System and method for automatically calculating precise size of mechanical part before surface treatment

Abstract

The invention discloses a system and a method for automatically calculating the precise size of a mechanical part before surface treatment. Comprising a multi-dimensional compensation rule base, a user interaction module and a core calculation engine, wherein the multi-dimensional compensation rule base is a structured parameter and rule base obtained according to film thickness characteristics of different surface treatment processes and influence rules on inner and outer contour sizes; the user interaction module is configured to input mechanical part surface treatment process parameters; the core calculation engine is configured to receive the mechanical part surface treatment process parameters input by the user interaction module, call rule subsets in the multi-dimensional compensation rule base and calculate the fine size of the mechanical part before surface treatment; the user interaction module is further configured to output the pre-surface-treatment fine size of the mechanical part calculated by the core calculation engine. According to the method, normal form transformation from human brain experience driving to system rule driving is achieved, the size precision qualification rate is increased, and waste and rework are reduced.

Description

Technical Field

[0001] This invention relates to the field of precision machinery manufacturing technology, and in particular to an automatic system and method for calculating the precision dimensions of mechanical parts before surface treatment. Background Technology

[0002] In the field of precision machinery manufacturing, after machining, parts often require various surface treatments such as anodizing, electroplating, and spraying to improve their wear resistance, corrosion resistance, or aesthetics. However, the coatings or film thicknesses formed by these treatments irreversibly alter the final dimensions of the parts. Especially for high-precision parts with fitting requirements, even micron-level dimensional deviations can lead to assembly failure or functional malfunctions. Traditional methods heavily rely on the personal experience of process engineers to manually calculate and experiment to allow for machining allowances. This lack of unified standards and scientific models not only results in low efficiency and a large amount of repetitive work but also makes it prone to batch dimensional deviations due to human error or experience differences, causing serious waste of materials and time. Although existing Computer-Aided Design (CAD) / Computer-Aided Manufacturing (CAM) software has basic tolerance analysis functions, it generally lacks dedicated, refined dimensional compensation modules for complex and diverse surface treatment processes. It cannot directly output accurate pre-machining control dimensions, and the industry has long faced the common bottleneck of "processes relying on experience and precision relying on luck." There is an urgent need for a professional, systematic, and intelligent solution to achieve standardization, automation, and predictability of dimensional control before surface treatment.

[0003] In summary, the reasons for dimensional deviations in parts caused by surface treatment in precision manufacturing are as follows: (1) Traditional methods that rely on manual experience to estimate processing allowance lack scientific calculation models, resulting in low accuracy, poor consistency, and high trial and error costs; (2) Existing general-purpose CAD / CAM software lacks a dedicated compensation module for the film thickness effect of diverse surface treatment processes (such as anodizing, chemical plating, spraying, etc.), and cannot achieve accurate calculation of the coupling of "process-feature-tolerance"; (3) The process knowledge is fragmented and implicit during the manufacturing process, making it difficult to standardize, inherit and optimize, resulting in quality fluctuations; (4) Under the trend of multi-variety, small-batch, and high-precision production, traditional methods are inefficient and cannot quickly respond to process design requirements, thus restricting production flexibility.

[0004] Therefore, those skilled in the art are dedicated to developing an automatic dimensional calculation system and method for mechanical parts before surface treatment, so as to achieve standardization, automation and predictability of dimensional control before surface treatment. Summary of the Invention

[0005] In view of the above-mentioned deficiencies of the prior art, the technical problem to be solved by the present invention is that the dimensional deviation of parts caused by surface treatment in precision manufacturing is out of tolerance.

[0006] To achieve the above objectives, the present invention provides an automatic dimensional calculation system for mechanical parts before surface treatment, comprising: A multi-dimensional compensation rule library, which is a structured parameter and rule library obtained based on the film thickness characteristics of different surface treatment processes and their influence on the inner and outer contour dimensions; The user interaction module is configured to input surface treatment process parameters for mechanical parts; the core computing engine is configured to receive the surface treatment process parameters for mechanical parts input by the user interaction module, call a subset of rules in the multi-dimensional compensation rule base, and calculate the precision dimensions of the mechanical parts before surface treatment; the user interaction module is also configured to output the precision dimensions of the mechanical parts before surface treatment calculated by the core computing engine.

[0007] Furthermore, the surface treatment process parameters of the mechanical parts include the characteristics of the mechanical parts, the target surface treatment process type, and the tolerances specified in the drawings.

[0008] Furthermore, the surface treatment process parameters for the mechanical parts also include film thickness parameters.

[0009] Furthermore, the mechanical part features include an outer contour and an inner contour.

[0010] Furthermore, the target surface treatment process types include anodizing, electroless plating, electroplating, electrolytic polishing, and surface spraying.

[0011] Furthermore, the tolerances specified in the drawings include upper tolerances and lower tolerances.

[0012] Furthermore, the film thickness parameter includes an upper limit and a lower limit.

[0013] Furthermore, the precision dimensions of the mechanical part before surface treatment include the tolerance before surface treatment, which includes an upper tolerance and a lower tolerance before surface treatment.

[0014] Furthermore, the precision dimensions of the mechanical parts before surface treatment include the internal control value of the film thickness.

[0015] This invention also provides a method for automatically calculating the precision dimensions of mechanical parts before surface treatment, comprising the following steps: Step 1: Based on the film thickness characteristics of different surface treatment processes and their influence on the internal and external contour dimensions, construct a multi-dimensional compensation rule library; Step 2: Input the surface treatment process parameters of the mechanical parts into the user interaction module; Step 3: The core computing engine receives the surface treatment process parameters of the mechanical parts input by the user interaction module, calls the rule subset in the multi-dimensional compensation rule base, and calculates the precision dimensions of the mechanical parts before surface treatment. Step 4: The user interaction module outputs the precise dimensions of the mechanical part before surface treatment, calculated by the core computing engine.

[0016] Compared with the prior art, the present invention has the following advantages: At the technical level, the system deeply integrates the principles of materials science, process engineering and dimensional chain calculation. The dynamic adaptive compensation algorithm it constructs far surpasses traditional experience-based lookup tables or simple addition and subtraction calculations. It can accurately handle micron-level tolerances and complex feature interactions, ensuring a significant improvement in first-pass yield. Its technical threshold and accuracy far exceed those of similar simple tools or general CAD plugins on the market.

[0017] In terms of cost and efficiency, the system enables rapid deployment using the lightweight, development-free Microsoft Excel platform. Enterprises do not need to invest in expensive customized software or long implementation cycles. It can be directly integrated into existing process flows, achieving a smooth transition with "zero learning cost," significantly shortening process preparation time and eliminating hidden costs caused by human calculation errors.

[0018] In terms of knowledge management, the system digitizes, modularizes, and standardizes core process knowledge (know-how), forming intellectual assets that can be permanently inherited and continuously optimized by the enterprise. This effectively breaks the dependence of high-end manufacturing on senior engineers and provides a standardized platform for the enterprise's large-scale expansion and talent cultivation.

[0019] In terms of industry applicability, the system rule base is derived from practical experience in top industries such as precision medical devices and semiconductor equipment. It has a high degree of professionalism and reliability and can be quickly reused in all manufacturing fields involving precision surface treatment, such as aerospace, automotive electronics, and optical instruments. It has strong scenario generalization ability.

[0020] In summary, this invention boasts core advantages such as "high technical precision, low barrier to entry, strong knowledge accumulation, and wide industry adaptability." It is not only a tool to improve efficiency but also a strategic asset that promotes the standardization and intelligent upgrading of enterprise process systems. In the wave of digital transformation in the manufacturing industry, it has clear pioneering and enabling value.

[0021] The following will further explain the concept, specific structure, and technical effects of the present invention in conjunction with the accompanying drawings, so as to fully understand the purpose, features, and effects of the present invention. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the system structure of a preferred embodiment of the present invention; Figure 2 This is a schematic diagram of a method flow according to a preferred embodiment of the present invention; Figure 3 This is a schematic diagram of the worksheet calculation results in Microsoft Excel, according to a preferred embodiment of the present invention. Detailed Implementation

[0023] The following description, with reference to the accompanying drawings, illustrates several preferred embodiments of the present invention to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms, and the scope of protection of the present invention is not limited to the embodiments mentioned herein.

[0024] In the accompanying drawings, components with the same structure are indicated by the same numerical designation, and components with similar structures or functions are indicated by similar numerical designations. The dimensions and thicknesses of each component shown in the drawings are arbitrary, and the present invention does not limit the dimensions and thicknesses of each component. To make the illustrations clearer, the thickness of some components has been appropriately exaggerated in the drawings.

[0025] The present invention aims to build a set of digital tools based on rule-driven and algorithmic models to solve the problem of accurate reservation of machining dimensions before surface treatment.

[0026] The system's overall architecture is divided into three layers: the data and rules layer, the core computing engine layer, and the user interaction and output layer. The data and rules layer is the cornerstone of the entire system. By systematically organizing and extracting internal and external process knowledge, historical data, and industry standards, it transforms the film thickness characteristics and their impact on internal and external contour dimensions of different surface treatment processes (such as natural / dyed / hard anodizing, electroless nickel plating, perfluoroalkoxy (PFA) / polytetrafluoroethylene (PTFE) coating, electropolishing, etc.) into a structured parameter and rule library. This library clearly records the film thickness range for each process, the corresponding dimensional compensation direction (inner contour addition, outer contour subtraction), the compensation value calculation formula or lookup table, and the mapping relationship between tolerance zone size and compensation coefficient. Furthermore, the rule library is scalable, allowing for additions and revisions as processes evolve.

[0027] The core computing engine layer is the "brain" of the system, responsible for executing intelligent decisions and precise calculations. Its core lies in implementing an automated compensation algorithm with multi-condition judgments. This algorithm receives three key variables from the user interaction layer: part features (inner / outer contour), target surface treatment process type, tolerances specified in the drawing (upper and lower deviations), and film thickness parameters required for certain processes. The engine first calls the corresponding rule subset based on the process type, and then enters different calculation branches according to the feature type. Its innovation lies in the fact that the compensation amount is not a fixed value, but dynamically adjusted according to the width of the original tolerance zone. For example, for features with extremely stringent tolerance requirements (such as a tolerance zone ≤ 0.02mm), the system will use a more conservative nonlinear compensation coefficient to ensure accuracy; for features with relatively loose tolerances, a more efficient linear compensation method can be used. For thick film processes such as hard anodizing, the algorithm also integrates film thickness uniformity control logic, automatically recommending the internal control target value for film thickness before machining. All computational logic is implemented through carefully constructed, nested conditional judgment functions (such as combinations of IF and AND functions) or callable modular scripts, ensuring automation, speed, and zero human error in the computation process.

[0028] In terms of implementation, the system will adopt a strategy of "centralized development of underlying logic and lightweight integration of the front-end interface." Initially, the widely used and highly flexible Microsoft Excel spreadsheet will be used as the primary development and deployment platform. Leveraging its powerful formula calculation, data validation (such as selecting process types via drop-down menus), and conditional formatting (highlighting key results or abnormal inputs), the system will quickly build prototypes and user interfaces. Users only need to input or select a few key parameters in a pre-set spreadsheet, and the system can instantly complete all background calculations and clearly output key process instructions such as the upper and lower tolerances of machining internal dimensions and the recommended film thickness control range. This approach eliminates the need for enterprises to invest in additional specialized software or complex information technology (IT) deployments, significantly reducing the barrier to entry and promotion costs.

[0029] To ensure the system's accuracy and practicality, the development process will adhere to the principles of "iterative verification and closed-loop optimization." The system prototype will be closely integrated with the most typical and critical part cases in the company's actual production, undergoing multiple rounds of calculation verification and result comparison. By comparing the system's output values ​​with the experience values ​​of senior process engineers and the measured data of the final qualified parts, the compensation coefficients and judgment logic in the rule base will be continuously calibrated and optimized. Ultimately, a set of accurate and reliable standard operating tools, refined through practice, will be formed. Simultaneously, detailed operation manuals and training materials will be compiled to ensure that frontline process personnel and technicians can quickly get started. The successful application of this system will, for the first time, realize a paradigm shift from "human experience-driven" to "system rule-driven" in the enterprise's process design process. This will not only directly improve the dimensional accuracy pass rate and reduce scrap and rework, but also lay a solid technical foundation for the enterprise's process standardization, talent cultivation, and continuous digital transformation through the digital accumulation of knowledge.

[0030] The key innovation of this invention lies in: 1. Multivariate Coupled Decision Algorithm This is the system's core computing engine. The key technology lies in establishing a conditional judgment model that can simultaneously process multiple input variables, such as part features (inner / outer contours), target process type, film thickness parameters, and original tolerance zones. The algorithm needs to automatically match and execute corresponding mathematical compensation rules (such as linear compensation, proportional compensation, and piecewise compensation) based on different combinations of these variables, rather than simply adding or subtracting fixed values, thereby achieving accurate simulation and forward-looking control of complex dimensional chains.

[0031] 2. Technology for Digitizing Process Knowledge and Constructing Rule Bases The process involves extracting, quantifying, and structuring non-standardized process knowledge implicit in engineers' experience (such as "how to reserve which features for which processes") and transforming it into a rule base that the system can recognize and execute. This involves mining and analyzing a large amount of historical process data and failure cases to form an accurate and complete set of "if-then" rules, which is the knowledge foundation for system intelligence.

[0032] 3. Dynamic tolerance zone analysis and adaptive compensation technology The system can automatically analyze user-input drawing tolerances (such as upper and lower deviations) and calculate their tolerance zone size. The key technology lies in dynamically adjusting the compensation strategy based on the width of the tolerance zone: for stringent tolerances (such as those at the micrometer level), a more conservative, non-linear compensation coefficient is used; for more lenient tolerances, a more efficient linear compensation can be employed. This adaptive capability ensures a balance between economy and reliability under different accuracy requirements.

[0033] 4. Technique for Generating Internal Control Values ​​of Process Parameters Based on Target Film Thickness For processes requiring precise film thickness control (such as hard anodizing), the system can automatically calculate recommended internal control values ​​(e.g., "10±2μm") based on the input film thickness range (upper and lower limits). This technology incorporates the concept of Statistical Process Control (SPC), aiming to narrow a broad process window to a more stable range with more controllable dimensional effects, thereby reducing variation at the source.

[0034] 5. Lightweight integration and high availability implementation technologies To enable rapid deployment and adoption of the system in production environments, the key technology lies in leveraging the advanced formulas, data validation, and conditional formatting features of general-purpose platforms (such as Microsoft Excel) to create a user interface that requires no specialized programming knowledge. This necessitates encapsulating complex backend logic through clear frontend interactions, achieving a highly available design of "complex backend, simple frontend," significantly reducing the barrier to entry and training costs.

[0035] The system's main technical specifications are reflected in four dimensions: accuracy, efficiency, coverage, and reliability. The core calculation output—the tolerance control accuracy of machining internal dimensions—achieves ≤0.001 mm (1 micrometer), with a recommended film thickness deviation of ≤±1 micrometer for thick film processes. In terms of processing capability, the system supports at least 15 mainstream surface treatment processes, covering features such as internal and external contours, and can intelligently analyze drawing tolerance zones ranging from 0.005 to 0.5 mm. The completeness of the process rule library is required to be ≥95%. Regarding efficiency, the response time for a single calculation is controlled within 2 seconds, and users can master the system operation within 30 minutes without professional training. The system stability must meet the requirement of continuous, fault-free calculations exceeding 100,000 times, and the automatic generated process parameters must have a higher than 99.5% match rate with the measured dimensions of the final qualified parts, thus comprehensively surpassing traditional manual experience-based methods at the technical level. Example 1

[0036] like Figure 1 As shown, this embodiment provides an automatic dimensional calculation system for mechanical parts before surface treatment, including a multi-dimensional compensation rule base 10, a user interaction module 20, and a core calculation engine 30.

[0037] The multi-dimensional compensation rule base 10 is a structured parameter and rule base obtained based on the film thickness characteristics of different surface treatment processes and their influence on the inner and outer contour dimensions; The user interaction module 20 inputs the surface treatment process parameters of the mechanical parts; the core calculation engine 30 receives the surface treatment process parameters of the mechanical parts input by the user interaction module 20, calls the rule subset 11 in the multi-dimensional compensation rule library 10, and calculates the precision dimensions of the mechanical parts before surface treatment; the user interaction module 20 outputs the precision dimensions of the mechanical parts before surface treatment calculated by the core calculation engine 30.

[0038] The surface treatment process parameters for mechanical parts include the characteristics of the mechanical parts, the type of target surface treatment process, the tolerances specified in the drawings, and the film thickness parameters required for some processes.

[0039] The features of mechanical parts include the outer contour and the inner contour.

[0040] The target surface treatment process types include anodizing, electroless plating, electroplating, electropolishing, surface spraying, and other surface treatment process types.

[0041] Anodizing includes intrinsic anodizing, dyed anodizing, and hard anodizing. Electroless plating includes electroless nickel plating. Surface coating includes PTFE coating and PFA coating. Electroplating includes zinc plating. Electropolishing includes electropolishing of steel (for high gloss), electropolishing of steel (without high gloss), and electropolishing of aluminum (without high gloss). Other surface treatment processes include sandblasting, conductive oxide coating, micro-arc oxidation, blackening treatment, and molybdenum disulfide coating.

[0042] Tolerances specified on drawings include upper tolerances and lower tolerances.

[0043] Film thickness parameters include an upper limit and a lower limit of film thickness.

[0044] The precision dimensions of mechanical parts before surface treatment include the tolerances before surface treatment, which include the upper tolerance and the lower tolerance before surface treatment.

[0045] Precision dimensions of mechanical parts before surface treatment include internal control values ​​for film thickness. Example 2

[0046] like Figure 2 As shown, this embodiment provides a method for automatically calculating the precision dimensions of mechanical parts before surface treatment, including the following steps: S1. Based on the film thickness characteristics of different surface treatment processes and their influence on the internal and external contour dimensions, a multi-dimensional compensation rule library is constructed. S2, User interaction module inputs surface treatment process parameters for mechanical parts; S3, the core computing engine receives the surface treatment process parameters of the mechanical parts input by the user interaction module, calls the rule subset in the multi-dimensional compensation rule library, and calculates the precise dimensions of the mechanical parts before surface treatment. S4, the user interaction module outputs the precise dimensions of the mechanical parts before surface treatment calculated by the core computing engine. Example 3

[0047] like Figure 3 As shown, this embodiment uses Microsoft Excel as the development and deployment platform, leveraging its powerful formula calculation, data validation, and conditional formatting functions to quickly build prototypes and user interfaces. The multi-dimensional compensation rule base involves mining and analyzing a large amount of historical process data and failure cases to form an accurate and complete set of "IF-THEN" rules.

[0048] The multi-dimensional compensation rule base includes, but is not limited to, the following: (1) Internal control value of film thickness, the calculation formula is as follows: , ; In the formula, This is the upper limit of film thickness. This is the lower limit of film thickness. This is the median film thickness. This is the internal control value for film thickness.

[0049] (2) The tolerance control value in the natural color anodizing process is calculated using the following formula: When the feature is an inner contour: , ; In the formula, Mark the tolerances on the drawings. Specify tolerances on the drawings. For the upper tolerance before surface treatment, The tolerance is set before surface treatment.

[0050] When the feature is an outer contour: , .

[0051] (3) The tolerance control value in the dyeing and anodizing process is calculated using the following formula: When the feature is an inner contour: , ; When the feature is an outer contour: , .

[0052] (4) The tolerance control value in the hard anodizing process is calculated using the following formula: When the feature is an inner contour: , ; When the feature is an outer contour: , .

[0053] (5) The tolerance control value in the chemical nickel plating process is calculated using the following formula: When the feature is an inner contour: , ; When the feature is an outer contour: , .

[0054] (6) The tolerance control value in the PTFE spraying process is calculated using the following formula: When the feature is an inner contour: , ; When the feature is an outer contour: , .

[0055] (7) The tolerance control value in the PFA spraying process is calculated using the following formula: When the feature is an inner contour: , ; When the feature is an outer contour: , .

[0056] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. An automatic dimensional calculation system for mechanical parts before surface treatment, characterized in that, include: A multi-dimensional compensation rule library, which is a structured parameter and rule library obtained based on the film thickness characteristics of different surface treatment processes and their influence on the inner and outer contour dimensions; The user interaction module and the core computing engine are configured to input surface treatment process parameters for mechanical parts. The core computing engine is configured to receive the surface treatment process parameters of the mechanical parts input by the user interaction module, call the rule subset in the multi-dimensional compensation rule base, and calculate the precise dimensions of the mechanical parts before surface treatment. The user interaction module is also configured to output the precision dimensions of the mechanical part before surface treatment, calculated by the core computing engine.

2. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 1, characterized in that, The surface treatment process parameters for mechanical parts include the characteristics of the mechanical parts, the target surface treatment process type, and the tolerances specified in the drawings.

3. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 2, characterized in that, The surface treatment process parameters for the mechanical parts also include film thickness parameters.

4. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 2, characterized in that, The mechanical part features include an outer contour and an inner contour.

5. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 2, characterized in that, The target surface treatment process types include anodizing, chemical plating, electroplating, electrolytic polishing, and surface spraying.

6. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 2, characterized in that, The tolerances specified in the drawings include upper tolerances and lower tolerances.

7. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 3, characterized in that, The film thickness parameters include an upper limit of film thickness and a lower limit of film thickness.

8. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 1, characterized in that, The precision dimensions of the mechanical parts before surface treatment include the tolerances before surface treatment, which include the upper tolerance and the lower tolerance before surface treatment.

9. The automatic dimensional calculation system for mechanical parts before surface treatment according to claim 7, characterized in that, The precision dimensions of the mechanical parts before surface treatment include the internal control value of the film thickness.

10. A method for automatically calculating the precision dimensions of mechanical parts before surface treatment, characterized in that, Includes the following steps: Step 1: Based on the film thickness characteristics of different surface treatment processes and their influence on the internal and external contour dimensions, construct a multi-dimensional compensation rule library; Step 2: Input the surface treatment process parameters of the mechanical parts into the user interaction module; Step 3: The core computing engine receives the surface treatment process parameters of the mechanical parts input by the user interaction module, calls the rule subset in the multi-dimensional compensation rule base, and calculates the precision dimensions of the mechanical parts before surface treatment. Step 4: The user interaction module outputs the precise dimensions of the mechanical part before surface treatment, calculated by the core computing engine.

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