Production and manufacturing risk monitoring method and device, vehicle, medium and product

Abstract

The invention relates to the technical field of automobile production, in particular to a production and manufacturing risk monitoring method and device, a vehicle, a medium and a product, and the method comprises the steps: obtaining production operation data of a plurality of production and manufacturing processes of a power battery; predicting production and manufacturing risks of the production and manufacturing processes according to the production operation data, and generating a risk list according to the plurality of production and manufacturing processes and the corresponding production and manufacturing risks; predicting a risk evolution process and a failure mode of the manufacturing process according to the risk factor data of the manufacturing process, and determining risk levels of different risks according to the risk evolution process and the failure mode; and generating a risk identification and management and control list according to the risk list and the risk levels of the different risks, and monitoring the production and manufacturing risks of the power battery in the plurality of production and manufacturing processes by using the risk identification and management and control list and the actual production and manufacturing data. Therefore, the problems of lack of systematic risk identification methods, incapability of quantifying risk points and the like in the prior art are solved.

Description

Technical Field

[0001] The present application relates to the field of automobile production technology, and in particular to a method, device, vehicle, medium and product for monitoring production and manufacturing risks. Background Art

[0002] The new energy vehicle industry has developed rapidly in recent years, but with it comes the safety risk issues in the production and manufacturing process, especially the safety performance of power batteries, which has become the key. Power batteries may cause serious accidents due to thermal runaway during production, storage, transportation and use, posing a threat to personnel, property and the environment.

[0003] In the existing technology, the safety risk control in the production and manufacturing process of new energy vehicles is mostly focused on the analysis and response of a single link or a single factor, lacking a systematic and comprehensive risk identification and control strategy. In particular, in the prevention and control of thermal runaway of power batteries, although there have been some research results and technical means, most of them focus on post-processing and emergency response, lacking a comprehensive solution for pre-prevention and in-process control; in addition, the risk identification and control in the production and manufacturing process of new energy vehicles still faces many challenges, such as complex production processes, many equipment involved, and different operating levels of personnel, all of which increase the possibility and complexity of risk occurrence. Summary of the invention

[0004] The present application provides a method, device, vehicle, medium and product for monitoring production and manufacturing risks to solve the problems in the prior art such as lack of a systematic risk identification method and inability to quantify risk points.

[0005] The first aspect of the present application provides a method for monitoring production risks, comprising the following steps: acquiring production operation data of multiple production processes of power batteries; predicting the production risks of the production processes based on the production operation data, and generating a risk list based on multiple production processes and corresponding production risks; predicting the risk evolution process and failure mode of the production processes based on the risk factor data of the production processes, and determining the risk levels of different risks based on the risk evolution process and failure mode; generating a risk identification and control list based on the risk list and the risk levels of different risks, and using the risk identification and control list and actual production data to monitor the production risks of power batteries in multiple production processes.

[0006] Optionally, the production and manufacturing risks of the production and manufacturing processes are predicted based on the production operation data, and a risk list is generated based on multiple production and manufacturing processes and the corresponding production and manufacturing risks, including: decomposing the production and manufacturing processes based on the work hazard analysis method to obtain detailed processes, finding dangerous work steps, and identifying the risks of the detailed processes, wherein the work steps include the division of work activities, decomposition selection, hazard source identification, etc.; calculating the risk weights of the risks of the detailed processes based on the production operation historical data and expert judgment; and generating a risk list based on the risk weights, the detailed processes and the corresponding risks.

[0007] Optionally, the risk evolution process and failure mode of the production and manufacturing process are predicted based on the risk factor data of the production and manufacturing process, including: obtaining the hazard source and analyzing the risk cause; determining the path of the risk evolving into an accident based on the hazard source and the risk inducing cause, and determining the target control point based on the risk path; determining the risk evolution speed based on historical production operation data and expert judgment, and determining the duration after the risk gets out of control based on the speed of the risk evolution accident; assessing the risk based on the target control point, the duration after the risk gets out of control and the consequences caused by the risk, and determining the risk level based on the operating condition hazard analysis method; determining the failure mode based on the risk level and expert judgment.

[0008] Optionally, the risk identification and control list and actual production data are used to monitor the production risks of power batteries in multiple production processes, including: identifying the current power, current temperature and target gas concentration in the actual production data; using the current power, current temperature and target gas concentration as indexes to query the risk identification and control list to obtain the production risk level of the current production process; determining the thermal runaway protection strategy of the current production process according to the production risk level.

[0009] Optionally, the thermal runaway protection strategy includes at least one of an engineering technology strategy, a safety management strategy, a training and education strategy, an individual protection strategy and an emergency response strategy, wherein the engineering technology strategy includes: setting up insulating covers at assembly and disassembly positions, setting up automatic temperature sensors at target locations and setting up fork protection covers at manual transfer positions; the safety management strategy includes: revising operating procedures, setting up a double insurance mechanism, and specifying the number of storage layers and stacking spacing in the storage area; the training and education measures include: forklift drivers and electricians holding certificates and special position training; individual protection measures include: wearing insulating shoes when entering the battery assembly workshop, wearing arc-proof clothing when disassembling the battery cells, and wearing insulating gloves when working with electricity; emergency response measures include: establishing emergency plans and conducting regular drills and evaluations, as well as equipping with emergency supplies.

[0010] Optionally, the production operation data includes at least one of tool equipment data, raw material data and personnel action data.

[0011] The second aspect of the present application provides a device for monitoring production risks, including: an acquisition module for acquiring production operation data of multiple production processes of power batteries; a generation module for predicting the production risks of the production processes based on the production operation data, and generating a risk list based on multiple production processes and corresponding production risks; a determination module for predicting the risk evolution process and failure mode of the production processes based on the risk factor data of the production processes, and determining the risk levels of different risks based on the risk evolution process and failure mode; a monitoring module for generating a risk identification and control list based on the risk list and the risk levels of different risks, and using the risk identification and control list and actual production data to monitor the production risks of power batteries in multiple production processes.

[0012] A third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for monitoring production risks as described in the above embodiment.

[0013] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement a method for monitoring production risks as described in the above-mentioned embodiment.

[0014] The fifth aspect of the present application provides a computer program product, including a computer program or instructions, for implementing a method for monitoring production risks as described in the above embodiment.

[0015] Therefore, this application includes the following beneficial effects:

[0016] The embodiments of the present application analyze production operation data in depth, accurately identify the risk sources, causes and potential consequences in each process of power battery production and manufacturing, quantify the risk level, implement risk prediction and evolution analysis, grasp the entire process from risk occurrence to disappearance, and clarify the risk failure mode; build a risk and control list, comprehensively cover various risk points in the production process, quickly locate risks, and implement targeted control measures. At the same time, a real-time monitoring and dynamic adjustment mechanism is introduced to ensure the effectiveness and adaptability of risk control measures and to ensure the safety and quality of power battery production. As a result, technical problems such as the lack of a systematic risk identification method and the inability to quantify risk points in the prior art are solved.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 A flowchart of a method for monitoring production risks provided according to an embodiment of the present application;

[0020] Figure 2 A diagram of a risk identification and analysis process for power battery storage provided according to an embodiment of the present application;

[0021] Figure 3 A schematic diagram of a power battery combustion result provided according to an embodiment of the present application;

[0022] Figure 4 A schematic diagram of a combustion result caused by inducing thermal runaway according to an embodiment of the present application;

[0023] Figure 5 A schematic diagram of temperature and gas concentration changes according to an embodiment of the present application;

[0024] Figure 6 A schematic diagram of the cause of thermal runaway and the safety risk model provided according to an embodiment of the present application;

[0025] Figure 7 A schematic diagram of a monitoring device for production and manufacturing risks provided in an embodiment of the present application;

[0026] Figure 8 It is a schematic diagram of the structure of a vehicle according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0028] The following describes the monitoring method, device, vehicle, medium and product of the production and manufacturing risks of the embodiments of the present application with reference to the accompanying drawings. In view of the safety management issues in the production and manufacturing process mentioned in the above background technology, the present application provides a monitoring method for production and manufacturing risks. In this method, by deeply analyzing the production operation data, the risk sources, inducements and potential consequences in each process of power battery production and manufacturing are accurately identified, and the risk level is quantified, and risk prediction and evolution analysis are implemented to grasp the whole process from the occurrence to the disappearance of the risk, and clarify the risk failure mode; build a risk and control list, comprehensively cover various risk points in the production process, quickly locate risks, and implement targeted control measures. At the same time, a real-time monitoring and dynamic adjustment mechanism is introduced to ensure the effectiveness and adaptability of risk control measures and ensure the safety and quality of power battery production. As a result, the problems of lack of systematic risk identification methods and inability to quantify risk points in the prior art are solved.

[0029] Specifically, Figure 1 A flow chart of a method for monitoring production risks provided in an embodiment of the present application.

[0030] like Figure 1 As shown, the method for monitoring production risks includes the following steps:

[0031] In step S101 , production operation data of multiple production processes of a power battery are obtained.

[0032] The production operation data may include at least one of tool equipment data, raw material data and personnel action data.

[0033] It can be understood that the embodiment of the present application obtains production operation data of multiple production and manufacturing processes of power batteries, which facilitates the subsequent quantification of risk levels based on the possibility of risk occurrence and the severity of consequences.

[0034] In step S102, the production and manufacturing risks of the production and manufacturing processes are predicted according to the production operation data, and a risk list is generated according to a plurality of production and manufacturing processes and the corresponding production and manufacturing risks.

[0035] It can be understood that the embodiments of the present application can accurately assess the risk level of the production process through real-time monitoring and analysis of production operation data, timely discover potential risk factors in the production process, and effectively control the risk factors in the production process.

[0036] In an embodiment of the present application, the production and manufacturing risks of the production and manufacturing processes are predicted based on the production operation data, and a risk list is generated based on multiple production and manufacturing processes and the corresponding production and manufacturing risks, including: disassembling the production and manufacturing processes based on the work hazard analysis method to obtain detailed processes, finding out the dangerous work steps, and identifying the risks of the detailed processes, wherein the work steps include the division of work activities, decomposition selection, hazard source identification, etc.; calculating the risk weights of the risks of the detailed processes based on the production operation historical data and expert judgment; and generating a risk list based on the risk weights, the detailed processes and the corresponding risks.

[0037] It is understandable that the embodiments of the present application can more clearly understand the specific content and operation details of each step by breaking down the production process into more detailed work steps, identify the potential dangers and harmful factors that may exist in each step, and use the historical data of production operations and expert judgment to quantitatively evaluate the identified risks and calculate their risk weights. Based on the risk weights, detailed processes and corresponding risks, a detailed risk list is generated, which helps to strengthen production safety management.

[0038] Specifically, the work hazard analysis method was used to gradually disassemble 24 production and manufacturing processes such as battery module transportation, battery assembly, battery testing, battery transportation, and battery assembly, to find out the work steps where the above hazards exist, analyze the tools, equipment, raw materials, and personnel actions used in each process, and use the "three-part argument" method to accurately describe the risks. Then, the safety operation observation method was used on site to supplement and improve the analysis results, and a total of 115 safety risks were identified. Taking the power battery storage process as an example, Figure 2 As shown in the figure, the transport vehicle arrives at the designated location in the warehouse; the vehicle is turned off, the forklift driver confirms the safety conditions and loads and unloads the power battery; the forklift is transported to the designated storage location in the warehouse, loaded and unloaded, and transferred and stacked according to the rules; the warehouse manager conducts daily inspections. Analyze the hazards that can be caused by each step of the operation, and describe them with "three-part argument", which are summarized into two risks: 1. During the storage process, the ambient temperature is too high, the factory building leaks, and the ventilation is poor, which induces thermal runaway of the battery, causing the battery to smoke, catch fire, and leak electrolyte; 2. During the forklift fork picking or transportation process, the fork picking position is wrong and the fork is not stable, resulting in external damage or falling of the battery, causing thermal runaway of the battery. Then go to the site to use the safe operation observation method to supplement and improve the results of the analysis, and find that the risk of "people wiping the battery surface with a wet rag will cause electric shock to people" was not identified. After that, the 23 processes were identified and analyzed using the same idea to form a risk list.

[0039] In step S103, the risk evolution process and failure mode of the production and manufacturing process are predicted based on the risk factor data of the production and manufacturing process, and the risk levels of different risks are determined based on the risk evolution process and failure mode.

[0040] Among them, the risk evolution process can refer to the entire development and change process from the emergence of risk factors to their ultimate leading to production accidents or failure modes. Failure mode refers to the specific way in which a certain link in the production and manufacturing process fails to perform as expected, resulting in reduced product quality, reduced production efficiency or safety accidents. Among them, it can manifest in various forms such as equipment failure, process deviation, material defects, etc. The risk levels can include low risk, medium risk and high risk.

[0041] It is understandable that the embodiments of the present application achieve proactive prevention of potential production problems by accurately predicting the evolution of risks and failure modes in the production process, effectively avoiding production interruptions and rework, and significantly improving production efficiency and product quality. At the same time, based on in-depth analysis of risk data, it is possible to optimize production processes and manage resources in a refined manner. In addition, by clarifying the risk level, it is possible to formulate targeted risk management strategies, effectively reduce direct economic losses caused by production failures, and reduce overall risk costs.

[0042] In an embodiment of the present application, the risk evolution process and failure mode of the production and manufacturing process are predicted based on the risk factor data of the production and manufacturing process, including: obtaining the hazard source and analyzing the risk cause; determining the path of the risk evolving into an accident based on the hazard source and the risk inducing cause, and determining the target control point based on the risk path; determining the risk evolution speed based on historical production operation data and expert judgment, and determining the duration after the risk gets out of control based on the speed of the risk evolution accident; assessing the risk based on the target control point, the duration after the risk gets out of control and the consequences caused by the risk, and determining the risk level based on the operating condition hazard analysis method; determining the failure mode based on the risk level and expert judgment.

[0043] Among them, the hazard source can refer to the source or starting point that may cause the risk, the risk cause can be the specific cause or condition that directly leads to the risk event, such as sudden failure of equipment due to long-term lack of maintenance, wrong operation caused by operators not following procedures, etc. The consequence of the risk can refer to the negative impact or loss caused by the risk event, which can include production interruption, product quality decline, equipment damage, casualties, economic losses, etc.

[0044] The risk path can be the complete process starting from the risk source, going through a series of risk-inducing causes, and finally leading to the occurrence of a risk event. The target control point can be the key link in the occurrence of a risk event. The risk evolution speed can be said to be the speed at which the risk is generated, developed, expanded, and finally occurs.

[0045] It is understandable that the embodiments of the present application have achieved accurate quantitative assessment of risks and avoided one-sided analysis by comprehensively considering the sources of danger, inducing factors and consequences, combined with scientific assessment methods. At the same time, the risk paths and key control points are clarified, and targeted risk control and emergency measures are formulated to effectively reduce the probability and impact of risk. In addition, it also promotes the improvement of production efficiency and product quality, reduces production interruptions and waste by preventing risks and optimizing production processes, achieves the reduction of production costs and the reasonable control of risk costs, and ensures the efficient use of resources.

[0046] Specifically, the risk evolution process and its failure mode are analyzed by comprehensively considering the causes, inducing causes of accidents, harmful substances, and injury methods. The possibility of risk occurrence, the time of risk exposure, and the serious consequences of risks are evaluated using the operating condition hazard analysis method. Risks are quantitatively evaluated and risk levels are determined. By analyzing key positions such as module grabbing, module assembly, and multiple parts assembly packages going online, it is found that the risk caused by internal short circuits in the battery assembly workshop is high; the risk caused by misoperation by personnel in the maintenance area is high; and the risk caused by internal short circuits in the module transfer area and power battery storage area is high. According to the level of risk and risk type, the fuzzy hierarchical analysis method is applied to focus the control on thermal runaway and arc burning caused by internal short circuits in batteries, and a risk identification and control list is formed.

[0047] In step S104, a risk identification and control list is generated according to the risk list and the risk levels of different risks, and the risk identification and control list and actual production data are used to monitor the production risks of power batteries in multiple production processes.

[0048] It can be understood that the embodiments of the present application can significantly improve the risk management level of the power battery production process, enhance the pertinence and effectiveness of risk control, improve production efficiency and product quality, and reduce production costs and risk costs by generating a risk identification and control list and performing risk monitoring in combination with actual production data.

[0049] In an embodiment of the present application, a risk identification and control list and actual production data are used to monitor the production risks of power batteries in multiple production processes, including: identifying the current power, current temperature and target gas concentration in the actual production data; using the current power, current temperature and target gas concentration as indexes, querying the risk identification and control list to obtain the production risk level of the current production process; determining the thermal runaway protection strategy of the current production process according to the production risk level.

[0050] Among them, the thermal runaway protection strategy may include at least one of an engineering technology strategy, a safety management strategy, a training and education strategy, a personal protection strategy, and an emergency response strategy.

[0051] It is understandable that the embodiments of the present application achieve real-time and accurate risk identification by real-time monitoring of key parameters in power battery production, avoiding the lag and subjectivity of traditional methods. Based on the risk assessment results, the thermal runaway protection strategy is optimized and dynamically adjusted to ensure production safety and improve efficiency. At the same time, thermal runaway accidents are effectively prevented, the defective product rate is reduced, and production safety and product quality are significantly improved.

[0052] Specifically, formulate an experimental plan for thermal runaway reaction of power batteries, study the impact and harm of thermal runaway caused by different reasons on the combustion process; measure the temperature change of thermal runaway reaction process of power batteries at the fire source. During the experiment, install a temperature sensor probe on the module inside the power battery, calculate the occurrence of thermal runaway through temperature change, and conduct the following experiments respectively.

[0053] Experiment 1: Select a type A power battery with SOC 80% and a type A power battery with SOC 30%, use the same fire source to heat them, and start timing when the open flame is caused by thermal runaway. Figure 3 As shown, the power battery with SOC80% continues to burn for 47 minutes, and the power battery with SOC30% continues to burn for 12 minutes. The duration of power battery combustion is proportional to its remaining power.

[0054] Experiment 2: Three A-type power batteries were subjected to external puncture, overcharging, and external heating respectively, resulting in three situations of thermal runaway induced by internal short circuit, overcharging, and external heating. The power batteries were heated using the same fire source, and the internal temperature of the batteries and the time it took to generate open flames were measured. Figure 4 As shown, the SEI film inside the power battery that was punctured from the outside was damaged first, followed by overcharging and external heating. The time required for an open flame to occur was measured to be 10 seconds, 60 seconds, and 600 seconds, respectively. Therefore, the time required to ignite the power battery is inversely proportional to the destruction rate of the SEI film inside the battery cell.

[0055] Experiment 3: A thermocouple was installed in module A inside a power battery to form a continuous heating experimental condition. Temperature sensor probes and gas concentration monitoring probes were installed at the thermocouple, module A near the battery cell, and module B near module A to measure the temperature changes at different locations inside the battery under continuous heating conditions and the types and concentrations of released gases. The measurement results are shown in the figure. Figure 5As shown, after 30 minutes of heating, the temperature of module A exceeded the thermocouple temperature, and rose rapidly in the next 10 minutes, and thermal runaway reaction began to occur. At 40 minutes, the temperature of module A reached 500°C and continued to maintain a high temperature state. The inside began to burn and gradually released gases such as C2H2, PH5, CH4, H2, and CO. At 50 minutes, the concentration of the released gas reached a peak and began to decrease, proving that the combustion reaction was violent and the released combustible gas was burned. The temperature of the surrounding module B rose rapidly, began to burn, and produced a large amount of open flames, indicating that the combustion form had spread.

[0056] In summary, the thermal runaway caused by the internal short circuit is the first to burn and reach a violent state; excluding external destructive factors such as puncture, thermal runaway is not formed instantly, but is a relatively slow process, and it takes some time for an open flame to be generated after thermal runaway occurs; according to the gas released in the experiment, if water is used to extinguish the fire, according to the chemical reaction principle: PF5+H2O→H3PO4+HF, a small amount of HF toxic gas will be generated. The above experiment verifies the thermal runaway cause and safety risk model established in the embodiment of the present application, such as Figure 6 As shown, it is consistent with the experimental results and has application value.

[0057] In the embodiments of the present application, the engineering and technical strategies include: installing insulating sleeves at assembly and disassembly positions, installing automatic temperature detectors at target locations, and installing fork protection sleeves at manual transfer positions; the safety management strategies include: revising operating procedures, installing a double insurance mechanism, and specifying the number of storage layers and stacking spacing in the storage area; the training and education measures include: forklift drivers and electricians must be certified to work and receive special position training; individual protection measures include: wearing insulating shoes when entering the battery assembly workshop, wearing arc-proof clothing when disassembling the inside of the battery cell, and wearing insulating gloves when working with electricity; emergency response measures include: establishing an emergency plan and conducting regular drills and evaluations, as well as equipping with emergency supplies.

[0058] It can be understood that the embodiments of the present application effectively prevent safety accidents and ensure the safety of employees and equipment by adopting multi-dimensional strategies such as engineering technology, safety management, and personal protection; at the same time, through strict operating procedures and quality control, improve product quality and stability; further optimize production processes, improve equipment efficiency, and reduce interruptions, thereby enhancing corporate production efficiency and market competitiveness; finally, through training, education, and emergency preparedness, comprehensively enhance employee safety awareness and create a positive safety culture environment.

[0059] Specifically, the engineering and technical measures include: installing insulating sleeves at power battery assembly and disassembly stations; installing automatic temperature detectors at target locations, and performing manual temperature measurement regularly if dynamic temperature probes cannot be installed; installing fork protection sleeves at manual transfer stations to prevent forks from piercing multiple parts packages or power batteries, etc.;

[0060] Safety management measures include: to prevent leakage of the cooling system, the operating procedures are revised to conduct air tightness inspection before maintenance and installation; at multiple parts assembly automatic loading and unloading positions, a double insurance mechanism of interlocking indicator light confirmation and driver on-site confirmation is installed; in the power battery storage area, the number of storage layers and stacking spacing are strictly regulated, and special equipment is required to be used for storage of battery packs and battery modules to ensure neat and stable placement, and each storage stacking area is ≤150㎡, the internal column spacing of the stack is ≥0.5m, and the distance between stacks is ≥1m; the distance between the stack and the wall is ≥0.5m, the distance from the column is ≥0.3m, the distance from the roof and beam is ≥0.3m, and the distance from the lamp is ≥0.5m; the width of the main channel is ≥2m, etc.

[0061] Education and training measures include: for forklift manual transfer positions, forklift drivers must hold a certificate before they can take up their posts; for power battery return and repair positions, electrician certificates must be held before they can take up their posts; positions for designing new energy power batteries must undergo special training, etc.

[0062] Individual protection measures include: wearing insulating shoes when entering the battery assembly workshop; wearing arc-proof clothing when disassembling the battery cell; wearing insulating gloves when performing live work such as battery maintenance, etc.

[0063] Emergency response measures include: establishing emergency plans and organizing drills and evaluations regularly; equipping with fire sand, smoke masks, mobile fans, emergency response pits, explosion-proof boxes and other emergency supplies.

[0064] According to the method for monitoring production and manufacturing risks proposed in the embodiment of the present application, by deeply analyzing the production operation data, the risk sources, inducements and potential consequences in each process of power battery production and manufacturing are accurately identified, and the risk level is quantified, risk prediction and evolution analysis are implemented, the whole process from risk occurrence to disappearance is mastered, and the risk failure mode is clarified; a risk and control list is constructed to comprehensively cover various risk points in the production process, quickly locate risks, and implement targeted control measures. At the same time, a real-time monitoring and dynamic adjustment mechanism is introduced to ensure the effectiveness and adaptability of risk control measures and to ensure the safety and quality of power battery production. In this way, the problems of the lack of a systematic risk identification method and the inability to quantify risk points in the prior art are solved.

[0065] Next, a device for monitoring production risks proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0066] Figure 7 It is a block diagram of a monitoring device for production and manufacturing risks according to an embodiment of the present application.

[0067] like Figure 7 As shown, the manufacturing risk monitoring device 10 includes: an acquisition module 100, a generation module 200, an acquisition module 300 and a monitoring module 400.

[0068] Among them, the acquisition module 100 is used to acquire the production operation data of multiple production and manufacturing processes of the power battery; the generation module 200 is used to predict the production and manufacturing risks of the production and manufacturing processes based on the production operation data, and generate a risk list based on multiple production and manufacturing processes and corresponding production and manufacturing risks; the determination module 300 is used to predict the risk evolution process and failure mode of the production and manufacturing processes based on the risk factor data of the production and manufacturing processes, and determine the risk levels of different risks based on the risk evolution process and failure mode; the monitoring module 400 is used to generate a risk identification and control list based on the risk list and the risk levels of different risks, and use the risk identification and control list and actual production and manufacturing data to monitor the production and manufacturing risks of power batteries in multiple production and manufacturing processes.

[0069] It should be noted that the aforementioned explanation of the embodiment of the method for monitoring production and manufacturing risks is also applicable to the device for monitoring production and manufacturing risks of this embodiment, and will not be repeated here.

[0070] According to the monitoring device for production and manufacturing risks proposed in the embodiment of the present application, by deeply analyzing the production operation data, the risk sources, inducements and potential consequences in each process of power battery production and manufacturing are accurately identified, and the risk level is quantified, risk prediction and evolution analysis are implemented, the whole process from risk occurrence to disappearance is mastered, and the risk failure mode is clarified; a risk and control list is constructed to comprehensively cover various risk points in the production process, quickly locate risks, and implement targeted control measures. At the same time, a real-time monitoring and dynamic adjustment mechanism is introduced to ensure the effectiveness and adaptability of risk control measures and to ensure the safety and quality of power battery production. In this way, the problems of the lack of a systematic risk identification method and the inability to quantify risk points in the prior art are solved.

[0071] Figure 8 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:

[0072] A memory 801 , a processor 802 , and a computer program stored in the memory 801 and executable on the processor 802 .

[0073] When the processor 802 executes the program, the method for monitoring production risks provided in the above embodiment is implemented.

[0074] Furthermore, the vehicle also includes:

[0075] The communication interface 803 is used for communication between the memory 801 and the processor 802 .

[0076] The memory 801 is used to store computer programs that can be executed on the processor 802 .

[0077] The memory 801 may include a high-speed RAM (Random Access Memory) memory, and may also include a non-volatile memory, such as at least one disk memory.

[0078] If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 can be connected to each other through a bus and communicate with each other. The bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0079] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0080] The processor 802 may be a CPU (Central Processing Unit), or an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application.

[0081] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for monitoring production risks.

[0082] An embodiment of the present application also provides a computer program product, including a computer program or instructions, for implementing the method for monitoring production risks as described in the above embodiment.

[0083] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0084] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0085] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0086] It should be understood that the various parts of the present application can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, the steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0087] A person of ordinary skill in the art may understand that all or part of the steps carried by the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the above-mentioned program may be stored in a computer-readable storage medium, which, when executed, includes one of the steps of the method embodiment or a combination thereof.

[0088] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for monitoring production risks, characterized in that: The following steps are involved: Obtain production operation data of multiple production and manufacturing processes of power batteries; Predicting the production and manufacturing risks of the production and manufacturing process according to the production operation data, and generating a risk list according to the multiple production and manufacturing processes and the corresponding production and manufacturing risks; Predicting the risk evolution process and failure mode of the manufacturing process according to the risk factor data of the manufacturing process, and determining the risk levels of different risks according to the risk evolution process and failure mode; A risk identification and control list is generated according to the risk list and the risk levels of the different risks, and the risk identification and control list and actual production data are used to monitor the production risks of the power battery in multiple production processes.

2. The method for monitoring production risks according to claim 1, characterized in that: The predicting the production and manufacturing risks of the production and manufacturing process according to the production operation data, and generating a risk list according to a plurality of production and manufacturing processes and corresponding production and manufacturing risks, comprises: Based on the work hazard analysis method, the manufacturing process is disassembled to obtain detailed processes, dangerous work steps are found, and the risks of the detailed processes are identified, wherein the work steps include the division of work activities, decomposition and selection, and identification of hazard sources; Calculating risk weights for the risks of the detailed processes based on historical production operation data and expert judgment; A risk list is generated according to the risk weights, the detailed processes and the corresponding risks.

3. The method for monitoring production risks according to claim 1, characterized in that: The predicting of the risk evolution process and failure mode of the manufacturing process according to the risk factor data of the manufacturing process includes: Obtain the source of danger and analyze the causes of risks; According to the hazard source and the risk-inducing cause, determine the path of the risk evolving into an accident, and determine the target control point according to the risk path; Determine the speed of risk evolution based on historical production operation data and expert judgment, and determine the duration of risk out of control based on the speed of the risk evolution accident; Evaluate the risk based on the target control point, the duration after the risk is out of control and the consequences of the risk, and determine the risk level based on the operational condition hazard analysis method; Based on the stated risk level and expert judgement, the failure mode is determined.

4. The method for monitoring production risks according to claim 1, characterized in that: The use of the risk identification and control list and actual production data to monitor the production and manufacturing risks of the power battery in multiple production and manufacturing processes includes: Identifying the current power, current temperature and target gas concentration in the actual production data; Using the current power, current temperature and target gas concentration as indexes, query the risk identification and control list to obtain the production and manufacturing risk level of the current production and manufacturing process; A thermal runaway protection strategy for the current production process is determined according to the production risk level.

5. The method for monitoring production risks according to claim 4, characterized in that: The thermal runaway protection strategy includes at least one of an engineering technology strategy, a safety management strategy, a training and education strategy, a personal protection strategy, and an emergency response strategy, wherein: The engineering technology strategy includes: installing insulating sleeves at assembly and disassembly positions, installing automatic temperature detectors at target locations, and installing fork protection sleeves at manual transfer positions; The safety management strategy includes: revising operating procedures, setting up a double insurance mechanism, and specifying the number of storage layers and stacking spacing in the storage area; The training and education measures include: certification of forklift drivers and electricians and special job training; The individual protection measures include: wearing insulating shoes when entering the battery assembly workshop, wearing arc-proof clothing when disassembling the battery cells, and wearing insulating gloves when working with electricity; The emergency response measures include: establishing emergency response plans and conducting regular drills and evaluations, as well as equipping with emergency supplies.

6. The method for monitoring production risks according to claim 1, characterized in that: The production operation data includes at least one of tool equipment data, raw material data and personnel action data.

7. A monitoring device for production and manufacturing risks, characterized in that: include: An acquisition module, used to acquire production operation data of multiple production and manufacturing processes of power batteries; A generating module, configured to predict the production and manufacturing risks of the production and manufacturing process according to the production operation data, and generate a risk list according to a plurality of production and manufacturing processes and corresponding production and manufacturing risks; A determination module, used to predict the risk evolution process and failure mode of the production and manufacturing process according to the risk factor data of the production and manufacturing process, and determine the risk levels of different risks according to the risk evolution process and failure mode; A monitoring module is used to generate a risk identification and control list based on the risk list and the risk levels of the different risks, and to monitor the production and manufacturing risks of the power battery in multiple production and manufacturing processes using the risk identification and control list and actual production and manufacturing data.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for monitoring production risks as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed, the method for monitoring production risks described in any one of claims 1-6 is implemented.

10. A computer program product comprising a computer program or instructions, characterized in that When the computer program or instruction is executed, the method for monitoring production risks described in any one of claims 1-6 is implemented.

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