Digital factory safety management system and method based on intelligent manufacturing

Abstract

The invention discloses a digital factory safety management system and method based on intelligent manufacturing, and relates to the technical field of factory management, production raw materials are divided into first-level change and second-level change by analyzing the change degree of the production raw materials, and when the production raw materials are in the first-level change and the control parameters of the management system are not changed, the control parameters of the management system are changed. The management system monitors real-time equipment parameters and environmental parameters, inputs the equipment parameters and the environmental parameters into a joint algorithm to calculate an influence factor, regularly combines the influence factor with the primary change of the production raw materials, analyzes whether the harmful gas state changes or not during the production of the chemical solvent, and if the harmful gas state changes, gives an alarm; and the management system generates a corresponding management strategy. The management system automatically recognizes whether the related variables of the chemical solvent are changed or not, and when the related variables of the chemical solvent are recognized to be changed and no manual intervention control exists, a control strategy is automatically generated for the production equipment, a warning signal is sent for prompting, and safe production of a digital factory is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of factory management, and in particular to a digital factory safety management system and method based on intelligent manufacturing. Background Art

[0002] Digital factory refers to a factory model that digitally transforms all aspects of traditional manufacturing enterprises through the comprehensive application of information technology and digital means to achieve efficient, intelligent and lean production. It is one of the core manifestations of intelligent manufacturing and a key component of Industry 4.0.

[0003] For digital factories that produce chemical solvents, since harmful gases are generated during the production process, the management system usually controls the ventilation system to exhaust the harmful gases. When production materials, equipment or environmental factors change, new control parameters need to be manually input into the management system to control the operation of the management system.

[0004] However, when new control parameters are manually input, there is a certain degree of uncertainty due to human participation (for example, when materials change, relevant personnel forget to input new control parameters, including environmental and equipment parameters, into the management system). At this time, due to changes in related variables, but no new control is performed on the management system, the harmful gas parameter speed and concentration of harmful gases in the chemical solvent production process may increase. The ventilation system cannot adaptively adjust the exhaust volume according to the changes in harmful gases. Insufficient exhaust capacity will cause the concentration of harmful gases in the workshop to exceed the safety standard, posing a threat to the health of workers inside the factory.

[0005] Based on this, the present invention proposes a digital factory safety management system and method based on intelligent manufacturing. The management system can automatically identify whether the relevant variables of chemical solvents have changed. When it is identified that the relevant variables of chemical solvents have changed and there is no manual intervention control, it automatically generates a control strategy for the production equipment and sends a warning signal to prompt, thereby ensuring the safe production of the digital factory. Summary of the invention

[0006] The purpose of the present invention is to provide a digital factory safety management system and method based on intelligent manufacturing to solve the shortcomings of the background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a digital factory safety management method based on intelligent manufacturing, the management method comprising the following steps:

[0008] When the chemical solvent production raw materials enter the production equipment, the management system detects the production raw materials through the built-in spectrometer of the production equipment, analyzes the degree of change of the production raw materials, and divides the production raw materials into primary change and secondary change;

[0009] When the production raw materials have a secondary change and the management system control parameters have not changed, the management system automatically controls the production equipment to stop running and sends a warning signal. When the production raw materials have a primary change and the management system control parameters have not changed, the management system controls the production equipment to run and monitors the real-time equipment parameters and environmental parameters.

[0010] The equipment parameters and environmental parameters are input into the joint algorithm to calculate the influencing factors. The influencing factors are regularly combined with the primary changes in production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents. When the state of harmful gases changes, the management system generates corresponding management strategies.

[0011] In a preferred embodiment, after analyzing the degree of change of production raw materials, the production raw materials are divided into primary change and secondary change, including the following steps:

[0012] After obtaining the change factors of all raw materials, they are summed up to get the change index, which is expressed as: In the formula, ch z is the change index, n is the number of raw material types, factor i is the variation factor of the i-th raw material;

[0013] The obtained change index is compared with the preset index threshold. The index threshold is used to analyze the degree of change of the production raw materials. If the change index is less than or equal to the index threshold, the degree of change of the production raw materials is small, and the production raw materials are classified into primary change. If the change index is less than or equal to the index threshold, the degree of change of the production raw materials is large, and the production raw materials are classified into secondary change.

[0014] In a preferred embodiment, the logic for obtaining the change factor is as follows: the management system obtains the types of raw materials for chemical solvent production, and when each raw material enters the production equipment, the actual reaction rate and actual volatility of the raw material are detected by the built-in spectrometer of the production equipment. After the actual reaction rates and actual volatility of all raw materials are obtained, the reaction rate deviation and volatility deviation of all raw materials are calculated, and the value ranges of the reaction rate deviation and the volatility deviation are mapped to [0,1], and the normalized value of the reaction rate deviation and the normalized value of the volatility deviation are obtained. The normalized value of the reaction rate deviation is added to the normalized value of the volatility deviation to obtain the change factor of the raw material.

[0015] In a preferred embodiment, real-time device parameters and environmental parameters are monitored, and the device parameters and environmental parameters are input into a joint algorithm to calculate the influencing factors, including the following steps:

[0016] Equipment parameters include mixed diffusion values, and environmental parameters include temperature and pressure deviation values;

[0017] The mixed diffusion value and the temperature-pressure deviation value are input into the joint algorithm to calculate the influencing factor. The algorithm expression is: ifn=α·mixdu+β·Tempr, where ifn is the influencing factor, mixdu is the mixed diffusion value, Tempr is the temperature-pressure deviation value, α and β are the adjustment coefficients of the mixed diffusion value and the temperature-pressure deviation value, respectively, and α and β are both greater than 0.

[0018] In a preferred embodiment, the influencing factors are regularly combined with the primary changes of the production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents, including the following steps:

[0019] Obtain the change index of the primary change production raw materials, and obtain the floating coefficient by correcting the change index with the impact factor. The logic for obtaining the floating coefficient is: multiply the change index by the impact factor to obtain the floating coefficient through comprehensive calculation;

[0020] The floating coefficient is compared with the preset coefficient threshold. The coefficient threshold is used to analyze whether the state of harmful gases will change during the production of chemical solvents. If the floating coefficient is less than or equal to the coefficient threshold, the state of harmful gases will not change during the production of chemical solvents. If the floating coefficient is greater than the coefficient threshold, the state of harmful gases will change during the production of chemical solvents.

[0021] In a preferred embodiment, when the analysis of harmful gas status changes, the management system generates a corresponding management strategy, including the following steps:

[0022] When the state of harmful gases changes, the management system obtains the current operating power of the ventilation equipment and adjusts the current operating power of the ventilation equipment according to the floating coefficient. The adjustment algorithm is: power after =power before (1+log2(float+1)), where power after The power after adjustment. before is the current operating power, float is the floating coefficient;

[0023] The management system controls the operation of the ventilation equipment according to the adjusted operating power, and dynamically updates the operating power of the ventilation equipment after regularly obtaining the floating coefficient.

[0024] In a preferred embodiment, when analyzing the change of the harmful gas state, the management system generates a corresponding management strategy, and further includes the following steps:

[0025] The management system adjusts the current operating power of the ventilation equipment according to the floating coefficient. After obtaining the adjusted operating power, the adjusted operating power is compared with the maximum operating power. If the adjusted operating power is less than or equal to the maximum operating power, the ventilation equipment operation is continued to be controlled by the adjusted operating power. If the adjusted operating power is greater than the maximum operating power, the management system controls the production equipment to stop running and sends a warning signal, and controls the ventilation equipment to run at the maximum operating power to quickly discharge harmful gases from the factory.

[0026] In a preferred embodiment, the calculation expression of the mixed diffusion value is: Where mixdu is the mixing diffusion value, μ is the fluid viscosity, v is the stirring speed, d is the characteristic size of the stirrer, κ is the diffusion coefficient, and L is the characteristic length.

[0027] In a preferred embodiment, the calculation expression of the temperature-pressure deviation value is: Where Tempr is the temperature and pressure deviation value, T 实际 is the actual temperature of the factory, T 设定 is the factory set temperature, P 实际 is the actual pressure of the factory, P 设定 is the factory set pressure, C is a constant factor, and its value is 1.212.

[0028] Digital factory safety management system based on intelligent manufacturing, including raw material detection module, warning control module, and joint monitoring module;

[0029] Raw material detection module: When the raw materials for chemical solvent production enter the production equipment, the raw materials are detected by the built-in spectrometer of the production equipment. After analyzing the degree of change of the raw materials, the raw materials are divided into primary change and secondary change. The primary change and secondary change classification results are sent to the warning control module and the joint monitoring module;

[0030] Warning control module: When the production raw materials are at the second level of change and the control parameters remain unchanged, the production equipment is automatically controlled to stop running and send a warning signal;

[0031] Joint monitoring module: When the production raw materials change at the first level and the control parameters do not change, the operation of the production equipment is controlled, and the real-time equipment parameters and environmental parameters are monitored. The equipment parameters and environmental parameters are input into the joint algorithm to calculate the influencing factors. The influencing factors are regularly combined with the first-level changes in the production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents. When the analysis shows that the state of harmful gases has changed, the corresponding management strategy is generated.

[0032] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0033] The present invention divides production raw materials into primary changes and secondary changes after analyzing the degree of change of production raw materials. When the production raw materials are primary changes and the control parameters of the management system are unchanged, the management system controls the operation of the production equipment, monitors the real-time equipment parameters and environmental parameters, inputs the equipment parameters and environmental parameters into the joint algorithm to calculate the influence factors, regularly combines the influence factors with the primary changes of production raw materials, analyzes whether the state of harmful gases will change during the production of chemical solvents, and when the analysis of the state of harmful gases changes, the management system generates corresponding management strategies. The management system can automatically identify whether the relevant variables of chemical solvents have changed. When the relevant variables of chemical solvents are identified to have changed and there is no manual intervention control, it automatically generates control strategies for production equipment, and sends warning signals for prompting, so as to ensure the safe production of digital factories. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0035] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Example 1: Please refer to Figure 1 As shown, the digital factory safety management method based on intelligent manufacturing described in this embodiment includes the following steps:

[0038] When the raw materials for chemical solvent production enter the production equipment, the management system detects the raw materials through the built-in spectrometer of the production equipment, analyzes the degree of change of the raw materials, and divides the raw materials into primary change and secondary change. When the raw materials are secondary change and the control parameters of the management system do not change, the management system automatically controls the production equipment to stop running and sends a warning signal. When the raw materials are primary change and the control parameters of the management system do not change, the management system controls the operation of the production equipment, monitors the real-time equipment parameters and environmental parameters, inputs the equipment parameters and environmental parameters into the joint algorithm to calculate the influencing factors, regularly combines the influencing factors with the primary changes of the raw materials, analyzes whether the state of harmful gases will change during the production of chemical solvents, and generates corresponding management strategies when the analysis of harmful gas state changes.

[0039] This application divides the production raw materials into primary changes and secondary changes after analyzing the degree of change of the production raw materials. When the production raw materials are primary changes and the management system control parameters do not change, the management system controls the operation of the production equipment and monitors the real-time equipment parameters and environmental parameters. The equipment parameters and environmental parameters are input into the joint algorithm to calculate the influencing factors, and the influencing factors are regularly combined with the primary changes of the production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents. When the analysis of the state of harmful gases changes, the management system generates corresponding management strategies. The management system can automatically identify whether the relevant variables of chemical solvents have changed. When it is identified that the relevant variables of chemical solvents have changed and there is no manual intervention control, it automatically generates a control strategy for the production equipment and sends a warning signal to prompt, so as to ensure the safe production of digital factories.

[0040] Embodiment 2: When the chemical solvent production raw materials enter the production equipment, the management system detects the production raw materials through the built-in spectrometer of the production equipment, analyzes the degree of change of the production raw materials, and divides the production raw materials into primary change and secondary change, including the following steps:

[0041] The management system obtains the types of raw materials for chemical solvent production. When each raw material enters the production equipment, the actual reaction rate and actual volatility of the raw material are detected by the built-in spectrometer of the production equipment. After obtaining the actual reaction rates and actual volatility of all raw materials, the reaction rate deviation and volatility deviation of all raw materials are calculated, and the value range of the reaction rate deviation and volatility deviation is mapped to [0,1] to obtain the normalized value of the reaction rate deviation and the normalized value of the volatility deviation. The normalized value of the reaction rate deviation is added to the normalized value of the volatility deviation to obtain the change factor of the raw material. After obtaining the change factors of all raw materials, they are summed to obtain the change index, which is expressed as: In the formula, ch z is the change index, n is the number of raw material types, factor iis the change factor of the i-th raw material, which reflects the overall change status of the chemical solvent raw materials. The larger the change factor, the greater the harmful gas generation rate and the concentration of harmful gases caused by the change of raw materials;

[0042] The obtained change index is compared with the preset index threshold. The index threshold is used to analyze the degree of change of the production raw materials. If the change index is less than or equal to the index threshold, the degree of change of the production raw materials is small, and the production raw materials are classified into primary change. If the change index is less than or equal to the index threshold, the degree of change of the production raw materials is large, and the production raw materials are classified into secondary change.

[0043] Among them, when the production raw materials are divided into primary changes, it indicates that the overall change degree of the chemical solvent is small; when the production raw materials are divided into secondary changes, it indicates that the overall change degree of the chemical solvent is large.

[0044] The logic for obtaining the reaction rate deviation is: obtain the standard reaction rate of the raw material, subtract the standard reaction rate from the actual reaction rate to obtain the reaction rate deviation; the logic for obtaining the volatility deviation is: obtain the standard volatility of the raw material, subtract the standard volatility from the actual volatility to obtain the volatility deviation;

[0045] The higher the reaction rate of the raw material, the faster the chemical reaction proceeds, and the faster the harmful gas is generated. The reaction rate not only determines the generation rate of harmful gases, but also affects their cumulative concentration. When the reaction rate is high, harmful gases will accumulate rapidly, causing the concentration of harmful gases in the local area or environment to rise rapidly. The higher the volatility of the raw material, the faster it converts from liquid or solid to gas, which directly increases the generation rate of harmful gases. Highly volatile raw materials will quickly increase the concentration of harmful gases.

[0046] When the production raw materials are at the second level of change and the management system control parameters remain unchanged, the management system automatically controls the production equipment to stop running and sends a warning signal, including the following steps:

[0047] The management system automatically issues a stop command to the production equipment to prevent the potential safety risk from further expanding, activates the warning system, and sends a warning signal to the operator. The warning can be conveyed in a variety of ways, such as:

[0048] Visual warning: flashing lights and displaying warning messages on the display screen.

[0049] Audible Alert: An alarm sounds.

[0050] SMS / email notification: Automatically send SMS or email to notify relevant personnel.

[0051] Monitor real-time equipment parameters and environmental parameters, input the equipment parameters and environmental parameters into the joint algorithm to calculate the influencing factors, including the following steps:

[0052] Equipment parameters include mixed diffusion values, and environmental parameters include temperature and pressure deviation values;

[0053] The calculation expression of the mixed diffusion value is: Where mixdu is the mixing diffusion value, μ is the fluid viscosity, and the worse the fluidity of the fluid, the higher the viscosity of the fluid, but in some cases, higher viscosity may lead to more uneven mixing and increased local concentration.

[0054] v is the stirring speed. The faster the stirring speed, the greater the mixing uniformity can be. However, if the speed is too fast, it may also cause excessive local reaction and increase the generation of harmful gases.

[0055] d is the characteristic size of the agitator, which usually refers to the diameter of the agitator or the size of the reactor. A larger agitator size will increase the mixing efficiency, but it may also increase the turbulence within the system, leading to intensified local reactions.

[0056] κ is the diffusion coefficient, which reflects the diffusion rate of a substance in a fluid. A higher diffusion coefficient may lead to faster mixing, but it may also increase the rate of generation of harmful gases.

[0057] L is the characteristic length, which is usually a typical distance in the reactor (such as the liquid level). When the characteristic length is small, the reactants are more likely to be concentrated in a smaller area, resulting in an increase in the local reaction rate.

[0058] The larger the mixed diffusion value, the stronger the mixing in the system, which may lead to intensified local reactions, thereby increasing the production rate and concentration of harmful gases. This formula takes into account the physical properties of the fluid (such as viscosity), stirring conditions (such as stirring speed and agitator size), as well as the diffusion coefficient and the geometric characteristics of the reactor.

[0059] Relationship between mixed diffusion value and harmful gas generation rate

[0060] Positive correlation: When the mixed diffusion value increases, the mixing efficiency increases and the reactants are more evenly distributed in the reactor. This uniformity may accelerate the chemical reaction, especially when the reaction rate is directly related to the concentration of the reactants. Therefore, an increase in the mixed diffusion value will lead to a faster generation of harmful gases.

[0061] Local over-reaction: In some cases, excessively high mixing diffusion values ​​may result in excessive concentrations of reactants in local areas, creating "hot spots" or overly violent reactions, which further accelerate the generation of harmful gases.

[0062] Relationship between mixed diffusion value and harmful gas concentration

[0063] Positive correlation: Increased mixing diffusion values ​​usually mean that the materials in the reactor are more fully mixed, which may lead to higher levels of harmful gas generation. If the generation rate of harmful gases in the reaction products increases and is not discharged or treated in time, the concentration of the gas will also increase.

[0064] The calculation expression of temperature and pressure deviation is:

[0065] Where Tempr is the temperature and pressure deviation value, T 实际 is the actual temperature of the factory, T 设定 is the factory set temperature, P 实际 is the actual pressure of the factory, P 设定 is the factory set pressure, C is a constant factor used to calibrate the deviation under different process conditions, and its value is 1.212.

[0066] Relationship between temperature and pressure deviation and harmful gas generation rate

[0067] Positive correlation: When the temperature and pressure deviation increases, it means that the actual temperature and pressure of the factory deviate from the set ideal value. This deviation may cause the rate of chemical reaction to change, especially when the deviation value is large, it may accelerate the chemical reaction, resulting in an increase in the rate of harmful gas production.

[0068] Relationship between temperature and pressure deviation and harmful gas concentration

[0069] Positive correlation: As the temperature and pressure deviation increases, the concentration of harmful gases will also increase. This is because when the deviation is large, more harmful gases may be produced in the products of chemical reactions. If the gas treatment or emission system does not respond or adjust in time, these gases may accumulate in the environment, causing the concentration to rise.

[0070] The mixed diffusion value and the temperature-pressure deviation value are input into the joint algorithm to calculate the influencing factor. The algorithm expression is: ifn=α·mixdu+β·Tempr, where ifn is the influencing factor, mixdu is the mixed diffusion value, Tempr is the temperature-pressure deviation value, α and β are the adjustment coefficients of the mixed diffusion value and the temperature-pressure deviation value, respectively, and α and β are both greater than 0.

[0071] Regularly combine the influencing factors with the primary changes in the production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents, including the following steps:

[0072] In practical applications, when the production raw materials change, but the change is relatively small, it may cause a small increase (such increase has little effect) or no increase in the rate of harmful gas generation and the concentration of harmful gases during chemical solvent production;

[0073] In the production process of chemical solvents, changes in production raw materials, especially when related equipment parameters and environmental parameters change at the same time, can lead to a significant increase in the rate and concentration of harmful gases even if the raw material changes are small;

[0074] When raw materials change, equipment parameters (such as mixed diffusion values) and environmental parameters (such as temperature and pressure deviation values) change simultaneously, these factors may reinforce each other, leading to a significant increase in the generation rate and concentration of harmful gases;

[0075] When the production raw materials change, and the related equipment parameters and environmental parameters change (the changes here refer to the changes in equipment parameters and environmental parameters that lead to an increase in the rate of harmful gas generation and the concentration of harmful gases), at this time, even if the change in the production raw materials is relatively small, it will still lead to an increase in the rate of harmful gas generation and the concentration of harmful gases. The existing management system has no effective monitoring and management for such problems. The solution proposed in this application is as follows:

[0076] Obtain the change index of the primary change production raw materials, and obtain the floating coefficient by correcting the change index with the impact factor. The logic for obtaining the floating coefficient is: multiply the change index by the impact factor to obtain the floating coefficient through comprehensive calculation;

[0077] The larger the floating coefficient, the greater the probability that the state of harmful gases will change during the production of chemical solvents. The floating coefficient is compared with the preset coefficient threshold. The coefficient threshold is used to analyze whether the state of harmful gases will change during the production of chemical solvents. If the floating coefficient is less than or equal to the coefficient threshold, the state of harmful gases will not change during the production of chemical solvents. If the floating coefficient is greater than the coefficient threshold, the state of harmful gases will change during the production of chemical solvents.

[0078] When analyzing the changes in the status of harmful gases, the management system generates a corresponding management strategy, including the following steps:

[0079] In the present application, the larger the floating coefficient, the faster the harmful gas generation rate and the concentration of harmful gases increase. Therefore, when the floating coefficient increases, the management system needs to increase the operating power of the ventilation equipment accordingly, so that the ventilation equipment can increase the exhaust volume and quickly discharge the harmful gases out of the factory when the harmful gas generation rate and the concentration of harmful gases increase.

[0080] When the state of harmful gases changes, the management system obtains the current operating power of the ventilation equipment and adjusts the current operating power of the ventilation equipment according to the floating coefficient. The adjustment algorithm is: power after =power before (1+log2(float+1)), where power after The power after adjustment.before is the current operating power, float is the floating coefficient;

[0081] The management system controls the operation of the ventilation equipment according to the adjusted operating power, and dynamically updates the operating power of the ventilation equipment after regularly obtaining the floating coefficient.

[0082] It should be noted that in actual applications, the ventilation equipment has a maximum operating power limit (when operating in excess of the maximum operating power, the energy consumption of the ventilation equipment will increase significantly, and the risk of failure will increase). Therefore, the management system adjusts the current operating power of the ventilation equipment based on the floating coefficient. After obtaining the adjusted operating power, the adjusted operating power is compared with the maximum operating power. If the adjusted operating power is less than or equal to the maximum operating power, the ventilation equipment operation will continue to be controlled by the adjusted operating power. If the adjusted operating power is greater than the maximum operating power, the management system controls the production equipment to stop operating and sends a warning signal, and controls the ventilation equipment to operate at the maximum operating power to quickly discharge harmful gases from the factory.

[0083] Embodiment 3: The digital factory safety management system based on intelligent manufacturing described in this embodiment includes a raw material detection module, a warning control module, and a joint monitoring module;

[0084] Raw material detection module: When the raw materials for chemical solvent production enter the production equipment, the raw materials are detected by the built-in spectrometer of the production equipment. After analyzing the degree of change of the raw materials, the raw materials are divided into primary change and secondary change. The primary change and secondary change classification results are sent to the warning control module and the joint monitoring module;

[0085] Warning control module: When the production raw materials are at the second level of change and the control parameters remain unchanged, the production equipment is automatically controlled to stop running and send a warning signal;

[0086] Joint monitoring module: When the production raw materials change at the first level and the control parameters do not change, the operation of the production equipment is controlled, and the real-time equipment parameters and environmental parameters are monitored. The equipment parameters and environmental parameters are input into the joint algorithm to calculate the influencing factors. The influencing factors are regularly combined with the first-level changes in the production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents. When the analysis shows that the state of harmful gases has changed, the corresponding management strategy is generated.

[0087] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0088] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", 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 invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0089] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A digital factory safety management method based on intelligent manufacturing, characterized by: The management method comprises the following steps: When the chemical solvent production raw materials enter the production equipment, the management system detects the production raw materials through the built-in spectrometer of the production equipment, analyzes the degree of change of the production raw materials, and divides the production raw materials into primary change and secondary change; When the production raw materials have a secondary change and the management system control parameters have not changed, the management system automatically controls the production equipment to stop running and sends a warning signal. When the production raw materials have a primary change and the management system control parameters have not changed, the management system controls the production equipment to run and monitors the real-time equipment parameters and environmental parameters. The equipment parameters and environmental parameters are input into the joint algorithm to calculate the influencing factors. The influencing factors are regularly combined with the primary changes in production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents. When the state of harmful gases changes, the management system generates corresponding management strategies.

2. The digital factory safety management method based on intelligent manufacturing according to claim 1 is characterized by: After analyzing the degree of change of production raw materials, the production raw materials are divided into primary change and secondary change, including the following steps: After obtaining the change factors of all raw materials, they are summed up to get the change index, which is expressed as: In the formula, ch z is the change index, n is the number of raw material types, factor i is the variation factor of the i-th raw material; The obtained change index is compared with the preset index threshold. The index threshold is used to analyze the degree of change of the production raw materials. If the change index is less than or equal to the index threshold, the degree of change of the production raw materials is small, and the production raw materials are classified into primary change. If the change index is less than or equal to the index threshold, the degree of change of the production raw materials is large, and the production raw materials are classified into secondary change.

3. The digital factory safety management method based on intelligent manufacturing according to claim 2 is characterized in that: The logic for obtaining the change factor is as follows: the management system obtains the types of raw materials for chemical solvent production. When each raw material enters the production equipment, the actual reaction rate and actual volatility of the raw material are detected by the built-in spectrometer of the production equipment. After obtaining the actual reaction rates and actual volatility of all raw materials, the reaction rate deviation and volatility deviation of all raw materials are calculated, and the value range of the reaction rate deviation and the volatility deviation is mapped to [0,1] to obtain the normalized value of the reaction rate deviation and the normalized value of the volatility deviation. The normalized value of the reaction rate deviation is added to the normalized value of the volatility deviation to obtain the change factor of the raw material.

4. The digital factory safety management method based on intelligent manufacturing according to claim 3 is characterized by: Monitor real-time equipment parameters and environmental parameters, input the equipment parameters and environmental parameters into the joint algorithm to calculate the influencing factors, including the following steps: Equipment parameters include mixed diffusion values, and environmental parameters include temperature and pressure deviation values; The mixed diffusion value and the temperature-pressure deviation value are input into the joint algorithm to calculate the influencing factor. The algorithm expression is: ifn=α·mixdu+β·Tempr, where ifn is the influencing factor, mixdu is the mixed diffusion value, Tempr is the temperature-pressure deviation value, α and β are the adjustment coefficients of the mixed diffusion value and the temperature-pressure deviation value, respectively, and α and β are both greater than 0.

5. The digital factory safety management method based on intelligent manufacturing according to claim 4 is characterized in that: Regularly combine the influencing factors with the primary changes in the production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents, including the following steps: Obtain the change index of the primary change production raw materials, and obtain the floating coefficient by correcting the change index with the impact factor. The logic for obtaining the floating coefficient is: multiply the change index by the impact factor to obtain the floating coefficient through comprehensive calculation; The floating coefficient is compared with the preset coefficient threshold. The coefficient threshold is used to analyze whether the state of harmful gases will change during the production of chemical solvents. If the floating coefficient is less than or equal to the coefficient threshold, the state of harmful gases will not change during the production of chemical solvents. If the floating coefficient is greater than the coefficient threshold, the state of harmful gases will change during the production of chemical solvents.

6. The digital factory safety management method based on intelligent manufacturing according to claim 5 is characterized by: When analyzing the changes in the status of harmful gases, the management system generates a corresponding management strategy, including the following steps: When the state of harmful gases changes, the management system obtains the current operating power of the ventilation equipment and adjusts the current operating power of the ventilation equipment according to the floating coefficient. The adjustment algorithm is: power after =power before (1+log2(float+1)), where power after The power after adjustment. before is the current operating power, float is the floating coefficient; The management system controls the operation of the ventilation equipment according to the adjusted operating power, and dynamically updates the operating power of the ventilation equipment after regularly obtaining the floating coefficient.

7. The digital factory safety management method based on intelligent manufacturing according to claim 6 is characterized by: When analyzing the changes in the status of harmful gases, the management system generates a corresponding management strategy, which also includes the following steps: The management system adjusts the current operating power of the ventilation equipment according to the floating coefficient. After obtaining the adjusted operating power, the adjusted operating power is compared with the maximum operating power. If the adjusted operating power is less than or equal to the maximum operating power, the ventilation equipment operation is continued to be controlled by the adjusted operating power. If the adjusted operating power is greater than the maximum operating power, the management system controls the production equipment to stop running and sends a warning signal, and controls the ventilation equipment to run at the maximum operating power to quickly discharge harmful gases from the factory.

8. The digital factory safety management method based on intelligent manufacturing according to claim 7 is characterized in that: The calculation expression of the mixed diffusion value is: Where mixdu is the mixing diffusion value, μ is the fluid viscosity, v is the stirring speed, d is the characteristic size of the stirrer, κ is the diffusion coefficient, and L is the characteristic length.

9. The digital factory safety management method based on intelligent manufacturing according to claim 8 is characterized by: The calculation expression of the temperature and pressure deviation value is: Where Tempr is the temperature and pressure deviation value, T 实际 is the actual temperature of the factory, T 设定 is the factory set temperature, P 实际 is the actual pressure of the factory, P 设定 is the factory set pressure, C is a constant factor, and its value is 1.

212.

10. A digital factory safety management system based on intelligent manufacturing, used to implement the management method according to any one of claims 1 to 9, characterized in that: Including raw material detection module, warning control module, and joint monitoring module; Raw material detection module: When the raw materials for chemical solvent production enter the production equipment, the raw materials are detected by the built-in spectrometer of the production equipment. After analyzing the degree of change of the raw materials, the raw materials are divided into primary change and secondary change. The primary change and secondary change classification results are sent to the warning control module and the joint monitoring module; Warning control module: When the production raw materials are at the second level of change and the control parameters remain unchanged, the production equipment is automatically controlled to stop running and send a warning signal; Joint monitoring module: When the production raw materials change at the first level and the control parameters do not change, the operation of the production equipment is controlled, and the real-time equipment parameters and environmental parameters are monitored. The equipment parameters and environmental parameters are input into the joint algorithm to calculate the influencing factors. The influencing factors are regularly combined with the first-level changes in the production raw materials to analyze whether the state of harmful gases will change during the production of chemical solvents. When the analysis shows that the state of harmful gases has changed, the corresponding management strategy is generated.

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