ISO system authentication service standard auditing system and method

Abstract

The invention discloses an ISO system authentication service standard auditing system and method, and relates to the technical field of information, and the system comprises a document management module, an auditing management module, a supplier relation module, a human resource module, a product development module, a customer relation module, an authentication module and an auditing module. The system optimizes the management process of the ISO system authentication service standard audit document through an automatic tool, and ensures the consistency of document versions and the accurate control of operation authority. Therefore, the document management efficiency is improved, and the security and confidentiality of the document are enhanced. Meanwhile, the examination and approval result is predicted through the machine learning model, the decision accuracy is improved, more reliable data support is provided for a management layer, the ISO system authentication service standard examination and approval process is systematically simplified, manual operation is reduced, the error rate is reduced, and the examination and approval accuracy and reliability are ensured.

Description

Technical Field

[0001] The present invention relates to the field of information technology, and in particular to an ISO system certification service standard review system and method. Background Art

[0002] In modern enterprise management, ISO system certification is an important means to improve the quality management level of enterprises and enhance market competitiveness. The ISO system certification service standard audit system is a key tool to ensure that the enterprise quality management system meets international standards. The ISO system certification service standard audit system usually includes multiple modules such as document management, audit management, supplier relationship management, human resource management, product development, customer relationship management, certification management and audit supervision. These modules rely heavily on manual operations:

[0003] However, the existing system mainly relies on manual operations when processing ISO system-related documents, such as quality manuals, procedure files, work instructions and quality records. This leads to inefficient document query, approval, management, release and archiving operations, and makes it difficult to ensure the consistency of document versions and the control of operating permissions. In addition, in the process of formulating internal audit plans, executing audits, generating reports and subsequent corrective measures, the existing system lacks automated and intelligent support, making the audit process cumbersome and error-prone.

[0004] In order to solve the above problems and improve the efficiency and accuracy of ISO system certification service standard audit, the present invention proposes an ISO system certification service standard audit system which integrates automation and intelligent technology. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides an ISO system certification service standard audit system and method, which solves the problem that the existing ISO system certification service standard audit system mentioned in the background technology mainly relies on manual operation when processing documents and executing the audit process, which leads to low document management efficiency and difficulty in ensuring the consistency of document versions and the control of operation permissions. At the same time, the audit process also becomes cumbersome and prone to errors due to the lack of automation and intelligent support.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: an ISO system certification service standard audit system and method, including a document management module, an audit management module, a supplier relationship module, a human resources module, a product development module, a customer relationship module, a certification module and an audit module; the document management module is responsible for managing all documents related to the ISO system, and the document management module ensures the consistency control of file versions, operation authority control and confidentiality of confidential files through document query, approval, management, release and archiving operations; the audit management module is used for internal audit plan management, audit list management, audit report management, external audit management, corrective and preventive measures, and manages the entire internal audit process, from planning to execution, to report generation and subsequent corrective measures; the supplier relationship module is used to manage supplier information, including Material classification, supplier files, supplier evaluation, supply records and supply statistics; the human resources module is used to maintain and update the organization's structure, ensure clear responsibilities, and the architecture diagram accurately reflects the company's organizational structure, and store employees' personal and professional information, including educational background, work experience, job changes and contract information, as well as collect and analyze human resources data to provide support for decision-making and to improve human resources management; the product development module is used to manage the product development process; the customer relationship module is used to manage customer information; the certification module is used for contract review, audit arrangement, certification assessment, certificate printing and customer service maintenance, and realizes one-click automatic export of commonly used work reports and verifies form data; the audit module is used to conduct supervisory audits during the validity period of the certificate to ensure that the company continues to meet the standard requirements, and conduct re-evaluation (renewal audit) before the certificate expires.

[0007] Preferably, the ISO system-related documents include quality manuals, procedure documents, work instructions, and quality records.

[0008] Preferably, the product development process includes development project establishment, development plan, development input, development change, development review, development verification, development output, test report and development appraisal.

[0009] Preferably, the customer information includes customer files, customer tracking, customer service, customer communication, customer complaints, customer satisfaction and customer contract management.

[0010] Preferably, the steps are as follows:

[0011] S01. Start-up preparation: Identify the internal audit team members through the human resources module and assign system permissions to ensure that they can access the system for audit work. Then initialize the system through the document management module and upload ISO system documents, including quality manuals, procedure documents, work instructions and quality records; S02. Document management and maintenance: Establish a document approval process through the document management module, implement version control, ensure that relevant personnel can be notified in time after the document is updated, maintain the current validity of the document, and enable the supplier relationship module to enter supplier information, evaluate and select suppliers on the basis of document management to ensure that suppliers meet ISO standards and support supply chain quality management; S03. Product development tracking: Use the processes and standards provided by the document management module through the product development module to record key activities in the product development process and ensure that the development process meets ISO system requirements; S04. Customer relationship maintenance: On the basis of ensuring product quality, the customer relationship module manages customer information, including service records and complaint handling, tracks customer satisfaction and ensures service quality; S05. Internal audit plan: The audit management module refers to the procedure documents and work instructions in the document management module to develop an internal audit plan, clarify the audit objectives, scope, methods, schedule and resource allocation; S06. Perform internal audits: The audit management module performs internal audits, including on-site audits, document audits and employee interviews, records audit findings, generates audit reports, and analyzes non-conformities found in the audit through the audit management module, formulates corrective and preventive measures, tracks the implementation effect of the measures, and ensures that the problems are resolved; S07. Management review: Use the data collected by the audit management module to conduct management reviews to evaluate the effectiveness, efficiency and improvement areas of the ISO system, and the certification module prepares certification application documents, including quality manuals, procedure documents and internal audit reports, arranges external audits, and manages the audit process; S08. Certificate management: Manage ISO certification certificates, including printing, issuing, updating and maintaining certificates, use system-automatically generated reports and data analysis to identify improvement opportunities, continuously improve the ISO system, and conduct re-evaluation and update certificates before they expire;

[0012] Preferably, in the S02 document management and maintenance, a workflow automation tool is introduced to reduce manual operations and improve approval efficiency and accuracy. The workflow automation tool predicts the approval result through a machine learning model to improve the accuracy of decision-making. The binary classification problem of predicting the approval result in the learning model is predicted by using a logistic regression algorithm. The prediction formula of the logistic regression model is:

[0013] h(x)=σ(θ T x)

[0014] Among them, h(x): prediction function, which gives the probability of the model predicting the positive class under the input feature x, σ(z): sigmoid function, which is an S-shaped function used to map the linear output to a probability value between 0 and 1. σ(z) is the sigmoid function, defined as:

[0015]

[0016] This function maps the predicted values ​​of linear regression to the interval (0,1) and interprets them as probabilities, θ T x is the dot product of the feature vector x and the weight vector θ, representing the linear part of the model.

[0017] Preferably, when training a logistic regression model, the maximum likelihood estimation is usually used to determine the parameter θ, and its cost function (CostFunction) is:

[0018]

[0019] Among them, J(θ) is the cost function used to measure the performance of the model parameter θ, m is the total number of training samples, i represents the index of a single training sample, and y (i) is the actual label (0 or 1) of the i-th training sample, x (i) is the feature vector of the i-th training sample, h θ (x (i) ) is the model's predicted probability for the i-th training sample, that is, σ(θ T ·x (i) ), θ is the model parameter vector, which contains the weight of each feature, θ T ·x (i) is the feature vector x (i) The dot product of the parameter vector θ represents the linear part of the model, and σ(z) is the sigmoid function, defined as Used to convert linear output into probability values.

[0020] Preferably, in order to improve the prediction accuracy of the model, regularization technology is also used to prevent overfitting. The regularized cost function can be expressed as:

[0021]

[0022] Where J(θ) is the cost function used to measure the performance of the model parameter θ and includes the regularization term, m is the total number of training samples, i is the index of a single training sample used to traverse all training samples, and y is the (i) : The actual label (0 or 1) of the i-th training sample, x (i) : The feature vector of the i-th training sample, h θ (x (i)): The model's predicted probability for the i-th training sample, i.e., σ(θ T ·x (i) ), θ model parameter vector, including the weight of each feature, θ j : The jth weight in the model parameter vector, representing the weight of a specific feature, λ: Regularization parameter, controlling the strength of the regularization term, larger λ values ​​increase the effect of regularization and make the weight value closer to zero; smaller λ values ​​reduce the effect of regularization, n: The number of features.

[0023] Preferably, in S06, robotic process automation (RPA) technology is used to automatically perform repetitive tasks in the internal audit process, including information retrieval, data collection, and document review, thereby improving efficiency and reducing human errors. An artificial intelligence (AI)-driven document management system is used to achieve automatic classification, extraction, tagging, and retrieval of documents, thereby simplifying the document management process and improving accuracy.

[0024] Preferably, in the AI-driven document management system, the automatic classification, extraction, marking and retrieval process of documents is as follows:

[0025] Data preprocessing: including noise reduction and image enhancement to improve the quality of document images, and document segmentation to break down documents into separate pages or regions; Optical Character Recognition (OCR): using image processing technology to identify text areas in documents, further segmenting them into individual characters or words, and extracting features such as shape, structure, grayscale, etc., and finally using pattern recognition algorithms to convert features into text information; Natural Language Processing (NLP): performing text cleaning to remove irrelevant characters and stop words, identifying the part of speech of each word, using NER models to identify entities in text, and applying statistical models or deep learning models to predict the probability distribution of text; Document Representation Learning: converting documents into numerical feature vectors The following are some of the key techniques used in the research: quantity, including bag-of-words model, TF-IDF or Word2Vec, and using deep learning models to learn embedded representations of documents to capture semantic information; document classification: using machine learning algorithms to train document classification models based on feature vectors, and make classification predictions for new documents; information extraction: combining rule-based extraction and machine learning models such as CRF and neural networks to identify and extract key information in documents; document tagging and indexing: adding tags or metadata to entities and key information in documents, and building indexes to speed up retrieval; retrieval and search: parsing user queries, calculating the relevance scores of documents to queries, ranking documents according to the scores, and returning the most relevant results.

[0026] The present invention provides an ISO system certification service standard review system and method. It has the following beneficial effects:

[0027] (1) This is an ISO system certification service standard review system and method. The system optimizes the management process of ISO system certification service standard review documents through automated tools to ensure the consistency of document versions and the precise control of operation permissions. This not only improves the efficiency of document management, but also enhances the security and confidentiality of documents. At the same time, the approval results are predicted through machine learning models, which improves the accuracy of decision-making and provides more reliable data support for management.

[0028] (2) This ISO system certification service standard audit system and method simplifies the ISO system certification service standard audit process, reduces manual operations, reduces the error rate, and ensures the accuracy and reliability of the audit. In addition, the system improves the efficiency of the internal audit process and the accuracy of document retrieval through robotic process automation (RPA) technology and AI-driven document management system. The precision of product development tracking ensures that the development process meets ISO system requirements, while the intelligence of supply chain and customer relationship management improves the quality of supply chain and customer service.

[0029] This solves the problem that the existing ISO system certification service standard audit system mainly relies on manual operations when processing documents and executing audit processes, which leads to inefficient document management and difficulty in ensuring the consistency of document versions and the control of operation permissions. At the same time, the audit process has become cumbersome and prone to errors due to the lack of automation and intelligent support. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of the module of the present invention;

[0031] Figure 2 It is a schematic diagram of the process of the present invention.

[0032] In the figure, 1. Document management module; 2. Audit management module; 3. Supplier relationship module; 4. Human resources module; 5. Product development module; 6. Customer relationship module; 7. Certification module; 8. Audit module. DETAILED DESCRIPTION

[0033] 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.

[0034] See also Figure 1-2, the embodiment of the present invention provides a technical solution: an ISO system certification service standard audit system and method, including a document management module 1, an audit management module 2, a supplier relationship module 3, a human resources module 4, a product development module 5, a customer relationship module 6, a certification module 7 and an audit module 8;

[0035] Document management module 1 is responsible for managing all documents related to the ISO system. Document management module 1 ensures the consistency control of file versions, operation authority control and confidentiality of confidential documents through document query, approval, management, release and archiving operations; Audit management module 2 is used for internal audit plan management, audit list management, audit report management, external audit management, corrective and preventive measures, and manages the entire internal audit process, from planning to execution, to report generation and subsequent corrective measures; Supplier relationship module 3 is used to manage supplier information, including material classification, supplier files, supplier evaluation, supply records and supply statistics; Human resources module 4 is used to maintain and update the organization's structure to ensure The responsibilities are clear, and the architecture diagram accurately reflects the company's organizational structure. It also stores personal and professional information of employees, including educational background, work experience, job changes and contract information, as well as collects and analyzes human resource data to support decision-making and improve human resource management. Product development module 5 is used to manage the product development process. Customer relationship module 6 is used to manage customer information. Certification module 7 is used for contract review, audit arrangement, certification assessment, certificate printing and customer service maintenance, and realizes one-click automatic export of common work reports and verifies table data. Audit module 8 is used to conduct supervision and audit during the validity period of the certificate to ensure that the company continues to meet the standard requirements and conduct re-evaluation (renewal audit) before the certificate expires. ISO system-related documents include quality manuals, procedure documents, work instructions, and quality records. The product development process includes development project establishment, development planning, development input, development changes, development review, development verification, development output, test reports and development identification. Customer information includes customer files, customer tracking, customer service, customer communication, customer complaints, customer satisfaction and customer contract management.

[0036] An ISO system certification service standard audit method, the steps are as follows:

[0037] S01. Start-up preparation: Identify the internal audit team members through the human resources module 4 and assign system permissions to ensure that they can access the system to conduct audits. Then initialize the system through the document management module 1 and upload ISO system documents, including quality manuals, procedure documents, work instructions and quality records.

[0038] S02. Document management and maintenance: Establish document approval process and implement version control through document management module 1 to ensure that relevant personnel can be notified in time after document update to maintain the current validity of the document. On the basis of document management, supplier relationship module 3 can input supplier information, conduct evaluation and selection to ensure that suppliers meet ISO standards and support supply chain quality management.

[0039] S03. Product development tracking: Use the processes and standards provided by the document management module 1 through the product development module 5 to record the key activities in the product development process and ensure that the development process complies with ISO system requirements;

[0040] S04. Customer relationship maintenance: Customer relationship module 6 manages customer information, including service records and complaint handling, tracks customer satisfaction, and ensures service quality on the basis of ensuring product quality;

[0041] S05. Internal audit plan: Audit management module 2 refers to the procedure documents and work instructions in document management module 1 to formulate an internal audit plan, clarify the audit objectives, scope, methods, schedule and resource allocation;

[0042] S06. Perform internal audit: Audit Management Module 2 performs internal audit, including on-site audit, document review and employee interview, records audit findings, generates audit reports, and analyzes non-conformities found in the audit through Audit Management Module 2, formulates corrective and preventive measures, tracks the implementation effect of the measures, and ensures that the problems are resolved;

[0043] S07. Management Review: Using the data collected by Audit Management Module 2, conduct management review to evaluate the effectiveness, efficiency and improvement areas of the ISO system, and prepare certification application documents, including quality manual, procedure documents and internal audit reports, arrange external audits, and manage the audit process in Certification Module 7;

[0044] S08. Certificate management: Manage ISO certification certificates, including printing, issuing, updating and maintaining certificates. Utilize reports and data analysis automatically generated by the system to identify improvement opportunities, continuously improve the ISO system, conduct re-evaluation and update certificates before they expire.

[0045] In S02 document management and maintenance, the introduction of workflow automation tools can reduce manual operations and improve approval efficiency and accuracy. The workflow automation tool predicts the approval results through machine learning models to improve the accuracy of decision-making. The learning model predicts the approval results of the binary classification problem of whether it is passed or not. The prediction is made by using the Logistic Regression algorithm. The prediction formula of the Logistic Regression model is:

[0046] h(x)=σ(θ T x)

[0047] Among them, h(x): prediction function, which gives the probability of the model predicting the positive class under the input feature x, σ(z): sigmoid function, which is an S-shaped function used to map the linear output to a probability value between 0 and 1. σ(z) is the sigmoid function, defined as:

[0048]

[0049] This function maps the predicted values ​​of linear regression to the interval (0,1) and interprets them as probabilities, θ T x is the dot product of the feature vector x and the weight vector θ, representing the linear part of the model.

[0050] When training a logistic regression model, maximum likelihood estimation is usually used to determine the parameter θ, and its cost function (CostFunction) is:

[0051]

[0052] Among them, J(θ) is the cost function used to measure the performance of the model parameter θ, m is the total number of training samples, i represents the index of a single training sample, and y (i) is the actual label (0 or 1) of the i-th training sample, x (i) is the feature vector of the i-th training sample, h θ (x (i) ) is the model's predicted probability for the i-th training sample, that is, σ(θ T ·x (i) ), θ is the model parameter vector, which contains the weight of each feature, θ T ·x (i) is the feature vector x (i) The dot product of the parameter vector θ represents the linear part of the model, and σ(z) is the sigmoid function, defined as Used to convert linear output into probability values.

[0053] In order to improve the prediction accuracy of the model, regularization technology is also used to prevent overfitting. The regularized cost function can be expressed as:

[0054]

[0055] Where J(θ) is the cost function used to measure the performance of the model parameter θ and includes the regularization term, m is the total number of training samples, i is the index of a single training sample used to traverse all training samples, and y is the (i) : The actual label (0 or 1) of the i-th training sample, x (i) : The feature vector of the i-th training sample, h θ(x (i) ): The model's predicted probability for the i-th training sample, i.e., σ(θ T ·x (i) ), θ model parameter vector, including the weight of each feature, θ j : The jth weight in the model parameter vector, representing the weight of a specific feature, λ: Regularization parameter, controlling the strength of the regularization term, larger λ values ​​increase the effect of regularization and make the weight value closer to zero; smaller λ values ​​reduce the effect of regularization, n: The number of features.

[0056] S06 uses Robotic Process Automation (RPA) technology to automate repetitive tasks in the internal audit process, including information retrieval, data collection, and document review, to improve efficiency and reduce human errors. It also uses an artificial intelligence (AI)-driven document management system to automatically classify, extract, tag, and retrieve documents, simplifying the document management process and improving accuracy.

[0057] In an AI-driven document management system, the process of automatic classification, extraction, tagging, and retrieval of documents is as follows:

[0058] Data preprocessing: including noise reduction and image enhancement to improve document image quality, and document segmentation to break down documents into separate pages or regions;

[0059] Optical Character Recognition (OCR): Identify text areas in documents through image processing technology, further segment them into individual characters or words, and extract features such as shape, structure, grayscale, etc. Finally, use pattern recognition algorithms to convert features into text information;

[0060] Natural Language Processing (NLP): Perform text cleaning to remove irrelevant characters and stop words, identify the part of speech of each word, use the NER model to identify entities in the text, and apply statistical models or deep learning models to predict the probability distribution of the text;

[0061] Document representation learning: converting documents into numerical feature vectors, including bag-of-words models, TF-IDF, or Word2Vec, and using deep learning models to learn embedding representations of documents to capture semantic information.

[0062] Document classification: Use machine learning algorithms to train document classification models based on feature vectors and make classification predictions for new documents;

[0063] Information extraction: Combining rule-based extraction and machine learning models such as CRF and neural networks to identify and extract key information from documents;

[0064] Document tagging and indexing: adding tags or metadata to entities and key information in documents and building indexes to speed up retrieval;

[0065] Retrieval and Search: Parse user queries, calculate the relevance scores of documents to the query, rank the documents based on the scores and return the most relevant results.

[0066] Experimental data table, used to show the specific application and effect of ISO system certification service standard audit system in different modules, such as Figure 1 shown.

[0067] serial number Modules Implementation content Expected Results Actual Results Remark 1 Document Management Automated processes 30% increase in efficiency 25% more efficient Version Control 2 Audit Management Process Automation Shorten review cycle by 25% Shorten review cycle by 20% Reduce manual input 3 Supplier Relationship Information Management Update efficiency increased by 40% Update efficiency increased by 35% Optimize the evaluation process 4 human Resources Information maintenance Decision support improved by 50% Decision support improved by 45% Data Automatically Collected 5 Product Development Process tracking Compliance rate increased by 40% Compliance rate increased by 35% Monitoring Automation 6 Customer Relationship Information Management Satisfaction increased by 25% Satisfaction increased by 20% Service record automation 7 Certification Process Management Improve process efficiency by 20% Improve process efficiency by 15% Certificate Automation 8 Audit supervision Audit Execution Coverage increased by 30% 25% increase in coverage Periodically trigger audits

[0068] Table 1

[0069] According to the experimental data table, this ISO system certification service standard audit system can significantly improve the work efficiency and quality of enterprises in document management, audit process, supplier relations, human resource management, product development, customer relations and certification by integrating automation and intelligent technology, helping enterprises to better meet the requirements of ISO system standards and enhance market competitiveness.

[0070] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0071] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. An ISO system certification service standard audit system, characterized by: It includes a document management module (1), an audit management module (2), a supplier relationship module (3), a human resources module (4), a product development module (5), a customer relationship module (6), a certification module (7) and an audit module (8); The document management module (1) is responsible for managing all documents related to the ISO system. The document management module (1) ensures the consistency control of file versions, operation authority control and confidentiality of confidential files through document query, approval, management, release and archiving operations; The audit management module (2) is used for internal audit plan management, audit checklist management, audit report management, external audit management, corrective and preventive measures, and manages the entire internal audit process, from planning to execution, to report generation and subsequent corrective measures; The supplier relationship module (3) is used to manage supplier information, including material classification, supplier files, supplier evaluation, supply records and supply statistics; The human resources module (4) is used to maintain and update the organization's structure, ensure that responsibilities are clear, and that the structure diagram accurately reflects the company's organizational structure, and store employees' personal and professional information, including educational background, work experience, job changes and contract information, as well as collect and analyze human resources data to support decision-making and improve human resources management; The product development module (5) is used to manage the product development process; The customer relationship module (6) is used to manage customer information; The authentication module (7) is used for contract review, audit arrangement, authentication assessment, certificate printing and customer service maintenance, and can automatically export common work reports with one click and verify table data; The audit module (8) is used to conduct supervisory audits during the validity period of the certificate to ensure that the enterprise continues to meet the standard requirements, and to conduct re-evaluation (certificate renewal audit) before the certificate expires.

2. According to claim 1, an ISO system certification service standard audit system is characterized by: The ISO system-related documents include quality manuals, procedure documents, work instructions, and quality records.

3. According to claim 1, an ISO system certification service standard audit system is characterized by: The product development process includes development project establishment, development plan, development input, development change, development review, development verification, development output, test report and development appraisal.

4. According to claim 1, an ISO system certification service standard audit system is characterized by: The customer information includes customer files, customer tracking, customer service, customer communication, customer complaints, customer satisfaction and customer contract management.

5. The ISO system certification service standard audit method according to any one of claims 1 to 4, characterized in that: The steps are as follows: S01. Start-up preparation: Identify the internal audit team members through the human resources module (4) and assign system permissions to ensure that they can access the system to conduct audits. Then initialize the system through the document management module (1) and upload ISO system documents, including quality manuals, procedure documents, work instructions, and quality records. S02. Document management and maintenance: Establish a document approval process and implement version control through the document management module (1) to ensure that relevant personnel are notified in a timely manner after document updates to maintain the current validity of the document. The supplier relationship module (3) can also input supplier information, conduct evaluation and selection based on document management to ensure that suppliers meet ISO standards and support supply chain quality management. S03. Product development tracking: Use the processes and standards provided by the document management module (1) through the product development module (5) to record key activities in the product development process and ensure that the development process complies with ISO system requirements; S04. Customer relationship maintenance: The customer relationship module (6) manages customer information, including service records and complaint handling, tracks customer satisfaction, and ensures service quality on the basis of ensuring product quality; S05. Internal audit plan: The audit management module (2) refers to the procedure documents and work instructions in the document management module (1) to formulate an internal audit plan and clarify the audit objectives, scope, methods, schedule and resource allocation; S06. Perform internal audits: Audit Management Module (2) performs internal audits, including on-site audits, document reviews, and employee interviews, records audit findings, generates audit reports, and analyzes non-conformities found during the audits through Audit Management Module (2), formulates corrective and preventive measures, and tracks the effectiveness of the measures to ensure that the problems are resolved; S07. Management review: Using the data collected by the audit management module (2), conduct management review to evaluate the effectiveness, efficiency and improvement areas of the ISO system, and the certification module (7) prepares certification application documents, including quality manuals, procedure documents and internal audit reports, arranges external audits, and manages the audit process; S08. Certificate Management: Manage ISO certification certificates, including printing, issuing, updating and maintaining certificates. Utilize reports and data analysis automatically generated by the system to identify improvement opportunities, continuously improve the ISO system, conduct re-evaluation and update certificates before they expire.

6. According to claim 5, an ISO system certification service standard audit method is characterized by: In the S02 document management and maintenance, the workflow automation tool is introduced to reduce manual operations and improve approval efficiency and accuracy. The workflow automation tool predicts the approval results through a machine learning model to improve the accuracy of decision-making. The binary classification problem of predicting the approval results in the learning model is predicted by using a logistic regression algorithm. The prediction formula of the logistic regression model is: h(x)=σ(θ T ·x) Among them, h(x): prediction function, which gives the probability of the model predicting the positive class under the input feature x, σ(z): sigmoid function, which is an S-shaped function used to map the linear output to a probability value between 0 and 1. σ(z) is the sigmoid function, defined as: This function maps the predicted value of linear regression to the interval (0, 1) and interprets it as a probability, θ T x is the dot product of the feature vector x and the weight vector θ, representing the linear part of the model.

7. The I10 system certification service standard audit method according to claim 6 is characterized by: When training a logistic regression model, maximum likelihood estimation is usually used to determine the parameter θ, and its cost function (CostFunction) is: Among them, J(θ) is the cost function used to measure the performance of the model parameter θ, m is the total number of training samples, i represents the index of a single training sample, and y (i) is the actual label (0 or 1) of the i-th training sample, x (i) is the feature vector of the i-th training sample, h θ (x (i) ) is the model's predicted probability for the i-th training sample, that is, σ(θ T ·x (i) ), θ is the model parameter vector, which contains the weight of each feature, θ T ·x (i) is the feature vector x (i) The dot product of the parameter vector θ represents the linear part of the model, and σ(z) is the sigmoid function, defined as Used to convert linear output into probability values.

8. The ISO system certification service standard audit method according to claim 7 is characterized by: In order to improve the prediction accuracy of the model, regularization technology is also used to prevent overfitting. The regularized cost function can be expressed as: Where J(θ) is the cost function used to measure the performance of the model parameter θ and includes the regularization term, m is the total number of training samples, i is the index of a single training sample used to traverse all training samples, and y is the (i) : The actual label (0 or 1) of the i-th training sample, x (i) : The feature vector of the i-th training sample, h θ (x (i) ): The model's predicted probability for the i-th training sample, i.e., σ(θ T ·x (i) ), θ model parameter vector, including the weight of each feature, θ j : The jth weight in the model parameter vector, representing the weight of a specific feature, λ: Regularization parameter, controlling the strength of the regularization term, larger λ values ​​increase the effect of regularization and make the weight value closer to zero; smaller λ values ​​reduce the effect of regularization, n: The number of features.

9. The ISO system certification service standard audit method according to claim 5, characterized in that: In S06, Robotic Process Automation (RPA) technology is used to automate repetitive tasks in the internal audit process, including information retrieval, data collection, and document review, thereby improving efficiency and reducing human errors. An artificial intelligence (AI)-driven document management system is used to achieve automatic classification, extraction, tagging, and retrieval of documents, simplifying the document management process and improving accuracy.

10. The ISO system certification service standard audit method according to claim 9, characterized in that: In the AI-driven document management system, the automatic classification, extraction, tagging and retrieval process of documents is as follows: Data preprocessing: including noise reduction and image enhancement to improve document image quality, and document segmentation to break down documents into separate pages or regions; Optical Character Recognition (OCR): Identify text areas in documents through image processing technology, further segment them into individual characters or words, and extract features such as shape, structure, grayscale, etc. Finally, use pattern recognition algorithms to convert features into text information; Natural Language Processing (NLP): Perform text cleaning to remove irrelevant characters and stop words, identify the part of speech of each word, use the NER model to identify entities in the text, and apply statistical models or deep learning models to predict the probability distribution of the text; Document representation learning: converting documents into numerical feature vectors, including bag-of-words models, TF-IDF, or Word2Vec, and using deep learning models to learn embedding representations of documents to capture semantic information. Document classification: Use machine learning algorithms to train document classification models based on feature vectors and make classification predictions for new documents; Information extraction: Combining rule-based extraction and machine learning models such as CRF and neural networks to identify and extract key information from documents; Document tagging and indexing: adding tags or metadata to entities and key information in documents and building indexes to speed up retrieval; Retrieval and Search: Parse user queries, calculate the relevance scores of documents to the query, rank the documents based on the scores and return the most relevant results.

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