production characteristics of small batches, multiple batches, changing product types, and rapid changeovers, it cannot quickly match the needs of workpiece category switching and process parameter changes. Furthermore, software customization is difficult; for different flexible manufacturing scenarios, robotic welding, intelligent warehousing, and other diverse chemical conditions, technicians need to manually rewrite the program code and re-debug and verify it, resulting in poor software module versatility and cross-scenario reusability.

[0004] Meanwhile, the traditional waterfall development model also has significant industry shortcomings. First, the development cycle is lengthy, with each stage proceeding sequentially and interconnected. Problems in any stage require backtracking and adjustments, resulting in long development cycles and high costs for process programming software for flexible manufacturing, making it difficult to quickly respond to the real-time and personalized needs of flexible manufacturing scenarios. Second, customization is difficult. The process requirements, equipment types, and operating environments of different flexible manufacturing scenarios vary significantly. The traditional development model requires manual customization for specific scenarios, resulting in poor system reusability and weak scalability. The software architecture and functional modules under different scenarios are difficult to generalize, making it impossible to achieve rapid generation and flexible adaptation of process programming software. Third, development efficiency is low. The entire process relies on manual participation. From requirements analysis to coding and testing, professional technicians need to advance each step, resulting in high labor costs and susceptibility to development defects introduced by human error, affecting system stability. Fourth, the efficiency of requirement iteration is low. Faced with frequent process adjustments and equipment updates in flexible manufacturing scenarios, the traditional development model requires re-running the entire process for requirement iteration, resulting in long iteration cycles and making it impossible to achieve continuous evolution and rapid adaptation of process programming software.

[0005] Meanwhile, existing industrial software development and mainstream offline programming software still rely on the traditional model of manual driving, stage-based fragmentation, and manual coding, which cannot meet the core needs of rapid changeover, efficient processing, and flexible adaptation in small-batch, multi-batch flexible manufacturing scenarios. Summary of the Invention

[0006] The purpose of this application is to provide an automated programming system for flexible manufacturing based on industrial languages, an automated programming method for flexible manufacturing based on industrial languages, an electronic device, and a readable storage medium. These solutions address the problems of traditional process programming software in small-batch, multi-batch flexible manufacturing scenarios, such as long development cycles, high customization difficulty, insufficient reusability and scalability, low demand iteration efficiency, reliance on manual operation, low efficiency, and difficulty in achieving rapid changeover and flexible adaptation.

[0007] To solve the above-mentioned technical problems, this application is implemented as follows: In a first aspect, embodiments of this application provide a method for generating an automated programming system for flexible manufacturing based on an industrial language, the method comprising: Based on pre-defined industrial language standards and the requirements of flexible manufacturing, an industrial language system model for realizing flexible manufacturing is constructed. The industrial language system model is analyzed to obtain the analysis results; Based on the analysis results, an automated programming system for flexible manufacturing is generated; wherein, the automated programming system is used to generate control instructions for controlling flexible manufacturing equipment.

[0008] Secondly, embodiments of this application provide an automated programming method for flexible manufacturing based on an industrial language, applied to an automated programming system for flexible manufacturing generated by the method described above. The method includes: Acquire processing-related data for flexible manufacturing and extract key processing parameters; Configure the process for the key processing parameters and complete the simulation verification of the processing scheme; After the simulation verification is successful, control commands for the operation of the flexible manufacturing equipment are automatically generated.

[0009] Thirdly, embodiments of this application provide a generation apparatus for an automated programming system for flexible manufacturing based on an industrial language, the apparatus comprising: The model building module is used to construct an industrial language system model for realizing flexible manufacturing based on preset industrial language specifications and the requirements of flexible manufacturing. The parsing module is used to parse the industrial language system model and obtain the parsing results; The system generation module is used to generate an automated programming system for flexible manufacturing based on the parsing results; wherein the automated programming system is used to generate control instructions for controlling flexible manufacturing equipment.

[0010] Fourthly, embodiments of this application provide an automated programming system for flexible manufacturing based on an industrial language, the system comprising: The parameter acquisition module is used to acquire processing-related data for flexible manufacturing and extract key processing parameters; The process configuration module is used to configure the key processing parameters and to perform simulation verification of the processing scheme. The instruction generation module is used to automatically generate control instructions for the operation of flexible manufacturing equipment after the simulation verification is passed.

[0011] Fifthly, embodiments of this application provide an electronic device including a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method described in the first or second aspect.

[0012] In a sixth aspect, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first or second aspect.

[0013] According to embodiments of the present invention, an industrial language system model is constructed based on preset industrial language specifications and the requirements of flexible manufacturing. After parsing the industrial language system model to obtain the parsing results, an automated programming system for flexible manufacturing is automatically generated based on the parsing results. This achieves an efficient and standardized transformation from flexible manufacturing requirements to an automated programming system, replacing the traditional waterfall development model of industrial software that relies on manual labor. This significantly shortens the development cycle of flexible manufacturing-related programming software, reduces the difficulty of customized development, and improves the adaptability and scalability of the generated programming system to different flexible manufacturing scenarios. It can better meet the real-time and personalized development needs of flexible manufacturing scenarios with small batches, multiple batches, and variable varieties. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating the steps of an embodiment of the method for generating an automated programming system for flexible manufacturing based on industrial languages, provided by an embodiment of the present invention. Figure 2 This is a schematic diagram of the flexible manufacturing programming development process; Figure 3 This is a flowchart illustrating the steps of an embodiment of an automated programming method for flexible manufacturing based on industrial languages, provided by an embodiment of the present invention. Figure 4 This is a structural block diagram of an embodiment of an automated programming system generation device for flexible manufacturing based on industrial languages, provided by an embodiment of the present invention. Figure 5 This is a structural block diagram of an embodiment of a flexible manufacturing automation programming system based on an industrial language, provided by an embodiment of the present invention; Figure 6 This is a structural block diagram illustrating an automated programming system for flexible manufacturing based on industrial languages, and an electronic device for automated programming of flexible manufacturing based on industrial languages, according to an exemplary embodiment. Detailed Implementation

[0015] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0016] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0017] The following description, in conjunction with the accompanying drawings, details the flexible manufacturing automated programming system and the flexible manufacturing implementation method based on automated programming provided in this application through specific embodiments and application scenarios.

[0018] The generation method and programming method of the automated programming system for flexible manufacturing based on industrial languages ​​in this invention embodiment can be executed by cloud services, local industrial control equipment, self-built server clusters, or deployed in any other applicable hardware and software environment. This invention embodiment does not impose any limitations on these methods. The automated programming method for flexible manufacturing can be applied to flexible manufacturing process programming scenarios for CNC machine tools, industrial robots, flexible production lines, intelligent processing units, and various intelligent manufacturing equipment.

[0019] Reference Figure 1 The diagram illustrates a flowchart of the steps involved in generating an automated programming system for flexible manufacturing based on an industrial language, according to an embodiment of this application. Specifically, the method may include the following steps: Step 101: Based on the preset industrial language specifications and the requirements of flexible manufacturing, construct an industrial language system model for realizing flexible manufacturing.

[0020] In this embodiment of the invention, the preset industrial language specification is a standardized language rule system formulated to adapt to industrial software development. It provides a unified basis for vocabulary, grammar, semantics and usage specifications for the construction of industrial language system models, and can adapt to the modeling needs of various flexible manufacturing scenarios. This embodiment of the invention does not limit the specific formulation basis or expression form of the specification.

[0021] In this embodiment of the invention, the demand information for flexible manufacturing refers to the various related requirements proposed in the context of flexible manufacturing to achieve automated programming. These requirements can cover multiple dimensions such as production processes, production line construction, equipment adaptation, and function implementation. This embodiment of the invention does not limit the specific form of the demand information or the method of collection.

[0022] In this embodiment of the invention, the industrial language system model is a standardized and structured modeling expression of flexible manufacturing demand information based on preset industrial language specifications. It is a linguistic representation of various elements and interactions in the flexible manufacturing scenario and can serve as the core basis for the subsequent generation of an automated programming system. This embodiment of the invention does not limit the specific storage format or modeling tools of the model.

[0023] In this embodiment of the invention, the specific implementation method for constructing the industrial language system model can be selected according to the actual development scenario. This embodiment of the invention does not limit this. For example, it can be manually written and constructed by developers based on preset industrial language specifications. Or, it can be automatically constructed by combining a dedicated industrial language editing tool with the requirement information text.

[0024] Step 102: Analyze the industrial language system model to obtain the analysis result.

[0025] In this embodiment of the invention, parsing the industrial language system model is a process of logically decomposing and extracting information from the standardized language model. This process can be executed by a dedicated parsing engine or parsing program. This embodiment of the invention does not limit the specific execution carrier or implementation algorithm of the parsing.

[0026] In this embodiment of the invention, the parsing process can achieve complete and accurate extraction of model information through multi-stage verification analysis, ensuring that the parsing results can truly reflect the flexible manufacturing demand information carried by the industrial language system model. This embodiment of the invention does not limit the specific execution steps or stage division of the parsing.

[0027] In this embodiment of the invention, the parsing result is a standardized data set obtained after parsing the industrial language system model. It is a structured presentation of the core information in the model and can be directly used as the data source for generating an automated programming system. This embodiment of the invention does not limit the specific data format or presentation form of the parsing result.

[0028] Step 103: Based on the analysis results, generate an automated programming system for flexible manufacturing; wherein, the automated programming system is used to generate control instructions for controlling flexible manufacturing equipment.

[0029] In this embodiment of the invention, generating an automated programming system based on the parsing results is a process of transforming structured parsed data into an industrial software system that can actually run. This process can realize the automatic construction of system architecture and the automatic generation and integration of functional modules. This embodiment of the invention does not limit the specific technical means or implementation path of the generation.

[0030] In this embodiment of the invention, the generated automated programming system for flexible manufacturing is a dedicated programming software system adapted to the flexible manufacturing scenario. It can independently realize programming operations related to flexible manufacturing. Its core function is to generate control instructions that can drive the operation of flexible manufacturing equipment, thereby meeting the core requirements of automated processing in flexible manufacturing. This embodiment of the invention does not limit the specific interface form or operation logic of the system.

[0031] In this embodiment of the invention, flexible manufacturing equipment refers to various industrial equipment used for processing and production in flexible manufacturing scenarios, and the control command refers to standardized instructions that can be recognized and executed by the flexible manufacturing equipment to guide the equipment to complete processing actions. This embodiment of the invention does not limit the specific type of flexible manufacturing equipment or the specific form of the control command.

[0032] According to embodiments of the present invention, an industrial language system model is constructed based on a preset industrial language specification and the requirements of flexible manufacturing. After parsing the industrial language system model to obtain the parsing results, an automated programming system for flexible manufacturing is automatically generated based on the parsing results. This achieves an efficient and standardized transformation from flexible manufacturing requirements to an automated programming system, replacing the traditional waterfall development model of industrial software that relies on manual labor. This significantly shortens the development cycle of flexible manufacturing-related programming software, reduces the difficulty of customized development, and improves the adaptability and scalability of the generated programming system to different flexible manufacturing scenarios. It can better meet the real-time and personalized development needs of small-batch, multi-batch flexible manufacturing scenarios.

[0033] Traditional industrial software development generally adopts the waterfall development process, such as Figure 2 As shown on the left, this process is characterized by full-process manual implementation, consisting of five sequential stages: requirements analysis, architecture design, detailed design, coding, and testing and delivery. Manual iteration and requirement adaptation are required throughout the entire process. In this model, the software development stages are fragmented yet interconnected; any problem in any stage necessitates backtracking and adjustments. This results in lengthy development cycles, high customization difficulty, and weak system reusability and scalability. Furthermore, the reliance on manual participation leads to high labor costs, susceptibility to human error, low efficiency in requirements iteration, and difficulty in quickly responding to the real-time and personalized development needs of flexible manufacturing scenarios.

[0034] The method for generating an automated programming system for flexible manufacturing provided by this invention adopts a novel development process oriented towards industrial languages, such as... Figure 2As shown on the right, a fully automated development chain of "requirements → model → software" is constructed with the three-dimensional four-layer unified model paradigm as the core support: First, taking the flexible manufacturing requirements of the industrial domain as input, a standardized industrial language system model (i.e., IL industrial language model) is built based on the preset industrial language specifications through manual modeling, completing the transformation from requirements to mathematical domain model; then, through the automatic parsing of the industrial language system model, an automated programming system for flexible manufacturing is automatically generated based on the parsing results, realizing the automated output from model to software domain. The entire process does not require manual coding development, and only manual iteration is needed to complete the continuous optimization of requirements and rapid iteration of the system.

[0035] Compared to the traditional waterfall development model, the core advantage of this invention is: Automated development process: It replaces the traditional manual development model that covers the entire process, and realizes efficient and automated transformation from requirements to models and then to software systems, which greatly shortens the software development cycle and reduces the difficulty of customized development.

[0036] Streamlined demand iteration: The entire process can be re-run without needing to go through it all again. The system can be updated and adapted quickly by manually adjusting the industrial language system model, which greatly improves the efficiency of demand iteration.

[0037] The system boasts strong adaptability and scalability: Based on a unified industrial language standard and a three-dimensional four-layer unified model paradigm, the generated system can flexibly adapt to different flexible manufacturing scenarios, significantly improving system reusability and scalability.

[0038] Controllable development quality: The system is generated through a standardized process of model analysis, which avoids human error caused by manual coding and improves the stability and reliability of the system.

[0039] In one optional embodiment of this application, a specific implementation method for constructing an industrial language system model for realizing flexible manufacturing based on a preset industrial language specification and according to the requirements of flexible manufacturing may include: constructing the industrial language system model based on the preset industrial language specification and in combination with the production line requirements, process definitions, functional requirements and equipment parameters of flexible manufacturing; wherein, the preset industrial language specification is formulated based on the three-dimensional four-layer unified model paradigm of industrial systems, and the industrial language system model includes three dimensions: method, process and entity, and four layers: system layer, unit layer, characteristic layer and data layer.

[0040] Under the constraints of pre-defined industrial language specifications, the core process of transforming the actual business needs of flexible manufacturing into standardized and structured models is achieved. By integrating multi-dimensional actual demand information, the constructed industrial language system model can fully and accurately carry the business logic and operational requirements of flexible manufacturing. This embodiment of the invention does not limit the specific modeling tools and implementation methods.

[0041] The pre-defined industrial language specification is based on the three-dimensional, four-layer unified model paradigm of industrial systems. It provides unified grammatical rules, semantic rules, and structural organization rules for the construction of industrial language system models, ensuring that the constructed models are standardized, universal, and parsable. This embodiment of the invention does not restrict the specific form of the specification clauses.

[0042] By combining the above-mentioned detailed requirements and parameters to construct an industrial language system model, the model can more accurately match the actual production and development needs of flexible manufacturing, ensuring that the subsequent automated programming system generated based on the model can be directly adapted to actual application scenarios. This embodiment of the invention does not restrict the specific order in which the model is constructed by combining various requirements and parameters.

[0043] The unified three-dimensional, four-layer model paradigm for industrial systems is a top-level framework paradigm used to guide the modeling of industrial language systems. By defining a unified method for dimensional and hierarchical division, it achieves a complete and structured expression of flexible manufacturing scenarios. The industrial language system model includes three dimensions: method, process, and entity; and four layers: system layer, unit layer, characteristic layer, and data layer. Based on this three-dimensional, four-layer paradigm, and combined with the needs of industrial scenarios, four core elements—human, machine, object, and environment—are clearly defined.

[0044] Before constructing an industrial language system model, a paradigm adaptation step needs to be performed. Specifically, this involves: identifying the core requirements of the target industrial scenario (flexible manufacturing, robotic welding, intelligent warehousing, etc.), and based on the unified three-dimensional four-layer model paradigm of the industrial system, clarifying the specific connotations, attributes, and interaction constraints of the four core elements: human, machine, object, and environment. During the adaptation and adjustment process, the core architecture of the three-dimensional four-layer paradigm is not changed (i.e., the division of the three dimensions and four levels is not adjusted), and only the attribute parameters and interaction rules of the four elements are optimized to adapt to the differentiated needs of different industrial scenarios.

[0045] After paradigm adaptation is completed, through the architecture mapping step, based on the adapted three-dimensional four-layer paradigm, a four-layer development architecture of system-unit-feature-data for industrial software is constructed. The four types of elements, namely people-machine-object-environment, are accurately mapped to the corresponding levels of the four-layer architecture, realizing the collaborative adaptation of elements and architecture.

[0046] The method dimension is used to characterize the implementation rules and means such as process methods, control methods, and scheduling methods used in flexible manufacturing; the process dimension is used to characterize the temporal and logical relationships such as processing procedures, production line flow, and task execution; and the entity dimension is used to characterize the physical objects and carriers existing in the flexible manufacturing scenario.

[0047] For example, the method dimension may include cutting methods and robot motion control methods; the process dimension may include the process flow of loading, processing, inspection and unloading; the entity dimension may include CNC machine tools, industrial robots, processed workpieces, tooling fixtures, etc.

[0048] The human element includes operators and managers, with corresponding attributes such as operating authority, skill level, and job responsibilities; the machine element includes industrial equipment such as CNC machine tools and industrial robots, with corresponding attributes such as equipment model, operating parameters, processing accuracy, and fault warning threshold; the material element includes processed parts and raw materials, with corresponding attributes such as size specifications, material, inventory information, and loss rate; and the environmental element includes environmental parameters such as workshop temperature, humidity, wind speed, and dust concentration, with corresponding attributes such as adaptability range, interference level, and control threshold.

[0049] The system layer describes the overall composition and macro-architecture of the industrial language system model, representing the top-level logic of the entire flexible manufacturing system; the unit layer is used to modularly decompose the system, describing the division and interaction relationships of each independent functional unit or equipment unit; the characteristic layer describes the attributes, capabilities, constraints, and other characteristics of each unit; and the data layer carries various basic data, parameter data, and status data that support the operation of the model.

[0050] For example, the system layer can characterize the overall control logic of the entire flexible production line; the unit layer can be divided into feeding units, processing units, and transfer units; the characteristic layer can describe the operating accuracy, load capacity, and speed range of each unit; and the data layer can store data such as equipment coordinates, process parameters, and environmental parameters.

[0051] Each level follows a preset hierarchical linkage rule: the system layer coordinates the collaborative work of each unit layer, the unit layer supports the design of the feature layer, the feature layer relies on the data layer to realize quantitative expression, and each layer completes data interaction and command transmission through standardized interfaces such as Modbus, Profinet, EtherCAT, and JSON to ensure consistent hierarchical collaboration.

[0052] The production line requirements, process definitions, functional requirements, and equipment parameters of flexible manufacturing are the specific business inputs for constructing the industrial language system model. Among them, production line requirements include requirements such as production line layout, capacity requirements, and linkage methods; process definitions include definitions such as processing steps, process standards, and precision requirements; functional requirements include the capabilities the system needs to achieve, such as data acquisition, simulation verification, and instruction generation; and equipment parameters include relevant parameters such as equipment model, operating range, interface type, and control parameters. This embodiment of the invention does not impose limitations on these parameters.

[0053] By establishing a pre-defined industrial language specification based on the unified three-dimensional four-layer model paradigm of industrial systems, and combining production line requirements, process definitions, functional requirements, and equipment parameters, an industrial language system model is constructed. The model is organized according to three dimensions (method, process, and entity) and four levels (system layer, unit layer, characteristic layer, and data layer). This results in a clear, hierarchical, and semantically complete model structure that can comprehensively and systematically express various requirements and operational logics of flexible manufacturing. This provides a stable and unified foundation for subsequent model parsing and automated programming system generation, further enhancing the model's versatility, parsingability, and scenario adaptability.

[0054] In one optional embodiment of this application, a specific implementation of parsing the industrial language system model to obtain the parsing result may include: performing lexical analysis, syntactic analysis, and semantic verification on the industrial language system model to extract structured elements; wherein, the structured elements include at least one of the following: system architecture, functional modules, process logic, control rules, and interface requirements; and generating standardized parsing results based on the structured elements.

[0055] Parsing the industrial language system model involves performing legality checks, logical organization, and information extraction on its content after model construction. This step standardizes the overall content of the model by sequentially performing lexical analysis, syntactic analysis, and semantic verification, and extracts key information that can be used for subsequent system generation. This embodiment of the invention does not restrict the specific execution order or implementation tools.

[0056] Lexical analysis refers to the basic identification and decomposition of language symbols used in industrial language system models. It involves identifying, classifying, and verifying basic language units such as characters, words, and keywords in the model to determine whether they belong to the set of legal symbols allowed by the preset industrial language specifications. This embodiment of the invention does not impose restrictions on specific lexical rules.

[0057] The pre-defined industrial language standard has a dedicated lexical specification that defines keywords, variables, constants, operators, and special symbols. Among them, special symbols include the unit group and unit name starting identifier "$", the characteristic and parameter starting identifier "*", the unit name or characteristic parameter name identifier "{}", the unit number or parameter value identifier "[]", and the environmental parameter identifier "#". The usage rules of various symbols correspond one-to-one with the hierarchy of the three-dimensional four-layer paradigm and the four element types of human-machine-object-environment.

[0058] For example, basic units such as process names, equipment types, and parameter names in the model text are identified and categorized, and character combinations that do not conform to the specifications are removed.

[0059] Syntax analysis, based on lexical analysis, further judges the legality of the sentence structure and combination relationship in the industrial language system model, verifies whether the combination of each language unit in the model conforms to the grammatical rules and compositional logic of the preset industrial language specification, and avoids problems such as structural errors and format confusion. The embodiments of this invention do not limit the specific grammatical rules.

[0060] For example, verify whether the statements in the model concerning process logic and control rules conform to the prescribed sentence structure to ensure that the statements can be correctly identified and parsed.

[0061] Semantic verification is a process of verifying the rationality of the actual meaning, logical relationships, and constraints expressed by the industrial language system model. It determines whether there are logical conflicts, contradictions, or situations that do not conform to common sense in industrial scenarios, and ensures that the requirements and rules carried by the model are executable. This embodiment of the invention does not limit the specific verification dimensions.

[0062] The standard simultaneously established semantic and pragmatic specifications. The semantic specifications clarified the one-to-one mapping relationship between industrial language vocabulary, sentence structure and the three-dimensional four-layer unified model paradigm (three dimensions and four levels), and the four elements of human-machine-object-environment. The pragmatic specifications defined the parsing logic of the parser and the conversion rules to software functional components. Semantic verification is based on the specifications to verify whether there are conflicts, out-of-bounds issues or other problems in the model logic.

[0063] For example, verifying whether the equipment operating parameters set in the verification model are within a reasonable range, and whether there are logical conflicts in the sequence of processes.

[0064] Structured elements refer to core information items with clear business meaning and fixed organizational form extracted from an analyzed and verified industrial language system model, used to directly generate software systems. Structured elements include at least one of the following: system architecture, functional modules, process logic, control rules, and interface requirements; however, this embodiment of the invention does not impose any limitations on these.

[0065] The system architecture characterizes the overall composition, hierarchical relationships, and module division of the automated programming system to be generated. For example, it determines the overall organizational form of the system, such as a layered architecture, a modular architecture, or a service-oriented architecture.

[0066] Functional modules are used to characterize the independent functional units that an automated programming system should possess. Examples include functional units such as equipment management, process configuration, path planning, simulation verification, and instruction generation.

[0067] Process logic is used to characterize the sequence of processes, processing flow, process constraints, and flow relationships in flexible manufacturing. For example, a process flow of loading materials first, then processing, and finally inspection, as well as the triggering conditions between each process.

[0068] Control rules are used to characterize equipment operating conditions, parameter thresholds, linkage constraints, safety limitations, and other rule content. For example, the upper limit of equipment operating speed, the timing of multi-device linkage, and the correlation constraints between environmental parameters and processing parameters.

[0069] Interface requirements characterize the interaction methods, displayed content, operation entry points, and layout of an automated programming system. Examples include requirements for parameter configuration interfaces, simulation display interfaces, and instruction export interfaces.

[0070] The extracted structured elements are organized, summarized, and packaged according to a unified format and structure to form standardized data content that is clear in structure, uniform in format, and easy for subsequent programs to read and use. This is the standardized parsing result. This embodiment of the invention does not limit the specific format.

[0071] Standardized parsing results can be presented in the form of structured data files, intermediate description files, configuration lists, model mapping tables, etc. Their purpose is to provide a unified, reliable, and complete input basis for the subsequent generation of automated programming systems, avoiding conversion errors or generation failures due to inconsistent formats and scattered information.

[0072] For example, structured elements such as system architecture, functional modules, and process logic can be organized into standard JSON, XML format files or configuration tables for direct use in subsequent system generation processes.

[0073] By performing lexical analysis, syntactic analysis, and semantic verification on the industrial language system model, at least one structured element from the system architecture, functional modules, process logic, control rules, and interface requirements is extracted. Based on the structured elements, standardized parsing results are generated, making the model parsing process more standardized and rigorous. The parsing results have a unified structure and complete content, which can stably support the automatic generation of subsequent automated programming systems, reduce human intervention and human error, and improve the efficiency and reliability of the conversion from requirement models to software systems.

[0074] In one optional embodiment of this application, a specific implementation of generating an automated programming system for flexible manufacturing based on the analysis results may include: generating the overall architecture of the automated programming system based on the analysis results, and breaking it down into corresponding core functional modules; wherein, the core functional modules include at least one of the following: equipment management module, process programming module, path planning module, code generation module, simulation verification module, task control module, and system management module.

[0075] The core of transforming standardized parsing results into a practically operable flexible manufacturing automated programming system lies in relying on the structured elements in the parsing results to complete the construction of the overall system framework and the decomposition of functional units, thereby realizing the automated conversion from structured data to a software system. This invention does not limit the specific generation tools or technical means.

[0076] The overall architecture of an automated programming system refers to the overall organizational form, hierarchical division, inter-module relationships, and operating mechanism of the software system to be generated. It is the "skeleton" of the system, which determines the overall operating logic and scalability of the system. Its design must fully match the system architecture elements extracted from the analysis results.

[0077] For example, based on the system architecture elements in the parsing results, a layered architecture of "data layer - logic layer - application layer" can be generated, clarifying the functional positioning and data flow relationship of each layer; or a modular architecture can be generated, clarifying the interface definition and linkage method of each module.

[0078] Core functional modules refer to units in an automated programming system that have independent functions, can operate independently, and can work collaboratively. They are the "flesh and blood" of the system to realize its core functions. The design of the functions of each module must completely correspond to the functional module elements extracted from the analysis results. This embodiment of the invention does not limit the specific number or combination of modules.

[0079] The core functional modules include at least one of the following, and the embodiments of the present invention do not limit this.

[0080] Equipment Management Module: Used for unified management, status monitoring, parameter configuration and fault warning of various equipment in flexible manufacturing scenarios to ensure normal equipment operation.

[0081] For example, managing the operating status of CNC machine tools and industrial robots, configuring equipment processing parameters and operating thresholds, and monitoring equipment for malfunctions in real time and issuing early warnings.

[0082] Process programming module: Used to plan, edit and optimize flexible manufacturing processes, supporting the configuration of processing parameters and the sorting of processes.

[0083] For example, the processing steps of flexible manufacturing can be edited, and process parameters such as toolpath planning, processing speed, and feed rate can be configured to optimize the process connection logic.

[0084] Path planning module: Used to plan the motion trajectory and processing path of flexible manufacturing equipment to ensure efficient and interference-free processing.

[0085] For example, planning the loading, processing, and unloading trajectories of industrial robots, and planning the tool paths of CNC machine tools to avoid collisions during equipment movement.

[0086] Code generation module: Used to automatically generate control commands that can drive the operation of flexible manufacturing equipment based on process configuration and path planning.

[0087] For example, generating NC code and G code adapted to CNC machine tools, and generating motion control programs adapted to industrial robots.

[0088] Simulation verification module: Used to simulate process configuration, path planning and control commands to verify their rationality and feasibility, and avoid problems in actual processing.

[0089] For example, simulations can be used to check for interference in the processing path and whether control commands can drive the equipment to operate normally, thus identifying potential faults in advance.

[0090] Task management module: Used for unified scheduling, progress management and priority allocation of processing tasks in flexible manufacturing to ensure the orderly progress of production tasks.

[0091] For example, assign processing tasks to each piece of equipment, monitor task completion progress, adjust task priorities, and ensure efficient progress of small-batch, multi-batch production.

[0092] System Management Module: Used to manage the automated programming system itself, including user permission management, data backup and recovery, system parameter configuration, etc.

[0093] For example, setting different user access permissions, regularly backing up system data, and configuring system operating parameters and communication protocols.

[0094] The process of generating the overall architecture and breaking down core functional modules can be automated, eliminating the need for manual coding and design. The system can automatically match the corresponding architecture templates and module templates based on the structured elements in the parsing results, quickly completing the construction and decomposition, and significantly shortening the system development cycle.

[0095] For example, the system can extract functional module elements such as "equipment management, process programming, and simulation verification" from the analysis results. The system can automatically split and generate three corresponding core functional modules, build an overall architecture that adapts to these three modules, and clarify the interface and data flow relationship between each module.

[0096] By generating the overall architecture of the automated programming system based on the parsing results, and breaking it down into at least one core functional module such as an equipment management module and a process programming module, the system achieves efficient and automated conversion from structured parsing data to an automated programming system. This replaces the cumbersome process of traditional manual architecture design and module coding, significantly shortening the system development cycle and reducing development difficulty. At the same time, the generated architecture and modules are perfectly matched to the needs of flexible manufacturing, ensuring that the subsequent system can stably realize the automatic generation of flexible manufacturing control commands, thereby improving the system's scenario adaptability and practical value.

[0097] Reference Figure 3 This document illustrates a flowchart of the steps involved in an automated programming method for flexible manufacturing based on an industrial language, according to an embodiment of this application. This method is applied to an automated programming system for flexible manufacturing and may specifically include the following steps: Step 201: Obtain processing-related data for flexible manufacturing and extract key processing parameters.

[0098] In this embodiment of the invention, the core of the basic preparation step for automated programming is to acquire various basic data required in the flexible manufacturing process and extract the core parameters that affect the processing quality, efficiency and equipment operation, so as to provide data support for subsequent process configuration and instruction generation. This embodiment of the invention does not limit the data acquisition method or parameter extraction method.

[0099] In this embodiment of the invention, the processing-related data of flexible manufacturing refers to various types of data directly related to processing and production during the flexible manufacturing process, covering multiple aspects such as processing objects, production line layout, and production environment. It is the basis for extracting key processing parameters. This embodiment of the invention does not limit the specific type or storage format of the data.

[0100] The processing-related data includes at least one of the following: part 3D model, workpiece model, and production line layout model. This embodiment of the invention does not limit this.

[0101] For example, a 3D model of a part is used to represent the core information such as the shape, size, and structure of the workpiece to be processed; a workpiece model is used to represent the initial state and processing requirements of the workpiece to be processed; and a production line layout model is used to represent information such as the equipment distribution and layout relationships of a flexible manufacturing production line.

[0102] Methods for obtaining processing-related data may include local import, cloud retrieval, and equipment acquisition. For example, a well-designed 3D model of a part can be imported from a local terminal into an automated programming system, or a production line layout model can be retrieved from a cloud server.

[0103] In this embodiment of the invention, the key processing parameters refer to the core parameters extracted from processing-related data that play a decisive role in the flexible manufacturing process, processing quality, and equipment operation. They directly affect the rationality of subsequent process configuration and the accuracy of control commands. This embodiment of the invention does not limit the specific number or value range of the parameters.

[0104] The key processing parameters include at least one of processing accuracy, equipment compatibility parameters, material specifications, and processing cycle time, and the embodiments of the present invention do not limit these parameters.

[0105] The specific explanations and examples of each key processing parameter are as follows: Machining accuracy: refers to the dimensional accuracy, surface roughness, and other quality requirements that the machined workpiece must achieve, and is the core indicator for measuring machining quality.

[0106] For example, when machining metal parts, the machining accuracy is set to ±0.01mm to ensure that the dimensional deviation of the parts is within the allowable range.

[0107] Equipment compatibility parameters: These are parameters that match the model, performance, and operating range of the flexible manufacturing equipment to ensure that the process configuration is compatible with the equipment capabilities.

[0108] For example, for a specific model of CNC machine tool, extract its spindle speed range, machining stroke and other equipment adaptation parameters to avoid configuring process parameters that exceed the equipment's capabilities.

[0109] Material specifications: These refer to the dimensions, material, quantity, and other relevant parameters of the materials to be processed or raw materials, which affect the design of the process plan.

[0110] For example, the dimensions of the part to be processed are 50mm×30mm×10mm, and the material is stainless steel, which serves as the basis for toolpath planning and processing speed setting in the process configuration.

[0111] Processing cycle time: refers to the time required for a single workpiece to be processed from start to finish. It is a core parameter for planning production schedules and optimizing production efficiency.

[0112] For example, the processing cycle is set to 10 minutes per workpiece to ensure that the production schedule meets the batch production requirements of flexible manufacturing.

[0113] In this embodiment of the invention, the extraction of key processing parameters can be automated. The automated programming system can automatically identify and extract core parameters from the imported processing-related data. If some parameters cannot be automatically extracted, the user can supplement the configuration based on actual processing needs. This embodiment of the invention does not impose any restrictions on this.

[0114] For example, the system automatically extracts parameters such as part size and machining accuracy from the 3D model of the part, and the user can supplement and configure the machining cycle parameters according to the actual production needs.

[0115] Step 202: Configure the process for the key processing parameters and complete the simulation verification of the processing scheme.

[0116] In this embodiment of the invention, the core of automated programming consists of two core actions: first, configuring the process based on key processing parameters to clarify the specific rules and parameters of the processing process; second, simulating and verifying the configured processing scheme to ensure the rationality and feasibility of the scheme and avoid failures during actual processing. This embodiment of the invention does not limit the specific method of process configuration or the specific means of simulation verification.

[0117] Step 203: After the simulation verification is passed, control commands for the operation of the flexible manufacturing equipment are automatically generated.

[0118] In this embodiment of the invention, the core of the final output stage of automated programming is that after the processing scheme simulation verification is passed and no problems are confirmed, the automated programming system automatically converts the process configuration results into control instructions that can be recognized and executed by the flexible manufacturing equipment, so as to realize the automated connection from process configuration to equipment control. This embodiment of the invention does not limit the specific form of the control instructions or the generation algorithm.

[0119] In this embodiment of the invention, the control instructions for controlling the operation of flexible manufacturing equipment are standardized instructions that can be directly recognized and executed by the flexible manufacturing equipment, used to guide the equipment to complete specific processing actions, and their form must be adapted to the type of equipment.

[0120] For example, it can adapt to NC code and G code of CNC machine tools, and motion control programs and trajectory planning paths of industrial robots. This embodiment of the invention does not limit these aspects.

[0121] The generated control commands can be directly sent to the flexible manufacturing equipment to drive the equipment to perform processing actions, or they can be exported as editable files for users to adjust and optimize later. This embodiment of the invention does not limit this.

[0122] According to embodiments of the present invention, by acquiring processing-related data of flexible manufacturing and extracting key processing parameters, configuring the process for the key processing parameters and completing the simulation verification of the processing scheme, and automatically generating control commands to control the operation of the flexible manufacturing equipment after the simulation verification is passed, the entire process of flexible manufacturing programming is automated, replacing the cumbersome process of traditional manual teaching and debugging and manual writing of control commands, which greatly improves programming efficiency and reduces the number of debugging times. At the same time, the simulation verification stage can identify potential problems in the processing process in advance, ensuring the accuracy and reliability of control commands, improving the processing quality and efficiency of flexible manufacturing, and adapting to the rapid changeover requirements of small-batch, multi-batch flexible manufacturing.

[0123] In one optional embodiment of this application, the processing-related data includes at least one of a three-dimensional model of the part, a workpiece model, and a production line layout model; the key processing parameters include at least one of processing accuracy, equipment adaptation parameters, material specifications, and processing cycle time.

[0124] Processing-related data and key processing parameters are the foundational data for flexible manufacturing automation programming. Their specific types, connotations, and forms of expression are as follows. This invention does not limit the specific details.

[0125] First, processing-related data refers to various basic data that support the automated programming and processing of flexible manufacturing. It is a prerequisite for extracting key processing parameters and configuring processes. Its core function is to provide comprehensive and accurate basic information for automated programming, ensuring that subsequent process configuration and control command generation are consistent with the actual processing scenario.

[0126] The processing-related data includes at least one of the following: part 3D model, workpiece model, and production line layout model. This embodiment of the invention does not limit this. The specific explanations and examples of each type of data are as follows: A 3D model of a part is a model that digitally represents the shape, size, structure, and machining features of the part to be machined. It is the core basis for extracting machining parameters and planning machining paths.

[0127] For example, a 3D model of a metal gear drawn using CAD software clearly marks the gear's machining features such as the number of teeth, module, and tip circle diameter. After being imported into an automated programming system, the system can automatically extract relevant machining parameters from it.

[0128] Workpiece model: A model that represents the initial state, processing requirements, and processing allowance of the workpiece to be processed. It differs from the three-dimensional model of the part and focuses more on the state description of the workpiece during the processing.

[0129] For example, the workpiece model of the sheet material to be processed is marked with information such as the initial size of the sheet material, machining allowance, and parts to be processed, which provides a basis for toolpath planning and machining depth setting in process configuration.

[0130] Production line layout model: This is a model that represents information such as equipment distribution, equipment spacing, material flow path, and workstation layout of a flexible manufacturing production line, and is used to adapt to scenarios where multiple devices work together.

[0131] For example, a production line layout model that includes CNC machine tools, industrial robots, and material conveyors can be used to mark the location and linkage relationship of each piece of equipment, providing a basis for multi-equipment collaborative process configuration and linkage timing setting.

[0132] The method of acquiring processing-related data can be selected according to actual production needs, such as importing from local terminals, retrieving from cloud servers, acquiring and modeling data from industrial cameras, etc. This embodiment of the invention does not limit the specific acquisition method, as long as complete and accurate basic data can be obtained.

[0133] Secondly, key processing parameters are core parameters extracted from processing-related data that play a decisive role in the flexible manufacturing process, processing quality, and production efficiency. They are the core basis for process configuration and directly affect the accuracy of control commands and processing results.

[0134] Key processing parameters include at least one of processing accuracy, equipment compatibility parameters, material specifications, and processing cycle time. This invention does not limit these parameters. Specific explanations and examples of each type of parameter are as follows: Machining accuracy: refers to the quality standards that the workpiece to be processed must meet, mainly including dimensional accuracy, surface roughness, geometric tolerances, etc. It is the core indicator for measuring machining quality and directly determines the performance of the workpiece.

[0135] For example, when machining precision bearing parts, the dimensional accuracy is set to ±0.005mm and the surface roughness is Ra0.8μm to ensure the rotational accuracy and service life of the bearing; when machining ordinary mechanical parts, the dimensional accuracy is set to ±0.1mm to meet the requirements of normal use.

[0136] Equipment compatibility parameters: These are parameters that match the performance, model, and operating range of the flexible manufacturing equipment. They are used to ensure that the process configuration parameters do not exceed the equipment's load-bearing capacity and to avoid equipment failure or processing errors.

[0137] For example, for a CNC machine tool with model number CK6140, extract its spindle speed range (100-1000 r / min), machining stroke (X-axis 400 mm, Z-axis 1000 mm), and other equipment adaptation parameters. The spindle speed and machining stroke in the process configuration must be set within this range. For industrial robots, extract their motion range, load capacity, and other adaptation parameters to ensure that the path planning conforms to the robot's motion capabilities.

[0138] Material specifications: refers to the core characteristic parameters of the materials and raw materials to be processed, including size, material, hardness, quantity, etc., which affect the design of the process plan (such as toolpath planning, processing speed, and tool selection).

[0139] For example, if the material to be processed is an aluminum alloy sheet with dimensions of 50mm×50mm×10mm and a hardness of HB100, based on the material specifications, appropriate cutting tools can be selected in the process configuration, and reasonable processing speed and feed rate can be set to avoid deformation caused by the material being too soft.

[0140] Processing cycle time: refers to the time required for a single workpiece to be processed from start to finish. It is a core parameter for planning production schedule and optimizing production efficiency, and is adapted to the production needs of flexible manufacturing with small batches and multiple batches.

[0141] For example, when producing mobile phone casing parts in small batches, the processing cycle is set to 8 minutes per workpiece to ensure that 7-8 workpieces can be completed per hour, meeting the requirements of mass production schedule; for customized parts, the processing cycle can be appropriately extended to ensure processing quality.

[0142] The extraction of key processing parameters can be automated. The automated programming system can automatically identify and extract the above-mentioned key parameters by parsing processing-related data. If some parameters cannot be automatically extracted from the data (such as precision parameters corresponding to special processing requirements), users can also manually supplement and configure them based on actual processing needs. This embodiment of the invention does not impose any restrictions on this.

[0143] Clearly defining the processing-related data includes at least one of the following: part 3D model, workpiece model, and production line layout model. Key processing parameters include at least one of the following: processing accuracy, equipment adaptation parameters, material specifications, and processing cycle time. This makes the basic data for automated programming clearer and more explicit, ensuring reliable data support for subsequent process configuration, simulation verification, and instruction generation. It avoids programming errors or processing failures caused by data ambiguity or missing parameters, further improving the accuracy and reliability of automated programming in flexible manufacturing and adapting to the processing needs of different flexible manufacturing scenarios.

[0144] In one optional embodiment of this application, a specific implementation of configuring the key processing parameters may include: configuring at least one of toolpath planning, processing speed, feed rate, process connection parameters, multi-device linkage timing, and action coordination parameters according to the processing steps and process rules of flexible manufacturing.

[0145] The core of process configuration is to clearly configure various specific parameters in the process based on the extracted key processing parameters and combined with the actual processing procedures and process rules of flexible manufacturing, so as to ensure that the processing is carried out in an orderly, efficient and high-quality manner. This embodiment of the invention does not restrict the specific order of configuration or the parameter values.

[0146] The processing steps in flexible manufacturing refer to a series of orderly processing steps that a workpiece must go through from its initial state to the completion of processing in the flexible manufacturing process. The sequence of processing and the core tasks of each step are clearly defined, which is the basis for process configuration.

[0147] For example, the processing steps for metal parts are: blanking → turning → milling → drilling → grinding → inspection; the processing steps for plastic parts are: injection molding → trimming → polishing → inspection. This embodiment of the invention does not limit the specific division of processing steps.

[0148] Process rules refer to the processing standards, operating procedures, and technical requirements that must be followed in flexible manufacturing. They are used to ensure processing quality and safety and serve as the basis for process configuration.

[0149] For example, the rule of "rough turning first and then finish turning" in turning process ensures machining accuracy; the rule of "positioning first and then drilling" in drilling process avoids drilling deviation; the rule of "loading first and then processing, processing first and then unloading" in multi-equipment collaborative processing ensures orderly production. The embodiments of the present invention do not limit the specific content of the process rules.

[0150] The specific parameters of the process configuration include at least one of the following: toolpath planning, machining speed, feed rate, process connection parameters, multi-device linkage timing, and motion coordination parameters. This embodiment of the invention does not impose any limitations on these parameters. Specific explanations and examples of each parameter are as follows: Toolpath planning refers to planning the tool movement trajectory of flexible manufacturing equipment (such as CNC machine tools and machining centers), clarifying the tool path, cutting depth, cutting width, etc. The core is to ensure machining accuracy, improve machining efficiency, and reduce tool wear.

[0151] For example, when machining planar parts, a "parallel feed" toolpath is used, with a cutting depth of 2mm and a cutting width of 5mm; when machining complex curved parts, a "constant height feed" toolpath is used to ensure smooth machining and meet the required accuracy.

[0152] Processing speed: refers to the processing execution speed of flexible manufacturing equipment, mainly including spindle speed, tool movement speed, etc. It needs to be configured according to the material specifications and processing accuracy in the key processing parameters to avoid processing errors caused by excessive speed and production efficiency affected by excessive speed.

[0153] For example, when machining steel with high hardness, the spindle speed is set to 500 r / min, which results in a slower machining speed and ensures machining accuracy; when machining aluminum alloys with lower hardness, the spindle speed is set to 1000 r / min to improve machining efficiency.

[0154] Feed rate: refers to the feed speed of the tool during the machining process, that is, the distance the tool moves per unit time. It is closely related to the machining speed, material specifications, and machining accuracy, and directly affects the surface quality and machining efficiency.

[0155] For example, during finish turning, the feed rate is set to 0.1 mm / r to ensure a smooth machined surface; during rough turning, the feed rate is set to 0.3 mm / r to improve machining efficiency.

[0156] Process connection parameters: These refer to parameters such as connection conditions, connection time, and connection method between various processing steps. They are used to ensure orderly connection between processes and avoid problems such as process disconnection or excessive waiting time.

[0157] For example, after the turning process is completed, the connection time is set to 10 seconds, and the milling process will start automatically after 10 seconds; after the milling process is completed, the connection condition of "part size deviation within ±0.01mm" must be met before the drilling process can be started.

[0158] Multi-device linkage timing: refers to the time sequence and time interval of each device starting, running and stopping when multiple devices are working together in a flexible manufacturing scenario, in order to ensure that the collaborative work of multiple devices is orderly and without conflict.

[0159] For example, after the industrial robot completes the loading action, it starts the CNC machine tool for processing after a 5-second delay; after the CNC machine tool completes the processing, it starts the industrial robot for unloading after a 3-second delay, to avoid equipment action conflicts.

[0160] Multi-equipment operation coordination parameters: These refer to parameters such as the range of motion, rhythm of motion, and coordination relationship of each piece of equipment when multiple pieces of equipment are working together. They are used to ensure efficient collaboration among multiple pieces of equipment and improve production efficiency.

[0161] For example, when a CNC machine tool is processing, an industrial robot prepares the next workpiece simultaneously. The robot's loading position is set to align with the CNC machine tool's processing position to ensure fast and accurate loading. The material conveyor belt's running speed is matched with the CNC machine tool's processing cycle to ensure timely material supply.

[0162] The process configuration can be automated. The automated programming system can automatically match the optimal process parameter configuration scheme based on key processing parameters, processing steps and process rules. If the user has special processing requirements, the process parameters can also be manually adjusted. This embodiment of the invention does not impose any restrictions on this.

[0163] For example, the system automatically configures the processing speed to 800 r / min and the feed rate to 0.15 mm / r based on the extracted material specifications (aluminum alloy sheet) and processing accuracy (±0.01 mm). Users can manually adjust the processing speed to 750 r / min and the feed rate to 0.12 mm / r according to the actual processing effect.

[0164] By configuring at least one process parameter, such as toolpath planning, machining speed, and feed rate, based on the processing procedures and process rules of flexible manufacturing, the process configuration scheme can be made more in line with the actual processing needs, ensuring that the processing process proceeds in an orderly, efficient, and high-quality manner. At the same time, for multi-device collaborative processing scenarios, configuring linkage timing and action coordination parameters can achieve efficient collaboration of multiple devices, avoid device action conflicts, further improve the production efficiency and processing quality of flexible manufacturing, and adapt to the rapid changeover and collaborative processing needs of small-batch, multi-batch flexible manufacturing.

[0165] In one optional embodiment of this application, a specific implementation of the simulation verification of the processing scheme may include: performing at least one simulation verification, such as interference analysis or collision detection, on the processing scheme after configuring process parameters; if the simulation verification fails, returning to the step of configuring the process key parameters until the simulation verification passes.

[0166] The core of simulation verification is to test the processing plan after configuring process parameters through simulation before actual processing, and to check for problems such as interference and collision that may occur during processing. This ensures the rationality and feasibility of the processing plan and avoids equipment damage and workpiece scrapping during actual processing. This embodiment of the invention does not limit the specific tools or implementation methods of simulation verification.

[0167] The machining scheme after configuring process parameters refers to the complete machining process scheme formed after process configuration, including all aspects such as machining steps, process parameters, toolpath planning, and equipment actions, and is the object of simulation verification.

[0168] For example, a machining scheme that includes two processes, turning and milling, and is configured with parameters such as toolpath planning, machining speed, and feed rate, as well as the linkage timing between the CNC machine tool and the industrial robot, is the object of this simulation verification.

[0169] The specific methods of simulation verification include at least one of interferometry and collision detection. This embodiment of the invention does not limit the methods. The specific explanations and examples of the two methods are as follows: Interference analysis refers to the use of simulation to detect whether there are interference problems such as spatial overlap or motion trajectory intersection between various components during the machining process (such as tool and workpiece, tool and fixture, workpiece and fixture, and multiple devices), ensuring that the movement of each component does not affect each other.

[0170] For example, simulating the tool path of a CNC machine tool can detect whether the tool interferes with the non-machined parts of the workpiece or the fixture during the machining process; simulating multi-device collaborative machining can detect whether the motion trajectory of the industrial robot interferes with the motion trajectory of the CNC machine tool, thus avoiding component collisions and damage.

[0171] Collision detection: refers to the detection of whether direct collisions will occur between physical components (such as tools, workpieces, equipment, and fixtures) during the processing through simulation. It is a detection method that focuses more on "physical contact" than interference analysis, and its core purpose is to avoid equipment damage and workpiece scrap.

[0172] For example, simulating the material loading process of an industrial robot can detect whether the robot arm will collide with the production line support or the CNC machine tool body; simulating the tool machining process can detect whether the tool will collide violently with the workpiece, causing the tool to break or the workpiece to deform.

[0173] The simulation verification process can be realized through the simulation verification module of the automated programming system. The system can build a virtual processing scenario based on the processing plan, process parameters, and equipment model, simulate the actual processing process, detect whether there are interference or collision problems in real time, and record the location, type and cause of the problem for users to view and adjust. This embodiment of the invention does not limit the specific accuracy and speed of the simulation.

[0174] For example, the system constructs a virtual scene that includes CNC machine tools, industrial robots, workpieces, and fixtures. According to the configured process parameters and processing flow, it simulates the entire processing process, detects the interference and collision between the tool and the workpiece and equipment in real time, and generates a simulation report.

[0175] The core of the closed-loop optimization process in simulation verification is to adjust parameters and optimize the scheme to address the problems found in the simulation verification, so as to ensure that the processing scheme ultimately meets the actual processing requirements. This embodiment of the invention does not limit the specific number of adjustments or the adjustment method.

[0176] Simulation verification failure means that problems such as interference or collision were detected during the simulation process, or the processing scheme does not meet the process rules or processing accuracy requirements and cannot be directly used for actual processing.

[0177] For example, if the simulation detects interference between the tool path and the workpiece fixture, or a collision between the industrial robot and the CNC machine tool, these are all cases where the simulation verification fails.

[0178] When the simulation verification fails, it is necessary to return to the steps of configuring the process key parameters and adjust the corresponding process parameters or processing plan for the problems detected by the simulation.

[0179] If interference between the tool and the workpiece is detected, the toolpath planning parameters can be adjusted (such as modifying the tool path and depth of cut), or the fixture position can be adjusted.

[0180] If a collision between multiple devices is detected, the linkage timing and action coordination parameters of the multiple devices can be adjusted (such as extending the device action interval and adjusting the device movement trajectory).

[0181] If the machining accuracy is found to be insufficient, parameters such as machining speed and feed rate can be adjusted.

[0182] After the adjustment is completed, the simulation verification of the processing plan is performed again. The above steps are repeated until the simulation verification is passed (that is, no interference, collision or other problems are detected, and the processing plan meets the process rules and processing accuracy requirements). Only then can the subsequent control command generation stage be entered.

[0183] For example, if the simulation detects interference between the tool and the fixture, return to the process configuration steps, adjust the toolpath planning, and repeat the simulation verification until there is no interference problem and the simulation verification is successful.

[0184] By performing at least one simulation verification, such as interference analysis or collision detection, on the processing scheme after configuring process parameters, if the simulation verification fails, the process configuration steps are returned to adjust the parameters until the verification passes. This allows for the early detection of potential problems in the processing process, avoiding situations such as equipment damage, workpiece scrapping, and excessive processing errors during actual processing, thereby reducing production costs and risks. At the same time, through closed-loop optimization, the final processing scheme is ensured to be reasonable and feasible, providing reliable support for the subsequent automatic generation of accurate control commands, and further improving the processing quality and efficiency of flexible manufacturing.

[0185] In one optional embodiment of this application, it may further include: collecting real-time environmental parameters of the flexible manufacturing process; and dynamically compensating and adjusting the processing-related parameters after the process configuration based on the real-time environmental parameters.

[0186] The core of dynamic compensation and adjustment is to collect on-site environmental parameters that affect processing quality and equipment operation in real time during flexible manufacturing, so as to provide data support for subsequent parameter adjustments and ensure that process configuration parameters can adapt to changes in the on-site environment. This embodiment of the invention does not limit the specific equipment or frequency of data collection.

[0187] Real-time environmental parameters in flexible manufacturing processes refer to environmental factors in the flexible manufacturing site that change over time and may affect processing quality and equipment operating status. These parameters include environmental indicators closely related to industrial processing, such as temperature, humidity, and wind speed. This invention does not limit the specific type or collection range of parameters.

[0188] For example, workshop temperature, workshop humidity, workshop wind speed, and ambient dust concentration, among which temperature, humidity, and wind speed are the core environmental parameters that have the most significant impact on flexible manufacturing processes. This invention focuses on explaining these three types of parameters.

[0189] Real-time environmental parameters can be acquired through environmental monitoring equipment in flexible manufacturing sites, such as temperature sensors, humidity sensors, and wind speed sensors. These devices can collect on-site environmental data in real time and transmit the data to an automated programming system for analysis and adjustment. This embodiment of the invention does not limit the specific model or installation location of the sensors.

[0190] For example, temperature and humidity sensors are installed next to CNC machine tools to collect workshop temperature and humidity data every 10 seconds; wind speed sensors are installed above the production line to collect workshop wind speed data every 15 seconds and transmit it to the automation programming system in real time.

[0191] The core of dynamic compensation adjustment is that the automated programming system analyzes the collected real-time environmental parameters to determine whether they exceed the preset reasonable range. If they exceed the range or change significantly, the system promptly compensates and adjusts the processing-related parameters after the process configuration to ensure that the processing quality is not affected by environmental changes. This embodiment of the invention does not limit the specific algorithm or adjustment range.

[0192] The machining-related parameters after process configuration refer to the various machining parameters determined after process configuration, including toolpath planning, machining speed, feed rate, process connection parameters, etc. These parameters are the objects of dynamic compensation and adjustment. The core purpose of adjustment is to adapt to environmental changes and ensure machining accuracy and quality.

[0193] The logic of dynamic compensation adjustment is as follows: based on the correlation between environmental parameters and processing parameters, compensation rules are established, and when environmental parameters change, the relevant processing parameters are automatically adjusted according to the compensation rules.

[0194] For example, a "temperature-processing speed" compensation rule can be established: when the workshop temperature is higher than the preset range (20-30℃), the processing speed is reduced by 5% for every 1℃ increase to avoid workpiece deformation and accelerated tool wear caused by excessive temperature; when the workshop temperature is lower than the preset range, the processing speed is increased by 3% for every 1℃ decrease to ensure processing efficiency while maintaining processing accuracy.

[0195] Specific examples are as follows: Temperature compensation adjustment: The preset workshop processing temperature range is 20-30℃, and the process speed is 800r / min. If the real-time workshop temperature is 32℃, which exceeds the preset range, the processing speed will be adjusted to 720r / min (800r / min×(1-5%×2)) according to the compensation rules to avoid workpiece size deviation caused by excessive temperature.

[0196] Humidity compensation adjustment: The preset workshop processing humidity range is 40%-60%, and the process configuration feed rate is 0.15mm / r; if the real-time collected workshop humidity is 70%, which exceeds the preset range, the feed rate will be adjusted to 0.13mm / r to avoid excessive humidity causing material rusting and excessive surface roughness.

[0197] Wind speed compensation adjustment: The preset workshop processing wind speed range is 0.3-0.8m / s, and the cutting depth configured in the process is 2mm; if the real-time collected workshop wind speed is 1.0m / s, which exceeds the preset range, the cutting depth will be adjusted to 1.8mm to avoid excessive wind speed causing tool vibration and reduced processing accuracy.

[0198] Dynamic compensation adjustment can be automated. The automated programming system can receive environmental parameters transmitted by environmental monitoring equipment in real time, automatically analyze and determine whether adjustment is needed, and automatically complete the adjustment of processing-related parameters according to preset compensation rules without manual intervention. If the user has special needs, the compensation rules or parameter adjustment range can also be manually adjusted. This embodiment of the invention does not limit this.

[0199] By collecting real-time environmental parameters of the flexible manufacturing process and dynamically compensating and adjusting the processing-related parameters after the process configuration based on these parameters, real-time adaptation of process parameters to the on-site environment can be achieved. This avoids processing errors and workpiece scrap caused by environmental changes, significantly improving the processing accuracy and stability of flexible manufacturing. At the same time, the automated dynamic compensation adjustment requires no manual intervention, further enhancing the automation level of flexible manufacturing programming and processing, and adapting to the flexible manufacturing needs under different environmental conditions.

[0200] In one optional embodiment of this application, it may further include: collecting quality inspection data of the flexible manufacturing process, comparing the quality inspection data with a preset quality standard; if the inspection data deviates from the preset standard, iteratively optimizing the key processing parameters and reconfiguring the process, and then generating control instructions based on the optimized scheme.

[0201] The core of the parameter iterative optimization is to collect quality inspection data during the processing, compare it with the preset quality standards, determine whether the processing quality meets the standards, identify quality deviations, and provide a basis for subsequent parameter optimization. This embodiment of the invention does not limit the specific equipment for data collection or the comparison method.

[0202] Quality inspection data in flexible manufacturing refers to the data obtained by inspecting the quality indicators of the processed workpiece during (or after) flexible manufacturing processing. It is a direct basis for measuring processing quality and covers various data related to processing quality, such as dimensional accuracy, surface roughness, and geometric tolerances. This embodiment of the invention does not limit the specific type of data or the detection method.

[0203] For example, after processing, the dimensional deviation data of the workpiece is detected by a precision measuring instrument, the surface roughness data of the workpiece is detected by a surface roughness meter, and the appearance defect data of the workpiece is detected by a vision inspection device. All of these data belong to quality inspection data.

[0204] Quality inspection data can be collected through quality inspection equipment in flexible manufacturing sites, such as precision measuring instruments, surface roughness testers, vision inspection systems, and non-destructive testing equipment. These devices can perform real-time or offline inspection of the processed workpieces, collect quality data, and transmit it to an automated programming system. This embodiment of the invention does not limit the specific model or frequency of the inspection equipment.

[0205] For example, after each workpiece is processed, the key dimensions of the workpiece are detected by a precision measuring instrument, and dimensional deviation data is collected; the appearance of the workpiece is detected by a vision inspection system, and appearance defect data is collected and transmitted to the system in real time.

[0206] Preset quality standards refer to the quality qualification standards set in advance based on the processing requirements and application of flexible manufacturing. They serve as the basis for judging whether the processing quality meets the standards and cover the qualified range and threshold requirements of various quality inspection data. This embodiment of the invention does not limit the specific values ​​of the preset quality standards.

[0207] For example, the preset acceptable range for part dimensional accuracy is ±0.01mm, the acceptable range for surface roughness is Ra0.8μm or less, and there are no appearance defects. These are all preset quality standards.

[0208] The core of comparing quality inspection data with preset quality standards is to determine whether the quality inspection data is within the preset acceptable range: if the inspection data is within the acceptable range, the processing quality is deemed to meet the standard, and no parameter optimization is required; if the inspection data exceeds the acceptable range, that is, the inspection data deviates from the preset standard, the processing quality is deemed to fail to meet the standard, and parameter iterative optimization is required.

[0209] For example, if the collected workpiece size deviation is 0.015mm, which exceeds the preset acceptable range of ±0.01mm, the processing quality is determined to be substandard and parameter optimization is required; if the collected surface roughness is Ra0.7μm, which is within the preset acceptable range, the processing quality is determined to be acceptable.

[0210] The core of parameter iterative optimization is to identify the causes of quality deviations caused by deviations in quality inspection data from preset standards, iteratively optimize key processing parameters, reconfigure the process and perform simulation verification, generate optimized control commands, and achieve continuous improvement in processing quality. This embodiment of the invention does not limit the specific number of optimizations or the optimization method.

[0211] Deviation of test data from preset standards means that the quality test data exceeds the preset acceptable range, resulting in substandard processing quality (such as excessive dimensional deviation, excessive surface roughness, or appearance defects). In this case, it is necessary to analyze the cause of the deviation and optimize the parameters accordingly.

[0212] For example, excessive dimensional deviation may be due to excessive machining speed or unreasonable toolpath planning; excessive surface roughness may be due to excessive feed rate or tool wear. The embodiments of the present invention do not limit the specific analysis method for the cause of deviation, and it can be determined by automatic system analysis or manual analysis.

[0213] Iterative optimization of key processing parameters refers to adjusting and optimizing the extracted key processing parameters in response to the causes of quality deviations. The optimization process can be repeated multiple times until the quality inspection data meets the standards, which is a closed-loop iterative process of "optimization-processing-inspection-re-optimization".

[0214] For example, if the excessive dimensional deviation is due to the excessive processing speed, the machining accuracy parameter in the key processing parameters can be optimized (to increase the accuracy requirements), while the processing speed parameter can be adjusted (to reduce the processing speed); if the excessive surface roughness is due to the excessive feed rate, the material specification parameters can be optimized (to clarify the material hardness requirements), while the feed rate parameter can be adjusted (to reduce the feed rate).

[0215] After iteratively optimizing the key machining parameters, the optimized key machining parameters are configured in the process (toolpath planning, machining speed, feed rate, etc. are reconfigured), and simulation verification is performed again to ensure that the optimized machining scheme has no interference, collision, or other problems. After the simulation verification is passed, new control commands are generated based on the optimized machining scheme for subsequent workpiece machining.

[0216] For example, optimize the machining speed in the key machining parameters (adjust it from 800 r / min to 700 r / min), reconfigure the process parameters, perform simulation verification, generate new NC code after verification, use it for machining the next workpiece, and if the dimensional deviation meets the standard after inspection, the optimization is completed; if it still does not meet the standard, continue to iterate and optimize the parameters until the quality meets the standard.

[0217] Parameter iterative optimization can achieve semi-automation or full automation: the system can automatically analyze the causes of quality deviations and automatically propose parameter optimization suggestions, which are then completed after user confirmation; alternatively, users can manually analyze the causes of deviations and manually optimize key processing parameters and process configurations. This embodiment of the invention does not impose any limitations on this.

[0218] By collecting quality inspection data from the flexible manufacturing process and comparing it with preset quality standards, if the inspection data deviates from the preset standards, the key processing parameters are iteratively optimized and the process is reconfigured. Then, control instructions are generated based on the optimized solution, forming a closed-loop control of "processing-inspection-optimization". This can continuously improve the processing quality of flexible manufacturing, reduce the generation of defective workpieces, and lower production costs. At the same time, the iterative optimization mechanism allows the automated programming system to gradually adapt to the actual processing scenarios of flexible manufacturing, improve the system's scenario adaptability and practicality, and better meet the personalized and high-precision processing needs of small-batch, multi-batch flexible manufacturing.

[0219] Reference Figure 4 This diagram illustrates a structural block diagram of an embodiment of an automated programming system for flexible manufacturing based on industrial languages, provided in this application. Specifically, it may include: The model building module 301 is used to build an industrial language system model for realizing flexible manufacturing based on the preset industrial language specifications and the requirements of flexible manufacturing. The parsing module 302 is used to parse the industrial language system model and obtain the parsing result; The system generation module 303 is used to generate an automated programming system for flexible manufacturing based on the parsing results; wherein the automated programming system is used to generate control instructions for controlling flexible manufacturing equipment.

[0220] Optionally, the model building module includes: The model building submodule is used to construct the industrial language system model based on the preset industrial language specifications and combined with the production line requirements, process definitions, functional requirements and equipment parameters of flexible manufacturing. The preset industrial language specifications are formulated based on the three-dimensional four-layer unified model paradigm of industrial systems. The industrial language system model includes three dimensions: method, process and entity, and four layers: system layer, unit layer, characteristic layer and data layer.

[0221] Optionally, the parsing module includes: The element extraction submodule is used to perform lexical analysis, syntactic analysis and semantic verification on the industrial language system model to extract structured elements; wherein, the structured elements include at least one of the following: system architecture, functional modules, process logic, control rules, and interface requirements; The result generation submodule is used to generate standardized parsing results based on the structured elements.

[0222] Optionally, the system generation module includes: The system generates a sub-module, which is used to generate the overall architecture of the automated programming system based on the parsing results, and to break it down into corresponding core functional modules; wherein, the core functional modules include at least one of the following: equipment management module, process programming module, path planning module, code generation module, simulation verification module, task control module, and system management module.

[0223] Reference Figure 5 This diagram illustrates a structural block diagram of an embodiment of a flexible manufacturing automation programming system 400 based on an industrial language, which may specifically include: The parameter acquisition module 401 is used to acquire processing-related data for flexible manufacturing and extract key processing parameters; The process configuration module 402 is used to configure the key processing parameters and to complete the simulation verification of the processing scheme. The instruction generation module 403 is used to automatically generate control instructions for the operation of the flexible manufacturing equipment after the simulation verification is passed.

[0224] Optionally, the processing-related data includes at least one of a 3D model of the part, a workpiece model, and a production line layout model; the key processing parameters include at least one of processing accuracy, equipment adaptation parameters, material specifications, and processing cycle time.

[0225] Optionally, the process configuration module includes: The configuration submodule is used to configure at least one of the following parameters based on the processing steps and process rules of flexible manufacturing: toolpath planning, processing speed, feed rate, process connection parameters, multi-device linkage timing, and motion coordination parameters.

[0226] Optionally, the process configuration module includes: The simulation verification submodule is used to perform at least one simulation verification, such as interference analysis and collision detection, on the processing scheme after configuring process parameters. The return submodule is used to return to the steps of configuring the key processing parameters if the simulation verification fails, until the simulation verification passes.

[0227] Optionally, the system further includes: The acquisition module is used to acquire real-time environmental parameters of the flexible manufacturing process; The adjustment module is used to dynamically compensate and adjust the processing-related parameters after the process configuration based on the real-time environmental parameters.

[0228] Optionally, the device further includes: The comparison module is used to collect quality inspection data of the flexible manufacturing process and compare the quality inspection data with preset quality standards. The iterative optimization module is used to iteratively optimize key processing parameters and reconfigure the process if the detection data deviates from the preset standard, and then generate control instructions based on the optimized solution.

[0229] According to embodiments of the present invention, by acquiring processing-related data of flexible manufacturing and extracting key processing parameters, configuring the process for the key processing parameters and completing the simulation verification of the processing scheme, and automatically generating control commands to control the operation of the flexible manufacturing equipment after the simulation verification is passed, the entire process of flexible manufacturing programming is automated, replacing the cumbersome process of traditional manual teaching and debugging and manual writing of control commands, which greatly improves programming efficiency and reduces the number of debugging times. At the same time, the simulation verification stage can identify potential problems in the processing process in advance, ensuring the accuracy and reliability of control commands, improving the processing quality and efficiency of flexible manufacturing, and adapting to the rapid changeover requirements of small-batch, multi-batch flexible manufacturing.

[0230] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0231] Figure 6 This is a structural block diagram of an electronic device 700 for generating an automated programming system for flexible manufacturing based on an industrial language, according to an exemplary embodiment. For example, the electronic device 700 may be a computer.

[0232] Reference Figure 6 The electronic device 700 may include one or more of the following components: a processing component 702, a memory 704, a power supply component 706, a multimedia component 708, an audio component 710, an input / output (I / O) interface 712, a sensor component 714, and a communication component 716.

[0233] Processing component 702 typically controls the overall operation of electronic device 700, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 702 may include one or more processors 720 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 702 may include one or more modules to facilitate interaction between processing component 702 and other components. For example, processing component 702 may include a multimedia module to facilitate interaction between multimedia component 708 and processing component 702.

[0234] Memory 704 is configured to store various types of data to support the operation of device 700. Examples of this data include instruction messages, pictures, videos, etc., for any application or method operating on electronic device 700. Memory 704 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0235] Power supply component 706 provides power to various components of electronic device 700. Power supply component 706 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 700.

[0236] Multimedia component 708 includes a screen that provides an output interface between the electronic device 700 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation.

[0237] Audio component 710 is configured to output and / or input audio signals. For example, audio component 710 includes a microphone (MIC) configured to receive external audio signals when electronic device 700 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 704 or transmitted via communication component 716. In some embodiments, audio component 710 also includes a speaker for outputting audio signals.

[0238] I / O interface 712 provides an interface between processing component 702 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0239] Sensor assembly 714 includes one or more sensors for providing state assessments of various aspects of electronic device 700. For example, sensor assembly 714 may detect the on / off state of device 700, the relative positioning of components such as the display and keypad of electronic device 700, changes in position of electronic device 700 or a component of electronic device 700, the presence or absence of user contact with electronic device 700, orientation or acceleration / deceleration of electronic device 700, and temperature changes of electronic device 700. Sensor assembly 714 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 714 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 714 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0240] Communication component 716 is configured to facilitate wired or wireless communication between electronic device 700 and other devices. Electronic device 700 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 716 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 716 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0241] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0242] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 704 including instructions, which can be executed by a processor 720 of an electronic device 700 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0243] A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a terminal's processor, enables the terminal to execute a method for generating an automated programming system for flexible manufacturing based on an industrial language, the method comprising: Based on pre-defined industrial language standards and the requirements of flexible manufacturing, an industrial language system model for realizing flexible manufacturing is constructed. The industrial language system model is analyzed to obtain the analysis results; Based on the analysis results, an automated programming system for flexible manufacturing is generated; wherein, the automated programming system is used to generate control instructions for controlling flexible manufacturing equipment.

[0244] Optionally, the step of constructing an industrial language system model for realizing flexible manufacturing based on preset industrial language specifications and the requirements of flexible manufacturing includes: Based on the preset industrial language standard, and combined with the production line requirements, process definitions, functional requirements and equipment parameters of flexible manufacturing, the industrial language system model is constructed. The preset industrial language standard is based on the three-dimensional four-layer unified model paradigm of industrial systems. The industrial language system model includes three dimensions: method, process and entity, and four layers: system layer, unit layer, characteristic layer and data layer.

[0245] Optionally, parsing the industrial language system model to obtain the parsing result includes: Lexical analysis, syntactic analysis, and semantic verification are performed on the industrial language system model to extract structured elements; wherein, the structured elements include at least one of the following: system architecture, functional modules, process logic, control rules, and interface requirements; Based on the structured elements, standardized analytical results are generated.

[0246] Optionally, the step of generating an automated programming system for flexible manufacturing based on the analysis results includes: Based on the analysis results, the overall architecture of the automated programming system is generated, and corresponding core functional modules are generated. The core functional modules include at least one of the following: equipment management module, process programming module, path planning module, code generation module, simulation verification module, task control module, and system management module.

[0247] A non-transitory computer-readable storage medium, when instructions in the storage medium are executed by a terminal's processor, enables the terminal to execute an automated programming method for flexible manufacturing based on an industrial language, applied to an automated programming system for flexible manufacturing generated by the method described above, the method comprising: Acquire processing-related data for flexible manufacturing and extract key processing parameters; Configure the process for the key processing parameters and complete the simulation verification of the processing scheme; After the simulation verification is successful, control commands for the operation of the flexible manufacturing equipment are automatically generated.

[0248] Optionally, the processing-related data includes at least one of a 3D model of the part, a workpiece model, and a production line layout model; the key processing parameters include at least one of processing accuracy, equipment adaptation parameters, material specifications, and processing cycle time.

[0249] Optionally, configuring the process for the key processing parameters includes: Based on the processing steps and process rules of flexible manufacturing, configure at least one of the following: toolpath planning, processing speed, feed rate, process connection parameters, multi-device linkage timing, and motion coordination parameters.

[0250] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts between the various embodiments, please refer to each other.

[0251] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0252] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. 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, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0253] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0254] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0255] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments, as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0256] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0257] The foregoing has provided a detailed description of the following: a method for generating an automated programming system for flexible manufacturing based on industrial languages; an automated programming method for flexible manufacturing based on industrial languages; a device for generating an automated programming system for flexible manufacturing based on industrial languages; an automated programming system for flexible manufacturing based on industrial languages; an electronic device; and a readable storage medium. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for generating an automated programming system for flexible manufacturing based on industrial languages, characterized in that, include: Based on pre-defined industrial language standards and the requirements of flexible manufacturing, an industrial language system model for realizing flexible manufacturing is constructed. The industrial language system model is analyzed to obtain the analysis results; Based on the analysis results, an automated programming system for flexible manufacturing is generated; wherein, the automated programming system is used to generate control instructions for controlling flexible manufacturing equipment.

2. The method according to claim 1, characterized in that, The aforementioned industrial language system model, constructed based on pre-defined industrial language standards and the requirements of flexible manufacturing, for realizing flexible manufacturing, includes: Based on the preset industrial language standard, and combined with the production line requirements, process definitions, functional requirements and equipment parameters of flexible manufacturing, the industrial language system model is constructed. The preset industrial language standard is based on the three-dimensional four-layer unified model paradigm of industrial systems. The industrial language system model includes three dimensions: method, process and entity, and four layers: system layer, unit layer, characteristic layer and data layer.

3. The method according to claim 1, characterized in that, The parsing of the industrial language system model to obtain the parsing results includes: Lexical analysis, syntactic analysis, and semantic verification are performed on the industrial language system model to extract structured elements; wherein, the structured elements include at least one of the following: system architecture, functional modules, process logic, control rules, and interface requirements; Based on the structured elements, standardized analytical results are generated.

4. The method according to any one of claims 1-3, characterized in that, The automated programming system for flexible manufacturing, generated based on the analysis results, includes: Based on the analysis results, the overall architecture of the automated programming system is generated, and corresponding core functional modules are generated. The core functional modules include at least one of the following: equipment management module, process programming module, path planning module, code generation module, simulation verification module, task control module, and system management module.

5. An automated programming method for flexible manufacturing based on industrial languages, characterized in that, An automated programming system for flexible manufacturing generated by the method described in any one of claims 1-4, comprising: Acquire processing-related data for flexible manufacturing and extract key processing parameters; Configure the process for the key processing parameters and complete the simulation verification of the processing scheme; After the simulation verification is successful, control commands for the operation of the flexible manufacturing equipment are automatically generated.

6. The method according to claim 5, characterized in that, The processing-related data includes at least one of the following: part 3D model, workpiece model, and production line layout model; the key processing parameters include at least one of the following: processing accuracy, equipment adaptation parameters, material specifications, and processing cycle time.

7. The method according to claim 5, characterized in that, The process configuration of the key processing parameters includes: Based on the processing steps and process rules of flexible manufacturing, configure at least one of the following: toolpath planning, processing speed, feed rate, process connection parameters, multi-device linkage timing, and motion coordination parameters.

8. A device for generating an automated programming system for flexible manufacturing based on industrial languages, characterized in that, include: The model building module is used to construct an industrial language system model for realizing flexible manufacturing based on preset industrial language specifications and the requirements of flexible manufacturing. The parsing module is used to parse the industrial language system model and obtain the parsing results; The system generation module is used to generate an automated programming system for flexible manufacturing based on the parsing results; wherein the automated programming system is used to generate control instructions for controlling flexible manufacturing equipment.

9. An automated programming system for flexible manufacturing based on industrial languages, characterized in that, include: The parameter acquisition module is used to acquire processing-related data for flexible manufacturing and extract key processing parameters; The process configuration module is used to configure the key processing parameters and to perform simulation verification of the processing scheme. The instruction generation module is used to automatically generate control instructions for the operation of flexible manufacturing equipment after the simulation verification is passed.

10. An electronic device, characterized in that, It includes a processor, a memory, and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the steps of the method for generating an automated programming system for flexible manufacturing based on an industrial language as described in any one of claims 1-4, or the steps of the automated programming method for flexible manufacturing based on an industrial language as described in any one of claims 5-7.

11. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions that, when executed by a processor, implement the steps of the method for generating an automated programming system for flexible manufacturing based on an industrial language as described in any one of claims 1-4, or the steps of the automated programming method for flexible manufacturing based on an industrial language as described in any one of claims 5-7.

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