Spaceflight high-grade component screening experiment optimization method
By constructing a component failure model library and nonlinear mapping relationships, the screening and testing process for high-grade components used in aerospace was optimized, solving the problems of high cost and cumbersome process, and achieving high reliability and low cost quality assurance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-02
- Publication Date
- 2026-03-10
AI Technical Summary
Existing technologies for screening and testing high-grade components for aerospace applications suffer from high costs and cumbersome processes, making it difficult to achieve low-cost quality assurance while ensuring high reliability.
By establishing a component failure model library, a nonlinear mapping relationship between production processes and screening tests is constructed, process defect levels are classified, and the screening test process is optimized based on these relationships to reduce unnecessary screening steps and lower costs.
This approach reduces the cost and expense of screening tests while ensuring the high quality of components, thereby improving the development process and service performance of components.
Smart Images
Figure CN121636896A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of high-level component reliability, and specifically relates to an optimization method for screening experiments of high-level components for aerospace applications. Background Technology
[0002] The rise of international commercial spaceflight signifies the formation of a new form of space competition. The shift towards a "cost-effectiveness-first" paradigm in commercial spaceflight is forcing space agencies worldwide to restructure their technological approaches. A pressing challenge for my country is how to maintain high reliability while building a low-cost, adaptable system for ensuring the quality of components. Under the impact of international commercial spaceflight, low cost and high reliability have become inevitable trends in the development of my country's space systems.
[0003] On the one hand, to improve the reliability of electronic components, manufacturers typically ensure long-term stable operation of components under designed working conditions through reasonable quality control and screening tests. In the field of screening tests for high-grade components used in aerospace, my country adopts a screening test standard (GJB 548C-2021) developed with reference to existing foreign screening test standards. The theoretical basis of the screening test relies on the component's failure bathtub curve (…). Figure 1 As shown by the bathtub curve, early failure rates can be eliminated by screening and identifying potential early failure units. Screening tests constitute a core guarantee for component quality. By applying appropriate strength stress to components, inherent quality defects and manufacturing process defects are revealed, eliminating early failures and reducing the defect rate, thereby ensuring the high reliability of the remaining products. Screening measures such as aging in screening tests can help products quickly pass through the early failure period and reach a period of low failure and stable performance, such as occasional failure. Figure 2 As shown.
[0004] On the other hand, as aerospace users place increasingly higher demands on cost control of aerospace products, the challenges of component procurement costs are constantly increasing. Aerospace models require components to meet military-grade or even space-grade standards, which translates to high costs. Currently, domestic aerospace high-grade components undergo 100% "first screening" and "second screening" according to standard requirements to ensure their quality and reliability. Reasonable optimization of screening tests can effectively avoid the increased costs and reduced reliability lifespan associated with numerous stringent and cumbersome screening tests. It also enables components and their associated equipment to operate with minimal stress damage, providing strong support for shortening the development process and improving the service performance of high-grade components. The United States established the microelectronic device screening test optimization standard JEDEC JEP121B as early as 1996; however, the development of domestic screening test optimization standards has long been lacking.
[0005] To address the issues of stringent screening test conditions and high screening costs associated with current high-grade components, and to achieve a low-cost approach to ensuring the quality of high-grade components, it is imperative to comprehensively and deeply analyze the optimization methods for screening tests of high-grade components while incorporating cost control. This involves appropriately simplifying the quality assurance methods for high-grade components, optimizing some screening test procedures while ensuring the high quality of components, and ultimately achieving highly reliable and low-cost development and use of microelectronic devices. Summary of the Invention
[0006] The purpose of this invention is to provide an experimental optimization method for screening high-grade components for aerospace applications, characterized by the following steps: Step 1: Based on failure data from the component manufacturing and screening processes, establish a component failure model library with quality consistency as one of the analytical elements; Step 2: Based on the component failure model library established in Step 1, and combined with the component manufacturing process and its production data, construct a nonlinear mapping relationship between the component manufacturing process and the component failure mode. Step 3: Based on the component failure model library established in Step 1, and combined with the component screening process and its data, construct a nonlinear mapping relationship between component screening tests and component failure modes. Step 4: Based on the nonlinear mapping relationship between the component manufacturing process and the component failure mode established in Step 2, and the nonlinear mapping relationship between the component screening test and the component failure mode established in Step 3, construct the nonlinear mapping relationship between the component manufacturing process and the component screening test. Step 5: Based on the nonlinear mapping relationship between component manufacturing process, component screening experiment, and component failure mode, construct a mapping relationship matrix among the three. Step Six: Based on the component manufacturing process, identify the potential process defects in each process and classify them into different levels; Step 7: Statistically analyze the production process data to determine the defect rate and confidence level of possible process defects in each production process of the components; Step 8: Based on the mapping relationship matrix between component manufacturing process, component screening experiment and component failure mode, as well as the defect rate and confidence rate in the component manufacturing process, design an optimized screening experiment scheme for components.
[0007] Preferably, in step one, based on the production and screening process data of multiple batches of components, combined with the physical characteristics of components and their failure modes and failure mechanisms, the quality consistency issues between batches and within batches in the component production process are fully analyzed, and a component failure model library with quality consistency as one of the analysis elements is established.
[0008] Preferably, in step six, different process defects in the component manufacturing process are classified into three defect levels: P, S, and T.
[0009] Preferably, the presence of P-level defects during the manufacturing process will directly cause the component to fail in subsequent screening tests, while the presence of S-level and T-level defects has a certain probability of causing the component to fail in subsequent screening tests, with S-level defects having a greater probability of causing the component to fail than T-level defects.
[0010] Preferably, based on the mapping relationship matrix between component manufacturing process, component screening test, and component failure mode, when all manufacturing processes that have a mapping relationship with a certain screening test meet the following conditions: P-level defects have a defect rate of less than 0.5% at a confidence level of 99%, S-level defects have a defect rate of less than 3% at a confidence level of 95%, and T-level defects have a defect rate of less than 4% at a confidence level of 90%, the screening test can be exempted or its screening conditions can be optimized.
[0011] This invention simplifies the quality assurance methods for high-grade components, optimizes some screening experimental procedures while ensuring the high quality of components, and achieves high-reliability and low-cost development and use of microelectronic devices. Attached Figure Description
[0012] Figure 1 A curve diagram of a bathtub; Figure 2 To screen the bathtub curve after the experiment; Figure 3 This is a flowchart of the screening experiment optimization method involved in the present invention. Detailed Implementation
[0013] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0014] This invention provides an optimization method for screening high-grade components for aerospace applications, such as... Figure 3 As shown, it mainly includes the following steps: Step 1: Based on the production and screening process data of multiple batches of components, combined with the physical characteristics of the components and their failure modes and mechanisms, and taking into full account the issues of inter-batch and intra-batch quality consistency in the component production process, establish a component failure model library that considers quality consistency.
[0015] Step 2: Based on the component failure model library and combined with the component manufacturing process and its production data, construct the nonlinear mapping relationship between the component manufacturing process and the component failure mode, as shown in the table below; Step 3: Based on the component failure model library, and combined with the component screening process and its data, construct a nonlinear mapping relationship between component screening tests and component failure modes, as shown in the table below; Step 4: Based on the nonlinear mapping relationship between component manufacturing process and component failure mode, and the nonlinear mapping relationship between component screening test and component failure mode, construct the nonlinear mapping relationship between component manufacturing process and component screening test, as shown in the table below; Step 5: Based on the nonlinear mapping relationship between component manufacturing process, component screening experiment, and component failure mode, construct a mapping relationship matrix among the three. Step Six: Based on the component manufacturing process, identify potential process defects in each step of the manufacturing process. Classify these defects into three levels: P, S, and T. Taking wire bonding as an example, as shown in the table below. The presence of a P-level defect in the manufacturing process will directly cause the component to fail subsequent screening tests. The presence of S-level and T-level defects has a certain probability of causing the component to fail subsequent screening tests, with S-level defects having a higher probability of causing the component to fail than T-level defects. Step 7: Statistically analyze the production process data to determine the defect rate and confidence level of possible process defects in each production process of the components; Step 8: Based on the mapping relationship matrix between component manufacturing process, component screening test, and component failure mode, when all manufacturing processes that have a mapping relationship with a certain screening test meet the following conditions: P-level defects have a defect rate of less than 0.5% at a confidence level of 99%, S-level defects have a defect rate of less than 3% at a confidence level of 95%, and T-level defects have a defect rate of less than 4% at a confidence level of 90%, then the screening test can be exempted or its screening conditions can be optimized, as shown in the table below. Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.
Claims
1. A method for optimizing screening experiments of high-level components for aerospace applications, characterized in that, The method comprises the following steps: Step one: according to the failure data in the production process and screening process of components, a component failure model library is established, in which quality consistency is one of the analysis elements; Step two: according to the component failure model library established in step one, combined with the production process of components and the production data thereof, a nonlinear mapping relationship between the production process of components and the component failure mode is constructed; Step three: according to the component failure model library established in step one, combined with the component screening process and the screening process data thereof, a nonlinear mapping relationship between the component screening test and the component failure mode is constructed; Step four: according to the nonlinear mapping relationship between the production process of components and the component failure mode constructed in step two, and the nonlinear mapping relationship between the component screening test and the component failure mode constructed in step three, a nonlinear mapping relationship between the production process of components and the component screening test is constructed; Step five: according to the nonlinear mapping relationship among the production process of components, the component screening test and the component failure mode, a mapping relationship matrix among the three is constructed; Step six: according to the production process of components, possible process defects in each production process of components are determined, and the process defects are divided into different grades; Step seven: the production process data are statistically analyzed to determine the defect rate and confidence of the possible process defects in each production process of components; Step eight: the mapping relationship matrix among the production process of components, the component screening test and the component failure mode, and the defect rate and confidence in the production process of components are comprehensively considered to design an optimized scheme for the component screening test.
2. The space-grade high-level device screening experiment optimization of claim 1, wherein, In step one, based on the production process and screening process data of multiple batches of components, combined with the physical characteristics of components and the failure mode and failure mechanism thereof, the batch-to-batch quality consistency and in-batch quality consistency in the production process of components are fully analyzed, and a component failure model library is established, in which quality consistency is one of the analysis elements.
3. The space-grade high-level device screening experiment optimization of claim 1, wherein, In step six, different process defects in the production process of components are divided into three defect grades, P, S and T.
4. The space-grade high-level device screening experiment optimization of claim 3, wherein, The existence of P-grade defects in the production process will directly lead to the unqualification of the component in the subsequent screening test, and the existence of S-grade and T-grade defects has a certain probability to lead to the unqualification of the component in the subsequent screening test, wherein the probability of unqualification of the component caused by S-grade defects is greater than that caused by T-grade defects.
5. The space-grade high-level device screening experiment optimization of claim 4, wherein, According to the mapping relationship matrix among the production process of components, the component screening test and the component failure mode, when all the production processes that have a mapping relationship with a certain screening test meet the conditions that the defect rate of P-grade defects is less than 0.5% at a confidence of 99%, the defect rate of S-grade defects is less than 3% at a confidence of 95%, and the defect rate of T-grade defects is less than 4% at a confidence of 90%, the screening test can be selected to be exempted or the screening conditions thereof can be optimized.