Intelligent change management system and method based on risk assessment

Abstract

The invention discloses an intelligent change management system and method based on risk assessment. The system comprises a change application module, a risk assessment module, a change approval module, a change tracking alarm module and a change verification module. According to the method, changes are automatically divided into emergency, conventional or significant types through a dynamic classification engine, and a differentiation auditing process is matched; performing quantitative risk assessment by using an analytic hierarchy process and a risk matrix to realize risk identification, analysis and rating; the NLP technology is adopted to automatically fill a structured change list, and the information processing efficiency is improved; full-process tracking and visual monitoring are carried out in the change implementation process, and an alarm is automatically given when abnormity occurs; after the change, trial production and mass production verification are sequentially executed and compared with the dynamic base line, and it is ensured that the change effect is stable and reliable. According to the invention, the problems of low efficiency, weak risk control and poor collaboration in the traditional change management are effectively solved, and the intelligent and structured management and control of the change of the full life cycle are realized.

Description

Technical Field

[0001] This invention relates to the field of change management technology, and in particular to an intelligent change management system and method based on risk assessment. Background Technology

[0002] Traditional change management processes have many shortcomings in the manufacturing field, mainly in the following aspects: Low review efficiency: The approval process is usually a single-line model, which is lengthy and cannot respond quickly to urgent changes, resulting in long change processing time and affecting production schedule; Insufficient risk control: There is a lack of effective verification of the entire change lifecycle. The trial production and mass production stages are disconnected, making it difficult to fully assess change risks and making changes prone to instability at different production stages; Poor collaboration: Communication and collaboration between cross-departmental roles rely on manual processes, information transmission is untimely and inaccurate, and operation logs are difficult to trace, which is not conducive to the tracking and supervision of the change management process.

[0003] In summary, the shortcomings of traditional change management processes in terms of efficiency, risk control, and collaboration have rendered them inadequate to meet the demands for real-time, accurate, and end-to-end control of change management. Therefore, a change management solution that integrates dynamic classification, intelligent assessment, and full lifecycle management is urgently needed to address these issues. Summary of the Invention

[0004] To address the above issues, this invention provides an intelligent change management system and method based on risk assessment. It aims to solve problems such as low efficiency and concentrated risks in traditional change process review by using dynamic classification, NLP technology, and full lifecycle risk management, thereby improving the success rate of changes and reducing the risk of exceeding the deadline.

[0005] In a first aspect, the present invention provides an intelligent change management system based on risk assessment, comprising the following modules: The change request module is used to receive process change requests submitted by users and to conduct a preliminary review of the request information; The risk assessment module is used to conduct risk assessments on process change requests, including risk identification, risk analysis, and risk evaluation. The change approval module is used to approve process changes based on risk assessment results and generate approval opinions; The change tracking and alarm module is used to track the implementation process of approved process changes, including developing change plans, executing change operations, monitoring the change process, and monitoring the status of the change process in real time. The change verification module is used to verify the implemented process changes, evaluate the effects of the changes, and decide whether to officially enable the changes based on the verification results.

[0006] Furthermore, the risk assessment module specifically includes: The risk identification unit is used to identify potential risks of change based on historical data, expert experience, and a built-in risk knowledge base; The risk analysis unit is used to determine the weight of each risk factor using the analytic hierarchy process (AHP) and to calculate the probability and impact of the risk. The risk assessment unit is used to calculate the risk value and determine the risk level based on the probability and impact of the risk.

[0007] By constructing a systematic risk assessment module that integrates risk identification, analysis, and evaluation, comprehensive and structured management of change risks has been achieved. This module transforms experience-based qualitative judgments into a combination of quantitative and qualitative analysis based on data and models, significantly improving the early detection of risks, the scientific rigor of the assessment process, and the accuracy of risk level determination.

[0008] Furthermore, the risk analysis unit uses expert scoring and a 1-9 scale to construct a judgment matrix. By calculating the maximum eigenvalue and the corresponding eigenvector of the judgment matrix, the weight of each risk factor is determined.

[0009] By introducing the Analytic Hierarchy Process (AHP) and the 1-9 scaling method to construct a judgment matrix, the weights of risk factors are scientifically quantified, avoiding the bias of subjective judgment, improving the objectivity and accuracy of risk assessment, and providing a reliable basis for subsequent risk classification and decision-making.

[0010] Furthermore, the risk assessment unit is specifically used for: The probability of risk occurrence and the degree of impact are divided into multiple levels to construct a risk matrix. The risk value R is calculated according to the risk value calculation formula R=P×I, where P is the probability of risk occurrence and I is the score of the degree of risk impact. The final risk level is determined in the risk matrix based on the risk value.

[0011] By constructing a risk matrix and using quantitative formulas to calculate risk values, an intuitive and standardized assessment of risk levels is achieved, which facilitates the identification and priority handling of high-risk changes, thereby improving the efficiency of risk management and the scientific nature of decision-making.

[0012] Furthermore, the change tracking alarm module includes: The planning unit is used to develop detailed change plans; The operation execution unit is used to execute specific change operations according to the change plan; The process monitoring unit is used to monitor the change process, visually display the process status in the change log through color markings, and trigger automated alarms and push them to the responsible person when there is an overdue or abnormal situation.

[0013] By displaying the process status in real time through color-coding and automatically triggering alarms when there are abnormalities or delays, the system enables visual monitoring and timely intervention of the change process, effectively reducing change delays and operational risks, and improving the responsiveness of process control.

[0014] Furthermore, the change verification module is also used for: After the change is implemented, trial production verification and mass production verification are performed in sequence, and the verification data is compared with the dynamic baseline. If the deviation exceeds the safety value, a rollback plan is triggered and a verification report is generated.

[0015] By verifying through two phases of trial production and mass production, and combining deviation detection with dynamic baselines, the stability and applicability of the change can be fully evaluated after its implementation. Once an anomaly is detected, a rollback can be triggered, which significantly reduces the operational risks after the change is introduced into the production environment.

[0016] Furthermore, baseline adjustments are performed as follows: The system automatically triggers baseline adjustments at fixed intervals, summarizes and analyzes production data within the period, assesses the differences from the original baseline, and determines whether to update. Technicians evaluate and revise the generated baseline adjustment plan.

[0017] By periodically and automatically triggering the baseline adjustment process, combined with manual corrections by technical personnel, the baseline data is ensured to always reflect the current production reality, improving the adaptability and accuracy of the verification process and avoiding misjudgments caused by outdated baselines.

[0018] Secondly, the present invention also provides an intelligent change management method based on risk assessment, comprising the following steps: S1 receives change requests and change documents, and automatically classifies them into urgent changes, routine changes, or major changes based on the urgency, scope of impact, and production stage of the change requests, combined with a dynamic classification engine and a preset rule base. S2 uses a dynamic classification engine to determine different multi-level review process nodes for each type of change, and submits the change application to the review node for review. S3, determine the change type based on the content of the change document, automatically classify and determine the change order template corresponding to the change type from the preset rule base, and match the standardized template from the template base; S4. Using NLP technology, extract field values ​​from the change file and automatically populate the template to generate a structured change order; S5. Determine the change category to which the change type belongs, and send the change order to the change location node corresponding to the change category for review. If the review is approved, extract the operation steps related to the change from the change order to perform the change operation on the target system.

[0019] Compared with existing technologies, the beneficial effects of this invention are as follows: By dynamically classifying and multi-level reviewing changes, the type of change is linked to the production stage. Emergency changes utilize a "green channel," while routine and major changes are reviewed in a tiered manner, balancing efficiency and risk control. A risk assessment mechanism is introduced during the change process, enabling systematic and scientific identification and evaluation of change risks, effectively reducing the failure rate and negative impacts. Simultaneously, verification during trial production and mass production stages is added to ensure the stability of changes in the production environment, avoiding the shortcomings of traditional methods that rely solely on single tests. Furthermore, NLP automatically fills templates, collects data in real time, and uses digital model predictions, reducing manual intervention and improving the scientific nature of decision-making. Finally, efficient cross-departmental collaboration is achieved based on the RBAC permission system and review chain records. This invention can accumulate and solidify change experience, providing data support for continuous enterprise improvement. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this drawing or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this drawing. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0021] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments provided by this invention without inventive effort are within the scope of protection of this invention.

[0023] This invention provides an intelligent change management system based on risk assessment. The system adopts a B / S architecture, and users can access the system through a browser. The system backend is developed using Java and built using the Spring Boot framework. The database uses MySQL to store information such as process change applications, risk assessment results, approval records, implementation plans, and verification data.

[0024] A risk-assessment-based intelligent change management system specifically includes the following modules: The change request module is used to receive process change requests submitted by users and to conduct a preliminary review of the request information.

[0025] Specifically, the application information in the change request module includes the reason for the change, the content of the change, and the expected goals. The application form should include the following fields: Applicant for change: Name and department of the person submitting the change application; Change time: The estimated time for the change to be implemented; Reason for change: Describe in detail the reasons for the change, such as improving product quality, reducing production costs, or meeting new regulatory requirements; Change details: Specify the changes, such as modifying process parameters, replacing equipment, or using new materials; Expected goals: Clearly define the goals to be achieved after the change, such as improving product qualification rate, reducing energy consumption, and shortening production cycle.

[0026] The risk assessment module is used to conduct risk assessments on process change requests, including risk identification, risk analysis, and risk evaluation.

[0027] Furthermore, the risk assessment module specifically includes: The risk identification unit is used to identify potential risks of change based on historical data, expert experience, and a built-in risk knowledge base; The risk analysis unit is used to determine the weight of each risk factor using the analytic hierarchy process (AHP) and to calculate the probability and impact of the risk. The risk assessment unit is used to calculate the risk value and determine the risk level based on the probability and impact of the risk.

[0028] Specifically, historical data is collected from the company's historical project database, reports, records, and other channels, covering system operation indicators before and after the change, business impact scope, risk event types and frequency of occurrence, etc. Based on the results, past experience is obtained, such as identifying potential hidden problems caused by the change and judging key risk points.

[0029] The Analytic Hierarchy Process (AHP) was used to decompose the potential risks of change into a hierarchical structure, such as three main categories: technical risks, business risks, and compliance risks. Each main category was further subdivided into specific risk factors, such as system compatibility risks and performance degradation risks under technical risks. The relative importance weight of each level of risk factor was determined through expert scoring.

[0030] When constructing the judgment matrix, a 1-9 scale is used. For example, if risk factor A is considered slightly more important than risk factor B, then the ratio of A to B is 3. The judgment matrix A for the two risk factors "system compatibility risk" (R1) and "performance degradation risk" (R2) under technical risk is constructed as follows: .

[0031] The weights of each risk factor are obtained by calculating the largest eigenvalue and the corresponding eigenvector of the judgment matrix. The specific calculation formula is as follows: ; Where W is the feature vector; n is the number of risk factors; It is the largest eigenvalue.

[0032] By combining the risk impact levels in historical data, the identified potential risks can be quantitatively assessed. A risk matrix method can be used to classify the probability and impact of risks into different levels (e.g., high, medium, low) to construct a risk matrix.

[0033] The probability of a risk occurring can be calculated by referring to the frequency of occurrence in historical data. For example, if a certain type of risk has occurred 20 times in the past 100 changes, then its probability of occurrence P = 20 / 100 = 0.2. The degree of risk impact can be quantified according to the regulations on indicators such as business interruption time, economic loss, and number of customer feedback. For example, the impact of a business interruption of less than 1 hour is low, corresponding to a score of 1 point; the impact of an interruption of 1-4 hours is medium, corresponding to a score of 3 points; and the impact of an interruption of more than 4 hours is high, corresponding to a score of 5 points.

[0034] The risk value R is calculated using the formula: R = P × I; where P is the probability of the risk occurring, and I is the score representing the degree of risk impact. Based on the calculated risk value, the risk level is determined in the risk matrix, thereby identifying high-risk, medium-risk, and low-risk potential changes.

[0035] The change approval module is used to approve process changes based on risk assessment results and generate approval opinions.

[0036] Specifically, process changes are approved based on risk assessment results and pre-defined approval rules. High-risk changes require multi-level approval and final decision-making by senior management; medium-risk changes require joint approval by department managers and technical experts; and low-risk changes only require approval by the department manager. The system automatically routes change requests to the appropriate approvers, such as department leaders, technical experts, and quality management personnel, and generates approval opinions, including "agree," "disagree," and "requires modification."

[0037] The change tracking and alarm module is used to track the implementation process of approved process changes, including developing change plans, executing change operations, monitoring the change process, and monitoring the status of the change process in real time.

[0038] Furthermore, the change tracking alarm module specifically includes: The planning unit is used to develop detailed change plans; The operation execution unit is used to execute specific change operations according to the change plan; The process monitoring unit is used to monitor the change process, promptly detect and handle abnormal situations, and visually display them in the change log through color markings (green - completed, orange - abnormal, red - overdue). When an overdue or abnormal situation occurs, an automated alarm is triggered and pushed to the responsible person.

[0039] Specifically, clearly define the key monitoring indicators during the change process, including: Time indicators: Change plan start time, plan end time, actual start time, actual progress time, etc., are used to determine whether the change has exceeded the time limit; Task completion indicators: The completion status of sub-tasks involved in the change, such as the product's test process data, product process completion status, etc.

[0040] These tools collect system status metrics in real time, automatically monitoring the operating parameters of servers, network devices, etc., and storing the data in a monitoring database. Simultaneously, they interface with project management systems (such as TAPD) via APIs to obtain information such as the timeline of change tasks and the completion status of subtasks. For data that cannot be collected automatically, such as user complaints in business impact metrics, dedicated personnel record and input them into a unified change management system.

[0041] Set up time monitoring rules in the change management system. When the actual progress time exceeds the planned end time, it is judged as an overdue anomaly. The system will automatically mark the change record in red and trigger the alarm mechanism.

[0042] Regularly check the completion status of subtasks involved in changes. If any subtask is not completed on time without a reasonable extension explanation, or if a critical subtask fails, mark the change record in orange. For example, if a product process task is not completed within the specified time and no valid extension application is submitted, it is considered abnormal.

[0043] When the system determines that a change has expired or is abnormal, it immediately triggers an automated alarm mechanism. The alarm information is pushed to the person in charge of the change, the head of the technical team, and the heads of relevant business departments through channels such as email, SMS, and instant messaging tools. The alarm information includes detailed information such as the change name, the type of abnormality, specific abnormal indicators, and the time.

[0044] Once the anomaly is resolved, the responsible person verifies that the system status has returned to normal, the business impact has been eliminated, and the change task can continue. In the change management system, the change record is marked green to indicate that the anomaly has been resolved, and the relevant processing records and verification results are submitted for subsequent auditing and review.

[0045] The change verification module is used to verify the implemented process changes, evaluate the effects of the changes, and decide whether to officially enable the changes based on the verification results.

[0046] Furthermore, the change verification module specifically includes: The effect evaluation unit is used to evaluate the effects of changes, including product quality, production efficiency, and cost control. The decision-making unit is used to decide whether to officially implement the changes based on the evaluation results.

[0047] Specifically, after the change is implemented, the change verification module sequentially performs trial production verification and mass production verification. The verification data is compared with the historical baseline. If the deviation exceeds the safety value, a rollback plan is triggered and a verification report is generated.

[0048] The historical baseline is a dynamic baseline, and baseline adjustments are made in the following ways: Set fixed time periods (such as weekly or monthly) as regular trigger points for baseline adjustment. At the end of each period, the system automatically starts the baseline adjustment process, summarizes and analyzes the production data within that period, assesses the difference between the current production status and the original baseline, and determines whether the baseline needs to be updated. Technical personnel evaluate and revise the baseline adjustment plan generated by the system based on production processes, equipment performance, market changes, and other factors.

[0049] After completing all processes, the system creates a closed-loop archive of documents, links change records to the audit chain and verification reports, and supports QR code scanning to trace the entire process.

[0050] This invention also provides an intelligent change management method based on risk assessment, such as... Figure 1 As shown, the specific steps include the following: S1 receives change requests and change documents, and automatically classifies them into urgent changes, routine changes, or major changes based on the urgency, scope of impact, and production stage of the change request, combined with a dynamic classification engine and a preset rule base.

[0051] Specifically, if keywords such as "serious risk" or "production stoppage" appear in the change application, it is directly determined to be an emergency change; or when the scope of the change involves product scrapping, production interruption, or overall downgrading, it also meets the conditions for an emergency change.

[0052] Changes that affect only non-core business modules, such as optimizing a parameter or performance; or changes marked as "executed as planned" and do not affect the current production schedule, can be considered routine changes.

[0053] A change is considered a major change if it involves significant adjustments to the production process, replacement of key equipment, or affects more than 50% of the production process, and the expected implementation period is more than 2 days.

[0054] S2 uses a dynamic classification engine to determine different multi-level review process nodes for each type of change, and submits the change application to the review node for review.

[0055] S3 determines the change type based on the content of the change document, automatically classifies and determines the change order template corresponding to the change type from the preset rule base, and matches the standardized template from the template library.

[0056] S4. Using NLP technology, extract field values ​​from the change file and automatically populate the template to generate a structured change order; Specifically, the auto-fill template has a dynamic expansion function, allowing users to customize template fields based on new terms added in the change management program.

[0057] S5. Determine the change category to which the change type belongs, and send the change order to the change location node corresponding to the change category for review. If the review is approved, extract the operation steps related to the change from the change order to perform the change operation on the target system.

[0058] It should be noted that the present invention is not limited to the above-described embodiments. The above embodiments are merely examples, and any embodiments that have the same structure and perform the same effects as the technical concept within the scope of the present invention are included within the scope of the present invention. Furthermore, various modifications that can be conceived by those skilled in the art to the embodiments, and other ways of constructing by combining some of the constituent elements of the embodiments, without departing from the spirit of the present invention, are also included within the scope of the present invention.

Claims

1. A risk-assessment-based intelligent change management system, characterized in that, Includes the following modules: The change request module is used to receive process change requests submitted by users and to conduct a preliminary review of the request information; The risk assessment module is used to conduct risk assessments on process change requests, including risk identification, risk analysis, and risk evaluation. The change approval module is used to approve process changes based on risk assessment results and generate approval opinions; The change tracking and alarm module is used to track the implementation process of approved process changes, including developing change plans, executing change operations, monitoring the change process, and monitoring the status of the change process in real time. The change verification module is used to verify the implemented process changes, evaluate the effects of the changes, and decide whether to officially enable the changes based on the verification results.

2. The intelligent change management system based on risk assessment as described in claim 1, characterized in that, The risk assessment module specifically includes: The risk identification unit is used to identify potential risks of change based on historical data, expert experience, and a built-in risk knowledge base; The risk analysis unit is used to determine the weight of each risk factor using the analytic hierarchy process (AHP) and to calculate the probability and impact of the risk. The risk assessment unit is used to calculate the risk value and determine the risk level based on the probability and impact of the risk.

3. The intelligent change management system based on risk assessment as described in claim 2, characterized in that, The risk analysis unit uses expert scoring and a 1-9 scale to construct a judgment matrix. By calculating the maximum eigenvalue and the corresponding eigenvector of the judgment matrix, the weight of each risk factor is determined.

4. The intelligent change management system based on risk assessment as described in claim 2, characterized in that, The risk assessment unit is specifically used for: The probability of risk occurrence and the degree of impact are divided into multiple levels to construct a risk matrix. The risk value R is calculated according to the risk value calculation formula R=P×I, where P is the probability of risk occurrence and I is the score of the degree of risk impact. The final risk level is determined in the risk matrix based on the risk value.

5. The intelligent change management system based on risk assessment as described in claim 1, characterized in that, The change tracking and alarm module includes: The planning unit is used to develop detailed change plans; The operation execution unit is used to execute specific change operations according to the change plan; The process monitoring unit is used to monitor the change process, visually display the process status in the change log through color markings, and trigger automated alarms and push them to the responsible person when there is an overdue or abnormal situation.

6. The intelligent change management system based on risk assessment as described in claim 1, characterized in that, The change verification module is also used for: After the change is implemented, trial production verification and mass production verification are performed in sequence, and the verification data is compared with the dynamic baseline. If the deviation exceeds the safety value, a rollback plan is triggered and a verification report is generated.

7. The intelligent change management system based on risk assessment as described in claim 6, characterized in that, Baseline adjustment is performed as follows: The system automatically triggers baseline adjustments at fixed intervals, summarizes and analyzes production data within the period, assesses the differences from the original baseline, and determines whether to update. Technicians evaluate and revise the generated baseline adjustment plan.

8. A risk-assessment-based intelligent change management method, characterized in that, Includes the following steps: S1 receives change requests and change documents, and automatically classifies them into urgent changes, routine changes, or major changes based on the urgency, scope of impact, and production stage of the change requests, combined with a dynamic classification engine and a preset rule base. S2 uses a dynamic classification engine to determine different multi-level review process nodes for each type of change, and submits the change application to the review node for review. S3, determine the change type based on the content of the change document, automatically classify and determine the change order template corresponding to the change type from the preset rule base, and match the standardized template from the template base; S4. Using NLP technology, extract field values ​​from the change file and automatically populate the template to generate a structured change order; S5. Determine the change category to which the change type belongs, and send the change order to the change location node corresponding to the change category for review. If the review is approved, extract the operation steps related to the change from the change order to perform the change operation on the target system.

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