Component type recommendation method and related device

Abstract

This disclosure provides a component type recommendation method and related apparatus. The method includes: determining component data for a target product; constructing a component parameter profile based on the component data; generating a candidate type pool based on the component parameter profile; performing constraint judgment on the components in the candidate type pool to obtain constraint judgment results; determining substitution relationships based on the constraint judgment results to obtain candidate type groups; and performing optimal recommendation on the candidate type groups to obtain a type recommendation result. This disclosure can reduce the number of component specifications while retaining the supply capabilities of multiple manufacturers, achieving optimal recommendation of component type.

Description

Technical Field

[0001] This disclosure relates to the field of component data processing technology, and in particular to a component type recommendation method and related apparatus. Background Technology

[0002] This section is intended to provide background or context for the embodiments of this disclosure as set forth in the claims. The description herein is not intended to be a prior art simply because it is included in this section.

[0003] Aerospace products are typically composed of a large number of components, characterized by a wide variety of component types, models, specifications, and manufacturers. For components with similar or identical functions, factors such as manufacturer, model, packaging, quality level, delivery time, and price often lead to their separate selection and management in different products, batches, or projects. As product models, development batches, and supply sources continue to increase, the number of component specifications used in aerospace products continues to expand, easily leading to problems such as duplicate selection, redundant coding, fragmented procurement, complex inventory, and increased difficulty in supply planning.

[0004] However, in related technologies, when managing components, there are problems such as inconsistent data expression, low degree of structure of performance parameters, and reliance on manual judgment of substitution relationships, which make it difficult to resolve the contradiction between the expansion of component specifications and the need for standardization. Summary of the Invention

[0005] In view of this, the purpose of this disclosure is to propose a method and related apparatus for recommending standardized components, which at least to some extent solves one of the technical problems in the related art.

[0006] To achieve the above objectives, the first aspect of the exemplary embodiments of this disclosure provides a component type recommendation method, the method comprising:

[0007] Determine the component data of the target product, and construct a component parameter profile based on the component data; Based on the component parameter profile, a candidate system pool is generated, and the components in the candidate system pool are constrained to obtain the constraint determination result. The constraint determination results are used to determine the substitution relationship to obtain candidate system types. The candidate typology groups are optimized and recommended to obtain the typology recommendation results.

[0008] Based on the same inventive concept, a second aspect of the exemplary embodiments of this disclosure provides a component type recommendation device, comprising: The parameter profile determination module is configured to determine the component data of the target product and construct a component parameter profile based on the component data. The determination result module is configured to generate a candidate system pool based on the component parameter profile, perform constraint determination on the components in the candidate system pool, and obtain the constraint determination result. The system type group determination module is configured to perform substitution relationship determination on the constraint determination result to obtain candidate system type groups; The recommendation result determination module is configured to make optimal recommendations for the candidate typology group and obtain the typology recommendation result.

[0009] Based on the same inventive concept, a third aspect of the exemplary embodiments of this disclosure provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method as described in the first aspect.

[0010] Based on the same inventive concept, a fourth aspect of the exemplary embodiments of this disclosure provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method as described in the first aspect.

[0011] Based on the same inventive concept, a fifth aspect of the exemplary embodiments of this disclosure provides a computer program product including computer program instructions that, when run on a computer, cause the computer to perform the method as described in the first aspect.

[0012] As can be seen from the above description, the component standardization recommendation method and related apparatus provided in this disclosure include: The method involves identifying component data for the target product, constructing a component parameter profile based on this data, generating a candidate type pool based on the component parameter profile, performing constraint determination on the components in the candidate type pool, obtaining constraint determination results, determining substitution relationships based on the constraint determination results, obtaining candidate type groups, and making optimal recommendations for the candidate type groups to obtain type recommendation results. This disclosure can reduce the number of component specifications while retaining the supply capabilities of multiple manufacturers, achieving optimal recommendation of component type. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in this disclosure or related technologies, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 A schematic diagram illustrating an application scenario of the component type recommendation method provided as an exemplary embodiment of this disclosure; Figure 2 A schematic flowchart of a component type recommendation method provided for exemplary embodiments of this disclosure; Figure 3 A schematic diagram of a component type recommendation device provided as an exemplary embodiment of the present disclosure; Figure 4 A schematic diagram of the hardware structure of an electronic device provided for an exemplary embodiment of this disclosure. Detailed Implementation

[0015] It is understood that before using the technical solutions disclosed in the various embodiments of this application, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this application in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0016] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this application's technical solution, based on the prompt message.

[0017] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0018] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this application. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this application.

[0019] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0020] To make the objectives, technical solutions, and advantages of this disclosure clearer, the principles and spirit of this disclosure will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided merely to enable those skilled in the art to better understand and implement this disclosure, and are not intended to limit the scope of this disclosure in any way. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of this disclosure to those skilled in the art.

[0021] In this article, it is important to understand that any number of elements in the accompanying figures is for illustrative purposes and not for limitation, and any naming is for distinction only and has no limiting meaning.

[0022] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this disclosure should have the ordinary meaning understood by one of ordinary skill in the art to which this disclosure pertains. The terms "first," "second," and similar words used in the embodiments of this disclosure do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly. The article "a" or "an" preceding an element does not exclude the existence of multiple such elements.

[0023] The principles and spirit of this disclosure will be explained in detail below with reference to several representative embodiments.

[0024] As described in the background section, in related technologies, component management suffers from inconsistent data representation, low structuring of performance parameters, and reliance on manual judgment of substitution relationships, making it difficult to resolve the contradiction between the expansion of component specifications and the need for standardization. Specifically, different manufacturers, batches, and even projects use different naming methods for the same type of component; the recording format for model specifications is inconsistent; the description of packaging forms lacks standardized expression; and quality grade identification also exhibits multiple misuses. Furthermore, historical data contains numerous abbreviations, synonym substitutions, unit conversion differences, and missing key fields, resulting in a highly fragmented and non-standardized state of basic component data at the source. This inconsistency in data representation directly leads to the inability to automatically identify and group components with the same or similar functions. Any subsequent standardization analysis must be conducted on a chaotic data foundation, severely restricting the efficiency and accuracy of standardization work.

[0025] The functional and performance specifications of electronic components are mostly recorded in text, semi-structured, or non-standard formats in various documents or databases. There is a lack of predefined standard parameter field systems for different component categories, and a lack of rules and tools to automatically parse text descriptions into comparable numerical values. This makes it difficult to establish correspondences between key parameters of different components, to automatically determine the superiority or inferiority of parameter values, and to quantify complex situations such as performance margins and coverage ranges.

[0026] Due to the lack of calculable component profiles based on unified data standards and structured parameters, engineers can only rely on their personal knowledge or simple classification rules to determine whether two components are equivalent and substitutable. Different personnel have varying judgment criteria, leading to strong subjectivity and difficulty in reproducing the results. This manual judgment method cannot systematically identify components with the same function, parameter level, or substitutable components, easily overlooking potential substitution relationships or misjudging non-substitutable models as equivalent, resulting in an incomplete and inaccurate establishment of substitution relationships.

[0027] To address the aforementioned issues, this disclosure provides a method for recommending standardized components and a related apparatus. The method specifically includes: This solution involves identifying the component data of the target product, constructing a component parameter profile based on this data, generating a candidate type pool based on the component parameter profile, performing constraint judgments on the components in the candidate type pool, obtaining constraint judgment results, determining substitution relationships based on the constraint judgment results, obtaining candidate type groups, and making optimal recommendations for the candidate type groups to obtain type recommendation results. This solution transforms scattered component information into a unified, computable data format by identifying the component data of the target product and constructing a component parameter profile, enabling the automatic identification and merging of components with the same or similar functions, thereby generating a candidate type pool.

[0028] Based on the candidate system pool, this solution performs constraint determination on components. Through hierarchical evaluation of hard constraints, performance constraints, and supply constraints, a systematic constraint determination result is obtained, which accurately identifies the substitution relationship between components and then groups the components with substitution relationship into the candidate system group.

[0029] This solution optimizes and recommends candidate standardized product groups to obtain standardized product recommendation results. This result converges scattered manufacturer models into a unified specification format while retaining multiple qualified manufacturer models. This not only reduces the number of component specifications but also preserves the supply capabilities of multiple manufacturers, thereby achieving optimized and recommended standardized product recommendations.

[0030] After introducing the basic principles of this disclosure, various non-limiting embodiments of this disclosure will be described in detail below.

[0031] refer to Figure 1 This is a schematic diagram illustrating an application scenario of the component type recommendation method provided in the exemplary embodiments of this disclosure.

[0032] This application scenario includes a terminal device 101 and a server 102. The terminal device 101 and the server 102 can be connected via a wired or wireless communication network to achieve data interaction.

[0033] Terminal device 101 may be an electronic device located close to the user side, possessing data transmission and multimedia input / output functions, including but not limited to desktop computers, mobile phones, portable computers, tablet computers, media players, smart wearable devices, personal digital assistants (PDAs), or other electronic devices capable of performing the aforementioned functions. This electronic device may include a processor and a display screen with touch input functionality. The display screen is used to present a graphical user interface (GUI), which can display an application interface. The processor is used to process application data, generate the GUI, and control the display of the GUI on the screen.

[0034] Server 102 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0035] In some exemplary embodiments, the component type recommendation method can be run on terminal device 101 or server 102.

[0036] When the component type recommendation method runs on server 102, server 102 is used to provide component type recommendation services to users of terminal device 101.

[0037] Server 102 determines the component data of the target product, and constructs a component parameter profile based on the component data. Server 102 generates a candidate system pool based on the component parameter profile, and server 102 performs constraint determination on the components in the candidate system pool to obtain constraint determination results. Server 102 performs substitution relationship determination on the constraint determination results to obtain candidate system type groups; Server 102 performs optimization and recommendation on the candidate typology group to obtain the typology recommendation result.

[0038] It should be noted that the above application scenarios are shown only to facilitate understanding of the spirit and principles of this disclosure, and the implementation of this disclosure is not limited in any way. On the contrary, the implementation of this disclosure can be applied to any applicable scenario.

[0039] refer to Figure 2 A method for recommending standardized components, the method comprising the following steps: Step S210: Determine the component data of the target product, and construct a component parameter profile based on the component data.

[0040] In some embodiments, the component data includes: unique component identifier, component category, classification code, component name, manufacturer, manufacturer model, package type, performance parameters, quality grade, price, delivery cycle, equipment used, location of use, quantity used, and historical quality information.

[0041] In practice, a unique component identifier refers to an identifier (such as an internal code or ID) used to uniquely distinguish and trace the component throughout the entire system analysis process.

[0042] In practice, component category refers to the classification attribute used to indicate the type of component, and can be used to distinguish components of different functions or types (such as resistors, capacitors, integrated circuits, etc.).

[0043] In practice, the classification code refers to a field used to represent the classification identifier of components in the enterprise's internal or industry standards, thereby excluding components with inconsistent categories.

[0044] In practice, the component name refers to the field used to record the business name or design name of the component.

[0045] In practice, "manufacturer" refers to the field used to identify products from a specific manufacturer.

[0046] In practice, the manufacturer's model number refers to the model identifier assigned to a product by a specific manufacturer.

[0047] In practice, the packaging form refers to the attribute field used to record the physical packaging, mounting method, or structural form of components.

[0048] In practice, performance parameters refer to data elements used to record the functional and performance indicators of components, covering specific technical indicators such as accuracy, power margin, frequency range, bandwidth, lifespan, and reliability level.

[0049] In practice, the quality grade refers to the data element used to determine technical compliance, which records the quality grade information of components.

[0050] In practice, price refers to the data element used to record the procurement cost or unit price of components.

[0051] In practice, the supply cycle refers to the data element used to record the time required from placing a purchase order to delivery of components.

[0052] In practice, the term "equipment" refers to the data element used to record which devices or products the component is applied to.

[0053] In practice, the "use location" refers to the data element used to record the specific location or assembly part of the component in the product or equipment.

[0054] In practice, the quantity used refers to the data element used to record the quantity of the component used in a relevant product, batch, or project.

[0055] In practice, historical quality information refers to data elements used to record the quality performance and reliability of the component during past use.

[0056] In some embodiments, a component parameter profile is constructed based on the component data, including: The component data is cleaned to obtain cleaned component data; The cleaned component data is standardized to obtain standard component data; Based on the standard component data, classification parameter templates are constructed to obtain a classification parameter template library; Based on the classification parameter template library, the performance parameter fields in the standard component data are structured and parsed to obtain the component parameter profile.

[0057] In specific implementation, the component data is cleaned to obtain the cleaned component data in the following way: The basic data of components is cleaned by removing the names, manufacturers, classification codes, packaging forms, quality grades and parameter units to eliminate problems such as synonyms, abbreviations, unit differences, missing fields and inconsistent formats, so as to obtain cleaned component data.

[0058] In practice, the cleaned component data is standardized to obtain standard component data in the following way: After obtaining the cleaned component data, the standardization methods include: normalizing component names and establishing a mapping relationship between standard names and aliases, abbreviations, and English abbreviations; normalizing manufacturers and establishing a unified mapping between manufacturer standard names and historical names, abbreviations, and English names; verifying and correcting classification codes to ensure that component categories are consistent with classification codes; standardizing packaging forms to form a unified packaging form and size expression; standardizing quality grades to form standard fields; and uniformly converting parameter units to ensure that the same parameter is comparable between different records, thereby obtaining standard component data.

[0059] In specific implementation, the classification parameter template library is constructed based on the standard component data in the following way: For different component categories, corresponding classification parameter templates are established. Each template contains a set of standard parameter fields, including data elements such as key functional parameters, packaging structure, electrical performance, quality level, and supply assurance. Parameter attributes are set for each parameter field, including required parameters, recommended parameters, optional parameters, hard constraint parameters, performance constraint parameters, and supply constraint parameters, thus forming a classification parameter template library.

[0060] In specific implementation, the performance parameter fields in the standard component data are structured and parsed based on the classification parameter template library to obtain the component parameter profile in the following way: First, the performance parameter fields are parsed in a structured manner; specifically, this means identifying parameter names, extracting parameter values, converting units, identifying ranges, identifying typical values, identifying minimum values, identifying maximum values, and identifying rated values ​​for text-based, semi-structured, or non-standard performance parameters, and converting each parameter field into a unified standard parameter item. Then, a parameter profile is generated for each component. Based on the parsed standard parameter items, a parameter profile is constructed for each component, and the profile is represented as follows:

[0061] in Indicates the first Parameter profile of each component; Represents a set of basic attributes; Represents a set of performance parameters; Represents a set of quality and standard attributes; This represents a set of supply attributes. The profile is a structured data object containing four dimensions: basic information, performance metrics, quality standards, and supply attributes, used for subsequent statistical analysis.

[0062] Meanwhile, to ensure the quality of parameter data and calculate a parameter integrity score:

[0063] in, Indicates the first Parameter integrity score of each component; Indicates the number of required parameters that have been parsed; This indicates the number of required parameters specified in the classification parameter template.

[0064] When the parameter integrity score is lower than the preset threshold, the component enters the manual review or data completion process (for example, the relevant system can automatically mark and generate a list of missing parameters, which is then assigned to component engineers or data administrators for manual intervention; the engineer first checks the original data source of the component (such as product datasheets, manufacturer specifications, or historical purchase records), verifies the accuracy and logical consistency of the existing parameters, and supplements the missing necessary parameters; for parameters that still cannot be obtained, they are supplemented by communicating with the manufacturer, querying the internal component library, or referring to data of similar components; the supplemented data re-enters the parameter parsing and integrity scoring process). When the parameter integrity score reaches the preset threshold, a component parameter profile is obtained.

[0065] Step S220: Generate a candidate model pool based on the component parameter profile, and perform constraint determination on the components in the candidate model pool to obtain the constraint determination result.

[0066] In specific implementation, the candidate model pool is generated based on the component parameter profile as follows: First, initial grouping is performed based on component category and classification code, excluding components with inconsistent categories or classification relationships. Then, functional family identification is performed based on name semantics and functional attributes, excluding components with incomparable functions. Finally, a candidate pool is generated based on key parameters, grouping components with the same function and comparable key parameters into the same candidate pool, while calculating functional similarity.

[0067] in, Indicates components With components Functional similarity; Indicates the similarity of classification codes; Indicates semantic similarity between names; Indicates the similarity of functional attributes; Indicates the similarity of key parameters; , , , These are the weighting coefficients.

[0068] when When the value exceeds a preset threshold, the components will be grouped into the same candidate type pool.

[0069] In some embodiments, constraint determination is performed on the components in the candidate pool to obtain constraint determination results, including: Hard constraint determination is performed on the components in the candidate pool to obtain the hard constraint determination result; In response to the hard constraint determination result satisfying the preset conditions, the component is subjected to performance constraint determination to obtain a performance constraint score; The supply constraints of the components are determined to obtain a supply assurance score; The constraint determination result is obtained based on the hard constraint determination result, the performance constraint score, and the supply guarantee score.

[0070] In specific implementation, hard constraint determination is performed on the components in the candidate pool, and the hard constraint determination result is obtained in the following way: Hard constraints are constraints that must be fully satisfied, including package, interface, electrical ratings, temperature range, size, pin definitions, and software compatibility, and are determined by a hard constraint decision function. For candidate components Compared to the original components Perform a step-by-step comparison:

[0071] in, Indicates candidate components Compared to the original components The hard constraint determination result.

[0072] when When, candidate components cannot be used as direct substitutes; when At that time, the candidate components enter the manual review process; when When that happens, the performance constraint determination process begins.

[0073] Specifically, when the hard constraint determination result is When a candidate component fails to meet hard constraints with the original component in areas such as packaging, interface, electrical ratings, temperature range, dimensions, pin definitions, or software compatibility (e.g., incomplete parameter information, inconsistent expression, or need for confirmation based on specific application scenarios), the candidate component enters a manual review process: Component engineers or technicians retrieve complete technical documentation (such as datasheets, application notes, or manufacturer specifications) from both components, comparing and confirming each questionable hard constraint parameter. Parameters that can be clearly determined with supplementary information are approved; parameters requiring further verification are marked as pending verification and physical testing or simulation verification is arranged. After review, the hard constraint determination is revised based on the confirmation results. (Not satisfied) or (Satisfying) the conditions, thus obtaining the final hard constraint determination result.

[0074] In specific implementation, in response to the hard constraint determination result satisfying the preset conditions, the component is subjected to performance constraint determination, and the performance constraint score is obtained in the following way: In response to the hard constraint determination result satisfying the preset condition (i.e.) When evaluating components, accuracy, power margin, frequency range, bandwidth, lifespan, and reliability level are used as performance constraint parameters, and each component is evaluated according to the principle that it is allowed to be better than the original component but not to be worse than the original component.

[0075] The criterion for determining whether a parameter is better the larger its value is:

[0076] The criterion for determining whether a parameter is better the smaller its value is:

[0077] The determination condition for range-type parameters is: and

[0078] in, Indicates the original component number Performance parameters, Indicates the candidate component number Performance parameters, and These represent the lower and upper limits of the parameter range, respectively.

[0079] Based on the performance constraint scoring formula:

[0080] in, Indicates the performance constraint score; Indicates the first Performance constraints are satisfied; Indicates the corresponding weight; Indicates the number of performance parameters.

[0081] This is used to quantify the performance substitutability of candidate components.

[0082] In specific implementation, the supply constraint determination of the components is performed, and the supply guarantee score is obtained in the following way: The supply assurance scoring formula uses multiple manufacturers' availability, delivery time, price, quality stability, and lifecycle health as supply constraint dimensions:

[0083] in, Indicates candidate components Supply security score; Indicates multi-source capability score; Indicates the delivery cycle score; Indicates price rating; Indicates the quality stability score; Indicates the life cycle health score; to These are the weighting coefficients.

[0084] A comprehensive quantitative calculation is performed on each dimension to obtain the supply assurance score for the candidate component.

[0085] In specific implementation, the constraint determination result is obtained based on the hard constraint determination result, the performance constraint score, and the supply guarantee score in the following way: The hard constraint determination results (including those obtained through) Not passed or pending review Performance constraint score and supply security score A comprehensive summary is compiled to form a constraint judgment result set for the candidate component. Among them, hard constraints serve as a prerequisite for technical feasibility, performance constraint scores are used to quantify the degree of performance matching, and supply guarantee scores are used to assess supply feasibility. The three together constitute the final judgment basis for whether the candidate component is qualified to be replaced and the level of replacement. This result serves as the input for subsequent determination of the type of replacement relationship.

[0086] Step S230: Perform substitution relationship determination on the constraint determination results to obtain candidate system groups.

[0087] In some embodiments, the constraint determination result is used to determine the substitution relationship to obtain a candidate system group, including: The constraint determination result is used to determine the substitution relationship type. In response to the substitution relationship type being fully equivalent or upwardly compatible, the corresponding components are merged to obtain the candidate system group.

[0088] In specific implementation, the substitution relationship is determined by evaluating the constraint determination result to obtain the substitution relationship type in the following way: The results will include hard constraint determinations. Performance constraint scoring Application adaptability and supply security score Substitute the constraint determination result into the substitution relation determination function:

[0089] in, Indicates components With candidate components The type of substitution relationship; This represents a classification function indicating substitution relationships.

[0090] Substitutional relationships include at least the following types.

[0091] First, complete equivalence. This means that the candidate component is of the same category and function as the original component, all hard constraints are met, key performance parameters meet the requirements, the application scenario is the same, and it can be classified into the same standard specification.

[0092] Second, upward compatibility. This means that the candidate component meets the hard constraints and has one or more performance parameters that are superior to the original component, and can be used as a preferred model or a high-level replacement model.

[0093] Third, conditional substitution. This indicates that the main parameters of the candidate component meet the requirements, but there are missing information, verification requirements, application limitations, or standard compliance issues that need to be confirmed, requiring further engineering verification or manual review.

[0094] Fourth, locally similar but not directly substitutable. This indicates that the candidate component is similar in category or function to the original component, but has hard constraints or key performance requirements that are not met, and therefore is not included in the same standard specification.

[0095] Fifth, non-substitutable. This indicates that the candidate component does not meet the substitution requirements with the original component in terms of function, packaging, interface, pin definition, or key parameters, and therefore cannot be merged.

[0096] In practice, in response to the substitution relationship type being fully equivalent or upwardly compatible, the corresponding components are merged to obtain the candidate system group.

[0097] Components that are fully equivalent, backward compatible, or have been confirmed to meet the conditions for substitution are associated to form a candidate type group.

[0098] Candidate phylogenetic groups can be represented as a graph structure:

[0099] in, Represents the set of component model nodes. This represents the set of edges representing the equivalent substitution relationships between components.

[0100] When two components are completely equivalent or backward compatible, substitute edges are established between the corresponding nodes. Candidate type groups are generated using connected component identification or clustering methods.

[0101] Candidate system groups should include at least the group number, component category, functional family, set of key parameters, number of included models and specifications, number of manufacturers involved, product range covered, type of substitution relationship, models and specifications to be reviewed, restricted models and specifications, and recommended standard specifications.

[0102] Step S240: Optimize and recommend the candidate typology group to obtain the typology recommendation result.

[0103] In some embodiments, the candidate typology group is preferentially recommended to obtain a typology recommendation result, including: The candidate system types are converged in terms of specifications to obtain the internal standard specifications; A comprehensive recommendation score is obtained by comprehensively evaluating the components under the aforementioned internal standard specifications. Based on the comprehensive recommendation score, the components are classified into recommendation levels to obtain the overall recommendation result.

[0104] In specific implementation, the method for sizing the candidate system group to obtain the internal standard specifications is as follows: The common technical characteristics (including key parameters, hard constraints, performance requirements, quality grade requirements, etc.) of all components in the same candidate model group are integrated and refined to form a specification document that describes the standard technical requirements recognized by the enterprise, without being bound to a specific manufacturer model. This specification document adopts a structure of mandatory requirements, recommended requirements, and restrictions, and sets fields such as standard specification code, standard specification name, component category, functional family, scope of application, restrictions, and prohibition conditions, thereby converging the scattered manufacturer models into a unified internal standard specification.

[0105] In practice, the comprehensive evaluation of components under the aforementioned internal standard specifications is conducted to obtain a comprehensive recommendation score, as follows: Calculate the technology matching score for each component Supply security score and cost-effectiveness score Then substitute it into the comprehensive recommendation score formula:

[0106] in, Model number Overall recommendation rating; Indicates the technical matching score; Indicates the supply security score; Indicates the cost-effectiveness score; , , This represents the weighting coefficient.

[0107] In specific implementation, based on the comprehensive recommendation score, the components are classified into recommendation levels to obtain the overall recommendation result in the following manner: Based on the comprehensive recommendation score of each component Based on the results of hard constraint assessment, performance constraint score, and supply guarantee score, qualified manufacturer models under each internal standard specification are divided into four levels: preferred model, alternative model, conditional replacement model, and restricted use model. Among them, the model with the highest comprehensive recommendation score, meeting all hard constraints, having performance no less than the original, strong supply guarantee capability, and better cost economy is determined as the preferred model; the model that meets the replacement requirements technically but has a comprehensive score lower than the preferred model is determined as the alternative model; the model that meets the main parameters but requires supplementary verification or condition confirmation is determined as the conditional replacement model; and the model that can be maintained in the existing stock but is not recommended for new design is determined as the restricted use model. This forms a unified recommendation result that includes the results of each level classification.

[0108] It should be noted that the method of this disclosure embodiment can be executed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method of this disclosure embodiment, and the multiple devices will interact with each other to complete the method described.

[0109] It should be noted that the above description describes some embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0110] Based on the same inventive concept, corresponding to any of the above-described embodiments, this disclosure also provides a component type recommendation device.

[0111] refer to Figure 3 The component standardization recommendation device includes: The parameter profile determination module 310 is configured to determine the component data of the target product and construct a component parameter profile based on the component data. The determination result module 320 is configured to generate a candidate system pool based on the component parameter profile, perform constraint determination on the components in the candidate system pool, and obtain the constraint determination result. The system type group determination module 330 is configured to perform substitution relationship determination on the constraint determination result to obtain candidate system type groups; The recommendation result determination module 340 is configured to make optimal recommendations for the candidate typology group and obtain the typology recommendation result.

[0112] In this exemplary embodiment, the parameter profiling determination module 310 is specifically configured as follows: The process involves identifying the component data of the target product, cleaning the component data to obtain cleaned component data, standardizing the cleaned component data to obtain standard component data, constructing classification parameter templates based on the standard component data to obtain a classification parameter template library, and performing structured parsing of the performance parameter fields in the standard component data based on the classification parameter template library to obtain the component parameter profile. The component data includes: a unique component identifier, component category, classification code, component name, manufacturer, manufacturer model, packaging form, performance parameters, quality grade, price, delivery cycle, equipment used, application location, quantity used, and historical quality information.

[0113] In this exemplary embodiment, the determination result module 320 is specifically configured as follows: A candidate model pool is generated based on the component parameter profile. Hard constraints are applied to the components in the candidate model pool to obtain hard constraint results. In response to the hard constraint results satisfying preset conditions, performance constraints are applied to the components to obtain performance constraint scores. Supply constraints are applied to the components to obtain supply guarantee scores. Based on the hard constraint results, performance constraint scores, and supply guarantee scores, the constraint determination result is obtained.

[0114] In this exemplary embodiment, the system group determination module 330 is specifically configured as follows: The constraint determination result is used to determine the substitution relationship type; in response to the substitution relationship type being completely equivalent or upwardly compatible, the corresponding components are merged to obtain the candidate system group.

[0115] In this exemplary embodiment, the recommendation result determination module 340 is specifically configured as follows: The candidate system types are converged in terms of specifications to obtain internal standard specifications; the components under the internal standard specifications are comprehensively scored to obtain a comprehensive recommendation score; based on the comprehensive recommendation score, the components are classified into recommendation levels to obtain the system type recommendation result.

[0116] For ease of description, the above apparatus is described in terms of its functions, divided into various modules. Of course, in implementing this disclosure, the functions of each module can be implemented in one or more software and / or hardware.

[0117] The apparatus described above is used to implement the corresponding component type recommendation method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0118] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the component type recommendation method described in any of the above embodiments.

[0119] Figure 4 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0120] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0121] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0122] The input / output interface 1030 is used to connect input / output modules to realize information input and output. The input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0123] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0124] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0125] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0126] The electronic devices described above are used to implement the corresponding component type recommendation method in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0127] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the component type recommendation method as described in any of the above embodiments.

[0128] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0129] The aforementioned non-transitory computer-readable storage media can be any available medium or data storage device that a computer can access, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MOs), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0130] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the component type recommendation method as described in any of the embodiments in the exemplary method section above, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0131] Based on the same inventive concept, corresponding to the component type recommendation method described in any of the above embodiments, this disclosure also provides a computer program product, which includes computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer to cause the computer and / or the processor to perform the component type recommendation method. Corresponding to the execution entity for each step in each embodiment of the component type recommendation method, the processor executing the corresponding step can belong to the corresponding execution entity.

[0132] The computer program products of the above embodiments are used to cause the computer and / or the processor to execute the component type recommendation method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0133] Those skilled in the art will recognize that embodiments of this disclosure can be implemented as a system, method, or computer program product. Therefore, this disclosure can be implemented as entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, this disclosure can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0134] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example,, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (not exhaustive) of a computer-readable storage medium may include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0135] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0136] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0137] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0138] It should be understood that each block of a flowchart and / or block diagram, as well as combinations of blocks in a flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine that, when executed by a computer or other programmable data processing device, creates means for implementing the functions / operations specified in the blocks of the flowchart and / or block diagram.

[0139] These computer program instructions may also be stored in a computer-readable medium that enables a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce a product comprising an instruction apparatus that implements the functions / operations specified in the boxes of a flowchart and / or block diagram.

[0140] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, such that the instructions that execute on the computer or other programmable apparatus can provide a process for implementing the functions / operations specified in the boxes of a flowchart and / or block diagram.

[0141] Furthermore, although the operations of the methods of this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowcharts may be executed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0143] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0144] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application (including the claims) is limited to these examples; within the framework of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in the details for the sake of brevity.

[0145] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0146] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0147] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

[0148] While the spirit and principles of this disclosure have been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined for benefit; such division is merely for convenience of expression. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. The scope of the appended claims is to be interpreted in the broadest sense, thereby encompassing all such modifications and equivalent structures and functions.

Claims

1. A method for recommending standardized electronic components, characterized in that, include: Determine the component data of the target product, and construct a component parameter profile based on the component data; Based on the component parameter profile, a candidate system pool is generated, and the components in the candidate system pool are constrained to obtain the constraint determination result. The constraint determination results are used to determine the substitution relationship to obtain candidate system types. The candidate typology groups are optimized and recommended to obtain the typology recommendation results.

2. The method according to claim 1, characterized in that, The component data includes: unique component identifier, component category, classification code, component name, manufacturer, manufacturer model, packaging form, performance parameters, quality grade, price, delivery cycle, equipment used, location of use, quantity used, and historical quality information.

3. The method according to claim 1, characterized in that, The process of constructing a component parameter profile based on the component data includes: The component data is cleaned to obtain cleaned component data; The cleaned component data is standardized to obtain standard component data; Based on the standard component data, classification parameter templates are constructed to obtain a classification parameter template library; Based on the classification parameter template library, the performance parameter fields in the standard component data are structured and parsed to obtain the component parameter profile.

4. The method according to claim 1, characterized in that, The constraint determination of the components in the candidate pool to obtain the constraint determination result includes: Hard constraint determination is performed on the components in the candidate pool to obtain the hard constraint determination result; In response to the hard constraint determination result satisfying the preset conditions, the component is subjected to performance constraint determination to obtain a performance constraint score; The supply constraints of the components are determined to obtain a supply assurance score; The constraint determination result is obtained based on the hard constraint determination result, the performance constraint score, and the supply guarantee score.

5. The method according to claim 1, characterized in that, The substitution relationship determination of the constraint determination result to obtain candidate system groups includes: The constraint determination result is used to determine the substitution relationship type. In response to the substitution relationship type being fully equivalent or upwardly compatible, the corresponding components are merged to obtain the candidate system group.

6. The method according to claim 1, characterized in that, The process of optimizing and recommending the candidate phenotypic groups to obtain phenotypic recommendation results includes: The candidate system types are converged in terms of specifications to obtain the internal standard specifications; A comprehensive recommendation score is obtained by comprehensively evaluating the components under the aforementioned internal standard specifications. Based on the comprehensive recommendation score, the components are classified into recommendation levels to obtain the overall recommendation result.

7. A component standardization recommendation device, characterized in that, include: The parameter profile determination module is configured to determine the component data of the target product and construct a component parameter profile based on the component data. The determination result module is configured to generate a candidate system pool based on the component parameter profile, perform constraint determination on the components in the candidate system pool, and obtain the constraint determination result. The system type group determination module is configured to perform substitution relationship determination on the constraint determination result to obtain candidate system type groups; The recommendation result determination module is configured to make optimal recommendations for the candidate typology group and obtain the typology recommendation result.

8. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing the computer to perform the method of any one of claims 1 to 6.

10. A computer program product, characterized in that, It includes computer program instructions that, when run on a computer, cause the computer to perform the method as described in any one of claims 1 to 6.

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