Enterprise safety production management method

Abstract

The invention discloses an enterprise safety production management method, and relates to the technical field of safety production, and the method comprises the steps: 1, obtaining food processing information: obtaining the processing information of a food processing production line; step 2, food processing information processing: according to the processing information of the food processing production line, processing to obtain a pollution degree judgment value and a microorganism breeding judgment value of the food processing production line, and judging whether the food processing production line needs to be cleaned and disinfected; step 3, generating a cleaning and disinfecting scheme, if the food processing production line needs to be cleaned, determining a cleaning scheme of the food processing production line, and if the food processing production line needs to be disinfected, determining a disinfecting scheme of the food processing production line; and step 4, display processing: displaying the cleaning and disinfection scheme to management personnel of the food processing production line, so that the cleaning and disinfection work better fits the actual pollution condition of the production line, and the cleaning and disinfection effects of the food processing production line are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of safe production, and in particular to a method for managing safe production in an enterprise. Background Art

[0002] In today's society, the food industry is booming, and the efficient operation of food processing production lines provides people with a rich variety of food choices. However, as food safety issues are increasingly concerned, the production safety management of food processing production lines has become increasingly important, which is related to the health of consumers, the survival of enterprises and the stability of society. Therefore, it is extremely necessary to manage the production of food processing production lines.

[0003] Prior art, such as the invention application patent with announcement number: CN116453292B, discloses a method for dividing production safety risk levels and early warning for chemical enterprises, which specifically includes: obtaining a personnel risk coefficient based on the proportion of staff members who do not use safety tools correctly. Obtain monitoring risk coefficients for different risk sources based on environmental monitoring data of the risk source area, and obtain risk source risk coefficients based on the proportion of risk sources that are greater than the monitoring risk design value. Obtain an operation risk coefficient based on the operation data of chemical production equipment, and obtain an equipment risk coefficient based on the operation risk coefficient and the proportion of fire hydrants with abnormal water pressure. Based on the personnel risk coefficient, equipment risk coefficient, and risk source risk coefficient, an assessment model is constructed to obtain a safety risk coefficient, and the production safety risk level is divided based on the safety risk coefficient, and whether to issue an early warning is determined based on the production safety risk level, thereby further improving production safety.

[0004] Prior art, such as the invention application patent with announcement number: CN111695743B, discloses a factory-based food production safety monitoring method, device, equipment and storage medium, the method comprising: starting a central monitoring model and a raw material source control model, and monitoring the source of production raw materials for procurement. Before processing and production, the quality level of the obtained food raw materials to be processed is determined, and the quality level of the finished food is predicted. It is determined whether the predicted quality level of the finished food meets the preset threshold. If it does, processing and production are carried out. In the entire process of processing and production, the scoring index value when each step of the process flow is completed is obtained. The finished quality of the finished food is comprehensively judged, the finished food is classified into different levels, and the classification results are sent to the central monitoring model to complete food production monitoring. This application can effectively monitor the production of food from the overall production process and improve the quality of food.

[0005] In combination with the above solutions, it can be found that there are still deficiencies in the existing technology, which are specifically reflected in the following aspects: the cleaning or disinfection of traditional food processing production lines mostly relies on fixed time or experience arrangements, is limited to fixed cleaning and disinfection cycles or operates based on experience, lacks in-depth mining of historical processing information, and uses it as a basis for judgment and evaluation, making it difficult for cleaning and disinfection work to fit the actual pollution status and microbial breeding risks of the production line. At the same time, when evaluating the pollution and microbial breeding of food processing production lines, there is a lack of consideration of multiple factors such as the type of processed food, processing volume, processing time interval, and temperature and humidity of the processing environment. It is difficult to ensure the comprehensiveness of the pollution and microbial breeding analysis of the food processing production line, thereby reducing the effectiveness of subsequent cleaning and disinfection of the food processing production line. Summary of the invention

[0006] The purpose of the present invention is to provide a method for enterprise safety production management, which solves the problems existing in the background technology.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an enterprise production safety management method, including: step one, food processing information acquisition, acquiring processing information of the food processing production line.

[0008] Step 2: Processing food processing information: According to the processing information of the food processing production line, the contamination judgment value and the microbial growth judgment value of the food processing production line are obtained, and it is judged whether the food processing production line needs to be cleaned and disinfected.

[0009] Step three: generate a cleaning and disinfection plan. If the food processing production line needs to be cleaned, determine the cleaning plan for the food processing production line. If the food processing production line needs to be disinfected, determine the disinfection plan for the food processing production line.

[0010] Step 4: Display processing: display the cleaning and disinfection plan to the food processing production line manager.

[0011] The beneficial effects of the present invention are as follows: (1) The present invention deeply mines historical processing information and uses it as the basis for judgment and evaluation, so that the cleaning and disinfection work is more in line with the actual pollution status and microbial breeding risks of the production line, which makes up for the shortcomings of the existing technology and is no longer limited to fixed cleaning and disinfection cycles or empirical operations, thus realizing the transformation from "timing" to "on-demand".

[0012] (2) When evaluating the contamination and microbial growth of a food processing production line, the present invention takes into account multiple factors such as the type of processed food, processing volume, processing time interval, and temperature and humidity of the processing environment, thereby ensuring the comprehensiveness of the contamination and microbial growth analysis of the food processing production line, thereby improving the effect of subsequent cleaning and disinfection of the food processing production line. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0016] Reference Figure 1 As shown, the present invention provides a method for enterprise production safety management, including: step one, obtaining food processing information, obtaining processing information of the food processing production line from a food processing production line monitoring center.

[0017] In a specific embodiment of the present invention, the processing information includes a historical processing data set, an operator behavior data set, and an environment data set.

[0018] The historical processing data set includes the type and quantity of food processed at each time point.

[0019] The operator behavior data set includes the output times and average risk distance of each risk action type at each time node.

[0020] The environmental data set includes characteristic parameters of each environmental data at each time node.

[0021] It should be noted that the food production line monitoring center integrates a variety of environmental monitoring sensors to monitor environmental data, including but not limited to temperature, humidity, wind speed, etc.

[0022] Step 2: Processing food processing information: According to the processing information of the food processing production line, the contamination judgment value and the microbial growth judgment value of the food processing production line are obtained, and it is judged whether the food processing production line needs to be cleaned and disinfected.

[0023] In a specific embodiment of the present invention, the pollution level judgment value of the food processing production line is specifically determined by extracting a historical processing data set, an operator behavior data set and an environmental data set from the processing information of the food processing production line, and respectively determining the first pollution level R1, the second pollution level R2 and the third pollution level R3 of the food processing production line.

[0024] like , then the contamination judgment value of the food processing production line is recorded as 1, indicating that the food processing production line needs to be cleaned. Represents the logical symbol OR.

[0025] like , then the contamination judgment value of the food processing production line is recorded as -1, indicating that the food processing production line does not need to be cleaned. Represents the logical symbol and.

[0026] In a specific embodiment of the present invention, the specific method for determining the first contamination degree of the food processing production line is as follows: extracting the type and quantity of food processed at each time node from the historical processing data set of the food processing production line, and matching the pollution characteristic parameters SE of the food type processed at each time node of the food processing production line from the pollution characteristic parameters corresponding to each food type stored in the web data warehouse, wherein the pollution characteristic parameters corresponding to each food type include a value of 0-1.

[0027] It should be noted that the pollution characteristic parameters corresponding to the various food types specifically reflect the probability of each food type causing pollution during processing. For example, for fried foods, oils have strong viscosity and adhesion, poor fluidity, and are easily attached to the equipment surface, inner wall of pipes and other parts of the food processing production line to form grease. For dairy products, proteins are easily denatured and coagulated under heating, acid and alkali conditions, and adhere to the surface of equipment to form stains. For candy foods, sugars have good solubility and conditional viscosity. Only under specific conditions such as high sugar concentration and low ambient humidity will relatively stubborn sticky stains be formed. Therefore, the pollution characteristic parameters of fried foods are greater than those of dairy products, and the pollution characteristic parameters of dairy products are greater than those of candy foods. For example, the pollution characteristic parameters of fried foods, dairy products and candy foods are set to 0.9, 0.7 and 0.5, respectively.

[0028] According to the time node, SE-t trend curve A and SL-t trend curve B are drawn in the plane rectangular coordinate system respectively, where t represents the time node number.

[0029] Correlation analysis is performed on curves A and B. If curves A and B meet two conditions respectively, the first contamination degree of the food processing production line is recorded as 1, otherwise it is recorded as -1. Condition 1 is that the number of vertices of curve A is greater than or equal to b, where b is the preset threshold. Condition 2 is that the overall trend of curve B is rising and the total processing quantity is greater than u, where u is the total suitable processing quantity of the food processing production line stored in the web data warehouse.

[0030] For condition 1, when the number of vertices of curve A is greater than or equal to b, assuming b=0, it means that the type of food processed by the processing line fluctuates greatly. This situation means that the risk of cross-contamination of food in the processing line is greater. Therefore, when the number of vertices of curve A is greater than or equal to b, it means that the risk of contamination of the food processing line is greater.

[0031] For condition 2, when the overall trend of curve B rises, it indicates that the processing volume of the food processing line is increasing. At the same time, the total processing quantity is greater than u, indicating that the total processing quantity exceeds the appropriate total processing quantity of the food processing line, and the risk of contamination is relatively high.

[0032] It should be noted that before a food processing production line is put into use, it is usually tested for contaminants. For example, different types of food are continuously processed and the volume of contaminants is continuously collected until it reaches the point where cleaning is required. The total continuous processing volume is recorded and the minimum continuous processing volume is recorded as the appropriate total processing quantity for the food processing production line.

[0033] In a specific embodiment of the present invention, the second contamination level of the food processing production line is determined by extracting the number of outputs and the average risk distance of each risk action type at each time node from the operator behavior data set of the food processing production line.

[0034] It should be noted that a three-dimensional space coordinate system is established with the center point of the food processing production line as the center point, and the risky action types of the operators are captured through monitoring equipment. The closest distance between the locator worn by the operator and the food processing production line is recorded as the risk distance, thereby obtaining the risk distance of each occurrence of each risky action type of the operator, and the average distance is obtained by averaging them.

[0035] The output times and average risk distance of each risk action type at each time node of the food processing production line are imported into the second pollution assessment model. , the second contamination level of the output food processing production line.

[0036] In the formula , They are represented as existential quantifiers and universal quantifiers respectively. , is the action risk index of the i-th time node of the food processing production line, , , are the allowed output times, safe average distance, and action risk index threshold of the mth risk action type stored in the web data warehouse, respectively. is the number of each time node, , is an integer greater than 2, is the number of each risk action type, , is an integer greater than 2.

[0037] In a specific embodiment of the present invention, the third pollution degree of the food processing production line is determined by the following specific determination method: characteristic parameters of each environmental data at each time node are extracted from the environmental data set of the food processing production line, and then the characteristic parameters of each pollution-related environmental data at each time node of the food processing production line are extracted in combination with each pollution-related environmental data stored in the web data warehouse, and the characteristic parameters are compared with the safety characteristic parameter interval of each pollution-related environmental data stored in the web data warehouse. If the characteristic parameter of a certain pollution-related environmental data is not in the safety characteristic parameter interval, the pollution-related environmental data is recorded as risky environmental data, and the risky environmental data are summarized to obtain the risky environmental data.

[0038] It should be noted that the pollution-related environmental data are specifically environmental data associated with pollution in the food processing production line, such as temperature, humidity, wind speed, air quality, ground dirt area, wall dirt area, etc.

[0039] It should be noted again that the characteristic parameter of each environmental data, such as the characteristic parameter of temperature, specifically refers to the average value of the temperature.

[0040] The number of risk environment data and the number of pollution-related environment data at each time node of the food processing production line are statistically obtained, and divided to obtain the environmental risk ratio Ht at each time node of the food processing production line. In the rectangular coordinate system, the Ht-t trend line P is fitted, and the slope of the line P is obtained. When the slope of the line P is greater than or equal to the preset growth slope, the third pollution degree of the food processing production line is recorded as 1, otherwise, it is recorded as -1.

[0041] In a specific embodiment of the present invention, the microbial growth judgment value of the food processing production line is specifically determined by extracting a historical processing data set, an operator behavior data set and an environmental data set from the processing information of the food processing production line, and respectively determining a first microbial growth value E1, a second microbial growth value E2 and a third microbial growth value E3 of the food processing production line.

[0042] like , the microbial growth judgment value of the food processing production line is recorded as 1, indicating that the food processing production line needs to be disinfected.

[0043] like , the microbial growth judgment value of the food processing production line is recorded as -1, indicating that the food processing production line does not need to be disinfected.

[0044] It should be noted that the method for determining the first microbial growth value E1, the second microbial growth value E2 and the third microbial growth value E3 of the food processing production line is the same as the method for confirming the first contamination degree, the second contamination degree and the third contamination degree.

[0045] When evaluating the contamination and microbial growth of a food processing production line, the present invention takes into account multiple factors such as the type of processed food, processing volume, processing time interval, temperature and humidity of the processing environment, etc., to ensure the comprehensiveness of the contamination and microbial growth analysis of the food processing production line, thereby improving the effect of subsequent cleaning and disinfection of the food processing production line.

[0046] Step three: generate a cleaning and disinfection plan. If the food processing production line needs to be cleaned, determine the cleaning plan for the food processing production line. If the food processing production line needs to be disinfected, determine the disinfection plan for the food processing production line.

[0047] In a specific embodiment of the present invention, the cleaning scheme of the food processing production line is determined by the following specific method: based on the first contamination degree, the second contamination degree and the third contamination degree of the food processing production line, when the first contamination degree, the second contamination degree and the third contamination degree are all 1, the cleaning rule code of the food processing production line is recorded as 111; when two of the first contamination degree, the second contamination degree and the third contamination degree are 1, the cleaning rule code of the food processing production line is recorded as 110; when one of the first contamination degree, the second contamination degree and the third contamination degree is 1, the cleaning rule code of the food processing production line is recorded as 100.

[0048] According to the cleaning rule code of the food processing production line, combined with the cleaning schemes corresponding to each cleaning rule code stored in the web data warehouse, the cleaning scheme of the food processing production line is matched, and the cleaning scheme includes the concentration of the cleaning liquid, the cleaning time and the cleaning power.

[0049] It should be noted that the cleaning scheme corresponding to each cleaning rule code is specifically obtained through training based on prior training data, wherein the prior training data includes the cleaning rule code, cleaning scheme and cleaning effect characterization value of each historical cleaning. The cleaning effect characterization value of each historical cleaning is homogenized to obtain the processed cleaning effect characterization value of each historical cleaning, which is then compared with the preset cleaning effect characterization value threshold of each cleaning rule code. If the cleaning effect characterization value of a historical cleaning is greater than or equal to the cleaning effect characterization value threshold, then the historical cleaning is recorded as a qualified historical cleaning, and the qualified historical cleanings are summarized.

[0050] Based on the cleaning rule code and cleaning scheme of each qualified cleaning, each qualified cleaning and cleaning scheme of each cleaning rule code are mapped, and the cleaning scheme of each qualified cleaning is averaged to obtain the cleaning scheme of each cleaning rule code.

[0051] The cleaning effect characterization value is specifically the pollutant parameter of the food processing production line identified by image recognition technology, wherein the pollutant parameter includes the volume of various pollutants, which is summarized to obtain the total volume of pollutants, and the total volume of pollutants is added to the compensation value and the inverse is taken to obtain the cleaning effect characterization value.

[0052] In a specific embodiment of the present invention, the disinfection scheme of the food processing production line is determined by the following specific determination method: based on the first microbial growth value, the second microbial growth value and the third microbial growth value of the food processing production line, when the first microbial growth value, the second microbial growth value and the third microbial growth value are all 1, the disinfection rule code of the food processing production line is recorded as 111; when two of the first microbial growth value, the second microbial growth value and the third microbial growth value are 1, the disinfection rule code of the food processing production line is recorded as 110; when one of the first microbial growth value, the second microbial growth value and the third microbial growth value is 1, the disinfection rule code of the food processing production line is recorded as 100.

[0053] Based on the historical processing data set, operator behavior data set and environmental data set of the food processing production line, the dominant microbial species of the food processing production line are determined.

[0054] Based on the dominant microbial species in the food processing production line and the ultraviolet sensitivity database of the dominant microbial species stored in the web data warehouse, the ultraviolet sensitive wavelength corresponding to the dominant microbial species in the food processing production line is screened and used as the ultraviolet wavelength.

[0055] According to the disinfection rule code and dominant microorganism types of the food processing production line, combined with the disinfection time corresponding to each disinfection rule code of each dominant microorganism type stored in the web data warehouse, the disinfection time of the food processing production line is matched.

[0056] Generate a disinfection plan for the food processing production line based on the ultraviolet wavelength and disinfection duration of the food processing production line.

[0057] In a specific embodiment of the present invention, the dominant microorganisms of the food processing production line are determined by the following specific method: the dominant microorganism types, historical processing data sets, operator behavior data sets and environmental data sets of each historical production are extracted from the prior data in the web data warehouse, and the historical processing data sets, operator behavior data sets and environmental data sets of the food processing production line are compared with them for similarity, so as to obtain the processing similarity, operator behavior similarity and environmental similarity between the food processing production line and each historical production, and the overall similarity between the food processing production line and each historical production is obtained by mean processing.

[0058] It should be noted that, for the two numerical sets of historical processing data sets and environmental data sets, the similarity can be calculated by calculating the mean square error and then the root mean square error. The similarity is inversely proportional to the root mean square error. It can also be calculated by the mean absolute error. The similarity is inversely proportional to the mean absolute error. Both are existing technologies and will not be elaborated here. For the operator behavior data set that is a set of keywords, the Jaccard similarity coefficient can be used to calculate the similarity of the operator behavior data set. This is also existing technology and will not be elaborated here.

[0059] If the overall similarity between a food processing production line and a certain historical production is the greatest, the dominant microbial species of the historical production will be used as the dominant microbial species of the food processing production line.

[0060] The present invention deeply mines historical processing information and uses it as the basis for judgment and evaluation, so that the cleaning and disinfection work is more in line with the actual pollution status and microbial breeding risks of the production line, which makes up for the shortcomings of the existing technology. It is no longer limited to fixed cleaning and disinfection cycles or operation based on experience, and realizes the transformation from "timing" to "on-demand".

[0061] Step 4: Display processing: display the cleaning and disinfection plan to the food processing production line manager.

[0062] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for enterprise production safety management, characterized in that: include: Step 1: Acquire food processing information, and obtain processing information of the food processing production line; Step 2: Processing food processing information: According to the processing information of the food processing production line, the contamination judgment value and the microbial growth judgment value of the food processing production line are obtained, and it is judged whether the food processing production line needs to be cleaned and disinfected; Step 3: Generate a cleaning and disinfection plan. If the food processing production line needs to be cleaned, determine the cleaning plan for the food processing production line. If the food processing production line needs to be disinfected, determine the disinfection plan for the food processing production line. Step 4: Display processing: display the cleaning and disinfection plan to the food processing production line manager.

2. The enterprise safety production management method according to claim 1, characterized in that: The processing information includes a historical processing data set, an operator behavior data set, and an environmental data set; The historical processing data set includes the type and quantity of food processed at each time point; The operator behavior data set includes the output times and average risk distance of each risk action type at each time node; The environmental data set includes characteristic parameters of each environmental data at each time node.

3. The enterprise safety production management method according to claim 2, characterized in that: The contamination judgment value of the food processing production line is specifically determined by: Extracting a historical processing data set, an operator behavior data set, and an environmental data set from processing information of a food processing production line, and determining a first contamination degree R1, a second contamination degree R2, and a third contamination degree R3 of the food processing production line, respectively; like , then the contamination judgment value of the food processing production line is recorded as 1, indicating that the food processing production line needs to be cleaned. Represents the logical symbol or; like , then the contamination judgment value of the food processing production line is recorded as -1, indicating that the food processing production line does not need to be cleaned. Represents the logical symbol and.

4. The enterprise safety production management method according to claim 3, characterized in that: The specific method for determining the first contamination level of the food processing production line is as follows: Extract the type and quantity of food processed at each time node from the historical processing data set of the food processing production line, and match the pollution characteristic parameter SE of the food type processed at each time node of the food processing production line from the pollution characteristic parameter corresponding to each food type stored in the web data warehouse, where the pollution characteristic parameter corresponding to each food type contains a value of 0-1; According to the time node, draw the SE-t trend curve A and SL-t trend curve B in the plane rectangular coordinate system, where t represents the time node number; Correlation analysis is performed on curves A and B. If curves A and B meet two conditions respectively, the first contamination degree of the food processing production line is recorded as 1, otherwise it is recorded as -1. Condition 1 is that the number of vertices of curve A is greater than or equal to b, where b is the preset threshold. Condition 2 is that the overall trend of curve B is rising and the total processing quantity is greater than u, where u is the total suitable processing quantity of the food processing production line stored in the web data warehouse.

5. The enterprise safety production management method according to claim 3, characterized in that: The specific method for determining the second contamination level of the food processing production line is as follows: The output times and average risk distance of each risk action type at each time node are extracted from the operator behavior dataset of the food processing production line; The output times and average risk distance of each risk action type at each time node of the food processing production line are imported into the second pollution assessment model. In the second pollution level of the output food processing production line; In the formula , They are represented as existential quantifiers and universal quantifiers respectively. , is the action risk index of the i-th time node of the food processing production line, , , are the allowed output times, safe average distance, and action risk index threshold of the mth risk action type stored in the web data warehouse, respectively. is the number of each time node, , is an integer greater than 2, is the number of each risk action type, , is an integer greater than 2.

6. The enterprise safety production management method according to claim 3, characterized in that: The specific method for determining the third contamination degree of the food processing production line is as follows: Extract the characteristic parameters of each environmental data at each time node from the environmental data set of the food processing production line, and then extract the characteristic parameters of each pollution-related environmental data at each time node of the food processing production line in combination with each pollution-related environmental data stored in the web data warehouse, and compare it with the safety characteristic parameter interval of each pollution-related environmental data stored in the web data warehouse. If the characteristic parameter of a certain pollution-related environmental data is not in the safety characteristic parameter interval, then record the pollution-related environmental data as risky environmental data, and summarize to obtain various risky environmental data; The number of risk environment data and the number of pollution-related environment data at each time node of the food processing production line are statistically obtained, and divided to obtain the environmental risk ratio Ht at each time node of the food processing production line. In the rectangular coordinate system, the Ht-t trend line P is fitted, and the slope of the line P is obtained. When the slope of the line P is greater than or equal to the preset growth slope, the third pollution degree of the food processing production line is recorded as 1, otherwise, it is recorded as -1.

7. The enterprise safety production management method according to claim 2, characterized in that: The microbial growth judgment value of the food processing production line is specifically determined by: Extracting a historical processing data set, an operator behavior data set, and an environmental data set from processing information of a food processing production line, and determining a first microbial growth value E1, a second microbial growth value E2, and a third microbial growth value E3 of the food processing production line, respectively; like , then the microbial growth judgment value of the food processing production line is recorded as 1, indicating that the food processing production line needs to be disinfected; like , the microbial growth judgment value of the food processing production line is recorded as -1, indicating that the food processing production line does not need to be disinfected.

8. The enterprise safety production management method according to claim 3, characterized in that: The specific method for determining the cleaning scheme of the food processing production line is as follows: According to the first contamination degree, the second contamination degree and the third contamination degree of the food processing production line, when the first contamination degree, the second contamination degree and the third contamination degree are all 1, the cleaning rule code of the food processing production line is recorded as 111; when two of the first contamination degree, the second contamination degree and the third contamination degree are 1, the cleaning rule code of the food processing production line is recorded as 110; when one of the first contamination degree, the second contamination degree and the third contamination degree is 1, the cleaning rule code of the food processing production line is recorded as 100; According to the cleaning rule code of the food processing production line, combined with the cleaning schemes corresponding to each cleaning rule code stored in the web data warehouse, the cleaning scheme of the food processing production line is matched, and the cleaning scheme includes the concentration of the cleaning liquid, the cleaning time and the cleaning power.

9. The enterprise safety production management method according to claim 7, characterized in that: The specific method for determining the disinfection scheme for the food processing production line is as follows: According to the first microbial growth value, the second microbial growth value and the third microbial growth value of the food processing production line, when the first microbial growth value, the second microbial growth value and the third microbial growth value are all 1, the disinfection rule code of the food processing production line is recorded as 111; when two of the first microbial growth value, the second microbial growth value and the third microbial growth value are 1, the disinfection rule code of the food processing production line is recorded as 110; when one of the first microbial growth value, the second microbial growth value and the third microbial growth value is 1, the disinfection rule code of the food processing production line is recorded as 100; Determine the dominant microbial species in food processing production lines based on historical processing data sets, operator behavior data sets, and environmental data sets; Based on the dominant microbial species in the food processing production line, combined with the UV sensitivity database of dominant microbial species stored in the web data warehouse, the UV sensitive wavelength corresponding to the dominant microbial species in the food processing production line is screened and obtained as the UV wavelength; According to the disinfection rule code and dominant microorganism species of the food processing production line, combined with the disinfection time corresponding to each disinfection rule code of each dominant microorganism species stored in the web data warehouse, the disinfection time of the food processing production line is matched; Generate a disinfection plan for the food processing production line based on the ultraviolet wavelength and disinfection duration of the food processing production line.

10. The enterprise safety production management method according to claim 9, characterized in that: The specific method for determining the dominant microorganisms in the food processing production line is as follows: The dominant microbial species, historical processing data sets, operator behavior data sets and environmental data sets of each historical production are extracted from the prior data in the web data warehouse, and the historical processing data sets, operator behavior data sets and environmental data sets of the food processing production line are compared with them for similarity, so as to obtain the processing similarity, operator behavior similarity and environmental similarity between the food processing production line and each historical production, and the overall similarity between the food processing production line and each historical production is obtained by mean processing; If the overall similarity between a food processing production line and a certain historical production is the greatest, the dominant microbial species of the historical production will be used as the dominant microbial species of the food processing production line.

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