Quality risk management method and system based on white spirit enterprise

Abstract

The invention discloses a quality risk management method and system based on a white spirit enterprise, and relates to the technical field of risk prediction. Comprising the steps of 1, creating a quality risk management system based on a white spirit enterprise, 2, collecting, verifying and storing risk data through a risk data collection module, 3, designing, managing and calling a risk identification template through a risk identification template management module, and 4, managing and calling the risk identification template. The method comprises the steps of 1, managing risk identification, processing and tracking through a management risk identification and processing module, 2, carrying out risk analysis, assessment, grade evaluation and potential risk mining through a risk analysis and assessment module, and 3, carrying out risk information auditing, publishing, tracking and reminding through a risk publishing and tracking module. And 7, through summarization and analysis of risk data, report generation and visual display of a quality analysis module, a complete risk management and control process is formed, and it is guaranteed that risk management and control are efficient and orderly.

Description

Technical Field

[0001] This invention discloses a quality risk management method and system for liquor enterprises, which relates to the field of risk prediction technology. Background Technology

[0002] Currently, many liquor companies have issues with their quality risk management. For example, each business unit identifies risks offline based on a risk survey form provided annually by the quality department. These risks are then compiled and submitted to the quality department for verification. Once verified, the forms are sent back to the respective business units for self-management, without a unified release process. Each workshop conducts two offline inspections and reports each week, treating any identified risks as abnormal quality events. Furthermore, there is a lack of template management for risk survey forms, and risk process tracking is completed offline without corresponding quality analysis.

[0003] This existing quality risk management approach, lacking historical risk accumulation, results in a complex and time-consuming risk identification process each time, and is prone to overlooking risks. Furthermore, the management process after risk release is difficult to effectively track and monitor, seriously affecting the efficiency and effectiveness of quality risk management and failing to meet the needs of enterprises for high-quality management. Summary of the Invention

[0004] This invention addresses the problems of existing technologies by providing a quality risk management method and system for liquor enterprises. It solves the problems of existing quality risk management, such as reliance on manual labor, low efficiency, incomplete coverage, and insufficient data utilization. It can realize the optimization of quality risk management by automating risk data collection, intelligent analysis and evaluation, full-process tracking, and closed-loop management of risk.

[0005] The specific solution proposed in this invention is as follows:

[0006] This invention also provides a quality risk management method for liquor enterprises, comprising:

[0007] Step 1: Create a quality risk management system for liquor enterprises. This system includes a risk data acquisition module, a risk identification template management module, a risk analysis and assessment module, a risk release and tracking module, a management risk identification and handling module, and a quality analysis module.

[0008] Step 2: Collect, verify, and store risk data through the risk data acquisition module.

[0009] Step 3: Design, manage, and call up risk identification templates through the risk identification template management module.

[0010] Step 4: Manage the identification, handling, and tracking of risks through the risk identification and handling module.

[0011] Step 5: Analyze, assess, and classify risks, and identify potential risks through the risk analysis and assessment module.

[0012] Step 6: Review, publish, track, and alert on risk information through the risk release and tracking module.

[0013] Step 7: Through the aggregation, analysis, report generation, and visualization of risk data in the quality analysis module, a complete risk management process is formed to ensure efficient and orderly risk management.

[0014] Furthermore, in step 2 of the aforementioned quality risk management method for liquor enterprises, the risk data acquisition module connects with the workshop inspection and reporting system via an interface, periodically sends data requests and receives returned data; at the same time, it uses regular expressions and other methods to verify the data to ensure data format and integrity, and stores the verified data into the database to form a risk database.

[0015] Furthermore, in step 3 of the aforementioned quality risk management method for liquor enterprises, the risk identification template is managed through a risk identification template management module. This module uses rich text editing to add text boxes, dropdown lists, and checkboxes, allowing users to customize the template structure, content, and attributes of each form element. The designed templates are stored in the risk identification template database in XML format. Upon receiving a risk identification request, a suitable template is selected from the risk identification template database based on the risk type and requirements, and then converted into a fillable form for display to the user.

[0016] Furthermore, in step 3 of the aforementioned quality risk management method for liquor enterprises, a unique version number is assigned to each risk identification template through the risk identification template management module. After a risk identification template is modified, the version number is automatically updated, and the modifier, time, and content are recorded for viewing historical versions and version rollback. Clear status indicators are set for different versions of the risk identification template, including draft, in effect, and obsolete. The draft status marks a version that is being designed or modified but not yet officially activated; the in effect status indicates a valid version currently being used by business units; and the obsolete status marks a version that is no longer in use, allowing users to quickly identify and distinguish the usage status of the template.

[0017] Furthermore, in step 4 of the aforementioned quality risk management method for liquor enterprises, risk identification is performed through a risk identification and processing module.

[0018] Conduct risk analysis: Extract risk-related data from the risk database by writing SQL queries, and ensure data quality by combining data cleaning rules and format conversion tools. Analyze risks using the maintained identification strategies.

[0019] Processing strategy generation and management: using pre-set algorithms, maintaining the correspondence between algorithms and different identification and maintenance, among which the random forest algorithm ranks the importance of risk influencing factors and identifies the core variables that play a key role in risk level;

[0020] The ARIMA time series analysis model uncovers trends in risk data over time, providing a basis for risk prediction.

[0021] The Apriori association rule algorithm uncovers hidden associations between different risk factors, helping to identify risk transmission paths.

[0022] Furthermore, in step 5 of the aforementioned quality risk management method for liquor enterprises, the risk analysis and assessment module is used to analyze, assess, and classify the risk level.

[0023] Conduct risk data assessment:

[0024] Design a scoring system: Based on a pre-set risk assessment index system, quantify the probability and impact of risks into points from 1 to 5, with 1 being the lowest and 5 the highest. This is achieved through the following formula:

[0025] Risk score = Likelihood score × Impact score, calculate the overall score;

[0026] Dynamic weight adjustments are implemented: differentiated indicator weights are set for different business scenarios, with increased weight for process compliance in the production process and increased weight for environmental stability in the warehousing process; at the same time, weights are dynamically calibrated through weighted regression analysis based on historical risk handling data to ensure that the scores closely reflect actual business operations.

[0027] Risk rating assessment: The final risk level is determined based on the risk score range (e.g., 1-3 points for low risk, 4-8 points for medium risk, and 9-25 points for high risk), and the results are transmitted to the risk release and tracking module.

[0028] Furthermore, in step 6 of the aforementioned quality risk management method for liquor enterprises, the risk information is reviewed, released, tracked, and alerted through a risk release and tracking module, including:

[0029] Conduct risk review: Provides a review interface where users can view risk information and analysis and assessment results reported by business units and fill in review comments;

[0030] Risk dissemination: Risk information is disseminated to the heads of relevant business units via system messages, emails, and SMS.

[0031] Processing and tracking: A unique tracking number is assigned to each risk. A built-in Snowflake algorithm + business rule dual-factor ID generator ensures that a unique group-level tracking number can still be generated even in a distributed deployment environment. The format is: FX-YYMMDD-CCCC-PP, where YYMMDD is the release date, CCCC is the four-digit code of the business unit, and PP is the daily transaction record. Templates are maintained for categories such as liquor production, packaging material procurement, and logistics warehousing. Each template contains n stages, time limits, responsible person roles, and acceptance fields. Business unit leaders can adjust the order or add / remove stages on the Web canvas by dragging and dropping. An XML version is automatically generated and entered into the database with the version number. The processing period for each stage is calculated based on the risk level and business calendar. Processing information is automatically recorded and a tracking log is generated.

[0032] Provide risk alerts: Based on the risk level and processing deadline, remind the business unit leader to handle the matter in a timely manner when the deadline is about to expire or has expired.

[0033] Furthermore, step 7 of the aforementioned quality risk management method for liquor enterprises forms a complete risk control process through the quality analysis module, including:

[0034] Conduct risk and liability analysis: statistical dimensions, time frame, and responsible parties.

[0035] The display format is a stacked bar chart: showing the risk distribution for the year, with different colors representing different quality risks and risk factors. Clicking on each bar displays the current risk list and completion status of the responsible department. The display format is a pie chart: showing the proportion of each responsible entity in the total risk, intuitively presenting the distribution of responsibility. In the statistical example, the stacked bar chart: the X-axis represents the responsible entity, the Y-axis represents the number of risks, and the stacked part represents different risk types. Clicking on any bar will bring up a detailed list.

[0036] Summarize the risk execution status: statistical dimensions, time range, and execution status.

[0037] Execution status: Completed, In Progress, Not Started, Expired

[0038] Presentation format: List, displaying the current year's risk list and its completion status, including quality risk response measures and risk factor response measures.

[0039] This invention also provides a quality risk management system for liquor enterprises, including a risk data acquisition module, a risk identification template management module, a risk analysis and assessment module, a risk release and tracking module, a management risk identification and handling module, and a quality analysis module.

[0040] The risk data acquisition module collects, verifies, and stores risk data.

[0041] The risk identification template management module is used for designing, managing, and calling risk identification templates.

[0042] The risk identification and handling module manages the identification, handling, and tracking of risks.

[0043] The risk analysis and assessment module performs risk analysis, assessment, rating, and potential risk identification.

[0044] The risk release and tracking module is responsible for reviewing, releasing, tracking, and alerting users regarding risk information.

[0045] The quality analysis module aggregates, analyzes, generates reports, and visualizes risk data, forming a complete risk management process to ensure efficient and orderly risk management.

[0046] The advantages of this invention are:

[0047] This invention can build a risk template library with version management, and accumulate risk lists from previous years to form a reuse library, solving the problems of existing models having no historical accumulation and cumbersome identification.

[0048] Achieve closed-loop process optimization: Standardize risk release and change approval processes, establish a closed-loop management system for the formulation, tracking, and monitoring of risk response measures, and achieve risk traceability.

[0049] Improve the efficiency of data-driven decision-making: Present risk status intuitively through multi-dimensional statistical analysis, plan risk prediction based on big data machine learning and artificial intelligence, and enhance management foresight.

[0050] It is versatile and scalable: applicable to multiple business units such as groups, companies, departments, workshops, and work teams, with room for adaptive adjustments during promotion. Attached Figure Description

[0051] Figure 1 This is a schematic diagram of the business process of the method of the present invention.

[0052] Figure 2 This is a schematic diagram of the system functional architecture of the present invention.

[0053] Figure 3 This is a schematic diagram of the risk situation statistics interface.

[0054] Figure 4 This is a schematic diagram of the risk response measures interface. Detailed Implementation

[0055] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, so that those skilled in the art can better understand and implement the present invention. However, the embodiments described are not intended to limit the present invention.

[0056] Example 1

[0057] This invention also provides a quality risk management method for liquor enterprises, comprising:

[0058] Step 1: Create a quality risk management system for liquor enterprises. This system includes a risk data acquisition module, a risk identification template management module, a risk analysis and assessment module, a risk release and tracking module, a management risk identification and handling module, and a quality analysis module.

[0059] Step 2: Collect, verify, and store risk data through the risk data acquisition module.

[0060] The risk data acquisition module connects with the workshop inspection and reporting system via an interface, periodically sending data requests and receiving returned data. At the same time, it uses regular expressions and other methods to validate the data, ensuring the data format and integrity. The validated data is then stored in the database to form a risk database.

[0061] Step 3: Design, manage, and call risk identification templates through the risk identification template management module.

[0062] The risk identification template management module manages risk identification templates and uses rich text editing to add text boxes, drop-down lists, and checkboxes as form elements, allowing users to customize the template structure, content, and attributes of each form element. The designed templates are stored in the risk identification template database in XML format. When a risk identification request is received, a suitable template is selected from the risk identification template database based on the risk type and requirements, and then converted into a fillable form to be displayed to the user.

[0063] Each risk identification template is assigned a unique version number through the risk identification template management module. After a risk identification template is modified, the version number is automatically updated and the modifier, time, and content are recorded for viewing historical versions and version rollback. Clear status indicators are set for different versions of risk identification templates, including draft, in effect, and obsolete. The draft status is used to mark a version that is being designed or modified and has not yet been officially launched; the in effect status indicates a valid version currently being used by business units; and the obsolete status is used to mark a version that is no longer in use, making it convenient for users to quickly identify and distinguish the usage status of the template.

[0064] Step 4: Manage the identification, handling, and tracking of risks through the risk identification and handling module.

[0065] Risk identification is performed through a risk identification and handling module.

[0066] Conduct risk analysis: Extract risk-related data from the risk database by writing SQL queries, and combine data cleaning rules such as removing duplicate values, filling missing values, correcting outliers, and format conversion tools such as converting unstructured text data into structured labels to ensure data quality. Perform risk analysis operations through maintained identification strategies.

[0067] Processing strategy generation and management: using pre-set algorithms, maintaining the correspondence between algorithms and different identification and maintenance, among which the random forest algorithm ranks the importance of risk influencing factors and identifies the core variables that play a key role in risk level;

[0068] The ARIMA time series analysis model uncovers trends in risk data over time, providing a basis for risk prediction.

[0069] The Apriori association rule algorithm uncovers hidden associations between different risk factors, helping to identify risk transmission paths.

[0070] Step 5: Analyze, assess, classify, and identify potential risks through the risk analysis and assessment module.

[0071] The risk analysis and assessment module is used to analyze, assess, and classify risks.

[0072] Conduct risk data assessment:

[0073] Design a scoring system: Based on a pre-set risk assessment index system, quantify the probability and impact of risks into points from 1 to 5, with 1 being the lowest and 5 the highest. This is achieved through the following formula:

[0074] Risk score = Likelihood score × Impact score, calculate the overall score;

[0075] Dynamic weight adjustments are implemented: Differentiated indicator weights are set for different business scenarios such as production, warehousing, and sales. In the production process, the weight of process compliance is increased, and in the warehousing process, the weight of environmental stability is increased. At the same time, based on historical risk handling data, the weights are dynamically calibrated through weighted regression analysis. For example, the weights of indicators with strong explanatory power are increased, and the weights of indicators with high deviation rates are decreased, to ensure that the scores are consistent with actual business operations.

[0076] Risk rating assessment: The final risk level is determined based on the risk score range (e.g., 1-3 points for low risk, 4-8 points for medium risk, and 9-25 points for high risk), and the results are transmitted to the risk release and tracking module.

[0077] Step 6: Review, publish, track, and alert on risk information through the risk release and tracking module.

[0078] The risk release and tracking module is used for the review, release, tracking, and alerting of risk information, including:

[0079] Conduct risk review: Provides a review interface where users can view risk information and analysis and assessment results reported by business units and fill in review comments;

[0080] Risk dissemination: Risk information is disseminated to the heads of relevant business units via system messages, emails, and SMS.

[0081] Processing and tracking: A unique tracking number is assigned to each risk. A built-in Snowflake algorithm + business rule dual-factor ID generator ensures that a unique group-level tracking number can still be generated even in a distributed deployment environment. The format is: FX-YYMMDD-CCCC-PP, where YYMMDD is the release date, CCCC is the four-digit code of the business unit, and PP is the daily transaction record. Templates are maintained for categories such as liquor production, packaging material procurement, and logistics warehousing. Each template contains n stages, time limits, responsible person roles, and acceptance fields. Business unit leaders can adjust the order or add / remove stages on the Web canvas by dragging and dropping. An XML version is automatically generated and entered into the database with the version number. Based on the risk level and business calendar, such as automatically skipping national statutory holidays and workshop downtime days, the processing period for each stage is calculated, and process information is automatically recorded and a tracking log is generated.

[0082] Provide risk alerts: Based on the risk level and processing deadline, remind the business unit leader to handle the matter in a timely manner when the deadline is about to expire or has expired.

[0083] Step 7: Through the aggregation, analysis, report generation, and visualization of risk data in the quality analysis module, a complete risk management process is formed to ensure efficient and orderly risk management.

[0084] A complete risk management process is formed through the quality analysis module, including:

[0085] Conduct risk responsibility analysis: statistical dimensions, time range, and responsible parties. Responsible parties are categorized by organizational level, such as group, company, department, workshop, and work team.

[0086] The display format is a stacked bar chart: showing the risk distribution for the year, with different colors representing different quality risks and risk factors. Clicking on each bar displays the current risk list and completion status of the responsible department. The display format is a pie chart: showing the proportion of each responsible entity in the total risk, intuitively presenting the distribution of responsibility. In the statistical example, the stacked bar chart: the X-axis represents the responsible entity, the Y-axis represents the number of risks, and the stacked part represents different risk types. Clicking on any bar will bring up a detailed list.

[0087] Summarize the risk execution status: statistical dimensions, time range, and execution status.

[0088] Execution status: Completed, In Progress, Not Started, Expired

[0089] Presentation format: List, displaying the current year's risk list and its completion status, including quality risk response measures and risk factor response measures.

[0090] Example 2

[0091] This invention also provides a quality risk management system for liquor enterprises, including a risk data acquisition module, a risk identification template management module, a risk analysis and assessment module, a risk release and tracking module, a management risk identification and handling module, and a quality analysis module.

[0092] The risk data acquisition module collects, verifies, and stores risk data.

[0093] The risk identification template management module is used for designing, managing, and calling risk identification templates.

[0094] The risk identification and handling module manages the identification, handling, and tracking of risks.

[0095] The risk analysis and assessment module performs risk analysis, assessment, rating, and potential risk identification.

[0096] The risk release and tracking module is responsible for reviewing, releasing, tracking, and alerting users regarding risk information.

[0097] The quality analysis module aggregates, analyzes, generates reports, and visualizes risk data, forming a complete risk management process to ensure efficient and orderly risk management.

[0098] The information interaction and execution process between the modules in the above system are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description in the method embodiment of the present invention, and will not be repeated here.

[0099] Similarly, the system of the present invention can build a risk template library with version management, and accumulate risk lists from previous years to form a reuse library, solving the problems of existing models having no historical accumulation and cumbersome identification.

[0100] Achieve closed-loop process optimization: Standardize risk release and change approval processes, establish a closed-loop management system for the formulation, tracking, and monitoring of risk response measures, and achieve risk traceability.

[0101] Improve the efficiency of data-driven decision-making: Present risk status intuitively through multi-dimensional statistical analysis, plan risk prediction based on big data machine learning and artificial intelligence, and enhance management foresight.

[0102] It is versatile and scalable: applicable to multiple business units such as groups, companies, departments, workshops, and work teams, with room for adaptive adjustments during promotion.

[0103] It should be noted that not all steps and modules in the above processes and system structures are mandatory; some steps or modules can be omitted as needed. The execution order of each step is not fixed and can be adjusted as required. The system structures described in the above embodiments can be physical or logical structures. That is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or they may be jointly implemented by certain components in multiple independent devices.

[0104] The above-described embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention. The scope of protection of the present invention is defined by the claims.

Claims

1. A quality risk management method for liquor enterprises, characterized by: include: Step 1: Create a quality risk management system for liquor enterprises. This system includes a risk data acquisition module, a risk identification template management module, a risk analysis and assessment module, a risk release and tracking module, a management risk identification and handling module, and a quality analysis module. Step 2: Collect, verify, and store risk data through the risk data acquisition module. Step 3: Design, manage, and call up risk identification templates through the risk identification template management module. Step 4: Manage the identification, handling, and tracking of risks through the risk identification and handling module. Step 5: Analyze, assess, and classify risks, and identify potential risks through the risk analysis and assessment module. Step 6: Review, publish, track, and alert on risk information through the risk release and tracking module. Step 7: Through the aggregation, analysis, report generation, and visualization of risk data in the quality analysis module, a complete risk management process is formed to ensure efficient and orderly risk management.

2. The quality risk management method for liquor enterprises according to claim 1, characterized in that: In step 2, the risk data acquisition module connects with the workshop inspection and reporting system via an interface, periodically sending data requests and receiving returned data. At the same time, the data is validated using methods such as regular expressions to ensure data format and integrity. The validated data is then stored in the database to form a risk database.

3. The quality risk management method for liquor enterprises according to claim 1, characterized in that: In step 3, the risk identification template is managed through the risk identification template management module. Rich text editing is used to add text boxes, drop-down lists, and checkboxes as form elements, allowing users to customize the template structure, content, and attributes of each form element. The designed templates are stored in the risk identification template database in XML format. Upon receiving a risk identification request, a suitable template is selected from the risk identification template database based on the risk type and requirements, and then converted into a fillable form to be displayed to the user.

4. The quality risk management method for liquor enterprises according to claim 1, characterized in that: In step 3, a unique version number is assigned to each risk identification template through the risk identification template management module. After a risk identification template is modified, the version number is automatically updated and the modifier, time, and content are recorded for viewing historical versions and version rollback. Clear status indicators are set for different versions of risk identification templates, including draft, in effect, and obsolete. The draft status is used to mark a version that is being designed or modified but has not yet been officially launched; the in effect status indicates a valid version currently being used by business units; and the obsolete status is used to mark a version that has been discontinued, making it convenient for users to quickly identify and distinguish the usage status of the template.

5. The quality risk management method for liquor enterprises according to claim 1, characterized in that risk identification is performed through a management risk identification and processing module in step 4: Conduct risk analysis: Extract risk-related data from the risk database by writing SQL queries, and ensure data quality by combining data cleaning rules and format conversion tools. Analyze risks using the maintained identification strategies. Processing strategy generation and management: using pre-set algorithms, maintaining the correspondence between algorithms and different identification and maintenance, among which the random forest algorithm ranks the importance of risk influencing factors and identifies the core variables that play a key role in risk level; The ARIMA time series analysis model uncovers trends in risk data over time, providing a basis for risk prediction. The Apriori association rule algorithm uncovers hidden associations between different risk factors, helping to identify risk transmission paths.

6. The quality risk management method for liquor enterprises according to claim 1, characterized in that: Step 5 involves analyzing, assessing, and rating risks using the risk analysis and assessment module. Conduct risk data assessment: Design a scoring system: Based on a pre-set risk assessment index system, quantify the probability and impact of risks into points from 1 to 5, with 1 being the lowest and 5 the highest. This is achieved through the following formula: Risk score = Likelihood score × Impact score, calculate the overall score; Dynamic weight adjustments are implemented: differentiated indicator weights are set for different business scenarios, with increased weight for process compliance in the production process and increased weight for environmental stability in the warehousing process; at the same time, weights are dynamically calibrated through weighted regression analysis based on historical risk handling data to ensure that the scores closely reflect actual business operations. Risk rating assessment: Determine the final risk level based on the risk score range (e.g., 1-3 points for low risk, 4-8 points for medium risk, and 9-25 points for high risk), and transmit the results to the risk release and tracking module.

7. A quality risk management method for liquor enterprises according to claim 1, characterized in that: Step 6 involves the risk release and tracking module for reviewing, releasing, tracking, and alerting about risk information, including: Conduct risk review: Provides a review interface where users can view risk information and analysis and assessment results reported by business units and fill in review comments; Risk dissemination: Risk information is disseminated to the heads of relevant business units via system messages, emails, and SMS. Processing and tracking: A unique tracking number is assigned to each risk. A built-in Snowflake algorithm + business rule dual-factor ID generator ensures that a unique group-level tracking number can still be generated even in a distributed deployment environment. The format is: FX-YYMMDD-CCCC-PP, where YYMMDD is the release date, CCCC is the four-digit code of the business unit, and PP is the daily transaction record. Templates are maintained for categories such as liquor production, packaging material procurement, and logistics warehousing. Each template contains n stages, time limits, responsible person roles, and acceptance fields. Business unit leaders can adjust the order or add / remove stages on the Web canvas by dragging and dropping. An XML version is automatically generated and entered into the database with the version number. The processing period for each stage is calculated based on the risk level and business calendar. Processing information is automatically recorded and a tracking log is generated. Provide risk alerts: Based on the risk level and processing deadline, remind the business unit leader to handle the matter in a timely manner when the deadline is about to expire or has expired.

8. A quality risk management method for liquor enterprises according to claim 1, characterized in that: Step 7 involves using the quality analysis module to develop a complete risk management process, including: Conduct risk and liability analysis: statistical dimensions, time frame, and responsible parties. The display format is a stacked bar chart: showing the risk distribution for the year, with different colors representing different quality risks and risk factors. Clicking on each bar displays the current risk list and completion status of the responsible department. The display format is a pie chart: showing the proportion of each responsible entity in the total risk, intuitively presenting the distribution of responsibility. In the statistical example, the stacked bar chart: the X-axis represents the responsible entity, the Y-axis represents the number of risks, and the stacked part represents different risk types. Clicking on any bar will bring up a detailed list. Summarize the risk execution status: statistical dimensions, time range, and execution status. Execution status: Completed, In Progress, Not Started, Expired Presentation format: List, displaying the current year's risk list and its completion status, including quality risk response measures and risk factor response measures.

9. A quality risk management system for liquor enterprises, characterized by: It includes a risk data acquisition module, a risk identification template management module, a risk analysis and assessment module, a risk release and tracking module, a management risk identification and handling module, and a quality analysis module. The risk data acquisition module collects, verifies, and stores risk data. The risk identification template management module is used for designing, managing, and calling risk identification templates. The risk identification and handling module manages the identification, handling, and tracking of risks. The risk analysis and assessment module performs risk analysis, assessment, rating, and potential risk identification. The risk release and tracking module is responsible for reviewing, releasing, tracking, and alerting users regarding risk information. The quality analysis module aggregates, analyzes, generates reports, and visualizes risk data, forming a complete risk management process to ensure efficient and orderly risk management.

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