Lightweight index calculation method and system based on civil aircraft manufacturing industry

Abstract

The invention discloses a lightweight index calculation method and system based on civil aircraft manufacturing industry. The method comprises the following steps of S1, defining index basic information; s2, selecting a unified online data source; s3, setting a basic index; s4, setting a composite index; s5, index multiplexing is carried out; s6, outputting a formula and an index calculation result; s7, setting a final output index; and S8, index display and application. Various business indexes can be conveniently and efficiently displayed and managed in real time, the efficiency and flexibility of index design are improved, the readability and verification convenience of formulas are enhanced, flexible output adapts to multiple requirements, the development efficiency, maintainability and expansibility of an index system are systematically improved, the implementation cost is reduced, the operation process is simplified, and the method is suitable for popularization and application. And the data security and consistency are improved, and the method is suitable for data modeling requirements in a dynamic service scene.

Description

Technical Field

[0001] The present invention relates to the field of aerospace technology, and in particular to a lightweight index calculation method and system based on the civil aircraft manufacturing industry. Background Art

[0002] Civil aircraft manufacturing is a highly complex, multi-stakeholder collaborative process. Managing the entire manufacturing lifecycle requires business and management personnel at all levels to monitor and maintain relevant indicators. The timeliness and accuracy of these indicators are directly related to aircraft safety performance, airline operating efficiency, and other aspects.

[0003] Aircraft manufacturing management systems are complex, with various highly specialized systems covering multiple manufacturing stages, from design, supply chain management, and parts production to assembly, testing, and delivery. These specialized and complex systems make data integration challenging and place high demands on real-time performance and flexibility. However, in real-world business scenarios, indicators often cannot be displayed independently within the system, requiring additional data to be pulled and indicators to be created independently of the system. This leads to fragmented indicators and makes their management difficult. This chaotic and decentralized approach to indicator management, in the context of constant business updates and changes, can easily lead to data inconsistencies and information lags, impacting a company's decision-making efficiency and overall operational quality.

[0004] Currently, the existing technical solutions for enterprises mainly include BI (business intelligence) dashboard production indicators and professional indicator production software.

[0005] The development and maintenance of BI dashboards typically requires the support of highly specialized technical teams, resulting in long development cycles and limited flexibility when adjusting or expanding metrics. Furthermore, BI tools are costly to implement, especially when production processes frequently require adjustments to business requirements. This increases developer input, leading to reduced overall efficiency. BI dashboards and metric management present data governance and security challenges. Aircraft manufacturers' internal aircraft-related systems are often separated from administrative maintenance systems, and data comes from a complex array of sources, including but not limited to databases, offline Excel files, and APIs. Errors in any of these sources can lead to errors in the generated dashboards. This diverse and unregulated data source cannot guarantee data quality, leading to data omissions and errors, resulting in poor dashboard quality. Furthermore, BI dashboards are often customized to meet specific business needs. However, as the business evolves, business requirements constantly evolve, requiring BI reports to be redeveloped for each requirement, making them inflexible. Furthermore, the procurement and deployment of commercial BI tools often comes with significant costs, including software licensing, hardware upgrades, and training. Furthermore, maintaining and supporting BI systems requires continuous human resources investment, such as the allocation and training of roles like data administrators and data analysts, further increasing time and operational costs. Development cycles are also lengthy. BI dashboards involve requirements analysis, resource integration, technology selection and implementation, and ultimately user testing and feedback. The entire process is time-consuming and can easily delay management and business decisions.

[0006] Overall, BI dashboards provide visual decision-making support tools for manufacturing companies. However, due to their high technical threshold and limited flexibility, the civil aircraft production and manufacturing process requires a more lightweight, flexible and responsive solution to make up for the shortcomings of BI dashboards.

[0007] However, the main drawback of existing specialized indicator management tools is that their implementation often involves long deployment cycles and high technical requirements. Initial system configuration and ongoing maintenance often require the support of specialized technical teams, resulting in high costs. Furthermore, these tools lack flexibility in the face of rapidly changing business environments. Each change or addition of a new indicator may require technical personnel to reconfigure and develop the new tool, resulting in a slow response time. Overall, specialized indicator management tools are suitable for large-scale, highly complex business environments, providing enterprises with in-depth indicator analysis and automated management support. However, enterprises need to balance implementation costs and benefits while maintaining a sufficient level of technical expertise to cope with long-term maintenance and expansion needs. While specialized indicator management tools for finance and engineering have performed well in their respective application areas, their application scenarios are limited. They require specialized indicator libraries for analysis and comparison, making them susceptible to external data impacts and inadequate for aircraft manufacturing indicator calculations. Furthermore, their configuration and operation are complex, requiring a high learning curve and the support of specialized consultants. Furthermore, they are expensive to use and maintain, and lack flexible approval functionality. Using general-purpose data processing tools for indicator management in the aircraft manufacturing sector also has drawbacks: the construction logic of specialized indicator management tools often focuses not on indicator calculations but on general data processing functions. These tools require strong user skills and have a high learning curve. Their processing capabilities may be limited when dealing with large-scale data scenarios. Furthermore, data security and transmission efficiency are not fully guaranteed, potentially leading to data loss or leakage.

[0008] As the complexity of civil aircraft manufacturing grows, existing management methods struggle to quickly respond to new demands and challenges. Rapidly applying metrics to business scenarios and instantly updating data are key challenges. Flexible interaction is also essential, using interactive "what you ask is what you get" logic to build tools that allow users to quickly adjust metrics and obtain the information they need within a dynamic business environment.

[0009] In view of the above problems, the existing technology is in urgent need of improvement. Summary of the Invention

[0010] In order to solve at least one of the problems existing in the prior art described above, a first aspect of the present invention provides a lightweight index calculation method based on the civil aircraft manufacturing industry, which includes the following steps:

[0011] Step S1: define basic indicator information; wherein the basic indicator information includes at least one of the following: indicator name, core business domain, related business domain, indicator description and indicator type, and the indicator type is divided into basic indicators and composite indicators;

[0012] Step S2: Select a unified online data source; wherein the data source is a uniformly managed online data table. When the user selects the data source, all fields and some sample data contained in the data table are displayed simultaneously;

[0013] Step S3: Setting basic indicators; wherein, all fields are extracted from the data table selected by the user and divided into two categories: metric fields or dimension fields according to field attributes;

[0014] Step S4: setting a composite indicator; wherein the composite indicator is obtained by superimposing a formula on one or more basic indicators, or is calculated by superimposing a formula on the composite indicator; during each formula definition process, the user can edit the expression through a low-code visual editing method;

[0015] Step S5: Indicator reuse; wherein, for composite indicators with similar calculation logic, at least the created composite indicators are copied, and the copied composite indicators are adjusted in name and calculation logic to avoid redundancy;

[0016] Step S6: Outputting the formula and indicator calculation results; wherein, during the calculation process of each indicator, a text format formula output and corresponding indicator output are generated to facilitate self-checking by the user;

[0017] Step S7: setting a final output indicator; wherein, a unique indicator is selected from all indicators generated in steps S1 to S6 as the final output indicator, and the final output indicator is modified to meet business needs;

[0018] Step S8: indicator display and application; wherein, the final output indicator is displayed in the form of a card, the card cover displays the content after the indicator is calculated and supports switching of the dimension range.

[0019] In the aforementioned lightweight index calculation method based on the civil aircraft manufacturing industry, optionally, step S1 includes the following steps:

[0020] Automatically classify and grade the core business domain and the related business domain based on the business process diagram or business logic tree within the enterprise;

[0021] Provides an interactive editing interface that allows users to adjust and supplement indicator descriptions and indicator type information in real time.

[0022] In the lightweight index calculation method based on the civil aircraft manufacturing industry as described above, optionally, in step S2, the field information, data type and sample data of the data table are extracted and preprocessed to ensure the integrity of the data table structure and data consistency.

[0023] In the lightweight indicator calculation method based on the civil aircraft manufacturing industry as described above, optionally, in step S3, the metric field is used to perform mathematical calculations including at least maximum value, minimum value, sum, and average value, and includes at least one of the following fields: sales, quantity, and temperature; the dimension field is used to describe the characteristics or attributes of the data, classify and / or group the data source according to the dimension field, and display and analyze the calculation results of the metric field by switching the scope and type of the dimension.

[0024] In the lightweight indicator calculation method based on the civil aircraft manufacturing industry as described above, optionally, the basic indicator needs to set a unique measurement field and at least one dimension field at the same time.

[0025] In the lightweight indicator calculation method based on the civil aircraft manufacturing industry as described above, optionally, in step S4, a formula is constructed through a low-code visual editing interface; specifically, a graphical componentization method is adopted in the editing process, and the formula is constructed by dragging, arranging and combining predefined graphical formula components.

[0026] In the aforementioned lightweight index calculation method based on the civil aircraft manufacturing industry, optionally, step S4 includes the following steps:

[0027] Define all the basic indicators required to form the formula of the lowest level of the composite indicator;

[0028] Superimposing the formula on the defined basic indicators;

[0029] During each formula editing process, the visual expression editing interface provides users with a list of defined indicators, a list of formula characters, and a list of commonly used formulas; wherein, the defined indicator list only displays the basic indicators created in the current formula design process; the formula character list includes at least addition, subtraction, multiplication, and division operators, small and big brackets, custom numbers, and custom percentages; the commonly used formula list includes at least year-on-year and quarter-on-quarter composite indicator calculation formulas.

[0030] To achieve the above-mentioned object, a second aspect of the present invention provides a lightweight index calculation system based on the civil aircraft manufacturing industry, wherein the lightweight index calculation method based on the civil aircraft manufacturing industry as described in any embodiment of the first aspect is used, including:

[0031] Indicator basic information definition module; wherein the indicator basic information includes at least one of the following: indicator name, core business domain, related business domain, indicator description and indicator type, and the indicator type is divided into basic indicators and composite indicators;

[0032] Online data source selection module; wherein the data source is a uniformly managed online data table. When the user selects the data source, all fields and some sample data contained in the data table are displayed simultaneously;

[0033] Basic indicator setting module; in which all fields are extracted from the data table selected by the user and divided into two categories: metric fields or dimension fields based on field attributes;

[0034] Composite indicator setting module; wherein the composite indicator is obtained by superimposing a formula on one or more basic indicators, or is calculated by superimposing a formula on the composite indicator; during each formula definition process, users can edit the expression through low-code visual editing;

[0035] An indicator reuse module; wherein, for composite indicators with similar calculation logic, the module at least includes duplicating the already created composite indicators and adjusting the names and calculation logic of the duplicated composite indicators to avoid redundancy;

[0036] Formula output and indicator calculation result display module; in which, during the calculation process of each indicator, the formula output and corresponding indicator output in text format are generated to facilitate self-checking by users;

[0037] A final output indicator setting module, wherein a unique indicator is selected from all indicators generated in the previous process as the final output indicator, and the final output indicator is modified to meet business needs;

[0038] Indicator display and application module; wherein, the final output indicator is displayed in the form of a card, the card cover displays the content after the indicator calculation and supports switching of the dimension range.

[0039] In order to achieve the above-mentioned purpose, the third aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor runs the program, the lightweight index calculation method based on the civil aircraft manufacturing industry as described in any one of the first aspects above is implemented.

[0040] In order to achieve the above-mentioned purpose, the fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions or a computer program, and when the computer-executable instructions or the computer program are processed and executed, the lightweight index calculation method based on the civil aircraft manufacturing industry as described in any one of the embodiments in the first aspect above is implemented.

[0041] The lightweight indicator calculation method and system provided by the present invention based on the civil aircraft manufacturing industry realize lightweight indicator calculation and management. By reusing the designed indicator logic, it reduces the workload of repeated development and the risk of human error, while ensuring the uniformity of indicator logic in multiple scenarios; the textual formula display simplifies the interpretation of complex logic, allowing developers to quickly verify the accuracy of relational expressions and reduce communication and understanding costs; and the present invention can select process indicators as the final output results, expand the analysis dimension selection, and meet the needs of phased verification or refined analysis; the process indicators of the present invention are reused across levels and self-called, which promotes modular design, supports the iterative construction of indicators for complex business scenarios, and improves resource utilization.

[0042] In summary, the present invention solves the problems of insufficient flexibility in indicator management, high implementation cost, and complex operation in the existing technology. It can display and manage various business indicators in real time, conveniently and efficiently, improve the efficiency and flexibility of indicator design, enhance the readability and verification convenience of formulas, and flexibly output to adapt to diverse needs. It systematically improves the development efficiency, maintainability and scalability of the indicator system, reduces implementation costs, simplifies operating procedures, and improves data security and consistency. It is suitable for data modeling needs in dynamic business scenarios.

[0043] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 This is a flow chart of an embodiment of a lightweight index calculation method based on the civil aircraft manufacturing industry of the present invention;

[0046] Figure 2 yes Figure 1 Schematic diagram of the specific process of calculating lightweight indicators based on the civil aircraft manufacturing industry. DETAILED DESCRIPTION

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0048] Terms such as “comprise” and “include” indicate that in addition to the components directly and explicitly stated in the description and claims, the technical solution of the present invention does not exclude the situation where it has other components that are not directly or explicitly stated.

[0049] like Figure 1 and Figure 2 As shown, the lightweight index calculation method based on the civil aircraft manufacturing industry of the present invention may include the following steps:

[0050] Step S1: Define basic indicator information.

[0051] In step S1, the basic indicator information may include indicator name, core business domain, related business domain, indicator description, indicator type, etc. Indicator types are divided into basic indicators and composite indicators.

[0052] Basic indicators refer to the design of atomic indicators directly citing a unified online data source, without the use of formulas, and only perform basic statistical calculations. Composite indicators are calculated by superimposing one or more formulas on the initially designed basic indicators.

[0053] In an optional embodiment, step S1 may further include the following steps:

[0054] The core business domain and the related business domain are automatically classified and graded based on the business process diagram or business logic tree within the enterprise.

[0055] Alternatively, machine learning algorithms can be used to analyze business process diagrams or business logic trees to identify key nodes and hierarchical relationships. Another approach is to use a rules engine to categorize business domains based on pre-set business rules. These automated methods can significantly reduce the workload and error rate of manual classification.

[0056] Since the source of indicator data and the scope of application may not be limited to one business domain, the selection and maintenance of relevant business domain modules are added to increase the applicability of the indicator.

[0057] Provides an interactive editing interface that allows users to adjust and supplement indicator descriptions and indicator type information in real time.

[0058] This step improves the efficiency and accuracy of the initial classification. The system then provides an interactive editing interface, allowing users to adjust and supplement indicator descriptions and indicator type information in real time. This approach leverages the system's automation capabilities while retaining active user participation, achieving efficiency and flexibility in the process of defining basic indicator information.

[0059] Step S2: Select a unified online data source.

[0060] In step S2, the data source is a uniformly managed online data table. When the user selects the data source, all fields and some sample data contained in the data table are displayed simultaneously.

[0061] In the civil aircraft manufacturing industry, data accuracy and consistency are crucial for indicator calculations. However, due to diverse data sources and non-uniform formats, we often face problems such as incomplete data table structures and inconsistent data. These problems may lead to errors in indicator calculations and affect the accuracy of decision-making. It should be noted that this embodiment does not support data from sources such as offline data, interface data, and data directly connected to databases. Data from any source needs to be uniformly managed with the system in which this function is embedded and used as a single data source for indicator tools.

[0062] In an optional embodiment, step S2 further includes extracting and preprocessing the field information, data types, and sample data of the data table to ensure the integrity of the data table structure and data consistency. Specifically, the extraction and preprocessing of field information may include the following steps: first, automatically scanning all fields in the data table to extract information such as field names and field descriptions; then, standardizing the field names to ensure consistent naming conventions; and finally, checking the relationships between fields to ensure that relationships such as primary keys and foreign keys are correctly defined. The extraction and preprocessing of data types may involve the following operations: first, identifying the data type of each field, such as text, number, date, etc.; then, checking whether the data type is consistent with the field purpose and performing type conversion if necessary; and finally, unifying the data format, such as standardizing the date format. The extraction and preprocessing of sample data may include: first, extracting a certain amount of sample data from the data table; then, performing data cleaning on the sample data, such as removing outliers and processing missing values; and finally, performing statistical analysis on the sample data to understand the data distribution characteristics.

[0063] Through these preprocessing steps, the present application can discover and solve potential data problems in the data source selection stage. For example, if text data is found mixed in a field that should be of digital type, the system will automatically mark it and prompt the user to process it. For another example, when checking sample data, if the values of certain fields are found to deviate significantly from the normal range, the system will remind the user to conduct further verification. The solution of this embodiment not only improves the data quality, but also simplifies the subsequent indicator calculation process. Since the data has been preliminarily cleaned and standardized, these high-quality data can be used directly when calculating indicators, reducing the intermediate data processing steps, which not only improves the calculation efficiency, but also reduces the risk of calculation errors caused by data problems.

[0064] Since users cannot have a clear understanding of the fields in a table based solely on the table name when selecting data, this method needs to display all the fields contained in the table and a small amount of sample data (for example, the amount of sample data is less than or equal to 10) when selecting a table.

[0065] Compared with existing technologies, traditional BI tools usually perform data cleaning and conversion after data is loaded, which may result in a lot of time and resources being wasted when data problems are discovered. However, this application can discover and solve data problems earlier by performing preprocessing at the data source selection stage, avoiding subsequent errors and rework. In addition, compared with professional ETL (extraction, transformation, loading) tools, the preprocessing method of this application is more lightweight and user-friendly, and is particularly suitable for civil aircraft manufacturing scenarios that require rapid response.

[0066] Step S3: Set basic indicators.

[0067] In step S3, all fields are extracted from the data table selected by the user and divided into two categories: metric fields or dimension fields according to field attributes.

[0068] In an optional embodiment, in step S3, metric fields are used for mathematical calculations, including maximum, minimum, sum, and average values. In this embodiment, these fields are quantifiable data, such as sales, quantity, or temperature. Calculations on these fields yield specific numerical results, providing a basis for quantifying indicators. Dimension fields describe the characteristics or attributes of the data, used to categorize and group data sources. In this embodiment, these fields may include time, location, product type, etc. For example, in the civil aircraft manufacturing industry, metric fields may include the production quantity of a component, the assembly time of an aircraft, or the operating temperature of a system. Dimension fields may include time (such as date, month, year), location (such as production line, workshop, factory), product type (such as aircraft model, component category), etc. Dimension fields allow data to be segmented from different perspectives, enabling multi-dimensional data analysis. This means that users can flexibly select different dimensions to view the same set of metric data. For example, one can view the production quantity of a specific component by month, or switch to viewing the same data by production line. This flexibility enables more comprehensive and in-depth data analysis.

[0069] In this embodiment, attributes in a data table can only be identified as either a metric or a dimension field. Basic indicators require both a unique metric field and at least one dimension field. This technical solution ensures that each basic indicator has a clear calculation object and analysis dimension, helping to improve the accuracy and analyzability of the indicator. The unique metric field ensures calculation consistency, while the at least one dimension field provides flexibility in data analysis.

[0070] Specifically, a unique metric field ensures that each basic indicator has a clear calculation focus, avoiding calculation conflicts and confusing results that may be caused by multiple metric fields. For example, when analyzing sales data, "sales amount" can be set as the only metric field. In this way, no matter which dimension is analyzed, the core object of the calculation is always the sales amount, ensuring the consistency of data analysis. At the same time, requiring at least one dimension field to be set provides flexibility for data analysis. Users can select one or more dimension fields as needed, such as "time", "region", "product type", etc., to achieve multi-angle analysis of data. For example, you can analyze changes in sales amounts in different time periods, different regions or different product types by switching dimension fields.

[0071] This design approach also promotes data standardization and consistency. Because each underlying metric follows the same structure, they can be more easily combined or compared, enabling more complex data analysis and report generation. For example, it's easy to compare the sales performance of different products in different regions, or analyze sales trends for a particular product over different time periods.

[0072] In summary, this embodiment not only solves the problem of selecting metric fields and dimension fields when setting basic indicators, but also lays the foundation for subsequent composite indicator calculation and data analysis. It makes the indicator system more structured and standardized, which is conducive to data consistency management and multi-dimensional analysis, thereby improving the usability and analytical value of the entire indicator system.

[0073] Step S4: Set the composite index.

[0074] In step S4, a composite indicator is calculated by superimposing a formula on one or more basic indicators, or by superimposing a formula on a composite indicator. During each formula definition, users can edit the expression using a low-code visual editing method.

[0075] In an optional embodiment, the present invention constructs formulas through a low-code visual editing interface, effectively solving the problems of complexity and user operation difficulty in the process of constructing composite indicator formulas. Specifically, a graphical componentization method is adopted in the editing process to construct formulas by dragging, arranging and combining predefined graphical formula components. This solution transforms traditional text-based formula editing into graphical component dragging and combination, which greatly reduces the user's operating threshold. Users do not need to master complex formula syntax and can complete the formula construction through simple mouse operations. Predefined graphical formula components further improve the user's operating efficiency and reduce repetitive work. This method not only simplifies the operating process, but also improves the accuracy of formula construction, effectively improving the efficiency and quality of indicator calculation.

[0076] Specifically, the low-code visual editing interface can use an interactive interface built with Web technology, or a graphical user interface developed based on desktop applications. The interface design should be intuitive and easy to use, and can include functional modules such as drag areas, component libraries, and preview areas. Formula components can be designed as different graphic shapes, such as rectangles for numerical input, circles for operators, diamonds for conditional judgments, etc. These components can be enhanced in visual recognition through color coding or icons. The predefined graphical formula component library can include basic operators (such as addition, subtraction, multiplication, and division), functions (such as SUM, AVERAGE, MAX, MIN), logical operators (such as AND, OR, NOT), and calculation components in specific fields (such as year-on-year growth rate and month-on-month growth rate).

[0077] It can be seen that this embodiment provides an intuitive operating environment through a low-code visual editing interface when solving the complexity and user operation difficulty problems in the process of constructing composite indicator formulas. Users can directly see all available formula components on this interface without having to remember complex function names or syntax rules. The graphical componentization method converts abstract formula concepts into specific visual elements, making it easier for users to understand the functions and effects of each component. Through dragging, arranging and combining operations, users can build formulas like building blocks. Compared with professional BI tools, the solution of this application is more lightweight and flexible. Users can quickly create and modify indicators without relying on a professional technical team, thereby improving business response speed.

[0078] Furthermore, step S4 may include the following steps:

[0079] Define all the basic indicators required to form the bottom-level formula for the composite indicator. This step ensures the preparation of the foundational data for the composite indicator calculation and provides the necessary elements for subsequent formula overlay. The definition of a basic indicator can include information such as the indicator name, data source, and calculation method. For example, in the civil aircraft manufacturing industry, basic indicators such as "production cost per flight" and "component qualification rate" can be defined.

[0080] Formulas are superimposed on defined base indicators. This step allows users to create more complex composite indicators by combining base indicators, increasing the flexibility and complexity of indicator calculations. As mentioned above, formula superposition can be performed visually. Users can select base indicators and construct the calculation formula for the composite indicator with a simple drag and drop or click.

[0081] During each formula editing process, the visual expression editing interface provides users with a list of defined indicators, a list of formula characters, and a list of commonly used formulas; wherein, the defined indicator list only displays the basic indicators created in the current formula design process; the formula character list includes at least addition, subtraction, multiplication, and division operators, small and big brackets, custom numbers, and custom percentages; the commonly used formula list includes at least year-on-year and quarter-on-quarter composite indicator calculation formulas.

[0082] Step S5: Indicator reuse. In this step, users can copy the created composite indicator and make adjustments based on it, which greatly simplifies the creation process of similar indicators.

[0083] In step S5, for composite indicators with similar calculation logic, at least the created composite indicators are copied, and the names and calculation logics of the copied composite indicators are adjusted to avoid redundancy.

[0084] It's important to note that defining complex composite indicators may involve indicators with essentially identical calculation logic, differing only slightly. To improve the efficiency of indicator design in this scenario, this method requires tools to provide reuse functionality—that is, the ability to directly create an indicator that is identical to the one being reused. To avoid indicator redundancy during composite indicator calculation, this method imposes requirements on the reused indicator from both the indicator name and calculation logic perspectives: the reused indicator must not be identical to the reused indicator, and the calculation logic must also be adjusted.

[0085] Step S6: Output formula and indicator calculation results. In order to provide a self-checking function for errors made by the user in defining a series of complex indicators, the method requires providing formula output and indicator output functions for each indicator calculation during the calculation process.

[0086] In step S6, the formula output and corresponding indicator output are generated in text format during the calculation process of each indicator, allowing users to self-check. The output formula here refers to the ability to display the specific content of the formula in a concise and easy-to-read text format after the indicator with the formula is defined in the visualization interface. The output indicator is the ability to calculate the indicator value at the current stage and output the result after the indicator is defined.

[0087] Step S7: Set the final output indicator, select a unique indicator from all the indicators generated in steps S1 to S6 as the final output indicator, and modify the final output indicator to meet business needs.

[0088] The final step in indicator design is selecting an output indicator. This step requires the user to select a single output indicator from among all the indicators generated throughout the indicator design process. To meet business needs, users can modify the final output indicator as needed, thus reducing duplication of work.

[0089] Step S8: indicator display and application.

[0090] In step S8, the final output indicators are displayed in the form of cards. The card cover shows the content after the indicator calculation and supports dynamic switching of dimension ranges, providing an intuitive and highly interactive data visualization effect.

[0091] In order to achieve the above-mentioned purpose, the present invention also provides a lightweight indicator calculation system based on the civil aircraft manufacturing industry, including an indicator basic information definition module, an online data source selection module, a basic indicator setting module, a composite indicator setting module, an indicator reuse module, a formula output and indicator calculation result display module, a final output indicator setting module and an indicator display and application module.

[0092] Specifically, in the indicator basic information definition module, basic indicator information can include the indicator name, core business domain, related business domain, indicator description, and indicator type. Indicator types are categorized as basic indicators and composite indicators. In the online data source selection module, the data source is a centrally managed online data table. When users select a data source, all fields in the data table and some sample data are displayed simultaneously. The basic indicator setting module extracts all fields from the user-selected data table and categorizes them as either metric fields or dimension fields based on their attributes. In the composite indicator setting module, composite indicators are calculated by superimposing formulas on one or more basic indicators, or by superimposing formulas on composite indicators. During each formula definition process, users can edit the expression using low-code visual editing. The indicator reuse module, for composite indicators with similar calculation logic, at least copies existing composite indicators and adjusts their names and calculation logic to avoid redundancy. The formula output and indicator calculation result display module generates text-formatted formula output and corresponding indicator output for each indicator calculation process, allowing users to easily verify the results. The final output indicator setting module selects a single indicator from all indicators generated by the preceding process as the final output indicator and modifies it to suit business needs. The indicator display and application module displays the final output indicator as a card. The card cover shows the calculated content of the indicator and supports switching the dimension range.

[0093] As a preferred embodiment, the lightweight indicator calculation system based on the civil aircraft manufacturing industry of the present application can be deployed in the cloud and adopt a microservice architecture. Each functional module runs as an independent microservice and communicates through an API gateway. This architecture provides better scalability and fault tolerance. For example, the indicator basic information definition module can be implemented as a RESTful service, providing an API for creating, reading, updating and deleting (CRUD) indicator definitions; the service can use a NoSQL database (such as MongoDB) to store indicator definitions to support flexible data structures. The online data source selection module can be implemented as a data integration service, using a message queue system such as Apache Kafka to implement real-time data stream processing, which allows the system to process large amounts of real-time data while maintaining good performance. The basic indicator setting module and the composite indicator setting module can be jointly implemented as an indicator calculation engine service, which can use a distributed computing framework such as Apache Spark to process large-scale data sets and support complex indicator calculation logic. The indicator reuse module can be implemented as a template management service, allowing users to save and share indicator templates, which can manage the version history of the template through a version control system (such as Git). The formula output and metric calculation result display module can be implemented as a logging and monitoring service, using the ELK (Elasticsearch, Logstash, Kibana) stack to collect, store, and visualize the calculation process and results. The final output metric setting module and the metric display and application module can be implemented as front-end services, using modern front-end frameworks such as React or Vue.js to build responsive user interfaces. These services can communicate with back-end services via a GraphQL API, providing more flexible data query capabilities.

[0094] Through the above microservice architecture, the system of the present invention can independently scale each module according to demand, improving the availability and performance of the overall system. For example, during peak metric calculation periods, the number of instances of the metric calculation engine service can be dynamically increased to handle the increased load. In addition, the system can also integrate machine learning capabilities, such as providing intelligent recommendations during the metric definition process or automatically detecting abnormal metric values. This can be achieved by adding a dedicated machine learning service that can use frameworks such as TensorFlow or PyTorch to train and deploy models.

[0095] In summary, this microservices-based cloud deployment solution provides the system with high flexibility, scalability, and reliability, and can better meet the complex and changing indicator calculation needs of the civil aircraft manufacturing industry.

[0096] In order to achieve the above-mentioned purpose, the present invention also provides a computer device, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor runs the program, it can implement the steps of a lightweight indicator calculation method based on the civil aircraft manufacturing industry as described in any of the aforementioned embodiments.

[0097] The processor and memory can be provided separately or integrated together, for example, integrated into a system-on-chip (SOC) of a terminal device. It should be understood that the processor of the embodiment of the present application may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by an integrated logic circuit of hardware in the processor or by instructions in the form of software. The above processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component. The various methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0098] In order to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, which stores executable instructions or programs. When the executable instructions or programs are processed and executed, the lightweight indicator calculation method based on the civil aircraft manufacturing industry as described in any of the previous embodiments is implemented.

[0099] The readable storage medium is, for example, a memory. The memory may be a volatile memory or a non-volatile memory, or the memory may include both volatile memory and non-volatile memory. The non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0100] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above-mentioned readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for causing one or more devices (such as personal terminals, clients, or network devices) to execute all or part of the steps of the methods described in various embodiments of the present invention.

[0101] The above describes in detail the preferred specific embodiments of the present invention, which only express several implementation methods of the present invention, but it cannot be understood as limiting the scope of the patent. The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various 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. It should be understood that ordinary technology in this field can make many modifications and changes based on the concept of the present invention without creative work. Therefore, without departing from the concept of the present invention, all technical solutions that can be obtained by technicians in this technical field through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of existing technology should be within the scope of protection determined by the claims.

Claims

1. A lightweight index calculation method based on the civil aircraft manufacturing industry, characterized in that: The following steps are involved: Step S1: define basic indicator information; wherein the basic indicator information includes at least one of the following: indicator name, core business domain, related business domain, indicator description and indicator type, and the indicator type is divided into basic indicators and composite indicators; Step S2: Select a unified online data source; wherein the data source is a uniformly managed online data table. When the user selects the data source, all fields and some sample data contained in the data table are displayed simultaneously; Step S3: Setting basic indicators; wherein, all fields are extracted from the data table selected by the user and divided into two categories: metric fields or dimension fields according to field attributes; Step S4: setting a composite indicator; wherein the composite indicator is obtained by superimposing a formula on one or more basic indicators, or is calculated by superimposing a formula on the composite indicator; during each formula definition process, the user can edit the expression through a low-code visual editing method; Step S5: Indicator reuse; wherein, for composite indicators with similar calculation logic, at least the created composite indicators are copied, and the copied composite indicators are adjusted in name and calculation logic to avoid redundancy; Step S6: Outputting the formula and indicator calculation results; wherein, during the calculation process of each indicator, a text format formula output and corresponding indicator output are generated to facilitate self-checking by the user; Step S7: setting a final output indicator; wherein, a unique indicator is selected from all indicators generated in steps S1 to S6 as the final output indicator, and the final output indicator is modified to meet business needs; Step S8: indicator display and application; wherein, the final output indicator is displayed in the form of a card, the card cover displays the content after the indicator is calculated and supports switching of the dimension range.

2. The lightweight index calculation method based on the civil aircraft manufacturing industry according to claim 1 is characterized in that: The step S1 comprises the following steps: Automatically classify and grade the core business domain and the related business domain based on the business process diagram or business logic tree within the enterprise; Provides an interactive editing interface that allows users to adjust and supplement indicator descriptions and indicator type information in real time.

3. The lightweight index calculation method based on the civil aircraft manufacturing industry according to claim 1 is characterized in that: In step S2, the field information, data types and sample data of the data table are extracted and preprocessed to ensure the integrity of the data table structure and data consistency.

4. The lightweight index calculation method based on the civil aircraft manufacturing industry according to claim 1 is characterized in that: In step S3, the metric field is used to perform mathematical calculations including at least maximum value, minimum value, sum, and average value, and includes at least one of the following fields: sales, quantity, and temperature; the dimension field is used to describe the characteristics or attributes of the data, classify and / or group the data source according to the dimension field, and display and analyze the calculation results of the metric field by switching the scope and type of the dimension.

5. The lightweight index calculation method based on the civil aircraft manufacturing industry according to claim 4 is characterized in that: The basic indicator needs to set a unique metric field and at least one dimension field at the same time.

6. The lightweight index calculation method based on the civil aircraft manufacturing industry according to claim 1 is characterized in that: In step S4, a formula is constructed through a low-code visual editing interface; specifically, a graphical componentization approach is adopted in the editing process, and the formula is constructed by dragging, arranging and combining predefined graphical formula components.

7. The lightweight index calculation method based on the civil aircraft manufacturing industry according to claim 6 is characterized in that: The step S4 comprises the following steps: Define all the basic indicators required to form the formula of the lowest level of the composite indicator; Superimposing the formula on the defined basic indicators; During each formula editing process, the visual expression editing interface provides users with a list of defined indicators, a list of formula characters, and a list of commonly used formulas; wherein, the defined indicator list only displays the basic indicators created in the current formula design process; the formula character list includes at least addition, subtraction, multiplication, and division operators, small and big brackets, custom numbers, and custom percentages; the commonly used formula list includes at least year-on-year and quarter-on-quarter composite indicator calculation formulas.

8. A lightweight index calculation system based on the civil aircraft manufacturing industry, characterized in that: The lightweight index calculation method based on the civil aircraft manufacturing industry according to any one of claims 1 to 7 comprises: Indicator basic information definition module; wherein the indicator basic information includes at least one of the following: indicator name, core business domain, related business domain, indicator description and indicator type, and the indicator type is divided into basic indicators and composite indicators; Online data source selection module; wherein the data source is a uniformly managed online data table. When the user selects the data source, all fields and some sample data contained in the data table are displayed simultaneously; Basic indicator setting module; in which all fields are extracted from the data table selected by the user and divided into two categories: metric fields or dimension fields based on field attributes; Composite indicator setting module; wherein the composite indicator is obtained by superimposing a formula on one or more basic indicators, or is calculated by superimposing a formula on the composite indicator; during each formula definition process, users can edit the expression through low-code visual editing; An indicator reuse module; wherein, for composite indicators with similar calculation logic, the module at least includes duplicating the already created composite indicators and adjusting the names and calculation logic of the duplicated composite indicators to avoid redundancy; Formula output and indicator calculation result display module; in which, during the calculation process of each indicator, the formula output and corresponding indicator output in text format are generated to facilitate self-checking by users; A final output indicator setting module, wherein a unique indicator is selected from all indicators generated in the previous process as the final output indicator, and the final output indicator is modified to meet business needs; Indicator display and application module; wherein, the final output indicator is displayed in the form of a card, the card cover displays the content after the indicator calculation and supports switching of the dimension range.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor runs the program, the lightweight indicator calculation method based on the civil aircraft manufacturing industry as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions or a computer program. When the computer-executable instructions or the computer program are processed and executed, the lightweight index calculation method based on the civil aircraft manufacturing industry as described in any one of claims 1 to 7 is implemented.

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