Process quality evaluation method in field of automotive electronic development

Abstract

The invention discloses a process quality assessment method in the field of automotive electronic development, and particularly relates to the technical field of quality assessment, and the method comprises the steps: generating an assessment report of an automotive electronic development process through nesting automotive electronic development authentication system assessment rules, and determining possible risk events and the probability of the risk events. The method comprises the following steps: establishing a risk matrix of an evaluation report, obtaining the state of a Markov chain through standard up-to-standard conditions in the evaluation report, determining a transition probability matrix and a steady-state vector in an automotive electronic development process, monitoring the automotive electronic development process, and determining and evaluating document change behaviors occurring in the automotive electronic development process. Based on the dependency relationship of the changed document and the influence possibly caused after the document is changed, the evaluation report of the automotive electronic development process and the document changing behavior with the large potential risk are early warned, the influence brought by the changed document can be comprehensively analyzed and evaluated, and the potential risk cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of quality assessment, and more specifically, to a process quality assessment method in the field of automotive electronics development. Background Art

[0002] Propose process quality requirements in the areas of systems, hardware and software involved in the field of automotive electronics development to ensure the quality of automotive electronics software and the key links in compliance with industry norms and international standards. Existing technologies such as ASPI CE PAM model, ISO 33001, ISO 33002, ISO 33003, ISO 33004, ISO 33020, ISO 26262 and ISO21434 provide detailed guidance for the automotive electronics software development process;

[0003] However, traditional process document management and evaluation methods mostly rely on offline document records. For online documents, any changes to documents or modules in the development process may trigger a chain reaction, affecting the functionality, security and reliability of the entire system. It is difficult to identify potential risks in real time, quantify the impact of changes on the system, or provide an effective early warning mechanism.

[0004] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a process quality assessment method in the field of automotive electronics development to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A process quality assessment method in the field of automotive electronics development includes the following steps:

[0008] S1: Generate an evaluation report on the automotive electronics development process by nesting the evaluation rules of the automotive electronics development certification system, determine possible risk events and the probability of risk events, build a risk matrix for the evaluation report, and determine the risk information in the automotive electronics development process;

[0009] S2: Obtain the state of the Markov chain by evaluating the compliance status of the specifications in the report, determine the transition probability matrix and steady-state vector in the automotive electronics development process, and determine the evaluation information in the automotive electronics development process;

[0010] S3: Monitor the automotive electronics development process, determine and evaluate the document change behavior that occurs in the automotive electronics development process, and determine the change information and potential risk information of the changed documents based on the dependency relationship of the changed documents and the possible impact of the changed documents;

[0011] S4: Provide early warning based on the evaluation report of the automotive electronics development process and the document change behaviors with greater potential risks.

[0012] In a preferred embodiment, determining risk information in the automotive electronics development process includes:

[0013] The risk information in the automotive electronics development process is expressed through risk assessment coefficients;

[0014] The logic for obtaining the risk hazard assessment coefficient is as follows: extracting specifications with labels that are not fully compliant, determining risk events that may be caused by specifications with labels that are not fully compliant, dividing the negative impacts of possible risk events into different levels, and quantifying scores according to the levels of negative impacts. By evaluating the negative impacts of risk events that may be caused by specifications with labels that are not fully compliant, and based on the principle of equal weight of experts, determining the grading of the negative impacts of risk events by different experts, obtaining the negative impact score of the risk event, and marking the negative impact score of the risk event as: YX nj ,in, k is the number of experts, p1, p2, p3, ..., p K is the classification of the negative impact of risk events by different experts, n = 1, 2, 3, ..., N, n is the number of the specification with the label that is not fully met, j = 1, 2, 3, ..., J, j is the risk event corresponding to the specification with the label that is not fully met, K, N, J are all positive integers;

[0015] According to the risk events that may be caused by the specifications with incomplete compliance labels, the probability of risk events is determined, the probability of risk events is graded, and the risk events are quantified in different probability intervals. Based on the principle of equal weight of experts, different experts are determined to score the probability of risk events, and the probability score of risk events is obtained. The probability score of risk events is marked as: GL nj ,in,

[0016] Based on the negative impact score of risk events and the probability score of risk events as evaluation dimensions, a risk matrix for the evaluation report is constructed and marked as follows: Calculate the risk assessment coefficient of the assessment report using the following formula: Among them, PF fx It is the risk assessment coefficient of the assessment report.

[0017] In a preferred embodiment, determining evaluation information in an automotive electronics development process includes:

[0018] The evaluation information in the automotive electronics development process is expressed by the standard compliance coefficient;

[0019] The logic for obtaining the specification compliance coefficient is as follows: by evaluating the compliance of the specifications in the report, determine the number of automotive electronics development processes that fully comply with the specifications and the number of automotive electronics development processes that do not fully comply with the specifications, and mark the number of automotive electronics development processes that fully comply with the specifications as: SL fh , the number of automotive electronics development processes that do not fully meet specifications is marked as: SL bf ;

[0020] Determine the state of the Markov chain, determine the transition probabilities of fully complying with the specification, not fully complying with the specification, and not complying with the specification in the automotive electronics development process through historical data and Monte Carlo simulation methods, construct the transition probability matrix in the automotive electronics development process, and mark the transition probability matrix in the automotive electronics development process as: H, where GL ata is the probability of fully compliant specifications to fully compliant specifications, GL ath is the probability of fully meeting the specification to not fully meeting the specification, GL atn is the probability of fully meeting the specification to not meeting the specification, GL hta is the probability of a product that does not fully meet the specification to fully meet the specification, GL hth is the probability of not fully meeting the specification to not fully meeting the specification, GL htn is the probability of not fully meeting the specification to not meeting the specification, GL nta is the probability of going from non-compliant to fully compliant, GL nth is the probability of not meeting the specification to not fully meeting the specification, GL ntn is the probability of going from non-conforming specifications to non-conforming specifications;

[0021] The steady-state vector of the automotive electronics development process is marked as: π, π = (π1, π2, π3), π1 is the probability that the automotive electronics development process is in a completely compliant state at steady state, π2 is the probability that the automotive electronics development process is in an incompletely compliant state at steady state, and π3 is the probability that the automotive electronics development process is in a non-compliant state at steady state. The steady-state vector of the automotive electronics development process is solved by the formula: π = πH, and the constraint condition is: π1 + π2 + π3 = 1;

[0022] Calculate the standard compliance coefficient, the calculation formula is: Among them, DB gfIt is the coefficient of compliance with the standard.

[0023] In a preferred embodiment, determining the change information of the modified document includes:

[0024] The change information of the changed document is represented by the propagation impact change coefficient;

[0025] The acquisition logic of the propagation influence variation coefficient is as follows: construct a document dependency graph, wherein each node in the document dependency graph represents a document, and an edge represents a dependency relationship of the document, and the dependency relationship is represented by a directed edge, wherein the direction of the arrow represents the dependency direction;

[0026] The coefficient of change of the propagation impact of the changed document is determined by using the propagation probability formula, which is calculated as: Among them, YX is the coefficient of change of the propagation impact after the document is changed, δ is the influence weight of the changed document a, YX(b) is the influence weight of document b that depends on the changed document a, and SL(b) is the number of dependencies on document b.

[0027] In a preferred embodiment, determining the potential risk information of modifying a document includes:

[0028] The logic for obtaining the risk coefficient of the impact of the changed document is as follows: according to the dependency graph of the document, determine the nodes that depend on the changed document, based on the compliance of the nodes that depend on the changed document, and in combination with the risk events that occurred in the historical data of the nodes that depend on the changed document and the impact of the risk events, score the nodes that depend on the changed document through the expert equal weight principle to determine the impact scores of nodes at different levels;

[0029] A regression model is constructed based on the number ratio of nodes at different levels in the automotive electronics development process and the impact scores of nodes at different levels to determine the coefficient of hidden dangers affected by changing documents. The calculation formula for the coefficient of hidden dangers affected by changing documents is:

[0030]

[0031] Among them, YH gg To change the document impact risk coefficient, FZ1, FZ2, FZ3, ..., FZ M Score the influence of nodes at different levels, ZB1, ZB2, ZB3, ..., ZB M is the number ratio of nodes at different levels, m = 1, 2, 3, ..., M, M is a positive integer, m is the number of nodes at different levels, and e is a natural number;

[0032] The calculation formula for the proportion of nodes at different levels is: Among them, ZB mis the proportion of nodes at different levels, S m is the number of nodes at different levels, and W is the total number of nodes at different levels.

[0033] In a preferred embodiment, the evaluation report of the automotive electronics development process provides an early warning, including:

[0034] Through comprehensive analysis of the risk information and assessment information of the automotive electronics development process, the risk potential assessment coefficient and the standard compliance coefficient are weighted and calculated to build a process assessment model and generate a process assessment coefficient. The calculation formula of the process assessment coefficient is: Among them, pg lc is the process evaluation coefficient, α1 and α2 are the proportional coefficients of the risk hazard evaluation coefficient and the standard compliance coefficient, respectively, and α1 and α2 are both greater than 0;

[0035] Set a process evaluation coefficient threshold, compare the process evaluation coefficient of the current automotive electronics development process with the process evaluation coefficient threshold, and generate a first warning signal when there are activities or projects that do not meet the specifications in the evaluation report of the automotive electronics development process. If the process evaluation coefficient is greater than the process evaluation coefficient threshold, a second warning signal is generated; if the process evaluation coefficient is less than the process evaluation coefficient threshold, no signal is generated.

[0036] In a preferred embodiment, an early warning is provided for document modification behaviors with greater potential risks, including:

[0037] Comprehensively analyze the change information and potential danger information of the changed document, perform weighted calculation on the coefficient of change in propagation impact and the coefficient of potential danger in the changed document, build a change assessment model, and generate the change assessment coefficient. The calculation formula of the change assessment coefficient is: Among them, pg gg is the change assessment coefficient, γ1 and γ2 are the proportional coefficients of the transmission impact change coefficient and the change document impact hidden danger coefficient, respectively, and γ1 and γ2 are both greater than 0;

[0038] By identifying the changed document, determining the change evaluation coefficient and process evaluation coefficient after the changed document, setting the change evaluation coefficient threshold, if the change evaluation coefficient is greater than the change evaluation coefficient threshold and the process evaluation coefficient is less than the process evaluation coefficient threshold, then generating a third warning signal, if the change evaluation coefficient is less than the change evaluation coefficient threshold and the process evaluation coefficient is less than the process evaluation coefficient threshold, then no signal is generated.

[0039] Technical effects and advantages of the present invention:

[0040] The present invention generates an evaluation report by nesting the evaluation rules of the automotive electronics development certification system, determines the compliance status of the specifications in the evaluation report, constructs a risk matrix of the evaluation report based on the compliance status of the specifications in the evaluation report, and determines the specific performance of the evaluation report through a Markov chain. The present invention can determine the possible risks in the automotive electronics development process in real time, and by constructing a dependency graph of documents and determining the documents changed by users in the automotive electronics development process, determining the dependency of the changed documents, and determining the impact of the changed documents on the nodes that depend on the changed documents. The present invention helps to identify potential risks in the automotive electronics development process more comprehensively and in real time, and helps to comprehensively analyze and evaluate the impact of changing documents, thereby reducing potential risk costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0042] Figure 1 The present invention is a flowchart of a process quality assessment method in the field of automotive electronics development. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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 creative work are within the scope of protection of the present invention.

[0044] Example 1

[0045] Figure 1 The flowchart of a process quality assessment method in the field of automotive electronics development of the present invention specifically includes the following steps:

[0046] S1: Generate an evaluation report on the automotive electronics development process by nesting the evaluation rules of the automotive electronics development certification system, determine possible risk events and the probability of risk events, build a risk matrix for the evaluation report, and determine the risk information in the automotive electronics development process;

[0047] S2: Obtain the state of the Markov chain by evaluating the compliance status of the specifications in the report, determine the transition probability matrix and steady-state vector in the automotive electronics development process, and determine the evaluation information in the automotive electronics development process;

[0048] S3: Monitor the automotive electronics development process, determine and evaluate the document change behavior that occurs in the automotive electronics development process, and determine the change information and potential risk information of the changed documents based on the dependency relationship of the changed documents and the possible impact of the changed documents;

[0049] S4: Provide early warning based on the evaluation report of the automotive electronics development process and the document change behaviors with greater potential risks.

[0050] The automotive electronics development certification system assessment rules are embedded in the process quality assessment in the automotive electronics development field to ensure that the activities in the automotive electronics development field meet the automotive electronics development certification system assessment rules, ensure that the quality of automotive electronics software meets the key links of industry specifications and international standards, and meet personalized quality specifications.

[0051] It should be noted that standards such as the ASPI CE PAM model, ISO 33001, ISO 33002, ISO 33003, ISO 33004, ISO 33020, ISO 26262 and ISO 21434 provide detailed guidance for the automotive electronics software development process.

[0052] Among them, personalized quality specifications include allowing customization or modification of evaluation rules according to the requirements of specific projects, setting different weights for different evaluation items for different quality requirements, and generating evaluation reports based on standard specifications and personalized quality specifications through automated evaluation, thereby improving the flexibility, accuracy and efficiency of quality management in the automotive electronics development process.

[0053] It should be noted that the certification requirements of the standard specifications are embedded in the tool to realize the online evaluation process. By adding personalized quality specifications, synchronously recording the evaluation results and automatically generating evaluation reports, the manual filling workload and time cost of making forms of the evaluation team are greatly reduced.

[0054] The evaluation report can display standard specifications and personalized quality specifications and the compliance status of the specifications in a structured manner, quantify the compliance status of the specifications, determine the risk information and evaluation information in the automotive electronics development process based on the evaluation report, represent the risk information in the automotive electronics development process through a risk hazard assessment coefficient, and represent the evaluation information in the automotive electronics development process through a specification compliance degree coefficient.

[0055] By evaluating the compliance of specifications in the report, the specifications with the label of not fully compliant are identified, and the possible risk events and the probability of risk events occurring for specifications with the label of not fully compliant are obtained. Based on the negative impact of risk events and the probability of risk events occurring, a risk matrix for the evaluation report is constructed.

[0056] It should be noted that the evaluation report divides the compliance of each specification into non-compliance, incomplete compliance and complete compliance. Among them, incomplete compliance indicates the completion rate of the specification, which is determined by the synchronous update of the automotive electronics development process by the staff. Non-compliance means that the automotive electronics development process does not meet the specifications and needs to be rectified in time.

[0057] Possible risk events are determined based on specifications with non-full compliance labels. If some specifications are not fully compliant, it means there are potential risks. Each specification that is not fully compliant may trigger different types of risks. The risk events corresponding to each specification that is not fully compliant and the probability of risk events are determined. The negative impact of risk events and the probability of risk events are determined through historical data of the automotive electronics development process.

[0058] Extract the specifications with incompletely compliant labels, determine the risk events that may be caused by the specifications with incompletely compliant labels, and classify the negative impacts of the possible risk events into different levels, usually divided into: ignore, minor, medium, serious, and malignant. Quantify the scores according to the level of negative impact, that is, assign the level of negative impact. Usually, the impact levels are graded from 1 to 5 from small to large according to the size of the impact level. By evaluating the negative impact of risk events that may be caused by the specifications with incompletely compliant labels, based on the principle of equal weight of experts, determine the classification of the negative impact of risk events by different experts, obtain the negative impact score of the risk event, and mark the negative impact score of the risk event as: YX nj ,in, k is the number of experts, p1, p2, p3, ..., p K is the classification of the negative impact of risk events by different experts, n = 1, 2, 3, ..., N, n is the number of the specification with the label that is not fully met, j = 1, 2, 3, ..., J, j is the risk event corresponding to the specification with the label that is not fully met, K, N, J are all positive integers;

[0059] According to the risk events that may be caused by the specifications with incomplete labels, the probability of risk events is determined, and the probability of risk events is graded, usually divided into: (0, 10%], (10%, 25%], (25, 50%], (50%, 75%], (90%, 100%], according to the risk events in different probability intervals, quantitative scores are given, that is, risk events are assigned values ​​in different probability intervals, usually according to the size of the probability, from small to large, the probability intervals are graded and assigned from 1 to 5, based on the principle of equal weight of experts, determine the scores of different experts on the probability of risk events, obtain the probability score of risk events, and mark the probability score of risk events as: GL nj ,in,

[0060] Based on the negative impact score of risk events and the probability score of risk events as evaluation dimensions, a risk matrix for the evaluation report is constructed and marked as follows: Calculate the risk assessment coefficient of the assessment report using the following formula: Among them, PF fx It is the risk assessment coefficient of the assessment report.

[0061] It can be seen from the formula that the larger the risk assessment coefficient is, the higher the risk is in the current automotive electronics development process. It may be necessary to mark the current automotive electronics development process, regularly review the specifications with incomplete compliance labels, ensure that the specifications that are not fully compliant in the automotive electronics development process are rectified to be fully compliant, and conduct manual quality review on the specifications with incomplete compliance labels.

[0062] The logic for obtaining the specification compliance coefficient is as follows: by evaluating the compliance of the specifications in the report, determine the number of automotive electronics development processes that fully comply with the specifications and the number of automotive electronics development processes that do not fully comply with the specifications, and mark the number of automotive electronics development processes that fully comply with the specifications as: SL fh , the number of automotive electronics development processes that do not fully meet specifications is marked as: SL bf ;

[0063] Determine the state of the Markov chain, determine the transition probabilities of fully complying with the specification, not fully complying with the specification, and not complying with the specification in the automotive electronics development process through historical data and Monte Carlo simulation methods, construct the transition probability matrix in the automotive electronics development process, and mark the transition probability matrix in the automotive electronics development process as: H, where GL ata is the probability of fully compliant specifications to fully compliant specifications, GL ath is the probability of fully meeting the specification to not fully meeting the specification, GL atn is the probability of fully meeting the specification to not meeting the specification, GL hta is the probability of a product that does not fully meet the specification to fully meet the specification, GL hth is the probability of not fully meeting the specification to not fully meeting the specification, GL htn is the probability of not fully meeting the specification to not meeting the specification, GL nta is the probability of going from non-compliant to fully compliant, GL nth is the probability of not meeting the specification to not fully meeting the specification, GL ntn is the probability of going from non-conforming specifications to non-conforming specifications;

[0064] It should be noted that the states of the Markov chain are full compliance, incomplete compliance and non-compliance. By using the Markov chain model, it is possible to analyze the transition probabilities between different states in the automotive electronics development process, and further calculate the long-term stable state distribution and potential risks.

[0065] The steady-state vector of the automotive electronics development process is marked as: π, π = (π1, π2, π3), π1 is the probability that the automotive electronics development process is in a completely compliant state at steady state, π2 is the probability that the automotive electronics development process is in an incompletely compliant state at steady state, and π3 is the probability that the automotive electronics development process is in a non-compliant state at steady state. The steady-state vector of the automotive electronics development process is solved by the formula: π = πH, and the constraint condition is: π1 + π2 + π3 = 1;

[0066] Calculate the standard compliance coefficient, the calculation formula is: Among them, DB gf It is the coefficient of compliance with the standard.

[0067] It can be seen from the formula that the greater the coefficient of compliance with standards, the greater the risk in the current automotive electronics development process, and the need to improve the enforcement of various standards and reduce the probability of non-compliance with standards.

[0068] Through comprehensive analysis of the risk information and assessment information of the automotive electronics development process, the risk potential assessment coefficient and the standard compliance coefficient are weighted and calculated to build a process assessment model and generate a process assessment coefficient. The calculation formula of the process assessment coefficient is: Among them, pg lc is the process assessment coefficient, α1 and α2 are the proportional coefficients of the risk hazard assessment coefficient and the standard compliance coefficient, respectively, and α1 and α2 are both greater than 0.

[0069] Set a process evaluation coefficient threshold, and compare the process evaluation coefficient of the current automotive electronics development process with the process evaluation coefficient threshold. When there are activities or projects that do not meet the specifications in the evaluation report of the automotive electronics development process, a first warning signal is generated to stop automotive electronics development and require staff to deal with the activities or projects that do not meet the specifications in a timely manner. If the process evaluation coefficient is greater than the process evaluation coefficient threshold, a second warning signal is generated to require staff to regularly monitor the actual process of automotive electronics development to avoid unexpected risks. If the process evaluation coefficient is less than the process evaluation coefficient threshold, no signal is generated.

[0070] Example 2

[0071] This embodiment is based on the monitoring of the automotive electronics development process in Embodiment 1, determines the document change behavior that occurs in the automotive electronics development process for evaluation, determines the potential risks caused by the document change behavior based on the dependency of the changed documents, and issues early warnings for change behaviors with greater potential risks.

[0072] Users can set the input and output documents of each document through the web application interface. The built-in graphics rendering module automatically generates a visual dependency graph based on the input and output document relationships defined by the user, ensuring the automation and visualization of the document dependency and organizational structure design of the automotive electronics development process.

[0073] The dependency diagram is used to clearly express the interdependencies between different documents and the role of each document in the automotive electronics development process, helping to identify the impact that changes to a document may have on other documents, and thus quantify potential risks. The advantages are:

[0074] The dependency diagram can graphically display the connections and dependencies between documents, helping developers quickly understand the role and importance of each document in the entire process.

[0075] When a document changes, the dependency graph can quickly identify which documents are affected, ensuring that the team can respond to changes in a timely manner. The changes and impacts of each document in the development process can be traced, thereby improving the transparency of process management and facilitating review and audit.

[0076] By quantifying the probability and impact of transmission between documents, it is possible to identify which document changes will cause greater risks;

[0077] By clarifying the input and output relationships between documents, repeated modifications or redundant work caused by unclear document dependencies can be avoided;

[0078] When documents change frequently, dependency diagrams can help assess the risk of the changes and decide whether other related documents need to be adjusted immediately.

[0079] Determine the document changed by the user, and based on the dependency of the changed document and the possible impact after the change, determine the change information and potential risk information of the changed document. The change information of the changed document is represented by the propagation impact change coefficient, and the potential risk information of the changed document is represented by the change document impact potential risk coefficient.

[0080] The acquisition logic of the propagation influence variation coefficient is as follows: construct a document dependency graph, wherein each node in the document dependency graph represents a document, and an edge represents a dependency relationship of the document, and the dependency relationship is represented by a directed edge, wherein the direction of the arrow represents the dependency direction;

[0081] The coefficient of change of the propagation impact of the changed document is determined by using the propagation probability formula, which is calculated as: Among them, YX is the coefficient of change of the propagation impact after the document is changed, δ is the influence weight of the changed document a, YX(b) is the influence weight of document b that depends on the changed document a, and SL(b) is the number of dependencies on document b.

[0082] It can be seen from the formula that the larger the coefficient of variation of the propagation impact, the greater the impact of the changed document on each document in the automotive electronics development process, indicating that the changed document has a wider or more far-reaching impact on other documents.

[0083] The logic for obtaining the risk coefficient of the impact of the changed document is as follows: according to the dependency graph of the document, determine the nodes that depend on the changed document, based on the compliance of the nodes that depend on the changed document, and in combination with the risk events that occurred in the historical data of the nodes that depend on the changed document and the impact of the risk events, score the nodes that depend on the changed document through the expert equal weight principle to determine the impact scores of nodes at different levels;

[0084] It should be noted that nodes at different levels are determined based on the dependencies and relative positions between documents. The changed document is taken as the root node, and the nodes in the dependency graph that depend on the root node are taken as intermediate nodes or leaf nodes. The intermediate nodes represent documents in the middle position. The closer to the root node, the lower the level. The leaf nodes are the terminal nodes of the dependency graph.

[0085] A regression model is constructed based on the number ratio of nodes at different levels in the automotive electronics development process and the impact scores of nodes at different levels to determine the coefficient of hidden dangers affected by changing documents. The calculation formula for the coefficient of hidden dangers affected by changing documents is:

[0086]

[0087] Among them, YH gg To change the document impact risk coefficient, FZ1, FZ2, FZ3, ..., FZ M Score the influence of nodes at different levels, ZB1, ZB2, ZB3, ..., ZB M is the number ratio of nodes at different levels, m = 1, 2, 3, ..., M, M is a positive integer, m is the number of nodes at different levels, and e is a natural number;

[0088] The calculation formula for the proportion of nodes at different levels is: Among them, ZB m is the proportion of nodes at different levels, S m is the number of nodes at different levels, and W is the total number of nodes at different levels.

[0089] It can be seen from the formula that the greater the risk coefficient of document change, the more nodes are affected after the document change, which means that the risk to automotive electronics development may be greater.

[0090] Comprehensively analyze the change information and potential danger information of the changed document, perform weighted calculation on the coefficient of change in propagation impact and the coefficient of potential danger in the changed document, build a change assessment model, and generate the change assessment coefficient. The calculation formula of the change assessment coefficient is: Among them, pg gg is the change assessment coefficient, γ1 and γ2 are the proportional coefficients of the transmission impact change coefficient and the change document impact hidden danger coefficient, respectively, and γ1 and γ2 are both greater than 0.

[0091] By identifying the changed document, determining the change assessment coefficient and process assessment coefficient after the changed document, and setting the change assessment coefficient threshold, if the change assessment coefficient is greater than the change assessment coefficient threshold and the process assessment coefficient is less than the process assessment coefficient threshold, then a third warning signal is generated, indicating that there may be major changes in the automotive electronics development process, and notifying the staff to promptly check the documents that depend on the changed document; if the change assessment coefficient is less than the change assessment coefficient threshold and the process assessment coefficient is less than the process assessment coefficient threshold, then no signal is generated.

[0092] The present invention generates an evaluation report by nesting the evaluation rules of the automotive electronics development certification system, determines the compliance status of the specifications in the evaluation report, constructs a risk matrix of the evaluation report based on the compliance status of the specifications in the evaluation report, and determines the specific performance of the evaluation report through a Markov chain. The present invention can determine the possible risks in the automotive electronics development process in real time, and by constructing a dependency graph of documents and determining the documents changed by users in the automotive electronics development process, determining the dependency of the changed documents, and determining the impact of the changed documents on the nodes that depend on the changed documents. The present invention helps to identify potential risks in the automotive electronics development process more comprehensively and in real time, and helps to comprehensively analyze and evaluate the impact of changing documents, thereby reducing potential risk costs.

[0093] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0094] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0095] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0096] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0097] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0098] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0099] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0100] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A process quality assessment method in the field of automotive electronics development, characterized in that: The specific steps include: S1: Generate an evaluation report on the automotive electronics development process by nesting the evaluation rules of the automotive electronics development certification system, determine possible risk events and the probability of risk events, build a risk matrix for the evaluation report, and determine the risk information in the automotive electronics development process; S2: Obtain the state of the Markov chain by evaluating the compliance status of the specifications in the report, determine the transition probability matrix and steady-state vector in the automotive electronics development process, and determine the evaluation information in the automotive electronics development process; S3: Monitor the automotive electronics development process, determine and evaluate the document change behavior that occurs in the automotive electronics development process, and determine the change information and potential risk information of the changed documents based on the dependency relationship of the changed documents and the possible impact of the changed documents; S4: Provide early warning based on the evaluation report of the automotive electronics development process and the document change behaviors with greater potential risks.

2. A process quality assessment method in the field of automotive electronics development according to claim 1, characterized in that: Identify risk information in the automotive electronics development process, including: The risk information in the automotive electronics development process is expressed through risk assessment coefficients; The logic for obtaining the risk hazard assessment coefficient is as follows: extracting specifications with labels that are not fully compliant, determining risk events that may be caused by specifications with labels that are not fully compliant, dividing the negative impacts of possible risk events into different levels, and quantifying scores according to the levels of negative impacts. By evaluating the negative impacts of risk events that may be caused by specifications with labels that are not fully compliant, and based on the principle of equal weight of experts, determining the grading of the negative impacts of risk events by different experts, obtaining the negative impact score of the risk event, and marking the negative impact score of the risk event as: YX nj ,in, k is the number of experts, p1, p2, p3, ..., p K is the classification of the negative impact of risk events by different experts, n = 1, 2, 3, ..., N, n is the number of the specification with the label that is not fully met, j = 1, 2, 3, ..., J, j is the risk event corresponding to the specification with the label that is not fully met, K, N, J are all positive integers; According to the risk events that may be caused by the specifications with incomplete compliance labels, the probability of risk events is determined, the probability of risk events is graded, and the risk events are quantified in different probability intervals. Based on the principle of equal weight of experts, different experts are determined to score the probability of risk events, and the probability score of risk events is obtained. The probability score of risk events is marked as: GL nj ,in, Based on the negative impact score of risk events and the probability score of risk events as evaluation dimensions, a risk matrix for the evaluation report is constructed and marked as follows: Calculate the risk assessment coefficient of the assessment report using the following formula: Among them, PF fx It is the risk assessment coefficient of the assessment report.

3. A process quality assessment method in the field of automotive electronics development according to claim 2, characterized in that: Identify evaluation information in the automotive electronics development process, including: The evaluation information in the automotive electronics development process is expressed by the standard compliance coefficient; The logic for obtaining the specification compliance coefficient is as follows: by evaluating the compliance of the specifications in the report, determine the number of automotive electronics development processes that fully comply with the specifications and the number of automotive electronics development processes that do not fully comply with the specifications, and mark the number of automotive electronics development processes that fully comply with the specifications as: SL fh , the number of automotive electronics development processes that do not fully meet specifications is marked as: SL bf ; Determine the state of the Markov chain, determine the transition probabilities of fully complying with the specification, not fully complying with the specification, and not complying with the specification in the automotive electronics development process through historical data and Monte Carlo simulation methods, construct the transition probability matrix in the automotive electronics development process, and mark the transition probability matrix in the automotive electronics development process as: H, where GL ata is the probability of fully compliant specifications to fully compliant specifications, GL ath is the probability of fully meeting the specification to not fully meeting the specification, GL atn is the probability of fully meeting the specification to not meeting the specification, GL hta is the probability of a product that does not fully meet the specification to fully meet the specification, GL hth is the probability of not fully meeting the specification to not fully meeting the specification, GL htn is the probability of not fully meeting the specification to not meeting the specification, GL nta is the probability of going from non-compliant to fully compliant, GL nth is the probability of not meeting the specification to not fully meeting the specification, GL ntn is the probability of going from non-conforming specifications to non-conforming specifications; The steady-state vector of the automotive electronics development process is marked as: π, π = (π1, π2, π3), π1 is the probability that the automotive electronics development process is in a completely compliant state at steady state, π2 is the probability that the automotive electronics development process is in an incompletely compliant state at steady state, and π3 is the probability that the automotive electronics development process is in a non-compliant state at steady state. The steady-state vector of the automotive electronics development process is solved by the formula: π = πH, and the constraint condition is: π1 + π2 + π3 = 1; Calculate the standard compliance coefficient, the calculation formula is: Among them, DB gf It is the coefficient of compliance with the standard.

4. A process quality assessment method in the field of automotive electronics development according to claim 3, characterized in that: Determine the change information of the modified document, including: The change information of the changed document is represented by the propagation impact change coefficient; The acquisition logic of the propagation influence variation coefficient is as follows: construct a document dependency graph, wherein each node in the document dependency graph represents a document, and an edge represents a dependency relationship of the document, and the dependency relationship is represented by a directed edge, wherein the direction of the arrow represents the dependency direction; The coefficient of change of the propagation impact of the changed document is determined by using the propagation probability formula, which is calculated as: Among them, YX is the coefficient of change of the propagation impact after the document is changed, δ is the influence weight of the changed document a, YX(b) is the influence weight of document b that depends on the changed document a, and SL(b) is the number of dependencies on document b.

5. A process quality assessment method in the field of automotive electronics development according to claim 4, characterized in that: Identify potential risks of changing documents, including: The logic for obtaining the risk coefficient of the impact of the changed document is as follows: according to the dependency graph of the document, determine the nodes that depend on the changed document, based on the compliance of the nodes that depend on the changed document, and in combination with the risk events that occurred in the historical data of the nodes that depend on the changed document and the impact of the risk events, score the nodes that depend on the changed document through the expert equal weight principle to determine the impact scores of nodes at different levels; A regression model is constructed based on the number ratio of nodes at different levels in the automotive electronics development process and the impact scores of nodes at different levels to determine the coefficient of hidden dangers affected by changing documents. The calculation formula for the coefficient of hidden dangers affected by changing documents is: Among them, YH gg To change the document impact risk coefficient, FZ1, FZ2, FZ3, ..., FZ M Score the influence of nodes at different levels, ZB1, ZB2, ZB3, ..., ZB M is the number ratio of nodes at different levels, m = 1, 2, 3, ..., M, M is a positive integer, m is the number of nodes at different levels, and e is a natural number; The calculation formula for the proportion of nodes at different levels is: Among them, ZB m is the proportion of nodes at different levels, S m is the number of nodes at different levels, and W is the total number of nodes at different levels.

6. A process quality assessment method in the field of automotive electronics development according to claim 5, characterized in that: The evaluation report of the automotive electronics development process provides early warning, including: Through comprehensive analysis of the risk information and assessment information of the automotive electronics development process, the risk potential assessment coefficient and the standard compliance coefficient are weighted and calculated to build a process assessment model and generate a process assessment coefficient. The calculation formula of the process assessment coefficient is: Among them, pg lc is the process evaluation coefficient, α1 and α2 are the proportional coefficients of the risk hazard evaluation coefficient and the standard compliance coefficient, respectively, and α1 and α2 are both greater than 0; Set a process evaluation coefficient threshold, compare the process evaluation coefficient of the current automotive electronics development process with the process evaluation coefficient threshold, and generate a first warning signal when there are activities or projects that do not meet the specifications in the evaluation report of the automotive electronics development process. If the process evaluation coefficient is greater than the process evaluation coefficient threshold, a second warning signal is generated; if the process evaluation coefficient is less than the process evaluation coefficient threshold, no signal is generated.

7. A process quality assessment method in the field of automotive electronics development according to claim 6, characterized in that , provide early warning for document modification behaviors with greater potential risks, including: Comprehensively analyze the change information and potential danger information of the changed document, perform weighted calculation on the coefficient of change in propagation impact and the coefficient of potential danger in the changed document, build a change assessment model, and generate the change assessment coefficient. The calculation formula of the change assessment coefficient is: Among them, pg gg is the change assessment coefficient, γ1 and γ2 are the proportional coefficients of the transmission impact change coefficient and the change document impact hidden danger coefficient, respectively, and γ1 and γ2 are both greater than 0; By identifying the changed document, determining the change evaluation coefficient and process evaluation coefficient after the changed document, setting the change evaluation coefficient threshold, if the change evaluation coefficient is greater than the change evaluation coefficient threshold and the process evaluation coefficient is less than the process evaluation coefficient threshold, then generating a third warning signal, if the change evaluation coefficient is less than the change evaluation coefficient threshold and the process evaluation coefficient is less than the process evaluation coefficient threshold, then no signal is generated.

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