TWI818737B - Production line critical process failure mode and failure tree risk probability assessment system and method - Google Patents

Abstract

The present invention discloses a system and method for assessing the risk probability of failure modes and failure trees of key processes in a production line, which includes an information processing module. The information processing module configuration includes failure mode and failure analysis module (FMEA), fault tree risk probability calculation module (FTA), big data acquisition module, expected cost analysis module and optimal cost analysis module. The failure mode and failure analysis module calculates multiple key processes of the production line based on the data captured by the big data capture module, and imports each key process into the error tree risk probability calculation module in order to calculate the risk probability from the error tree. The calculation module evaluates and tracks each possible failure process step of each key process to perform risk probability model decision-making failure calculations to evaluate the risk probability information of the production line producing defective products under failure, and use the risk probability information as a basis to reduce high risk The basis for decentralizing or re-planning key processes, so that failure modes and failure analysis can be used to identify key processes and then import error trees to assess the potential loss probability and cost of defective products due to failure. And combined with the expected improvement cost information of the possible failure process steps of each key process, the size information of the improvement expected cost information of the possible failure process steps of each key process is evaluated, and then the priority of the key process is generated according to the order of the size information. Improve sequence information.

Description

Production line critical process failure mode and failure tree risk probability assessment system and method

The present invention relates to a system and method for evaluating the risk probability of failure modes and failure trees of key processes in a production line. In particular, it relates to a system and method that can use failure modes and failure analysis to find out key processes and then introduce a fault tree to evaluate the potential loss probability of defective products due to failure. Process mode failure analysis technology with loss cost.

According to what we know, Failure Mode and Effects Analysis (FMEA) is mainly used to analyze the steps and processes of the manufacturing process of products, and take precautions to prevent product defects caused by operational errors in the production process. This is systematic Use the statistical reliability probability analysis model to understand in advance the main causes of malfunctions that are likely to cause malfunctions with great probability, and then understand the potential factors of malfunctions and propose solutions and improvements. Generally speaking, regardless of R&D design or process processing or product production process, failure mode and failure analysis is used to improve its reliability, so as to reduce the costs derived from possible engineering design changes or process improvements in the future, thus improving the reliability of various procedures. degree and reduce the cost of improvement after failure. If "Design FMEA" can be used in the development stage for pre-assessment, "Process FMEA" can be used for pre-planning before mass production to prevent equipment failure and even occupational disasters in personnel operations and identify the main key factors. Focusing on cost reduction.

Currently, this method has been used in various industries such as the manufacturing industry (especially the vehicle manufacturing industry, aviation industry, machine tool industry, hardware tool industry, etc.) for the application of Failure Mode and Effect Analysis (FMEA). It has been widely used. As for design FMEA, it is aimed at various R&D designs such as equipment development, Automated production line design, new product conceptual design, and pre-prototype model production, etc., conduct analysis of each step, hoping to find out the most likely potential failure risks in advance and formulate preventive or improvement measures to improve the reliability of equipment introduction or product development. , and can reduce the cost and risk of failure. The above-mentioned functions are used to prevent the cost of inputting raw materials or reprocessing or scrapping or even sales and affecting goodwill in the event of defective products or loss of mechanical design. If potential problems can be prevented or reduced before the official mass production of products, it will lead to great cost savings for future derivative problems. This critical process decision generally uses the risk priority (RPN) indicator to determine the order of priority improvement.

In addition, fault tree analysis (Fault Tree Analysis) (FTA) is a deductive derivation algorithm based on probability that combines the union and intersection of logic gates. It starts from the structural expansion of the final system from the mother layer to the child layer. , through the series (and) relationship of each independent event and the parallel (or) relationship of each independent event, the failure probability mode of the possible system is integrated and calculated. In addition, Failure Mode and Effect Analysis (FMEA) is an algorithm of induction. After estimating the importance, frequency of occurrence and detectability table through empirical values, the system is first decomposed into sub-systems and then the probability is calculated. The model calculates the risk priority of each subsystem and analyzes the impact of the possible functional failure probability of elements or parts of the subsystem. It is structured and extended from the sub-layer to the parent layer. The difference between the two is that fault tree analysis uses the correlation of independent events to find out the system risk probability when performing system failure analysis. It cannot independently calculate the initial failure probability of sub-layers that individually affect the system. Looking back at the failure mode and impact analysis, all the initial failure probabilities of each sub-layer can be listed, but the interaction correlations of each sub-layer cannot be combined and calculated, and the relationship between the merged to the parent layer cannot be estimated. The former FTA is the overall system assessment concept, and the latter FMEA is the subsystem assessment concept. Therefore, by combining the two, we can reduce the cost factors of prevention failure risk, and then extrapolate from the overall risk assessment to the local risk assessment.

Furthermore, with the development of workpieces becoming miniaturized and requiring high precision, the processing accuracy and speed requirements of various production lines have become increasingly stringent. Although the rapid development of precision machinery and smart production line industries has caused the shipment volume of process equipment to increase year by year, Many manufacturers hope to seize the opportunity and have invested a lot of research and development costs; however, they have been unable to further break through the technical bottleneck in improving processing quality and stability. Investigating the reason, the technical bottleneck is that the conventional process equipment does not have a set of technologies that can integrate process models and fault failure analysis, so that the production cost of the production line cannot be optimized for decision-making purposes. In addition to being unable to In addition to effectively reducing future loss costs and production risks, it will also reduce the quality yield of the production line, thus causing inconvenience and trouble during production. Therefore, how to develop a production line technology that can integrate key process faults and error tree risk probability assessment technology to optimize production costs has become a technical issue that industry players in related technical fields are eager to solve and challenge.

In view of this, the above-mentioned conventional technologies are indeed not perfect, and there is still a need for further improvement. Moreover, based on the urgent needs of related industries, the inventor has finally developed an effective set of technology through continuous efforts in research and development. The present invention is different from the above-mentioned conventional technologies and previously disclosed patents.

The first object of the present invention is to provide a system and method for evaluating the risk probability of failure modes and failure trees of key processes in a production line. The main purpose is to use failure modes and failure analysis to find out the key processes and then introduce the failure tree to evaluate the potential of defective products due to failure. The loss probability and loss cost enable the production line's production cost to achieve optimal decision-making purposes and reduce production risks. The technical means to achieve the first purpose mentioned above include information processing modules. The information processing module configuration includes the failure mode and failure analysis module (FMEA) and the fault tree risk probability calculation module (FTA). The failure mode and failure analysis module (FMEA) includes a module with data to build possible faulty process steps, and the big data acquisition module includes a production line-side big data acquisition module. During the manufacturing process of the production line, failure mode and failure analysis modules are used to calculate multiple key processes of the production line. Import each key process into the error tree risk probability calculation module in order, and then the error tree risk probability calculation module will Evaluate and track the possible failure process steps of each key process to perform risk probability model decision-making and failure calculations to evaluate the risk probability information of the production line producing defective products due to failure, and use the risk probability information as a basis to identify high-risk key processes. Basis for decentralization or replanning. Among them, it also includes a big data acquisition module, an expected cost analysis module and an optimal cost analysis module. The failure mode and failure analysis module (FMEA) includes a data mapping module for possible faulty process steps. Big data acquisition The module includes a production line-side big data capture module. The production line-side big data capture module captures a plurality of process data of a plurality of key processes of the production line. The data classification module builds possible faulty process steps based on the plurality of process data. Then, the possible failure process steps of each key process are built, and the production line-side big data acquisition module is used to retrieve the scheduled improvement cost information of the possible failure process steps of each of the plurality of key processes in a database, and the expected cost The analysis module evaluates the expected improvement cost information of each possible failure process step of each of the plurality of critical processes based on the scheduled improvement cost information of the possible failure process steps; and the optimal cost analysis module evaluates the expected improvement cost information of each of the possible failure process steps based on each of the possible failure processes. The step improvement expected cost information is used to evaluate the size information of the improvement expected cost information of the possible faulty process steps of the plurality of critical processes, and information on the priority improvement order of the plurality of critical processes is generated according to the order of the size information.

The second purpose of the present invention is to provide a system and method for risk probability assessment of key process failure modes and failure trees of production lines that can disperse or re-plan high-risk processes and reduce future loss costs. Mainly, failure modes and failure analysis can be used After identifying the key processes, the error tree is introduced to evaluate the potential loss probability and loss cost of defective products due to failure, so that the production cost of the production line can be optimized for decision-making purposes and production risks can be reduced. The technical means to achieve the aforementioned second purpose include information processing modules. The information processing module configuration includes the failure mode and failure analysis module (FMEA) and the fault tree risk probability calculation module (FTA). During the manufacturing process of the production line, failure mode and failure analysis modules are used to calculate multiple key processes of the production line. close all Key manufacturing processes are sequentially imported into the error tree risk probability calculation module for evaluation, and each possible failure process step of each key process is tracked to perform risk probability model decision failure calculations to evaluate the production line. Information on the risk probability of defective products due to failure, and use the risk probability information as a basis for decentralizing or re-planning high-risk key processes. Among them, the information processing module further includes a decision feedback module, which is used to perform decentralized or re-planned calculations on the high-risk key process to obtain decision information for rebuilding the key process.

The third object of the present invention is to provide a production line key process failure mode and failure tree risk probability assessment system that can integrate production line end and user end data to more accurately evaluate the priority improvement order of possible failure process steps of key processes. method. The technical means to achieve the third purpose mentioned above, in addition to the basic technical features of the second stage of the purpose, the big data acquisition module also includes a user-side big data acquisition module; using the user-side big data acquisition module to acquire Obtain a plurality of product failure data of at least one user end; use the data to construct a possible faulty process step module. The module receives the plurality of product failure data and combines the plurality of process data of the production line to construct the production line. The plurality of critical processes and possible faulty process steps of each of the plurality of critical processes.

The fourth object of the present invention is to provide a wrench production line failure analysis method that applies the critical process failure mode and failure tree risk probability assessment system and method of the production line. The technical means to achieve the aforementioned fourth purpose include information processing modules. The information processing module configuration includes the failure mode and failure analysis module (FMEA) and the fault tree risk probability calculation module (FTA). During the manufacturing process of the production line, failure mode and failure analysis modules are used to calculate multiple key processes of the production line. Introduce each key process into the error tree risk probability calculation module in order, and then conduct the assessment by the error tree risk probability calculation module and track the possible failure process steps of each key process. Perform risk probability model decision-making failure calculation to evaluate the risk probability information of the production line producing defective products under failure, and use the risk probability information as the basis for decentralizing or re-planning high-risk key processes. Among them, during the manufacturing process of the wrench production line, the failure mode and failure analysis module (FMEA) was used to calculate a first critical process, a second critical process, a third critical process and a third critical process of the wrench production line. The fourth critical process, the first critical process includes heating, preliminary forging, precision forging and cutting and other possible faulty process steps, the second critical process includes possible faulty process steps such as forming, roller, annealing and punching, the third critical process includes The key process includes possible failure process steps such as turning and milling, grinding, heat treatment, and engraving. The fourth critical process includes possible failure process steps such as electroplating, sandblasting, assembly, and straightening. The first critical process to the fourth critical process are based on The program is imported into the error tree risk probability calculation module (FTA), so that the error tree risk probability calculation module (FTA) evaluates and tracks each possible failure process step from the first critical process to the fourth critical process. The risk probability model determines the failure calculation to evaluate the risk probability information of the wrench production line producing defective products under failure.

10:Information processing module

11: Failure Mode and Failure Analysis Module (FMEA)

12: Failure tree risk probability calculation module (FTA)

13: Decision feedback module

14:Big data acquisition module

140:Production line-side big data capture module

141:User-side big data acquisition module

15:Expected cost analysis module

16: Optimal cost analysis module

17:TRIZ evaluation module

20:Production line

30: First logic gate operation

31: Second logic gate operation

32: The third logic gate operation

Figure 1 is a specific schematic diagram of the implementation architecture of the system of the present invention.

Figure 2 is a schematic diagram of a process architecture for the implementation of the present invention.

Figure 3 is a schematic diagram of the steps of setting up the error tree risk probability calculation module in a specific implementation of the present invention.

Figure 4 is a schematic diagram of the steps of setting up the error tree risk probability calculation module in the application implementation of the present invention.

Figure 5 is a schematic diagram of the implementation of the present invention in calculating error tree risk probability in a hand tool wrench manufacturing process.

Figure 6 is a schematic diagram of the specific implementation process of using the key processes output by the failure mode and failure analysis module to import the error tree risk probability calculation module according to the present invention.

Figure 7 shows the key process introduction error tree risk based on the failure mode and failure analysis module output of the present invention. Schematic diagram of the system architecture of the probability calculation module.

In order to allow your review committee to further understand the overall technical characteristics of the present invention and the technical means to achieve the purpose of the present invention, specific embodiments are described in detail with the drawings as follows: Please refer to Figures 1 to 2. In order to achieve the purpose of the present invention, A first embodiment of the first object of the invention includes an information processing module 10. The information processing module 10 is configured to include a failure mode and failure analysis module (FMEA) 11 and a failure tree risk probability calculation module ( FTA) 12; The present invention mainly uses the failure mode and failure analysis module (FMEA) 11 to calculate multiple key processes of the production line 20 and the possible failure process steps of each key process in the manufacturing process of a production line 20. Then, the plurality of critical processes are sequentially introduced into the fault tree risk probability calculation module (FTA) 12, so that the fault tree risk probability calculation module (FTA) 12 conducts evaluation and tracks the possible faulty process steps of the plurality of critical processes. The risk probability model decision-making failure calculation is performed to evaluate the risk probability information of the production line 20 producing defective products under failure, and the risk probability information is used as a basis for decentralizing or re-planning high-risk key processes. Specifically, the risk probability information may be one of information on error risk probability and potential loss cost of defective products. Among them, the technical features of the present invention further include a large data acquisition module 14, an expected cost analysis module 15 and an optimal cost analysis module 16; the failure mode and failure analysis module (FMEA) includes a data regression module. Build a possible faulty process step module; the big data acquisition module 14 includes a production line-side big data acquisition module 140; use the production line-end big data acquisition module 140 to acquire the plurality of keys of the production line A plurality of process data of the production process; using the data to construct a possible faulty process step module, the module receives the plurality of process data of the production line captured by the production line-side big data acquisition module 140, and based on the plurality of processes The plurality of key processes of the production line and the number of each of the plurality of key processes are constructed based on the data. Possible failure process steps; the production line-side big data acquisition module 140 is used to retrieve the scheduled improvement cost information of the possible failure process steps of each of the plurality of key processes in a database; the expected cost analysis module 15 is based on the The production line-side big data acquisition module 140 captures the scheduled improvement cost information of each possible faulty process step of the plurality of critical processes, and evaluates the expected improvement cost information of each of the possible faulty process steps; and uses the most appropriate The cost analysis module 16 evaluates the size information of the improvement expected cost information of the possible failure process steps of the plurality of critical processes based on the improvement expected cost information of each possible failure process step, and generates the size information in the order of the size information. Information on the priority improvement order of multiple critical processes. The production line-side big data acquisition module 140 of the big data acquisition module 14 is used to acquire a plurality of process data of key processes of the production line (such as processing condition parameters of processing machines and sensing parameters of the processing status of processing machines: for example Parameters generated by sensing signals such as current, temperature, vibration, etc.). As shown in Figure 1, in a preferred embodiment of the present invention, the failure mode and failure analysis module (FMEA) is further combined with a TRIZ evaluation module 17 to analyze a plurality of key processes of a production line and each of the Possible failure process steps of multiple key processes. Among them, the application technology of TRIZ evaluation module 17 is as stated in the detailed description of the Republic of China Patent No. I643145, or as stated in the detailed description of the Republic of China Patent No. I627597. Technology defined in the scope of the patent application.

Please refer to FIG. 1 . In order to achieve the second purpose of the present invention, the second embodiment of the present invention includes, in addition to the overall technical content of the above-mentioned first embodiment, the information processing module 10 further includes a decision feedback module. Group 13, the decision feedback module 13 is used to perform decentralized or re-planned calculations on high-risk critical processes to obtain decision-making information for rebuilding critical processes.

Please refer to FIG. 1 . In order to achieve the third purpose of the present invention, the second embodiment, that is, a better embodiment of the present invention, is that the big data acquisition module 14 further includes a client big data acquisition module. 141; Use the client big data capture module 141 to capture at least one user A plurality of product failure data at the user end; using the data to construct a possible faulty process step module, the module receives the plurality of product failure data and combines the plurality of process data of the production line to construct the plurality of key points of the production line process and possible faulty process steps for each of the plurality of critical processes. That is to say, in this preferred embodiment, in addition to the production line-side big data acquisition module 140, the big data acquisition module 14 also includes a user-side big data acquisition module 141, so that the data can be The possible failure process step module integrates the plurality of product use failure data and the plurality of process data of the production line to more accurately construct the plurality of key processes of the production line and the possible failure process steps of each of the plurality of key processes.

Specifically, this embodiment is a first application embodiment based on the failure mode and failure analysis module (FMEA) 11 in the first embodiment. The failure mode and failure analysis module (FMEA) 11 is based on The risk priority coefficient method (RPN) is used to calculate the multiple key processes of the production line 20 and the possible failure process steps of each key process. The relationship of the risk priority coefficient method (RPN) is expressed as: RPN=O×D× S, where O is the frequency of occurrence, indicating the probability of failure; D is the difficulty of detection, indicating the chance that a product produced by the process will malfunction without being noticed or the difficulty of detection; S is the severity, indicating the process The consequences or opportunity costs caused by the failure of manufactured products.

For example, an application implementation of importance (S) is shown in Table 1: Table 1 Importance (S)

For example, an application implementation of occurrence frequency (O) is shown in Table 2:

For example, an application implementation of detection difficulty (D) is shown in Table 3:

，其中n為零組件同一嚴重等級失效模式的數目，Cm=β α λpt。在Cm中的各項因子為，β為失效效應機率；α為失效模式比)；λp為零件失效率；t為零件的作業時間。 Specifically, this embodiment is a second application embodiment based on the specific application of the failure mode and failure analysis module (FMEA) 11 in the first embodiment. The failure mode and failure analysis module (FMEA) 11 is based on Criticality analysis and criticality matrix method are used to calculate the plurality of critical processes of the production line 20 and the possible failure process steps of each critical process. The criticality value Cr of the component failure mode can be calculated by the criticality of all failure modes in the component. The relationship between the criticality analysis and the criticality matrix method is expressed as:

, where n is the number of failure modes of the same severity level of components, Cm=β α λpt. The factors in Cm are: β is the probability of failure effect; α is the failure mode ratio); λp is the failure rate of the part; t is the operating time of the part.

Please refer to Figures 3 and 6. This embodiment is a third application embodiment based on the specific application of the error tree risk probability calculation module (FTA) in the first embodiment. The error tree risk probability calculation module Group (FTA) 12 includes a fault tree risk probability calculation module (FTA) construction step, which includes the following steps:

Step 1: Define multiple error risk factors for each processing step of multiple critical processes imported into the Failure Mode and Failure Analysis Module (FMEA) 11.

Step 2: Preset the value of each error risk factor for each processing step;

Step 3: Perform the first logic gate operation 30 on each error risk factor of each processing step to obtain the error risk value of a possible faulty process step for each processing step.

Step 4: Perform the second logic gate operation 31 on the error risk value of each processing step to obtain the process error risk value of each process.

Step 5: Perform a third logic gate operation 32 on each process error risk value of each process to obtain risk probability information of the production line 20 .

Specifically, this embodiment is a preferred embodiment based on the specific application described in the above-mentioned third embodiment. The first logic gate operation 30 is selected from one of the AND gate and the OR gate. operation; the second logic gate operation 31 is an OR gate (OR GATE) operation; the The third logic gate operation 32 is an AND gate (AND GATE) operation.

Please refer to FIG. 5 . This embodiment is a specific example of an application for calculating the error tree risk probability A of the hand tool wrench manufacturing defect rate risk assessment, in which the error tree risk of the hand tool wrench manufacturing defect rate risk assessment is used. The probability A is calculated as follows: A=X×Y×Z.

A=(X1+X2)(Y1+B3)(Z1+B3).

A=(X1+X2)×(Y1+Y21+Y22)×Z.

A= [(B1+X11)+(B3+X21)] × [(Y11+Y12)+B3] × [(Z11+Z12)+B3] .

A= [(B1+B2+B1)+(B3+B1+B2)] × [(B3+B2)+B3] × [(B4+B2)+B3] .

A=[B1+B2+B3]×[B2+B3]×[B2+B3+B4].

A=[0.1+0.5+0.3]×[0.5+0.3]×[0.5+0.3+0.05].

A=0.9×0.8×0.85.

A=(B2+B3+B4+B5+B6×B1.

A=(0.1+0.1+0.02+0.01+0.01)×0.2. Finally, the risk probability of the above event is calculated as A=0.612.

Please refer to Figures 4 and 6. In order to achieve the third purpose of the present invention, a third embodiment is shown. In addition to the overall technical content of the above-mentioned first embodiment, this embodiment is also included in the manufacturing process of the wrench production line. Use the Failure Mode and Failure Analysis Module (FMEA) 11 to calculate a first critical process, a second critical process, a third critical process and a fourth critical process of the wrench production line. The first critical process includes heating , preliminary forging, precision forging and cutting and other possible faulty process steps. The second critical process includes possible faulty process steps such as forming, roller, annealing and punching. The third critical process includes turning and milling, grinding, heat treatment and engraving. Possible faulty process step, the fourth critical The process includes possible failure process steps such as electroplating, sandblasting, assembly and straightening; the first critical process to the fourth critical process are sequentially imported into the fault tree risk probability calculation module (FTA) 12 to calculate the risk probability from the fault tree. Group (FTA) 12 evaluates and tracks each possible failure process step from the first critical process to the fourth critical process to perform risk probability model decision-making failure calculations to evaluate the risk probability information of the wrench production line producing defective products due to failure.

Please refer to Figures 4 and 6. This embodiment is a fourth application embodiment based on the specific application of the error tree risk probability calculation module (FTA) in the third embodiment. The error tree risk probability calculation module Group (FTA) 12 includes a fault tree risk probability calculation module (FTA) construction step, which includes the following steps:

Step 1: Define multiple error risk factors for each processing step from the first critical process to the fourth critical process imported into the failure mode and failure analysis module (FMEA) 11 .

Step 2: Pre-set the value of each error risk factor for each processing step.

Step 3: Perform the first logic gate operation 30 on each error risk factor of each processing step to obtain the processing step error risk value of each processing step.

Step 4: Perform a second logic gate operation 31 on each processing step error risk value of each processing step to obtain each process error risk value from the first critical process to the fourth critical process.

Step 5: Perform a third logic gate operation 32 on each process error risk value from the first critical process to the fourth critical process to obtain risk probability information of the wrench process producing defective products.

In addition, P01~P32 shown at the bottom of Figure 6 represent multiple error risk factors that have been defined.

Please refer to FIG. 6 . This embodiment is a preferred embodiment based on the fourth application embodiment described above. The first logic gate operation 30 is selected from the AND gate (AND GATE) and the OR gate ( OR GATE); the second logic gate operation 31 is an OR gate. (OR GATE) operation; the third logic gate operation 33 is an AND gate (AND GATE) operation.

In addition, the failure mode and failure analysis calculates the main key process, and the key process of the target Q1(A) FMEA is expressed as, RPN1=S1×O1×D1, RPN2=S2×O1×D2, RPNm=Sm×Om×Dm, the key (key)RPN=max[RPN1,RPN2,...RPNm]. Secondly, the risk probability of the main key process error tree is calculated. The target Q2(B) FTA is expressed as, and the risk probability (Risk probability) is expressed as, P=(x1 or x2 or x3)and(y1 or y2 or y3)and(z1 or z2).

The objective function of minimizing manufacturing cost for the main key process of objective Q3(C) is expressed as; Cost MIN Z=C ₁ X ₁ +C ₂ X ₂ +…….+C _n X _n

Restricted formula a ₁₁ X ₁ +a ₁₂ X ₂ +……+a _1n X _n >b ₁

Restricted formula a ₂₁ X ₁ +a ₂₂ X ₂ +……+a _2n X _n >b ₂

Restricted formula a _m1 X ₁ +a _m2 X ₂ +……+a _mn X _n >b _m

The import of multiple targets (targets Q1, Q2, Q3) is expressed as, MAX

Z(Q1,Q2,Q3)=[Q1(x1,x2,x3….Xn),Q2((x1,x2,x3….Xn),Q3(x1,x2,x3….Xn)]

Restricted formula a ₁₁ X ₁ +a ₁₂ X ₂ +……+a _1n X _n >b _m

Restricted formula a _m1 X ₁ +a _m2 X ₂ +……+a _mn X _n >b _m

Please refer to Figure 7, which is a system architecture implementation diagram of the present invention using the key process output of the failure mode and failure analysis module to introduce the error tree risk probability calculation module. The failure analysis module (FMEA) includes equipment function analysis, process Steps such as processing mode analysis and statistical failure analysis to determine key processes. As for the fault tree risk probability calculation module (FTA), it includes steps such as selecting key events, establishing fault trees, and minimum risk cut set fault trees.

Therefore, after the detailed description of the above specific embodiments, the present invention does have the following characteristics:

1. This invention can indeed use fault mode and failure analysis to find out key processes and then introduce a fault tree to evaluate the potential loss probability and loss cost of defective products under failure, so that the production cost of the production line can be optimized and the decision-making purpose can be reduced. risk.

2. This invention can indeed decentralize or re-plan high-risk processes to reduce future loss costs.

3. The present invention is indeed a wrench production line failure analysis method that applies the key process failure mode of the production line and the failure analysis link failure tree risk probability assessment model of the cost optimization decision-making system to optimize the production cost of the wrench production line. decision-making purpose.

The above is only a relatively feasible embodiment of the present invention, and is not intended to limit the patent scope of the present invention. Any equivalent implementation of other changes based on the content, features and spirit described in the following claims, All should be included in the patent scope of the present invention. The structural features specifically defined in the claim of the present invention have not been found in similar articles, and are practical and progressive. They have met the requirements for an invention patent. I file an application in accordance with the law. I sincerely request the Office to approve the patent in accordance with the law to protect this invention. The legitimate rights and interests of the applicant.

10:Information processing module

11: Failure Mode and Failure Analysis Module (FMEA)

12: Failure tree risk probability calculation module (FTA)

13: Decision feedback module

14:Big data acquisition module

140:Production line-side big data capture module

141:User-side big data acquisition module

20:Production line

Claims (10)

A production line critical process failure mode and failure tree risk probability assessment system, including: an information processing module; the information processing module configuration includes a failure mode and failure analysis module (FMEA) and a failure tree risk probability calculation module group (FTA); the failure mode and failure analysis module (FMEA) is used to analyze a plurality of critical processes of a production line and the possible failure process steps of each of the plurality of critical processes; the failure tree risk probability calculation module (FTA) ) is used to import the possible failure process steps of each of the plurality of critical processes for evaluation, and track the possible failure process steps of the plurality of critical processes to perform risk probability model decision-making failure calculations to evaluate the failure of the production line. The risk probability information of defective products is generated, and the risk probability information is used as the basis for decentralizing or re-planning the high-risk key process; it is characterized by: it also includes a large data acquisition module and an expected cost analysis module. and an optimal cost analysis module; the failure mode and failure analysis module (FMEA) includes a data mapping module for possible failure process steps; the big data acquisition module includes a production line-side big data acquisition module; The production line end big data acquisition module is used to retrieve a plurality of process data of the plurality of key processes of the production line from a database; the data is compiled into a possible fault process step module to receive the production line end The plurality of process data of the production line is captured by the big data acquisition module, and based on the plurality of process data, the plurality of key processes of the production line and the possible fault processes of each of the plurality of key processes are constructed Steps; the production line-end big data acquisition module is used to retrieve scheduled improvement cost information of each possible failure process step of the plurality of key processes from a database; the expected cost analysis module is based on the production line-end big data acquisition module. The data acquisition module acquires the scheduled improvement cost information of each possible failure process step of the plurality of critical processes, and evaluates the expected improvement cost information of each possible failure process step; and the optimal cost analysis module is based on each possible failure process step. A possible faulty process The step improvement expected cost information is used to evaluate the size information of the improvement expected cost information of the possible faulty process steps of the plurality of critical processes, and information on the priority improvement order of the plurality of critical processes is generated according to the order of the size information. The production line key process failure mode and failure tree risk probability assessment system as described in claim 1, wherein the big data acquisition module further includes a client big data acquisition module; with the client big data acquisition The module captures a plurality of product failure data of at least one user end; uses the data to construct a possible faulty process step. The module receives the plurality of product failure data and combines the plurality of process data of the production line to construct the process step. The plurality of critical processes of the production line and the possible faulty process steps of each of the plurality of critical processes. The production line key process failure mode and failure tree risk probability assessment system as described in claim 1, wherein the information processing module further includes a decision feedback module, and the decision feedback module is used to classify the high-risk key process Perform decentralized or re-planned calculations to obtain decision-making information for rebuilding this critical process. The critical process failure mode and failure tree risk probability assessment system of the production line as described in claim 1, wherein the failure mode and failure analysis module (FMEA) uses the risk priority method (RPN) to calculate the risk probability of the production line. For the plurality of critical processes and the possible failure process steps of each of the plurality of critical processes, the relationship of the risk priority coefficient method (RPN) is expressed as: RPN=O×D×S, where O is the frequency of occurrence and represents the failure. The probability of occurrence; D is the difficulty of detection, which indicates the chance that the product produced by the process will malfunction without being noticed or the difficulty of detection; S is the severity, indicating the consequences caused by the failure of the product produced by the process or Opportunity cost; the failure mode and failure analysis module (FMEA) uses criticality analysis and criticality matrix methods to calculate the plurality of critical processes of the production line and the possible failure process steps of each of the plurality of critical processes, The criticality value Cr of the component failure mode can be obtained by summing the criticality values (Cm) of all failure modes in the component. The relationship between the criticality analysis and the criticality matrix method is expressed as:

, where n is the number of failure modes of the same severity level of components, Cm=β α λpt. The various factors in Cm are: β is the probability of failure effect; α is the failure mode ratio); λp is the failure rate of the part; t is the operating time of the part. The production line critical process failure mode and failure tree risk probability assessment system as described in claim 1, wherein the failure tree risk probability calculation module (FTA) includes a failure tree risk probability calculation module (FTA) building step, It includes the following steps: Step 1, import the failure mode and failure analysis module (FMEA) to define multiple error risk factors for each processing step of the critical process; Step 2, pre-set each processing step for each The value of the error risk factor; Step 3: Perform the first logic gate operation on each error risk factor of each processing step to obtain the processing step error risk value of each processing step; Step 4: Calculate the error risk value of each processing step. 1. Perform a second logic gate operation on the error risk value of each processing step to obtain the process error risk value of each process; and step 5, combine the process error risk value of each process The third logic gate operation is performed to obtain the risk probability information of the production line. The production line key process failure mode and failure tree risk probability assessment system as described in claim 1, wherein the big data acquisition module further includes a client big data acquisition module; with the client big data acquisition The module captures a plurality of product failure data of at least one user end; uses the data to construct a possible faulty process step. The module receives the plurality of product failure data and combines the plurality of process data of the production line to construct the process step. The plurality of critical processes of the production line and the possible faulty process steps of each of the plurality of critical processes. A cost-optimization decision-making system for linking the failure mode and failure analysis of critical production lines to the failure tree risk probability assessment model as described in request 1, wherein the failure mode and failure analysis module (FMEA) is further combined with a TRIZ assessment The module is used to analyze multiple critical processes of a production line and the possible faulty process steps of each of the multiple critical processes. A method for assessing the risk probability of production line critical process failure modes and failure trees using the system described in claim 1, which includes: providing the information processing module; the information processing module configuration includes the failure mode and failure analysis module (FMEA) and the failure tree risk probability calculation module (FTA); use the failure mode and failure analysis module (FMEA) to analyze the multiple critical processes of the production line and the possible fault processes of each of the multiple critical processes Steps: Import the possible failure process steps of each of the plurality of critical processes into the error tree risk probability calculation module (FTA) in sequence, use the error tree risk probability calculation module (FTA) to evaluate, and track the plurality of critical processes Perform risk probability model decision-making failure calculations on each possible failure process step of the process to evaluate the risk probability information of the production line producing defective products under failure, and use the risk probability information as a way to disperse the high-risk key processes Or the basis for re-planning; it is characterized in that: it further includes the big data acquisition module, the expected cost analysis module and the optimal cost analysis module; the failure mode and failure analysis module (FMEA) includes the The data is returned to build a module for possible faulty process steps; the big data acquisition module includes the production line-side big data acquisition module; the production line-end big data acquisition module is used to capture the plurality of key processes of the production line A plurality of process data; using the data to construct a possible faulty process step module, the module receives the plurality of process data of the production line captured by the production line-side big data acquisition module, and based on the plurality of process data The plurality of critical processes of the production line and the possible faulty processes of each of the plurality of critical processes are constructed. Steps; use the production line-end big data acquisition module to acquire scheduled improvement cost information of possible failure process steps of each of the plurality of key processes in a database; the expected cost analysis module is based on the production line-end big data acquisition Obtain the scheduled improvement cost information of each possible failure process step of the plurality of critical processes captured by the module, and evaluate the expected improvement cost information of each possible failure process step; and use the optimal cost analysis module according to each The scheduled improvement cost information of the possible failure process steps is used to evaluate the size information of the expected improvement cost information of the possible failure process steps of the plurality of critical processes, and the priority improvement order of the plurality of critical processes is generated according to the order of the size information. information. A failure analysis method for a wrench production line using the method described in claim 8, which includes: during the manufacturing process of a wrench production line, using the failure mode and failure analysis module (FMEA) to calculate the wrench production line A first critical process, a second critical process, a third critical process and a fourth critical process of the line. The first critical process includes heating, preliminary forging, precision forging and cutting and other possible faulty process steps. The third critical process The second critical process includes possible faulty process steps such as molding, roller, annealing and punching. The third critical process includes possible faulty process steps such as turning and milling, grinding, heat treatment and engraving. The fourth critical process includes electroplating, sandblasting, assembly and Straightening possible faulty process steps; and sequentially importing the first critical process to the fourth critical process into the error tree risk probability calculation module (FTA), so that the error tree risk probability calculation module (FTA) Evaluate and track each possible failure process step from the first critical process to the fourth critical process to perform risk probability model decision-making failure calculations to evaluate the risk probability information of the wrench production line producing defective products under failure. The wrench production line failure analysis method as described in claim 9, wherein the fault tree risk probability calculation module (FTA) includes a fault tree risk probability calculation module (FTA) building step, which includes It includes the following steps: Step 1: Define multiple error risk factors for each processing step from the first critical process to the fourth critical process imported into the failure mode and failure analysis module (FMEA); Step 2: Pre-set each process step 1. The value of each error risk factor of the processing step; Step 3: Perform a first logic gate operation on each error risk factor of each processing step to obtain the processing step error risk value of each processing step ; Step 4: Perform a second logic gate operation on the error risk value of each processing step to obtain the process error risk value from the first critical process to the fourth critical process; and Step 5, Perform a third logic gate operation on each process error risk value from the first critical process to the fourth critical process to obtain risk probability information of the wrench process producing defective products.

Images