Risk vector control system

Abstract

The invention provides a risk vector control system comprising a risk vector generation and calculation module, an alert module, an algorithm module, and a decision-making module. The risk vector generation and calculation module is configured to receive a first instruction from a first event to generate a total risk priority number. The alert module pre-stores a threshold. The alert module is configured to receive the total RPN for generating a first signal and a first alert signal from the total RPN exceeding the threshold. The algorithm module is configured to receive the first signal to generate a second signal and a negative vector comprising a negative RPN. The decision-making module is configured to receive the second signal to generate an audit plan report and a corrective and preventive action report. The risk vector control system can quantify event risks and adjust negative RPN calculation parameters to enhance risk control efficiency.

Description

[Technical Field]

[0001] This invention relates to a risk control system, and more particularly to a risk vector control system based on quality management. [Previous Technology]

[0002] Quality management aims to ensure that companies maintain product stability while complying with relevant regulatory requirements. To achieve this goal, ISO 9001:2015 requires companies to incorporate risk management concepts into their quality management system, systematically identifying and assessing potential internal and external risks to develop appropriate response strategies and ensure the company's quality and compliance. Biomedical and pharmaceutical products are often used in applications related to human treatment, and any quality issues can have serious consequences for patients. Therefore, risk management is particularly crucial in quality management systems within the biomedical and pharmaceutical field.

[0003] However, conventional risk management only assesses individual events and provides improvement strategies manually. In the process of manually formulating improvement strategies, decisions are often influenced by personal experience, subjective judgment, and cognitive biases, causing the strategies to fail to reflect objective facts and actual needs, thus leading to strategy deviations. Furthermore, due to the lack of systematic data support, manually formulated improvement strategies may suffer from insufficient operability at the implementation level, making them difficult to adapt to real-world applications. Moreover, without an effective monitoring and feedback mechanism, it is difficult to identify potential problems during strategy implementation, resulting in an inability to adjust and optimize in a timely manner. Furthermore, conventional control systems assess individual events independently. Conventional control systems cannot integrate the risks of various events or detect key risks within a single event, nor can they cover time risks that accumulate slowly over time. This results in incomplete risk assessments, leading to biased improvement strategies and hindering the improvement of the accuracy of risk management and the long-term effectiveness of improvement measures. [Summary of the Invention]

[0004] In view of the above, the present invention provides a risk vector control system, comprising: a risk vector generation and calculation module for receiving a first instruction of a first event to generate an overall risk priority number (RPN); an alarm module for pre-storing a threshold, the alarm module being connected to the risk vector generation and calculation module for receiving the overall RPN and generating a first signal and a first alarm signal based on the overall RPN exceeding the threshold range; an algorithm module connected to the alarm module for receiving the first signal to generate a second signal and a negative vector, the negative vector including a negative RPN; and a decision module connected to the algorithm module for receiving the second signal to generate an audit plan and a proposed improvement plan.

[0005] The risk vector control system further includes a database, which pre-stores a risk calculation table. The risk calculation table includes a severity index, a detectability index, and an incidence index. The algorithm module generates the negative RPN based on the severity index, the detectability index, and the incidence index of the risk calculation table.

[0006] Wherein, the risk vector generation calculation module is used to receive a first instruction of a first event to generate a first event risk multidimensional vector, and the first event risk multidimensional vector further includes M components and a first RPN.

[0007] Wherein, the overall RPN includes the first RPN in the first event risk multidimensional vector and one of the second RPNs in the second event risk multidimensional vector, the M components include a time component, and one of the non-time components of the M components of the first event risk multidimensional vector is the same as one of the non-time components of the M components of the second event risk multidimensional vector.

[0008] The algorithm module includes a first parameter processing unit, which is connected to the alarm module to receive the first signal and sum the first RPN and the second RPN to generate an event RPN.

[0009] The algorithm module further includes a negative vector generation unit, which is used to receive the first signal to generate the negative vector.

[0010] The algorithm module further includes a second parameter processing unit, which is connected to the first parameter processing unit and the negative vector generation unit to receive the event RPN and the negative RPN to generate a second alarm signal and a timing start signal.

[0011] The algorithm module further includes a timing unit, which is connected to the second parameter processing unit to receive the timing start signal and start timing to a preset time value.

[0012] The algorithm module further includes a parameter setting interface unit, which is connected to the timing unit and is used to provide a user with input of the preset time value in the parameter setting interface unit.

[0013] The timing unit is connected to the parameter setting interface unit, the negative vector generation unit, and the risk vector generation calculation module. The negative vector generation unit is connected to the risk vector generation calculation module. When within the preset time value range, the risk vector generation calculation module generates a fifth event risk multidimensional vector and a reconstructed negative vector signal by receiving a fifth instruction of a fifth event. One of the non-time components of the M components of the fifth event risk multidimensional vector is the same as the non-time component of the M components of the first event risk multidimensional vector.

[0014] The risk vector control system further includes a historical risk vector library, and the algorithm module further includes a third parameter processing unit. The third parameter processing unit is connected to the historical risk vector library to extract a specific component from the historical risk vector library, so as to sum the overall RPN with the same specific component in the risk vector control system.

[0015] In summary, the risk vector generation and calculation module of the risk vector control system of the present invention can comprehensively identify each risk component in a single event risk and the risk multiplication effect between each single event to calculate the overall RPN that best matches the actual situation, and further drive the algorithm module to generate negative vectors to assist the decision-making module in producing the optimal suggestion improvement plan. Compared with conventional risk control systems, the present invention can produce the most accurate risk response strategy that better meets actual needs, thereby improving decision-making efficiency and risk control capabilities.

[0016] Furthermore, the algorithm module of the risk vector control system of the present invention automatically generates negative vectors to produce actionable improvement plans. By quantifying improvement measures, the present invention not only ensures the objectivity and traceability of these measures but also verifies their effectiveness to assess whether the negative vector is correctly constructed. Moreover, the risk vector control system of the present invention is highly adaptable, flexibly adjusting the negative vector according to the nature and scope of impact of different risk events, enabling the present invention to cope with diverse and dynamically changing risk environments. Simultaneously, the risk vector control system of the present invention can also dynamically present the relationship between risk increases and risk decreases, making risk change trends clearer and more quantifiable, thereby improving the accuracy of decision-making and the effectiveness of risk management.

[0017] Furthermore, compared to conventional risk control systems that rely solely on static assessment mechanisms and generate audit plans from a single point in time (such as quarterly or annually), the risk vector control system of this invention adopts a dynamic risk management architecture, enabling it to respond to risk events in real time. Once the risk vector control system receives a risk event, it automatically generates a corresponding audit plan. Upon receiving another such risk event, it can dynamically monitor changes in the risk value and generate a corresponding audit plan and suggested improvement plans. [Simplified Explanation of the Diagram]

[0045] Figure 1 is a functional block diagram illustrating a risk vector control system according to a specific embodiment of the present invention.

[0046] Figure 2 is a functional block diagram illustrating a risk vector control system according to another specific embodiment of the present invention.

Implementation Method

[0018] To make the advantages, spirit, and features of the present invention easier and clearer to understand, detailed descriptions and discussions will follow with reference to the accompanying drawings and specific embodiments. It should be noted that these specific embodiments are merely representative examples of the present invention, and the specific methods, apparatuses, conditions, etc., exemplified are not intended to limit the present invention or the corresponding specific embodiments. Furthermore, the elements in the figures are only used to express their relative positions and are not drawn to scale; the step numbers in the present invention are only for distinguishing different steps and do not represent the order of the steps, as will be stated previously.

[0019] Please refer to Figure 1. Figure 1 is a functional block diagram illustrating a risk vector control system 10 according to a specific embodiment of the present invention. As shown in Figure 1, the risk vector control system 10 of the present invention includes a risk vector generation and calculation module 20, an alarm module 30, an algorithm module 40, and a decision module 50. The risk vector generation and calculation module 20 is used to receive a first instruction of a first event to generate an overall risk priority number (RPN) (hereinafter referred to as the overall RPN). The alarm module 30 pre-stores a threshold and is connected to the risk vector generation and calculation module 20. The alarm module 30 is used to receive the overall RPN and generate a first signal and a first alarm signal based on the overall RPN exceeding the threshold range, so as to systematically and automatically execute preset countermeasures and immediately notify relevant personnel of this abnormal situation. The first alarm signal is indicated by a red light. The algorithm module 40 is connected to the alarm module 30 and is used to receive the first signal to generate a second signal and a negative vector, the negative vector containing a negative RPN. By generating negative RPN through negative vectors, the excessively high overall RPN caused by the first event is offset, thereby reducing the risk value to a stable state. Decision module 50 is connected to algorithm module 40 to receive the second signal to generate an audit plan and to generate a suggested improvement plan based on the negative vectors.

[0020] In this specific embodiment, the risk vector control system 10 further includes a database (not shown in the figure). The database pre-stores a risk calculation table, which includes a severity index, a detectability index, and an incidence index. The algorithm module 40 generates a negative RPN based on the severity index, detectability index, and incidence index of the risk calculation table. The calculation formula for the negative RPN is as follows: Negative RPN = -(Severity index × Detectability index × Incidence index). However, in practice, the parameters of the negative RPN are not limited to the above scope. In addition to multiplying the severity index, detectability index, and incidence index, the generation of the negative RPN can also be multiplied by various control measures that can reduce the risk value, such as the number and intensity levels of education and training, shift system adjustment parameters, and the establishment of a cross-departmental communication platform to exchange risk parameters, so as to further strengthen the overall risk management mechanism.

[0021] In this specific embodiment, the database (not shown in the figure) further includes a historical risk vector database (not shown in the figure), which pre-stores a second event risk multidimensional vector for the second event and a third event risk multidimensional vector for the third event. Furthermore, the second event risk multidimensional vector further includes M components and a second RPN, and the third event risk multidimensional vector further includes M components and a third RPN. M is a natural number greater than 1. The M components further include personnel components, machinery components, raw material components, standard components, environmental components, event components, and time components. However, in practice, the M components are not limited to the above categories and can be expanded according to actual needs to cover the composition and classification structure of all risk factors.

[0022] In this specific embodiment, the risk vector generation and calculation module 20 in the risk vector control system 10 is further capable of receiving a first instruction of the first event to generate a first event risk multidimensional vector based on the first instruction. The first event risk multidimensional vector further includes M components and a first RPN. In this specific embodiment, the overall RPN includes the first RPN in the first event risk multidimensional vector, the second RPN in the second event risk multidimensional vector, the third RPN in the third event risk multidimensional vector, and the time RPN. The risk vector generation and calculation module 20 generates the overall RPN according to the following formula:

[0023] Where V is the first RPN of the first event risk multidimensional vector; n is the sum of the number of the first event risk multidimensional vector and the second event risk multidimensional vector; V' is the third RPN of the third event risk multidimensional vector; a is the risk reduction coefficient; n' is the number of the third event risk multidimensional vectors; b is the risk warning specification constant; x is the time interval between the occurrence time of the most recent second event among n-1 second events and the occurrence time of the first event. However, in practice, x is not limited to this; x can be the time interval between the occurrence time of one of the n-1 second events and the occurrence time of the first event.

[0024] In this specific embodiment, the M components include a time component. The non-time components of the M components of the first event risk multidimensional vector are the same as the non-time components of the M components of the second event risk multidimensional vector. That is, the time components in the first event risk multidimensional vector and the second event multidimensional vector are different, but the first RPN and the second RPN can be the same or different, and the second event is a historical event of the first event. At least one component of the M components of the first event risk multidimensional vector is the same as at least one component of the M components of the third event risk multidimensional vector. That is, the first event risk multidimensional vector and the third event risk multidimensional vector are similar, and the first event and the third event are related risk events.

[0025] This invention provides a risk vector calculation system that can be applied to factories of Contract Development and Manufacturing Organizations (CDMOs), including product development and commercial production services for pharmaceuticals and biologics. However, in practical applications, the risk vector calculation system of this invention is not limited to the above scope and can also be widely applied to other industries to meet the quality management needs of different fields and improve risk identification and response capabilities.

[0026] In addition to the above embodiments, the present invention may also cover other application forms. Please refer to Figure 2. Figure 2 is a functional block diagram illustrating a risk vector control system 10' according to another specific embodiment of the present invention. As shown in Figure 2, the difference between this specific embodiment and the above specific embodiments is that the algorithm module 40 in the risk vector calculation system 10' of this specific embodiment further includes a first parameter processing unit 401, a negative vector generation unit 402, a second parameter processing unit 403, a timing unit 404, a parameter setting interface unit 405, and a third parameter processing unit 406. The first parameter processing unit 401 is connected to the alarm module 30 to receive a first signal and sums the first RPN and the second RPN to generate an event RPN. The event RPN is used to accumulate risk data from each event to the present, quantify the event risk level, and serve as the basis for dynamically adjusting the risk management strategy. The negative vector generation unit 402 is used to receive the first signal to generate a negative vector. The second parameter processing unit 403 is connected to the first parameter processing unit 401 and the negative vector generation unit 402 to receive the event RPN and the negative RPN, thereby generating a second alarm signal and a timing start signal. The timing start signal is the timing monitoring mechanism of this system. Please note that the risk vector control system 10' in this specific embodiment has the same or corresponding components and modules as those in the aforementioned specific embodiments, which have been described in detail in the aforementioned specific embodiments, and therefore will not be repeated here.

[0027] In this specific embodiment, the second alarm signal is indicated by a yellow light, indicating that the event type has entered the risk control stage. The timing unit 404 is connected to the second parameter processing unit 403 to receive the timing start signal to start timing to a preset time value. If no event of the same type occurs within the preset time value, the risk assessment mechanism is recalibrated and the status is restored to normal (green light), and the validity of its negative vector is confirmed at the same time. The parameter setting interface unit 405 is connected to the timing unit 404 to provide the user with the option to input a preset time value in the parameter setting interface unit 405. The timing unit 404 is connected to the parameter setting interface unit 405, the negative vector generation unit 402, and the risk vector generation calculation module 20. The negative vector generation unit 402 is connected to the risk vector generation calculation module 20. When within the preset time value range in the timing unit 404, the risk vector generation calculation module 20 generates the overall RPN of the fifth event and the risk multidimensional vector and reconstructed negative vector signal of the fifth event by receiving the fifth instruction of the fifth event. Alarm module 30 receives the overall RPN of the fifth event to generate the first signal and the first alarm signal of the fifth event, indicated by a red light. The non-temporal components of the M components of the risk multidimensional vector of the fifth event are the same as the non-temporal components of the M components of the risk multidimensional vector of the first event. This means that if the same type of event continues to occur within a preset time, leading to further accumulation of risk values, it can be determined that the negative vector control mechanism has failed or that the negative vector component has a design flaw. This situation indicates that the existing risk control mechanism has failed to effectively reduce the event occurrence rate. At this time, risk vector generation and calculation module 20 outputs a reconstructed negative vector signal to negative vector generation unit 402 to regenerate the negative vector, activate a higher-level response mechanism, and thereby optimize the control strategy to ensure risk management effectiveness. Then, the second parameter processing unit 403 is connected to the first parameter processing unit 401. The second parameter processing unit 403 receives the event RPN of the fifth event from the first parameter processing unit 401 and the negative RPN of the self-negative vector generation unit 402 to generate a second alarm signal and a timing start signal so that the timing unit restarts timing 404.

[0028] In this specific embodiment, the risk vector control system 10' of the present invention further includes a database (not shown in the figure), which includes a historical risk vector database (not shown in the figure). The third parameter processing unit 406 in the algorithm module 40 connects to the historical risk vector database to extract a specific component from the historical risk vector database, and sums up the overall RPN with the same specific component within the risk vector control system 10', thereby generating a key risk component. The risk vector control system 10' of the present invention can accumulate the risk values ​​of specific problem personnel to clearly present their risk burden as a basis for decision-making and management. In addition, the present invention can also identify high-risk equipment to assist in determining whether a brand change is necessary, thereby improving management efficiency and operational stability. Furthermore, the third parameter processing unit 406 can also identify potential high-risk combinations and predict possible risk chain reactions, so that the unit can formulate appropriate preventive measures in advance.

[0029] Please refer to Figure 2. In a practical application scenario, the risk vector generation calculation module 20 receives a first instruction for a first event to generate the overall RPN. The risk vector generation calculation module 20 is connected to a historical risk vector database (not shown in the figure). The risk vector generation calculation module 20 can receive the first instruction to generate a multi-dimensional risk vector for the first event. The multi-dimensional risk vector for the first event contains M components and a first RPN. The first RPN is generated based on a risk calculation table, which is as follows:

[0030] The calculation formula for the first RPN is as follows: First RPN = Severity Index × Detectability Index × Occurrence Index. The calculated value is: First RPN = 3 × 3 × 2 = 18. In this actual application scenario, the first instruction is "On January 1, 2025, the QC specialist operated the microscope in laboratory R01 and forgot to turn off the power after use, causing the lamp to burn out." The first event risk multidimensional vector is "(00100, QC, Microscope, N / A, QC-Laboratory Microscope Operation Manual, Laboratory R01, Operating the microscope without turning off the power according to regulations caused the lamp to burn out, January 1, 2025, 18)". Among them, the components are, in order, the serial number component, the personnel component, the machine component, the raw material component, the standard component, the environmental component, the event component, and the time component. The historical risk vector database pre-stores the second event risk multidimensional vector of the second event and the third event risk multidimensional vector of the third event. The second event risk multidimensional vector is "(00090, QC, Microscope, N / A, QC-Laboratory Microscope Operation Manual, Laboratory R01, The power supply to the microscope was not turned off according to the specifications, resulting in the lamp burning out, May 1, 2024, 18)". The third event risk multidimensional vector is "(00045, RD, Microscope, N / A, QC-Laboratory Microscope Operation Manual, Laboratory R01, The power supply to the microscope was not turned off according to the specifications, resulting in the lamp burning out, April 1, 2024, 18)". In practice, the ordinal component of the first event risk multidimensional vector is not included in the comparison range with the second and third event risk multidimensional vectors. If one component of the third event risk multidimensional vector differs from one component of the first event risk multidimensional vector, the risk reduction coefficient is 0.8; if two components of the third event risk multidimensional vector differ from two components of the first event risk multidimensional vector, the risk reduction coefficient is 0.64, and so on. However, in practice, this is not the only applicable rule. The reduction rule of the risk reduction coefficient can be adjusted on a rolling basis according to each unit's risk tolerance and external objective factors. The risk warning specification constant is preset to 50, and there are 245 calendar days from May 1, 2024 to January 1, 2025, so x is 245. Based on the above formula, the calculated values ​​are: ; and therefore, the calculated overall RPN value is: Overall RPN = 36 + 14.4 + 33.6 = 84.

[0031] Alarm module 30 pre-stores a threshold value and is connected to risk vector generation and calculation module 20. The threshold value is 50, but in practice it is not limited to this. The threshold value can be adjusted in a rolling manner according to the risk tolerance of each unit and external objective factors. Alarm module 30 is used to receive the overall RPN. The overall RPN value is 84. If the overall RPN value is greater than the preset threshold, alarm module 30 generates a first signal and a first alarm signal based on the overall RPN value exceeding the threshold range. The first alarm signal is indicated by a red light.

[0032] The first parameter processing unit 401 is connected to the alarm module 30 to receive the first signal, and sums the first RPN and the second RPN to generate an event RPN. The calculated event RPN is: event RPN = 18 + 18 = 36.

[0033] The negative vector generation unit 402 is used to receive the first signal to generate a negative vector. The negative vector contains a negative RPN, and the severity index of the negative RPN is 3, which is the same as the severity index of the first RPN. The detectability index of the negative RPN is 4 because it is preset to "with SOP and automated detection system". The occurrence rate index of the negative RPN is 5 because it is preset to never occur again. The calculated value is: negative RPN = -(3×4×5) = -60. Therefore, the negative vector is "(00100, QC, Microscope, N / A, QC-Laboratory Microscope Operation Manual, Laboratory R01, The power supply of the microscope was not turned off according to the specifications, causing the lamp to burn out, January 1, 2025, -60)".

[0034] The second parameter processing unit 403 is connected to the first parameter processing unit 401 and the negative vector generation unit 402 to receive the event RPN and the negative RPN, and calculate a safe range RPN value. The safe range RPN value is a value less than a threshold. The calculated safe range RPN is: 36 + (-60) = -24. The second parameter processing unit 403 calculates the safe range RPN to generate a second alarm signal and a timer start signal. The second alarm signal is indicated by a yellow light, indicating that the alarm is temporarily lifted, the event type has entered the risk control stage, and timer observation has begun.

[0035] The decision module 50 connects to the algorithm module 40 to receive the second signal to generate an audit plan and a suggested improvement plan based on the negative vector. The audit plan is generated based on the multi-dimensional vector of the first event risk. In this practical application scenario, the audit plan includes "auditing the training records of QC personnel, especially the usage records of microscopes, and reviewing whether there are any unclear descriptions in the QC-Laboratory Microscope Operation Manual, and assessing whether there are any problems with the laboratory R01 environment, such as the voltage of the sockets." Since the detection index of the negative vector in the suggested improvement plan is preset to "having SOPs and automated detection systems," the suggested improvement plan includes "please establish relevant automated detection systems, such as monitors."

[0036] The timing unit 404 is connected to the second parameter processing unit 403 to receive the timing start signal, which is used to start timing to the preset time value. In this actual application scenario, the preset time value is one year, but in practice it is not limited to this. The preset time value can be adjusted in a rolling manner according to the risk tolerance of each unit and external objective factors. The parameter setting interface unit 405 is connected to the timing unit 404 to provide the user with the option to input the preset time value in the parameter setting interface unit 405. If there is no recurrence of the event within the preset time value, the negative vector is established as "(00100, QC, Microscope, N / A, QC-Laboratory Microscope Operation Manual, Laboratory R01, The power supply to the microscope was not turned off according to the specifications, causing the light source to burn out, January 1, 2025, -60)", the second alarm signal is released, and the yellow light indicator turns into a green light indicator.

[0037] In another practical application scenario, if the second parameter processing unit 403 cannot calculate the safe range RPN, that is, the negative vector cannot withstand the risk of the multi-dimensional vector of the first event risk, and the existing risk control strategy fails to achieve the expected effect. At this time, the negative vector generation unit 402 increases the value of the detection index, setting the pre-stored detection index value of 4 "with SOP and automated detection system" to "with SOP and AI detection system", which is 5, to generate a higher negative RPN and obtain the safe range RPN. However, in practice, it is not limited to this; the negative vector generation unit can also generate the optimal negative RPN by increasing other index parameters.

[0038] In another practical application scenario, the timing unit 404 is connected to the parameter setting interface unit 405, the negative vector generation unit 402, and the risk vector generation calculation module 20. The negative vector generation unit 402 is connected to the risk vector generation calculation module 20. Within the preset time value range in the timing unit 404, the risk vector generation calculation module 20 receives the fifth instruction of the fifth event to generate the fifth event risk multidimensional vector, the overall RPN of the fifth event, and the reconstructed negative vector signal. The alarm module 30 receives the overall RPN of the fifth event to generate the first signal of the fifth event and the first alarm signal of the fifth event, which is indicated by a red light. The non-time components of the M components of the fifth event risk multidimensional vector are the same as the non-time components of the M components of the first event risk multidimensional vector. That is, if the same type of event continues to occur within the preset time, causing the risk value to accumulate further, it can be determined that the negative vector control mechanism has failed or that the negative vector component has a design defect. This situation shows that the existing risk control mechanism has failed to effectively reduce the event occurrence rate. At this point, the risk vector generation and calculation module 20 outputs a reconstructed negative vector signal to the negative vector generation unit 402 to regenerate the negative vector, initiating a higher-level response mechanism and optimizing control strategies to ensure risk management effectiveness. Upon receiving the reconstructed negative vector signal, meaning the negative RPN of the first event's negative vector fails, the generation of the fifth negative RPN, in addition to multiplying severity, detectability, and incidence indicators, can also multiply parameters such as the number and intensity levels of training, shift system adjustment parameters, and the establishment of a cross-departmental communication platform to exchange risk parameters—all parameters that could reduce risk values ​​and further strengthen the overall risk management mechanism. In this practical application scenario, increasing the number of training sessions from one to two can generate a higher negative RPN, thus optimizing risk control strategies. However, in practice, this is not limited to this; in other practical application scenarios, the intensity level of training can also be increased, meaning classroom instruction can be transformed into practical examinations, thus changing the intensity level from 1 to 2, and so on, to enhance the effectiveness of risk control. In this practical application scenario, the second parameter processing unit 403 is connected to the first parameter processing unit 401, and receives the event RPN of the fifth event from the first parameter processing unit 401 and the negative RPN from the negative vector generation unit 402 to generate a second alarm signal and a timing start signal, so that the timing unit restarts timing 404 to the expected time value.

[0039] The above practical application scenario demonstrates how the present invention, through the risk vector generation calculation module 20, alarm module 30, algorithm module 40, and decision module 50, automatically identifies and assesses risks in quality management to generate an audit plan and a recommended improvement plan. Through the algorithm module, the present invention can not only calculate event risks to quantify their scope and severity of impact, but also further generate corresponding negative vectors, thereby deriving the best improvement measures. By dynamically adjusting the negative RPN calculation parameters, the effectiveness of risk intervention is improved, achieving the purpose of risk control.

[0040] In summary, the risk vector generation and calculation module of the risk vector control system of the present invention can comprehensively identify each risk component in a single event risk and the risk multiplication effect between each single event to calculate the overall RPN that best matches the actual situation, and further drive the algorithm module to generate negative vectors to assist the decision-making module in producing the optimal suggestion improvement plan. Compared with conventional risk control systems, the present invention can produce the most accurate risk response strategy that better meets actual needs, thereby improving decision-making efficiency and risk control capabilities.

[0041] Furthermore, the algorithm module of the risk vector control system of the present invention automatically generates negative vectors to produce actionable improvement plans. By quantifying improvement measures, the present invention not only ensures the objectivity and traceability of these measures but also verifies their effectiveness to assess whether the negative vector is correctly constructed. Moreover, the risk vector control system of the present invention is highly adaptable, flexibly adjusting the negative vector according to the nature and scope of impact of different risk events, enabling the present invention to cope with diverse and dynamically changing risk environments. Simultaneously, the risk vector control system of the present invention can also dynamically present the relationship between risk increases and risk decreases, making risk change trends clearer and more quantifiable, thereby improving the accuracy of decision-making and the effectiveness of risk management.

[0042] Furthermore, compared to conventional risk control systems that rely solely on static assessment mechanisms and generate audit plans from a single point in time (such as quarterly or annually), the risk vector control system of this invention adopts a dynamic risk management architecture, enabling it to respond to risk events in real time. Once the risk vector control system receives a risk event, it automatically generates a corresponding audit plan. Upon receiving another such risk event, it can dynamically monitor changes in the risk value and generate a corresponding audit plan and suggested improvement plans.

[0043] It should be noted that relational terms in this specification, such as “first” and “second”, are used only to distinguish an entity or operation from another entity or operation, and do not require or imply any actual relationship or order between these entities or operations. Furthermore, the words “comprising,” “having,” and “including,” as well as other similar forms, are intended to be equivalent in meaning and are open-ended; one or more items following any of these words do not imply an exhaustive list of such one or more items, or that the list is limited to one or more items.

[0044] The detailed description of the preferred embodiments above is intended to more clearly illustrate the features and spirit of the present invention, and is not intended to limit the scope of the present invention by the preferred embodiments disclosed above. Rather, the aim is to cover various changes and equivalent arrangements within the scope of the patent claims made by the present invention. Therefore, the scope of the patent claims made by the present invention should be interpreted in the broadest possible sense based on the foregoing description, so as to cover all possible changes and equivalent arrangements.

Claims

1. A risk vector control system, comprising: a risk vector generation and calculation module for receiving a first instruction of a first event to generate an overall risk priority number (RPN); an alarm module for pre-storing a threshold, the alarm module being connected to the risk vector generation and calculation module for receiving the overall RPN and generating a first signal and a first alarm signal based on the overall RPN exceeding the threshold range; an algorithm module connected to the alarm module for receiving the first signal to generate a second signal, and the algorithm module further comprising a negative vector generation unit for receiving the first signal to generate a negative vector, the negative vector including a negative RPN; and a decision module connected to the algorithm module for receiving the second signal to generate an audit plan and a proposed improvement plan.

2. The risk vector control system as described in claim 1 further includes a database that pre-stores a risk calculation table, the risk calculation table including a severity index, a detectability index and an incidence index, the algorithm module generating the negative RPN based on the severity index, the detectability index and the incidence index of the risk calculation table.

3. The risk vector control system as described in claim 1, wherein the risk vector generation and calculation module is used to receive a first instruction of a first event to generate a first event risk multidimensional vector, and the first event risk multidimensional vector further includes M components and a first RPN.

4. The risk vector control system as described in claim 3, wherein the overall RPN includes the first RPN in the first event risk multidimensional vector and a second RPN in a second event risk multidimensional vector, the M components include a time component, and a non-time component of the M components of the first event risk multidimensional vector is the same as a non-time component of the M components of the second event risk multidimensional vector.

5. The risk vector control system as described in claim 4, wherein the algorithm module includes a first parameter processing unit connected to the alarm module to receive the first signal and sum the first RPN and the second RPN to generate an event RPN.

6. The risk vector control system as described in claim 5, wherein the algorithm module further includes a second parameter processing unit connected to the first parameter processing unit and the negative vector generation unit to receive the event RPN and the negative RPN to generate a second alarm signal and a timing start signal.

7. The risk vector control system as described in claim 6, wherein the algorithm module further includes a timing unit connected to the second parameter processing unit to receive the timing start signal to start timing to a preset time value.

8. The risk vector control system as described in claim 7, wherein the algorithm module further includes a parameter setting interface unit connected to the timing unit, for providing a user with the option to input the preset time value in the parameter setting interface unit.

9. The risk vector control system as described in claim 8, wherein the timing unit is connected to the parameter setting interface unit, the negative vector generation unit, and the risk vector generation calculation module, the negative vector generation unit is connected to the risk vector generation calculation module, and within the preset time value range, the risk vector generation calculation module generates a fifth event risk multidimensional vector and a reconstructed negative vector signal by receiving a fifth instruction of a fifth event, wherein one of the M components of the fifth event risk multidimensional vector is a non-time component that is the same as the non-time component of the M components of the first event risk multidimensional vector.

10. The risk vector control system as described in claim 1 further includes a historical risk vector library, and the algorithm module further includes a third parameter processing unit connected to the historical risk vector library to extract a specific component from the historical risk vector library to sum the overall RPN with the same specific component in the risk vector control system.

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