AI technological process design device

Abstract

The invention relates to the technical field of process design, in particular to an AI process design device, which can solve the problems of low efficiency, insufficient standardization, knowledge loss and the like in the existing traditional process design to a certain extent. The AI technological process design device comprises a manual input module which is used for selecting a technological type and inputting technological parameters based on a product development stage; the automatic generation module is connected with the manual input module and is used for automatically generating a process file according to the input parameters; the knowledge base module is used for storing typical cases and mature process data of various processes; the man-hour database module is used for recording standard man-hour data of different processes; and the key process data monitoring module is used for collecting production equipment data in real time and carrying out analysis and early warning.

Description

Technical Field

[0001] The present application relates to the field of process design technology, and in particular, to an AI process design device. Background Art

[0002] Process Planning refers to the core link in product development, which converts design drawings into executable manufacturing instructions. It covers tasks such as process scheduling, process parameter setting, tool and equipment selection, man-hour calculation and quality control. Traditional process design is highly dependent on the experience of engineers and requires manual analysis of product structure, material properties and production conditions to gradually generate process documents.

[0003] With the development of intelligent manufacturing, AI-Driven Process Planning Assistant has emerged. It uses artificial intelligence algorithms (such as rule engines, knowledge graphs, and machine learning) to achieve digital management of process knowledge, automatic generation of process documents, and real-time optimization of the production process.

[0004] However, existing traditional process designs have problems such as low efficiency, insufficient standardization, and knowledge loss. Summary of the invention

[0005] In order to solve the problems of low efficiency, insufficient standardization, knowledge loss, etc. in the existing traditional process design, the present application provides an AI process design device.

[0006] The embodiment of the present application is implemented as follows:

[0007] In a first aspect, the present application provides an AI process design device, comprising:

[0008] Manual entry module, used to select process type and input process parameters based on product development stage;

[0009] An automatic generation module, connected to the manual input module, for automatically generating a process file according to input parameters;

[0010] Knowledge base module, used to store typical cases and mature process data of various processes;

[0011] Working time database module, used to record standard working time data of different processes;

[0012] The key process data monitoring module is used to collect production equipment data in real time and conduct analysis and early warning.

[0013] In a possible implementation, the manual entry module includes:

[0014] Select the process type: output files according to different stages of product development;

[0015] 3D video assembly display: define the assembly sequence of product parts;

[0016] Process flow arrangement: key and special process designation, general process designation;

[0017] General process content description module: can call the process assembly requirements in the process knowledge base;

[0018] Process plan entry.

[0019] In one possible implementation, the process files generated by the automated generation module include process plans, process flow charts, process assembly process cards, control plans, potential failure mode analysis, production flow cards, 3D assembly files, and the working hours of each process are automatically filled into the process assembly process cards.

[0020] In one possible implementation, the processes stored in the knowledge base module include assembly process, surface treatment process, wiring harness process, heat treatment process, coil winding process, sheet metal process, epoxy casting process, machining process, APG casting process, welding process, fastener assembly process, special process, various equipment operating procedures, tool use requirements, potential failure mode library, coil varnishing process, vacuum circuit breaker disassembly process, grounding switch disassembly process, cleaning process, controlled disassembly process, sealing process and riveting process.

[0021] In one possible implementation, the working time database module includes working time data for installing different screws, working time data for carrying different heavy objects, working time data for waiting for transportation in different processes, working time data for rest, working time data for the length of offline production, working time data for welding printed circuit boards, working time data for rework in different processes, and SMT working time data.

[0022] In one possible implementation, the key process data monitoring and management module includes data monitoring of workshop production equipment, special process expiration reminders, tool validity expiration reminders, tool and equipment life management, and data analysis and data mining capabilities for the equipment being tested, extracting useful information from large amounts of data.

[0023] In a possible implementation, the manual entry module supports customized input of rework product processes and associates historical rework cases in the knowledge base module.

[0024] In a possible implementation, it also includes a tool library module;

[0025] The tool library module is used to collect and summarize commonly used fasteners, crimping pliers, needle-nose pliers, diagonal pliers and torque wrenches;

[0026] According to the fasteners selected on the assembly card, the tool name and model are automatically brought to the process assembly card;

[0027] Automatically generate tool list.

[0028] In a possible implementation, it also includes a device module;

[0029] The equipment module is used to collect and summarize equipment, bind the equipment to the general process, and automatically fill in the process assembly card when calling the process;

[0030] Automatically generate equipment lists.

[0031] In a possible implementation, it also includes an outsourcing management module;

[0032] The outsourcing management module is used for outsourcing enterprise process archiving and special process identification and verification.

[0033] The technical solution provided by this application can at least achieve the following beneficial effects:

[0034] The AI ​​process design device provided by this application, through the establishment of a knowledge base module, eliminates the risk of engineers leaving and taking away valuable experience. Through daily data updates, the design device provided by this application can continue to grow. With the continuous improvement of the database, the borrowing rate of similar products is getting higher and higher, and the development cycle of the same type of products is shortened. Each process module in the knowledge database has typical cases and mature processes, and each process of the case can be called when writing a new file.

[0035] In addition, all process files in the design device provided by this application are conveniently queried in one software, and the problem of secondary editing will not occur. The product design and development cycle can be shortened. The key process data monitoring and management in this application improves product deficiencies and improves product quality and reliability through real-time monitoring of data mining of aging products. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0037] Figure 1 It is a structural schematic diagram of an AI process design device shown in an exemplary embodiment of the present application.

[0038] Reference numerals:

[0039] 1. Manual input module; 2. Automatic generation module; 3. Knowledge base module; 4. Working time database module; 5. Tool library module; 6. Equipment module; 7. Outsourcing management module; 8. Key process data monitoring and management module. DETAILED DESCRIPTION

[0040] In order to make the purpose, implementation mode and advantages of the present application clearer, the exemplary implementation mode of the present application will be clearly and completely described below in conjunction with the drawings in the exemplary embodiments of the present application. Obviously, the described exemplary embodiments are only part of the embodiments of the present application, not all of the embodiments. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

[0041] It should be noted that the brief description of terms in this application is only for the convenience of understanding the embodiments described below, and is not intended to limit the embodiments of this application. Unless otherwise specified, these terms should be understood according to their common and usual meanings.

[0042] The terms "first", "second", "third", etc. in the specification and claims of this application and the above drawings are used to distinguish similar or similar objects or entities, and do not necessarily mean to limit a specific order or sequence, unless otherwise noted. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances.

[0043] The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover but not exclude inclusion, for example, a product or device comprising a list of components is not necessarily limited to all the components expressly listed but may include other components not expressly listed or inherent to such product or device.

[0044] Before explaining the AI ​​process design device provided in the embodiment of the present application, the application scenario and implementation environment of the embodiment of the present application are first introduced.

[0045] Process Planning refers to the core link in product development, which converts design drawings into executable manufacturing instructions. It covers tasks such as process scheduling, process parameter setting, tool and equipment selection, man-hour calculation and quality control. Traditional process design is highly dependent on the experience of engineers and requires manual analysis of product structure, material properties and production conditions to gradually generate process documents.

[0046] With the development of intelligent manufacturing, AI-Driven Process Planning Assistant has emerged. It uses artificial intelligence algorithms (such as rule engines, knowledge graphs, and machine learning) to achieve digital management of process knowledge, automatic generation of process documents, and real-time optimization of the production process.

[0047] However, existing traditional process designs have problems such as low efficiency, insufficient standardization, and knowledge loss.

[0048] Based on this, this application provides an AI process design device. By using this system to apply mature processes, only mechanized operation selection is required to write process documents with guiding value. This system meets the requirements of TS22163 and ISO9001 systems.

[0049] Through the establishment of the knowledge base module, the risk of engineers leaving and taking away valuable experience is eliminated. Through daily data updates, the design device provided by this application can continue to grow. With the continuous improvement of the database, the borrowing rate of similar products is getting higher and higher, and the development cycle of the same type of products is shortened. Each process module in the knowledge database has typical cases and mature processes, and each process of the case can be called when writing a new file.

[0050] Next, the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems will be described in detail through embodiments and in combination with the accompanying drawings. The embodiments may be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. Obviously, the described embodiments are part of the embodiments of the present application, not all of them.

[0051] Figure 1 It is a structural schematic diagram of an AI process design device shown in an exemplary embodiment of the present application.

[0052] In an exemplary embodiment, Figure 1 As shown, an AI process design device is provided, which may include:

[0053] Manual input module 1, used to select process type and input process parameters based on product development stage;

[0054] The automatic generation module 2 is connected to the manual input module and is used to automatically generate a process file according to the input parameters;

[0055] Knowledge base module 3, used to store typical cases and mature process data of various processes;

[0056] The working time database module 4 is used to record the standard working time data of different processes;

[0057] The key process data monitoring module 8 is used to collect production equipment data in real time and conduct analysis and early warning.

[0058] In one possible implementation, the manual entry module can:

[0059] Select the process type: output files according to different stages of product development;

[0060] 3D video assembly display: define the assembly sequence of product parts;

[0061] Process flow arrangement: key and special process designation, general process designation;

[0062] General process content description module: can call the process assembly requirements in the process knowledge base;

[0063] Enter the process plan.

[0064] Among them, the process files generated by the automatic generation module include process plan, process flow chart, process assembly process card, control plan, potential failure mode analysis, production flow card, 3D assembly file and the working hours of each process are automatically filled into the process assembly process card.

[0065] The processes stored in the knowledge base module include assembly process, surface treatment process, wiring harness process, heat treatment process, coil winding process, sheet metal process, epoxy casting process, machining process, APG casting process, welding process, fastener assembly process, special process, various equipment operating procedures, tool use requirements, potential failure mode library, coil varnishing process, vacuum circuit breaker disassembly process, grounding switch disassembly process, cleaning process, control disassembly process, sealing process and riveting process.

[0066] The working time database module includes working time data for installing different screws, working time data for carrying different heavy objects, working time data for waiting for transportation in different processes, working time data for rest, working time data for the length of offline production, working time data for welding printed circuit boards, working time data for rework in different processes and SMT working time data.

[0067] The key process data monitoring and management module includes data monitoring of workshop production equipment, special process expiration reminders, tool validity expiration reminders, tool equipment life management, and data analysis and data mining capabilities for the tested equipment to extract useful information from large amounts of data.

[0068] In a possible implementation, the manual entry module supports customized input of rework product processes and associates historical rework cases in the knowledge base module.

[0069] In a possible implementation, the design device provided by the present application further includes a tool library module 5, a device module 6 and an outsourcing management module 7;

[0070] The tool library module is used to collect and summarize commonly used fasteners, crimping pliers, needle-nose pliers, diagonal pliers and torque wrenches, and automatically bring out the tool name and model to the process assembly card based on the fasteners selected on the assembly card, and automatically generate a tool list.

[0071] The equipment module is used to collect and summarize equipment, bind the equipment to a general process, automatically fill in the process assembly card when calling the process, and automatically generate an equipment list.

[0072] The outsourcing management module is used for outsourcing enterprise process archiving and special process identification and verification.

[0073] Based on the AI ​​process design device provided in this application, the advancement of this application is verified in combination with actual needs.

[0074] 1: Mechanical assembly process file generation

[0075] 1. Process type selection: The user selects the "mechanical assembly" process type through the interactive interface of the manual entry module and specifies the product development stage as "trial production".

[0076] 2. Parameter input:

[0077] Enter the fastener type as "M8 hexagon socket bolt", and the system automatically calls the matching installation torque range (20-25N·m) and tool model (TX40 torque wrench) from the knowledge base module.

[0078] Input assembly sequence: The system supports drag-and-drop 3D model operation, defines the assembly path of "base → bearing → gearbox", and generates a 3D video preview.

[0079] 3. Automatic generation:

[0080] Based on the input parameters, the system generates a process flow chart through a rule engine (based on a decision tree algorithm), which includes four nodes: "cleaning → pre-installation → tightening → inspection", and automatically associates the inspection standards in the control plan (such as torque tolerance ±5%).

[0081] Generate process cards for assembly processes and automatically fill in standard data in the time database: pre-assembly time is 2.5 minutes / piece, and tightening time is 1.8 minutes / piece.

[0082] 4. Tool and device binding:

[0083] The tool library module automatically matches the "AGV-2030 assembly robot" in the equipment list based on the "TX40 torque wrench" model, and marks the tool calibration cycle as 30 days.

[0084] 5. Monitoring and early warning:

[0085] The key process monitoring module collects the torque data of the assembly robot in real time through the PLC interface. If the torque value is detected to be lower than 18N·m for three consecutive times, the system triggers a red warning and pushes it to the workshop dashboard.

[0086] 2. Electronic Manufacturing SMT Process Optimization

[0087] 1. Rework process call: The user selects "SMT rework process" in the manual entry module, and the system calls the historical case "BGA chip solder joint repair process" from the knowledge base module, and prompts the rework equipment model to be matched (such as IR-650 hot air rework station).

[0088] 2. Automatic filling of parameters:

[0089] The input PCB board size is 200mm×150mm, and the system automatically generates the hot air temperature curve: preheating zone 150℃±5℃, reflow zone 240℃±3℃.

[0090] The work time database module calculates the standard work time according to the board size: preheating for 2 minutes, reflow for 1.5 minutes, and cooling for 3 minutes.

[0091] 3. File generation and synchronization:

[0092] The automated generation module outputs a potential failure mode analysis table, lists the risk item of "temperature deviation leading to solder voids", and associates it with the solution in the control plan (increasing the frequency of infrared temperature measurement).

[0093] The system synchronizes process parameters to SMT production line equipment through the OPC UA protocol to realize automatic loading of temperature curves.

[0094] 4. Outsourcing process validation:

[0095] The outsourcing company submits a "high-density PCB welding process plan" and the system uses the compliance verification module to check whether it complies with the IPC-A-610 standard. Once the verification is passed, it is archived in the "Electronic Process - Outsourcing" category of the knowledge base.

[0096] 3: Dynamic adjustment in sheet metal processing

[0097] 1. Process scheduling exception handling:

[0098] When the user arranges the process flow, if "laser cutting" is placed after "bending", the system will prompt a logical error based on the process rule library in the knowledge base (storing more than 500 sheet metal process constraints) and recommend the correct order as "cutting → laser cutting → bending".

[0099] 2. Dynamic correction of working hours:

[0100] The input material thickness is 3mm stainless steel plate. The system calculates the cutting time according to the nonlinear formula in the time database: T = 0.5 × (thickness / 2) + 1.2, and obtains T = 2.7 minutes / piece.

[0101] 3. Equipment life management:

[0102] The key process monitoring module records the cumulative working time of the laser cutting machine. When the threshold of 2000 hours is reached, the maintenance task is automatically pushed to the equipment management department, and the process file generation function is locked until the maintenance is completed.

[0103] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0104] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. An AI process design device, characterized in that: include: Manual entry module, used to select process type and input process parameters based on product development stage; An automatic generation module, connected to the manual input module, for automatically generating a process file according to input parameters; Knowledge base module, used to store typical cases and mature process data of various processes; Working time database module, used to record standard working time data of different processes; The key process data monitoring module is used to collect production equipment data in real time and conduct analysis and early warning.

2. The AI ​​process design device according to claim 1, characterized in that: The manual entry module includes: Select the process type: output files according to different stages of product development; 3D video assembly display: define the assembly sequence of product parts; Process flow arrangement: key and special process designation, general process designation; General process content description module: can call the process assembly requirements in the process knowledge base; Process plan entry.

3. The AI ​​process design device according to claim 1, characterized in that: The process files generated by the automatic generation module include process plan, process flow chart, process assembly process card, control plan, potential failure mode analysis, production flow card, 3D assembly file and the working hours of each process are automatically filled into the process assembly process card.

4. The AI ​​process design device according to claim 1, characterized in that: The processes stored in the knowledge base module include assembly process, surface treatment process, wiring harness process, heat treatment process, coil winding process, sheet metal process, epoxy casting process, machining process, APG casting process, welding process, fastener assembly process, special process, various equipment operating procedures, tool use requirements, potential failure mode library, coil varnishing process, vacuum circuit breaker disassembly process, grounding switch disassembly process, cleaning process, control disassembly process, sealing process and riveting process.

5. The AI ​​process design device according to claim 1, characterized in that: The working time database module includes working time data for installing different screws, working time data for carrying different heavy objects, working time data for waiting for transportation in different processes, working time data for rest, working time data for the length of offline production, working time data for welding printed circuit boards, working time data for rework in different processes and SMT working time data.

6. The AI ​​process design device according to claim 1, characterized in that: The key process data monitoring and management module includes data monitoring of workshop production equipment, special process expiration reminders, tool validity expiration reminders, tool equipment life management, and data analysis and data mining capabilities for the tested equipment to extract useful information from large amounts of data.

7. The AI ​​process design device according to claim 1, characterized in that: The manual entry module supports customized input of rework product processes and associates historical rework cases in the knowledge base module.

8. The AI ​​process design device according to claim 1, characterized in that: Also includes tool library module; The tool library module is used to collect and summarize commonly used fasteners, crimping pliers, needle-nose pliers, diagonal pliers and torque wrenches; According to the fasteners selected on the assembly card, the tool name and model are automatically brought to the process assembly card; Automatically generate tool list.

9. The AI ​​process design device according to claim 1, characterized in that: Also includes equipment modules; The equipment module is used to collect and summarize equipment, bind the equipment to the general process, and automatically fill in the process assembly card when calling the process; Automatically generate equipment lists.

10. The AI ​​process design device according to claim 1, characterized in that: It also includes an outsourcing management module; The outsourcing management module is used for outsourcing enterprise process archiving and special process identification and verification.

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