A cloud-edge collaborative dangerous chemical management method, system, device and medium

Abstract

A cloud-edge collaborative dangerous chemical management method, system, device and medium are provided, and relate to the field of dangerous chemical management. In the method, a chemical compatibility risk value, an environmental out-of-control risk value, an equipment failure risk value and an operation risk value are weighted and summed to obtain a comprehensive risk value; when the comprehensive risk value is less than a preset first threshold value, a local demand prediction value is predicted, a local safety stock is calculated according to a service level and a demand fluctuation rate, a local gap value is determined according to a current inventory quantity of a first target region, the local demand prediction value and the local safety stock, and the local gap value is uploaded to the cloud; and a cross-warehouse allocation suggestion and a purchase suggestion of a target chemical are generated in the cloud according to a plurality of local gap values. By implementing the technical solution provided in the application, risk assessment and inventory analysis are performed by comprehensively considering various data, and effective management of dangerous chemicals is realized through cloud-edge collaboration.

Description

Technical Field

[0001] The present application relates to the technical field of hazardous chemicals management, and specifically to a cloud-edge collaborative hazardous chemicals management method, system, equipment and medium. Background Art

[0002] Traditionally, hazardous chemical management and control relies primarily on regular manual inspections to obtain relevant data. Staff assess the risks of hazardous chemicals based on their experience, drawing on their accumulated work experience to determine potential risks. However, manual inspections are prone to data omissions and errors, resulting in inaccurate information and making it difficult to fully and timely understand the actual situation of hazardous chemicals. Risk assessments based solely on experience lack a scientific basis, making it impossible to accurately calculate various risk values ​​and effectively prevent potential hazards. Summary of the Invention

[0003] This application provides a cloud-edge collaborative hazardous chemicals management method, system, equipment and medium, which realizes effective cloud-edge collaborative management of hazardous chemicals by conducting risk assessment and inventory analysis through comprehensive consideration of multiple data.

[0004] In a first aspect of the present application, a cloud-edge collaborative hazardous chemicals management and control method is provided, which is applied to a hazardous chemicals management and control platform. The method includes:

[0005] Obtain chemical data, environmental data, equipment data, and operational data for the first target area. The chemical data includes the chemical name and expiration date. The environmental data includes temperature, humidity, and light. The equipment data includes operational status data for the ventilation system, fire protection facilities, shelf load-bearing capacity, and explosion-proof electrical appliances. The operational data includes operator authority and protective equipment wearing status.

[0006] Constructing a taboo substance matrix based on a preset material safety data sheet and the chemical data, determining a chemical compatibility risk value for the first target area based on the taboo substance matrix, determining an environmental out-of-control risk value based on a degree of deviation between the environmental data and a preset safety threshold, determining an equipment failure risk value based on historical equipment failure data and the equipment data, determining an operational risk value based on the operational data, and performing a weighted summation of the chemical compatibility risk value, the environmental out-of-control risk value, the equipment failure risk value, and the operational risk value to obtain a comprehensive risk value;

[0007] When the comprehensive risk value is less than a preset first threshold, a preset forecasting algorithm is used to combine seasonal factors and event factors to generate a local demand forecast value for the target chemical, calculate a local safety stock based on the service level and demand volatility, determine a local gap value based on the current inventory of the first target area, the local demand forecast value, and the local safety stock, and upload the local gap value to the cloud;

[0008] The local gap values are uploaded to the cloud to generate cross-warehouse allocation suggestions and procurement suggestions for the target chemical.

[0009] By adopting the technical scheme, the chemical data, environmental data, equipment data and operation data are acquired, and a taboo substance matrix is constructed based on a preset material safety data sheet, so that the chemical compatibility risk value can be accurately determined. When the comprehensive risk value is less than a preset first threshold value, a preset prediction algorithm is used in combination with seasonal factors and event factors to generate a local demand prediction value of the target chemical. This prediction method considering various influencing factors can more accurately predict the demand of the chemical in a future period of time, and improve the accuracy of demand prediction. According to the current inventory of the first target region, the local demand prediction value and the local safety stock, the local gap value is determined, so that the situation of insufficient inventory can be found in time, and the local gap value is uploaded to the cloud to provide accurate information support for subsequent cross-warehouse allocation and procurement. By comprehensively considering the gap situations of multiple regions, global optimization of resources is realized, and the problems of local resource waste or shortage are avoided. The cross-warehouse allocation suggestion can reasonably arrange the allocation of chemicals according to the inventory situation of each warehouse and transportation cost and other factors, so as to reduce transportation cost and inventory cost. The procurement suggestion can select appropriate suppliers and procurement time according to the gap situation and market supply situation, so as to ensure timely supply of chemicals and improve resource utilization efficiency.

[0010] Optionally, the constructing a taboo substance matrix according to the preset material safety data sheet and the chemical data, and determining the chemical compatibility risk value of the first target region according to the taboo substance matrix comprises:

[0011] extracting chemical properties of all chemicals in the first target region from the preset material safety data sheet, and taking all combinations of the chemicals in the first target region as row and column indexes of the taboo substance matrix;

[0012] if the first chemical and the second chemical have a taboo relationship, marking a conflict probability of the first chemical and the second chemical at a corresponding position of the taboo substance matrix;

[0013] traversing storage positions of all chemicals in the first target region, and checking whether there is a target combination with a conflict probability greater than a preset second threshold value in the taboo substance matrix in adjacent storage positions;

[0014] determining the chemical compatibility risk value according to the conflict probability and the conflict severity of all target combinations.

[0015] By employing this technical solution, the chemical properties of all chemicals within the first target area are extracted from pre-set Material Safety Data Sheets (MSDSs). This provides comprehensive and accurate baseline data for the subsequent construction of a prohibited substance matrix, ensuring that all factors potentially influencing chemical compatibility within the target area are covered. All chemical storage locations within the first target area are traversed, and adjacent storage locations are checked for target combinations with a value greater than a preset second threshold in the prohibited substance matrix. This preset threshold allows for rapid screening of high-risk chemical combinations, improving the efficiency and targeting of risk screening, avoiding indiscriminate screening of all combinations, and saving time and computing resources. A chemical compatibility risk value is determined based on the conflict probability and conflict severity of all target combinations. This comprehensive consideration of the likelihood of a conflict (conflict probability) and the severity of the consequences of a conflict (conflict severity) makes the calculation of the chemical compatibility risk value more scientific and rational, accurately reflecting the chemical compatibility risk level of chemicals stored within the target area and providing a reliable quantitative basis for subsequent hazardous chemical control decisions.

[0016] Optionally, determining the chemical compatibility risk value of the first target area according to the taboo substance matrix, determining the environmental out-of-control risk value according to the degree of deviation between the environmental data and a preset safety threshold, determining the equipment failure risk value based on historical equipment failure data and the equipment data, and determining the operation risk value according to the operation data include:

[0017] The chemical compatibility risk value is calculated using the following formula:

[0018] ;

[0019] in, R 相容 Indicates the chemical compatibility risk value, P i Indicates the i The conflict probability of target combinations, S i Indicates the i The conflict severity of the target combination, i ∈[1, n ];

[0020] The risk value of environmental loss of control is calculated by the following formula:

[0021] ;

[0022] in, R 环境 Indicates the risk value of environmental loss of control, W j Indicates the j The weight of the environmental factors, T j Indicates thej The preset safety threshold of each environmental factor, V j Indicates the j The actual value of the environmental factor, j ∈[1, m ];

[0023] The equipment failure risk value is calculated using the following formula:

[0024] ;

[0025] in, R 设备 represents the equipment failure risk value, represents the failure rate, t Indicates the running time;

[0026] The operational risk value is calculated using the following formula:

[0027] ;

[0028] in, R 操作 Indicates the operation risk value. Illegal operations include inconsistent operator authority and incomplete wearing of protective equipment.

[0029] By employing this technical solution, chemical compatibility risk can be accurately quantified by multiplying and summing the conflict probability and conflict severity, clearly reflecting the impact of different chemical combinations on the overall risk. This provides a scientific basis for rationally planning chemical storage locations and avoiding high-risk combinations. This calculation method covers all combinations that may pose chemical compatibility risks within the target area, ensuring that no potential risk points are missed, making risk assessment more comprehensive and thorough, and facilitating the early detection and prevention of safety incidents caused by chemical incompatibility. By calculating the relative deviation between the actual value and the safety threshold and multiplying it by a weight, the contribution of each environmental factor to the overall risk of environmental uncontrollable conditions is scientifically assessed, making the assessment of environmental uncontrollable conditions more objective and accurate, and facilitating the development of targeted environmental control strategies. The ability to quickly determine the risk value of equipment failure allows managers to promptly understand the operating status of equipment, plan maintenance plans in advance, reduce the impact of equipment failure on hazardous chemical management, and improve production safety and stability. The operational risk value is calculated using a simple counting method, and the results are intuitive and easy to understand, allowing managers to quickly understand the overall level of operational risk and take corresponding measures to strengthen management, such as strengthening supervision, improving operating procedures, etc., to reduce the incidence of accidents caused by improper operations.

[0030] Optionally, the generating of a local demand forecast value for the target chemical using a preset forecasting algorithm in combination with seasonal factors and event factors, calculating a local safety stock based on a service level and a demand volatility, and determining a local gap value based on a current inventory level in the first target area, the local demand forecast value, and the local safety stock includes:

[0031] Determine an initial demand forecast value using the preset forecast algorithm;

[0032] Calculate the ratio of the average demand data of the current month to the average demand data of other months in the historical data, calculate the average of the ratio as the seasonal factor, and determine the event type and impact coefficient of the event that occurs within a preset time from the current moment, and determine the event factor based on the event type and the impact coefficient;

[0033] Correcting the initial demand forecast value according to the seasonal factor and the event factor to obtain a local demand forecast value;

[0034] Determine a service level coefficient based on a normal distribution table and the service level, calculate demand volatility using a standard deviation formula, and determine a local safety stock based on a replenishment cycle, the service level coefficient, and the demand volatility;

[0035] The local gap value is calculated by the following formula:

[0036] G=max(0,D−(I−S));

[0037] Where G represents the local gap value, D represents the local demand forecast value, I represents the current inventory of the first target area, S represents the local safety stock, and max(0, D−(I−S)) represents the maximum value between 0 and D−(I−S).

[0038] By employing this technical solution, an initial demand forecast is first generated using a preset forecasting algorithm, which is then corrected by introducing seasonal and event factors. The seasonal factor is determined by analyzing the ratio of average monthly demand values ​​in historical data, accurately capturing seasonal variations in chemical demand. The event factor is determined based on the type and impact coefficient of events occurring within a preset timeframe from the current time. This effectively accounts for the impact of special events (such as industry trade shows) on chemical demand, making the demand forecast more realistic. The local demand forecast, corrected by seasonal and event factors, comprehensively considers multiple factors influencing demand, reducing the limitations of a single forecasting method and significantly improving the accuracy and reliability of demand forecasts, providing a robust basis for companies to rationally plan production and procurement. The service level coefficient, determined based on a normal distribution table and service level, transforms the abstract service level into a concrete quantitative indicator, enabling companies to clearly define the inventory coverage required to achieve a specific service level when setting safety stocks. The demand volatility, calculated using the standard deviation formula, accurately measures fluctuations in chemical demand. The local safety stock is determined by combining the replenishment cycle, service level coefficient and demand fluctuation rate, so that the setting of safety stock can not only cope with normal fluctuations in demand but also avoid inventory backlogs, thereby improving the scientificity and economy of inventory management.

[0039] Optionally, generating the cross-warehouse allocation suggestion and the procurement suggestion of the target chemical in the cloud according to the multiple local gap values ​​includes:

[0040] screening a first target warehouse having redundant inventory in a cloud database based on the plurality of local gap values;

[0041] Generate multiple potential cross-warehouse transfer plans based on the spatial distance between the first target warehouse and the second target warehouse with a shortage, transportation costs, transportation time, and storage and transportation safety requirements of the chemicals;

[0042] For each potential cross-depot transfer plan, we screen target suppliers that meet the requirements based on the type and quantity of the missing chemicals and market dynamics data. We then use a pre-set cost-benefit analysis model to calculate the cost of direct procurement and, taking into account delivery times, generate multiple potential direct procurement plans.

[0043] A multi-attribute decision-making method is used to comprehensively evaluate the potential cross-warehouse transfer plan and the potential direct procurement plan to generate a cross-warehouse transfer suggestion and a procurement suggestion.

[0044] By employing this technical solution, the cloud database quickly identifies the first target warehouse with excess inventory based on multiple local shortage values. Leveraging the cloud's powerful data processing and storage capabilities, the cloud efficiently integrates inventory information from various warehouses, accurately identifying the source of available resources, avoiding blind searches and improving the accuracy and efficiency of resource location. When generating potential cross-warehouse transfer plans, the company comprehensively considers the spatial distance between the first target warehouse and the second target warehouse with a shortage, transportation costs and time, as well as the chemical storage and transportation safety requirements. This multi-dimensional consideration ensures that the transfer plan is both economical and meets safety and timeliness requirements, making transfer decisions more scientific and rational. Using a pre-defined cost-benefit analysis model, the cost of direct procurement is calculated and, based on delivery time, multiple potential direct procurement options are generated. This cost-benefit analysis model quantifies key factors such as procurement costs, transportation costs, and delivery time, providing a clear overview of the costs and benefits of procurement options, facilitating comparison and selection. A multi-attribute decision-making approach is used to comprehensively evaluate potential cross-warehouse transfer and direct procurement options. The multi-attribute decision-making method can comprehensively consider the weights and influences of multiple attributes such as cost, time, safety, and risk, and conduct a comprehensive and objective evaluation of different options, avoiding the limitations of single-factor decision-making and ensuring that the generated cross-warehouse allocation and procurement recommendations are the optimal or better options.

[0045] Optionally, the method further includes:

[0046] When the comprehensive risk value is greater than or equal to a preset first threshold, a second target area with the lowest current comprehensive risk value is determined, and the compatibility of the chemicals to be transferred in the first target area with all chemicals on the first path is checked to determine whether there is any taboo mixing, where the first path is any path from the first target area to the second target area;

[0047] A second path without taboo mixing is selected from the first path as a candidate path, and an optimal warehouse transfer path is determined based on the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area.

[0048] By employing the above technical solution, when the comprehensive risk value is greater than or equal to a preset first threshold, the system automatically identifies a second target area with the lowest current comprehensive risk value. This operation quickly locates a relatively safe storage location for the chemicals to be transferred, effectively reducing the probability of safety incidents potentially caused by the high risk of the first target area and ensuring the overall safety of hazardous chemical storage. The compatibility of the chemicals to be transferred in the first target area with all chemicals along the first route is checked to determine if any contraindicated mixing exists. This rigorous review of chemical compatibility prevents serious safety incidents such as chemical reactions, explosions, and fires caused by the contraindicated mixing of different chemicals during the transfer process, eliminating potential safety hazards at the source. A second route from the first route that does not contain contraindicated mixing is selected as the candidate route. This step ensures the safety of chemical storage along the transfer route, making the transfer operation physically and chemically feasible and avoiding delays or safety incidents caused by inappropriate route selection. The optimal transfer route is determined based on the risk scores of all areas along the candidate route and the distance to the detour area around equipment failures. By comprehensively considering the regional risk scores and detour distances, a route that strikes a balance between safety and efficiency can be found. It not only ensures that the chemicals are in a relatively safe storage environment during the transfer process, but also minimizes the time and cost of transfer, thereby improving the efficiency and economic benefits of the transfer operation.

[0049] Optionally, determining the optimal warehouse transfer path according to the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area includes:

[0050] The optimal transfer path is determined by the following formula:

[0051] ;

[0052] in, R i Indicates the first i The comprehensive risk value of the target area, D j Indicates detour j The distance to the equipment failure area, Indicates the weight corresponding to the comprehensive risk value, The weight representing the distance to avoid the equipment failure area.

[0053] By adopting the above technical solution, the comprehensive risk value of each target area on the candidate path and the distance to the bypass equipment failure area are quantified and assigned corresponding weights. This quantification method frees path assessment from the limitations of subjective experience and uses objective data as a basis, making the determination of the optimal transfer path more scientific and accurate. The comprehensive risk value weight reflects the importance attached to safety risks during the transfer process. During the calculation, multiple risk factors such as chemical compatibility, environment, equipment, and operation that may exist in each target area are comprehensively considered to ensure that the selected path can minimize the safety risks of hazardous chemicals during the transfer process and protect personnel and the environment. The weight of the distance to the bypass equipment failure area reflects the efficiency requirements of the transfer. While ensuring safety, try to choose a path with the shortest detour distance to reduce transfer time, reduce transportation costs, improve overall logistics efficiency, and make the transfer operation both safe and efficient.

[0054] In a second aspect of the present application, a cloud-edge collaborative hazardous chemicals management and control system is provided, including a collection module, a calculation module, a prediction module, and a suggestion module, wherein:

[0055] a collection module configured to acquire chemical data, environmental data, equipment data, and operation data of the first target area, wherein the chemical data includes name, expiration date, and chemical properties; the environmental data includes temperature, humidity, and light; the equipment data includes operating status data of the ventilation system, fire protection facilities, shelf load-bearing capacity, and explosion-proof electrical appliances; and the operation data includes operator authority and protective equipment wearing status;

[0056] a calculation module configured to construct a taboo substance matrix based on a preset material safety data sheet and the chemical data, determine a chemical compatibility risk value for the first target area based on the taboo substance matrix, determine an environmental loss of control risk value based on a degree of deviation between the environmental data and a preset safety threshold, determine an equipment failure risk value based on historical equipment failure data and the equipment data, determine an operational risk value based on the operational data, and perform a weighted summation of the chemical compatibility risk value, the environmental loss of control risk value, the equipment failure risk value, and the operational risk value to obtain a comprehensive risk value;

[0057] a forecasting module configured to, when the comprehensive risk value is less than a preset first threshold, use a preset forecasting algorithm in combination with seasonal factors and event factors to generate a local demand forecast value for the target chemical, calculate a local safety stock based on a service level and a demand volatility, determine a local gap value based on a current inventory level in the first target area, the local demand forecast value, and the local safety stock, and upload the local gap value to the cloud;

[0058] A suggestion module is configured to generate cross-warehouse allocation suggestions and procurement suggestions for the target chemical in the cloud according to the multiple local gap values.

[0059] In the third aspect of the present application, an electronic device is provided, including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs any of the methods described above.

[0060] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions. When the instructions are executed, any one of the methods described above is executed.

[0061] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0062] 1. By acquiring multi-source information such as chemical data, environmental data, equipment data, and operational data, and constructing a prohibited substance matrix based on the preset material safety data sheet, it is possible to comprehensively and accurately identify the potential risks in the first target area from multiple dimensions such as chemical compatibility, environmental out-of-control risk, equipment failure, and operational risk. The weighted sum of the chemical compatibility risk value, environmental out-of-control risk value, equipment failure risk value, and operational risk value is used to obtain a comprehensive risk value, thus achieving a quantitative assessment of the risk. This quantification method makes the size of the risk comparable, can clearly reflect the overall risk status of the target area, and provide a clear basis for subsequent risk response measures. Due to the continuous acquisition of various types of data and the real-time calculation of risk values, the risk status of the target area can be dynamically monitored. When the data changes, such as the ambient temperature rises, the equipment has a fault warning, etc., the risk value will be adjusted accordingly, so that new risks or risk trends can be discovered in a timely manner, preventive measures can be taken in advance, and accidents can be effectively avoided;

[0063] 2. When the comprehensive risk value is less than the preset first threshold, a preset forecasting algorithm is used in combination with seasonal factors and event factors to generate a local demand forecast for the target chemical. This forecasting method takes into account a variety of influencing factors and can more accurately predict the demand for chemicals in the future, avoiding inventory backlogs or out-of-stock problems caused by inaccurate demand forecasts. Calculating local safety stock based on service level and demand volatility makes the setting of safety stock more scientific and reasonable. Service level reflects the extent to which an enterprise meets customer needs, while demand volatility reflects the uncertainty of demand. By comprehensively considering these two factors, a suitable safety stock level can be determined, which can not only ensure that production or use needs can be met when demand fluctuates, but also avoid capital occupation and inventory cost increases caused by excessive reserves. The local gap value is determined based on the current inventory level of the first target area, the local demand forecast value and the local safety stock, so that it can be accurately known how many chemicals are needed to meet future demand. This provides accurate basic data for subsequent cross-warehouse transfers and procurement decisions, ensuring that enterprises can replenish inventory in a timely manner and avoid normal production or operations affected by out-of-stock activities;

[0064] 3. Generate cross-warehouse allocation suggestions for target chemicals in the cloud based on multiple local gap values, which can achieve the optimal allocation of resources between internal warehouses of the enterprise. By comprehensively considering the inventory situation and gap situation of each warehouse and rationally arranging the allocation of chemicals, it can reduce the simultaneous occurrence of inventory backlogs and out-of-stock phenomena, improve the overall inventory turnover efficiency of the enterprise, and reduce inventory costs. The generated procurement suggestions can help enterprises make more reasonable procurement decisions. Combined with local gap values ​​and market demand conditions, enterprises can determine the types, quantities and time of purchased chemicals to avoid blind procurement and excessive procurement. The entire management and control method is based on a large amount of actual data for risk assessment, demand forecasting, inventory management and decision-making, avoiding subjective conjecture and empiricism, and improving the scientific nature and accuracy of decision-making. The data sources are extensive and authentic and reliable, which can fully reflect the actual situation of the target area and provide strong support for decision-making;

[0065] 4. By monitoring risk values ​​and inventory levels in real time, the system can promptly issue warnings upon detecting anomalies, alerting relevant personnel to take emergency measures. This rapid response mechanism can shorten emergency response times, reduce the likelihood of accidents, and minimize the extent of losses. The cloud-edge collaborative architecture enables information sharing and collaboration across departments and warehouses within the enterprise. In emergencies, departments can quickly organize the allocation and procurement of chemicals based on cloud-generated allocation and procurement recommendations, ensuring the timely supply of emergency supplies and enhancing the enterprise's emergency response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1This is a flow chart of a cloud-edge collaborative hazardous chemicals management method disclosed in an embodiment of the present application;

[0067] Figure 2 This is a module diagram of a cloud-edge collaborative hazardous chemicals management and control system disclosed in an embodiment of the present application;

[0068] Figure 3 This is a structural diagram of an electronic device disclosed in an embodiment of the present application.

[0069] Explanation of the accompanying drawings: 201, acquisition module; 202, calculation module; 203, prediction module; 204, suggestion module; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0070] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0071] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0072] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0073] This embodiment discloses a cloud-edge collaborative hazardous chemicals management method. Figure 1 This is a flow chart of a cloud-edge collaborative hazardous chemicals management method disclosed in the embodiment of this application, which is applied to the hazardous chemicals management platform, such as Figure 1 As shown, the method includes the following steps:

[0074] S101. Acquire chemical data, environmental data, equipment data, and operation data for a first target area. The chemical data includes chemical name and expiration date; the environmental data includes temperature, humidity, and light intensity; the equipment data includes operating status data of ventilation systems, fire protection facilities, shelf loads, and explosion-proof electrical appliances; and the operation data includes operator authority and protective equipment wearing status.

[0075] S102. Constructing a contraindication substance matrix based on a preset material safety data sheet and the chemical data, determining a chemical compatibility risk value for the first target area based on the contraindication substance matrix, determining an environmental out-of-control risk value based on a degree of deviation between the environmental data and a preset safety threshold, determining an equipment failure risk value based on historical equipment failure data and the equipment data, determining an operational risk value based on the operational data, and performing a weighted summation of the chemical compatibility risk value, the environmental out-of-control risk value, the equipment failure risk value, and the operational risk value to obtain a comprehensive risk value;

[0076] S103. When the comprehensive risk value is less than a preset first threshold, a preset prediction algorithm is used in combination with seasonal factors and event factors to generate a local demand forecast value for the target chemical, a local safety stock is calculated based on the service level and demand volatility, a local shortfall value is determined based on the current inventory level of the first target area, the local demand forecast value, and the local safety stock, and the local shortfall value is uploaded to the cloud.

[0077] S104: Generate cross-warehouse allocation suggestions and procurement suggestions for the target chemical in the cloud according to the multiple local gap values.

[0078] Chemical data: includes the name and expiration date of the chemical. The name is used to identify the chemical, while the expiration date is related to the quality and safety of the chemical. Expired chemicals may have changed performance or even increased hazards. Environmental data: involves temperature, humidity, and light. These environmental factors have a significant impact on the storage stability of chemicals. For example, some chemicals may decompose at high temperatures, high humidity environments may cause chemicals to absorb moisture and clump or undergo chemical reactions, and light may cause some photosensitive chemicals to deteriorate. Equipment data: includes operating status data of ventilation systems, fire-fighting facilities, shelf load-bearing capacity, and explosion-proof electrical appliances. The ventilation system affects the air circulation in the area and is crucial for controlling chemical volatilization and maintaining air quality; the status of fire-fighting facilities is directly related to the ability to respond in the event of a fire; shelf load-bearing capacity data ensures the safety of chemical storage and avoids the collapse of overloaded shelves; the normal operation of explosion-proof electrical appliances can prevent accidents such as explosions caused by electrical failures. Operational data: covers the operator's authority and the wearing of protective equipment. Operator access management prevents unauthorized access to chemicals, reducing operational errors and safety risks. The proper use of protective equipment is crucial to operator safety; proper protective equipment can effectively minimize harm from chemicals. A prohibited substance matrix is ​​constructed based on pre-set material safety data sheets and collected chemical data. This matrix identifies any prohibited relationships between different chemicals—combinations of chemicals that should not be mixed, stored, or exposed to each other—providing a basis for subsequent chemical compatibility risk assessments. A chemical compatibility risk value is used to assess the potential risk posed by chemical incompatibilities within the first target area based on the prohibited substance matrix. An environmental out-of-control risk value is used to determine the risk to chemical storage safety posed by uncontrolled environmental factors by comparing the degree of deviation of environmental data from pre-set safety thresholds. An equipment failure risk value is used to determine the likelihood of equipment failure and its impact on chemical management, combining historical and current equipment failure data. An operational risk value is used to assess operational risks arising from operator access issues or improper use of protective equipment based on operational data. Calculate the comprehensive risk value: The chemical compatibility risk value, environmental loss of control risk value, equipment failure risk value, and operational risk value are weighted and summed to obtain the comprehensive risk value. This weighted summation method takes into account the impact of different risk factors on the overall risk, so that the comprehensive risk value can more accurately reflect the chemical management risk status of the first target area. Use a preset forecasting algorithm and combine seasonal factors and event factors to forecast local demand for target chemicals. Seasonal factors take into account the seasonal changes in chemical demand, while event factors cover special events that may affect chemical demand, such as industry exhibitions, to make demand forecasts more accurate. Calculate local safety stock based on service level and demand volatility. Service level reflects the extent to which a company meets customer needs, while demand volatility reflects the uncertainty of chemical demand.By calculating the safety stock, we ensure that there is enough inventory to meet demand when demand fluctuates and avoid out-of-stock situations. Calculate the local gap value based on the current inventory level of the first target area, the local demand forecast value, and the local safety stock. The local gap value indicates the amount by which the current inventory cannot meet future demand, providing a basis for subsequent inventory allocation and procurement. Upload the calculated local gap value to the cloud so that inventory management and allocation decisions can be made on a larger scale. Analyze the local gap values ​​and inventory conditions in different regions, consider factors such as transportation costs and time, and generate reasonable cross-library transfer suggestions to achieve optimal inventory configuration, improve inventory utilization, and reduce overall inventory costs. Based on the local gap value and market demand, combined with supplier information, procurement costs and other factors, generate procurement suggestions to ensure that companies can replenish inventory in a timely and economical manner to meet production or sales needs.

[0079] Optionally, constructing a taboo substance matrix according to a preset material safety data sheet and the chemical data, and determining the chemical compatibility risk value of the first target area according to the taboo substance matrix includes:

[0080] Extracting chemical properties of all chemicals in the first target area from the preset material safety data sheet, and using any two combinations of all chemicals in the first target area as row and column indexes of the prohibited substance matrix;

[0081] If a taboo relationship exists between the first chemical and the second chemical, the conflict probability between the first chemical and the second chemical is marked at the corresponding position of the taboo substance matrix;

[0082] Traversing all storage locations of chemicals in the first target area, and checking whether there is a target combination with a mark greater than a preset second threshold in the taboo substance matrix in adjacent storage locations;

[0083] The chemical compatibility risk value is determined based on the conflict probability and conflict severity of all target combinations.

[0084] A pre-set Material Safety Data Sheet (MSDS) is a database containing extensive chemical information, detailing the chemical properties of each chemical, such as composition, reactivity, and stability. Extracting these chemical properties from this table for all chemicals within the first target area allows for accurate subsequent assessment of any potential compatibility relationships between them. Chemical properties determine how chemicals interact. For example, contact between a strongly oxidizing chemical and a flammable chemical can trigger a violent reaction or even explosion. Pairwise combinations of all chemicals within the first target area serve as row and column indices for the taboo substance matrix. This means that both the rows and columns of the matrix represent different chemicals within the target area. This combination systematically covers all possible pairwise combinations of chemicals within the target area, establishing a framework for comprehensive chemical compatibility risk assessment. For example, if there are three chemicals, A, B, and C, within the target area, the row and column indices of the taboo substance matrix would include (A, B), (A, C), (B, A), (B, C), (C, A), and (C, B). For each combination of the first and second chemicals, the presence of a taboo relationship is determined based on pre-set rules and knowledge. A taboo relationship indicates that two chemicals cannot be mixed, stored, or come into contact with each other, as this could lead to hazardous situations such as chemical reactions, fires, and explosions. If a taboo relationship exists between the first and second chemicals, their conflict probability is marked at the corresponding location in the taboo matrix. The conflict probability is a quantitative indicator that indicates the likelihood of conflict between the two taboo chemicals under specific conditions. For example, some chemicals may react only slowly at room temperature and pressure, resulting in a low conflict probability. However, under conditions of high temperature, high pressure, or in the presence of catalysts, the reaction may intensify, significantly increasing the conflict probability. By marking the conflict probability, the risk level of different taboo chemical combinations can be more accurately assessed. A comprehensive traversal of all chemical storage locations within the first target area is performed to gain a realistic understanding of the spatial distribution of chemicals, as their storage location directly influences their potential for interaction. For example, chemicals stored adjacent to each other are much more likely to come into contact than those stored farther apart. During the traversal, adjacent storage locations are checked for target combinations with a conflict probability greater than a preset second threshold in the taboo matrix. This second threshold is a critical value set based on safety standards and actual needs. Only taboo chemical combinations with a conflict probability greater than this threshold are considered to have a high risk. This screening method can screen for chemical combinations that could pose serious safety risks in actual storage. For example, if the second threshold is set at 0.7, only adjacent storage of prohibited chemicals with a conflict probability greater than 0.7 will be considered. Conflict severity refers to the severity of the consequences that could arise if prohibited chemicals clash.The consequences of conflicts between different prohibited chemical combinations can vary widely, ranging from simple chemical deterioration to potentially large-scale explosions or fires, resulting in significant casualties and property damage. Therefore, when assessing chemical compatibility risk, it's important to consider not only the probability of conflict but also the severity of the conflict. By combining the conflict probability and severity of all target combinations, a chemical compatibility risk value is determined using a pre-set mathematical model or algorithm. This risk value comprehensively reflects the chemical compatibility safety status of chemicals in the first target area. A higher risk value indicates a greater likelihood of safety incidents due to chemical incompatibility in that area. For example, a weighted summation approach can be used to multiply the conflict probability and severity of each target combination by their respective weights and then add them together to determine the chemical compatibility risk value. This approach allows for a more scientific and comprehensive assessment of the chemical compatibility risk in the first target area, providing a basis for subsequent safety management and decision-making.

[0085] Optionally, determining the chemical compatibility risk value of the first target area according to the taboo substance matrix, determining the environmental out-of-control risk value according to the degree of deviation between the environmental data and a preset safety threshold, determining the equipment failure risk value based on historical equipment failure data and the equipment data, and determining the operation risk value according to the operation data include:

[0086] The chemical compatibility risk value is calculated using the following formula:

[0087] ;

[0088] in, R 相容 Indicates the chemical compatibility risk value, P i Indicates the i The conflict probability of target combinations, S i Indicates the i The conflict severity of the target combination, i ∈[1, n ];

[0089] The risk value of environmental loss of control is calculated using the following formula:

[0090] ;

[0091] in, R 环境 Indicates the risk value of environmental loss of control, W j Indicates the j The weight of the environmental factors, T j Indicates the j The preset safety threshold of each environmental factor,V j Indicates the j The actual value of the environmental factor, j ∈[1, m ];

[0092] The equipment failure risk value is calculated using the following formula:

[0093] ;

[0094] in, R 设备 represents the equipment failure risk value, represents the failure rate, t Indicates the running time;

[0095] The operational risk value is calculated using the following formula:

[0096] ;

[0097] in, R 操作 Indicates the operation risk value. Illegal operations include inconsistent operator authority and incomplete wearing of protective equipment.

[0098] By multiplying the conflict probability and conflict severity and summing them, we can comprehensively consider the possibility and consequences of conflicts among different target combinations, thereby more accurately assessing the chemical compatibility risk of the first target area. For example, if there are multiple target combinations, some of which have a high probability of conflict but a low severity, while others have a low probability of conflict but a high severity, the above formula can combine these factors to give a reasonable risk value. Environmental factor weight W j Reflects the j The degree of impact of environmental factors on chemical storage safety. Different environmental factors have different effects on chemicals. For example, for some volatile chemicals, the weight of temperature may be higher; while for some hygroscopic chemicals, the weight of humidity may be higher. The weight value is usually determined based on actual experience and expert evaluation, ranging from 0 to 1, and the sum of the weights of all environmental factors is 1. Preset safety threshold T j It is the pre-set jAn upper or lower limit value of a safety range of an environmental factor. When the actual value of the environmental factor exceeds this threshold, it may have an adverse effect on the safety of chemical storage. For example, the upper limit of the storage temperature of some chemicals is 30°C, so 30°C is the preset safety threshold of the environmental factor of temperature. Failure rate refers to the probability of equipment failure per unit time. It can be obtained by statistical analysis of historical failure data of the equipment, or it can be estimated according to the reliability model of the equipment. The higher the failure rate, the more likely the equipment is to fail during operation. For example, some old equipment or frequently used equipment may have a relatively high failure rate. The running time is the total running time of the equipment from the time of putting into use to the current time. The longer the running time, the higher the probability of equipment failure. For example, a device that has been running for several years is more likely to fail than a newly installed device. Inappropriate operator authority refers to the operator not performing chemical operations according to the prescribed authority, for example, unauthorized personnel entering the chemical storage area or performing operations, which may lead to misoperation or misuse of chemicals, increasing the safety risk. Incomplete wearing of protective equipment: If the operator does not correctly wear protective equipment such as protective clothing, gloves, and goggles when contacting chemicals, they may directly contact the chemicals, causing physical harm. At the same time, incomplete wearing of protective equipment may also affect the accuracy and safety of the operator's operation. By evaluating and quantifying the violation of the operator's authority and the incomplete wearing of protective equipment, the operation risk value can be determined. The larger the value, the more unsafe factors exist in the operation process, and the higher the probability of an operation accident. For example, if multiple instances of inappropriate operator authority or incomplete wearing of protective equipment are found within a certain period of time, the operation risk value will increase accordingly, and the management and training of the operator need to be strengthened.

[0099] Optionally, the preset prediction algorithm is used to generate a local demand prediction value of the target chemical in combination with a seasonal factor and an event factor, a local safety stock is calculated according to a service level and a demand fluctuation rate, and a local gap value is determined according to a current inventory of the first target area, the local demand prediction value, and the local safety stock, comprising:

[0100] An initial demand prediction value is determined using the preset prediction algorithm;

[0101] The average value of the demand data of the current month and the average value of the demand data of other months in the historical data are calculated, the average value of the ratio of the average value of the demand data of the current month to the average value of the demand data of other months is calculated as a seasonal factor, the type of an event occurring within a preset time from the current time and an influence coefficient are determined, and an event factor is determined according to the type of the event and the influence coefficient;

[0102] The initial demand prediction value is corrected according to the seasonal factor and the event factor to obtain a local demand prediction value.

[0103] Determine a service level coefficient based on a normal distribution table and the service level, calculate demand volatility using a standard deviation formula, and determine a local safety stock based on a replenishment cycle, the service level coefficient, and the demand volatility;

[0104] The local gap value is calculated by the following formula:

[0105] G=max(0,D−(I−S));

[0106] Where G represents the local gap value, D represents the local demand forecast value, I represents the current inventory of the first target area, S represents the local safety stock, and max(0, D−(I−S)) represents the maximum value between 0 and D−(I−S).

[0107] Use a preset forecasting algorithm to determine the initial demand forecast. This can be a variety of common forecasting models, such as moving average, exponential smoothing, and linear regression. These algorithms analyze and calculate historical demand data, fitting the changing trends in the target chemical's demand over a period of time to produce a preliminary forecast result, known as the initial demand forecast. For example, when using the simple moving average method, demand data from several past periods is selected and averaged to serve as the initial demand forecast for the next period. The average demand data for the current month and the average demand data for each of the other months in the historical data are calculated. The ratio of the current month's average demand data to the average demand data for each of the other months is then calculated. For example, if it is May, the ratio of the average demand data for May to the average demand data for January, February, March, April, and June is calculated. The average of all these ratios is calculated and used as the seasonal factor. The seasonal factor reflects the relative variation in the target chemical's demand across different months. For example, if demand for certain chemicals increases in the summer due to high temperatures, the corresponding seasonal factor will be greater than 1; while demand decreases in the winter, the seasonal factor will be less than 1. Identify events occurring within a preset timeframe from the current time. These events could include industry trade shows, new product launches, and so on. For each event, analyze its impact on the demand for the target chemical and determine the corresponding event type and impact coefficient. The impact coefficient can be determined based on historical data for similar events. Its value typically ranges from -1 to 1, with a positive number indicating an increase in demand and a negative number indicating a decrease. Larger absolute values ​​indicate a greater impact. Based on the event type and impact coefficient, the event factor is calculated using specific rules or models. For example, the impact coefficients of multiple events can be weighted and summed to produce a comprehensive event factor that reflects their overall impact on the demand for the target chemical. The calculated seasonal and event factors are applied to the initial demand forecast to correct it. This correction can be performed by multiplying the initial demand forecast by the product of the seasonal and event factors, or by using other appropriate correction methods based on the specific business logic and model design. This correction ensures that the local demand forecast more accurately reflects actual demand, taking into account seasonal variations and the impact of special events. The service level represents the probability that a company will meet customer demand. For example, a service level of 95% means there is a 95% probability that the company will be able to meet customer demand for the target chemical on time. Based on a normal distribution table, find the quantile corresponding to the service level; this quantile is the service level coefficient. For example, a service level of 95% corresponds to a service level coefficient of approximately 1.645. The standard deviation formula is used to calculate demand volatility.First, collect historical demand data, calculate the deviation between the demand value and the average demand value for each period, then square, sum, and average these deviations, and finally take the square root to obtain the standard deviation of the demand, that is, the demand volatility. The demand volatility reflects the degree of uncertainty in the demand for the target chemical. The greater the volatility, the more unstable the demand. Determine the local safety stock based on the replenishment cycle, service level coefficient, and demand volatility. The replenishment cycle refers to the time required from the issuance of the replenishment order to the arrival of the goods at the first target area. In an embodiment of the present application, the calculation formula for the local safety stock is simplified to: local safety stock = service level coefficient × demand volatility × replenishment cycle. By calculating the local safety stock, it can be ensured that within the replenishment cycle, even if demand fluctuates, the company will have enough inventory to meet customer demand and avoid out-of-stock situations. In the above formula, G represents the local gap value: that is, the amount of the current inventory in the first target area that cannot meet the local demand forecast value. If the calculation result is a negative number, it means that the current inventory is sufficient to meet the demand, and 0 is taken as the local gap value. D represents the local demand forecast: it is the target chemical demand forecast adjusted for seasonal and event factors, reflecting the expected demand for the target chemical in the first target region over the next period of time. I represents the current inventory level in the first target region: the actual quantity of the target chemical in hand at the current moment. S represents the local safety stock: a level of inventory established to account for demand fluctuations and uncertainties in replenishment cycles. In the formula, D−(I−S) represents the local demand forecast minus the current available inventory (current inventory minus the safety stock). By taking the maximum of 0 and D−(I−S), the local gap value is guaranteed to be non-negative, thus more accurately reflecting the actual inventory gap. For example, if D−(I−S) = −10, the local gap value G = 0; if D−(I−S) = 20, the local gap value G = 20.

[0108] Optionally, generating the cross-warehouse allocation suggestion and the procurement suggestion of the target chemical in the cloud according to the multiple local gap values ​​includes:

[0109] screening a first target warehouse having redundant inventory in a cloud database based on the plurality of local gap values;

[0110] Generate multiple potential cross-warehouse transfer plans based on the spatial distance between the first target warehouse and the second target warehouse with a shortage, transportation costs, transportation time, and storage and transportation safety requirements of the chemicals;

[0111] For each potential cross-warehouse transfer plan, we screen target suppliers that meet the requirements based on the type and quantity of the missing chemicals and market dynamics data. We then use a pre-set cost-benefit analysis model to calculate the cost of direct procurement and, taking into account delivery times, generate multiple potential direct procurement plans.

[0112] A multi-attribute decision-making method is used to comprehensively evaluate the potential cross-warehouse transfer plan and the potential direct procurement plan to generate a cross-warehouse transfer suggestion and a procurement suggestion.

[0113] A cloud-based database stores inventory information for each warehouse. Through query and comparison, it identifies warehouses with inventory exceeding their normal needs (i.e., excess inventory) and marks them as primary target warehouses. For example, if a warehouse's normal inventory requirement is 100 units of a target chemical based on historical sales data and safety stock settings, but its current inventory is 150 units, then this warehouse would be considered a primary target warehouse with excess inventory. The distance between the primary target warehouse and the secondary target warehouse with a shortage is a key consideration. The closer the distance, the lower the time and cost of transportation, while also reducing the potential safety risks of chemicals exposed to prolonged transportation. Transportation costs include transportation fees, loading and unloading charges, and other factors. Different transportation methods (such as road, rail, and air) have significantly different costs. Choosing the appropriate transportation method based on the characteristics and urgency of the chemical is crucial to manage transportation costs. Transportation time: For urgently needed target chemicals, transportation time is crucial. Shorter transportation times can more quickly meet the shortage at the secondary target warehouse, minimizing production or sales disruptions caused by stockouts. Chemical storage and transportation safety requirements: Target chemicals may be flammable, explosive, or corrosive, requiring specific safety conditions during transportation and storage. For example, some chemicals require refrigerated transportation, so the appropriate refrigeration equipment and conditions must be available when selecting a transportation solution. Taking these factors into consideration, generate multiple potential cross-warehouse transfer options for each pair of a primary target warehouse with excess inventory and a secondary target warehouse with a shortage. These options may involve different transportation methods, routes, and timelines. Based on the type and quantity of the missing chemicals, screen target suppliers based on market dynamics data. This data includes information such as supplier product range, inventory levels, production capacity, and reputation. Ensure that the target supplier can provide the required type and quantity of the target chemicals and has a good reputation and stable supply capacity. For example, for a specialty chemical, select a supplier with production qualifications and reliable product quality. Calculate direct procurement costs: Using a pre-defined cost-benefit analysis model, factoring in market prices, transportation costs, and tariffs (if import or export is involved), calculate the cost of directly procuring the missing chemical from each target supplier. In addition to cost, delivery time is also a key consideration for direct procurement. Based on the supplier's promised delivery time and the urgency of the shortage at the secondary target warehouse, multiple potential direct procurement options are generated. These options may vary in cost and delivery time. For example, some suppliers may offer lower prices but longer delivery times, while others may offer higher prices but faster delivery. A multi-attribute decision-making method is used to comprehensively evaluate potential cross-warehouse transfer options and potential direct procurement options. This method can simultaneously consider multiple evaluation metrics, such as cost, time, safety, and reliability, and assign appropriate weights to each metric.Based on the company's strategic goals and actual circumstances, various metrics are determined for evaluating the options, such as a weight of 0.4 for cost, 0.3 for time, 0.2 for safety, and 0.1 for reliability. Each potential cross-pool transfer and direct procurement option is scored based on its performance in each metric. For example, for cost, the option's actual cost is scored relative to the budgeted cost; for time, the option's estimated delivery time matches the required time. Each option's score for each metric is multiplied by its corresponding weight and added together to create a comprehensive score. All options are ranked based on their comprehensive scores, and the option with the highest comprehensive score is selected as the recommended option. Cross-pool transfer and procurement recommendations are generated. For example, if the cross-pool transfer option has a higher comprehensive score than the direct procurement option, cross-pool transfer is recommended to meet the shortfall; otherwise, direct procurement is recommended. Alternative options are also provided based on their strengths and weaknesses for decision-making.

[0114] Optionally, the method further includes:

[0115] When the comprehensive risk value is greater than or equal to a preset first threshold, a second target area with the lowest current comprehensive risk value is determined, and the compatibility of the chemicals to be transferred in the first target area with all chemicals on the first path is checked to determine whether there is any taboo mixing, where the first path is any path from the first target area to the second target area;

[0116] A second path without taboo mixing is selected from the first path as a candidate path, and an optimal warehouse transfer path is determined based on the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area.

[0117] When the calculated comprehensive risk value is greater than or equal to a preset first threshold, it indicates that the first target area faces a high level of comprehensive risk. This risk may include chemical compatibility risk, environmental loss of control risk, equipment failure risk, and operational risk, reaching a level that requires action. At this point, a second target area with the lowest comprehensive risk value must be identified within the entire system. The comprehensive risk value is calculated through a quantitative assessment of multiple risk factors. A lower risk value indicates a relatively safer and more stable area. Selecting such an area as a transfer target can reduce the overall risk of chemical transfer and storage. For example, within a chemical storage warehouse, there are multiple areas. By comparing the comprehensive risk values ​​of each area, the area with the lowest risk value can be identified as the second target area. The first path is defined as any path from the first target area to the second target area. In practice, there may be multiple feasible paths, each of which may pass through different intermediate areas and equipment. The compatibility of the chemicals to be transferred in the first target area with all chemicals along the first path is checked to determine whether any prohibited mixing exists. Contraindications for co-location refer to the situation where certain chemicals, due to their chemical properties, cannot come into contact or be stored together. Doing so could trigger a chemical reaction, leading to serious accidents such as fire, explosion, and poisoning. For example, acids and bases are generally not allowed to be stored together because they undergo neutralization reactions and release significant amounts of heat. By consulting the chemical's Material Safety Data Sheet (MSDS), chemical compatibility matrix, and other information, the chemical to be transferred can be compared with the chemical properties of the chemicals already stored in each area along the first path to determine if there is a contraindication. If there is a contraindication for co-location, the first path cannot be used as the transfer route. From all first paths, paths with contraindications for co-location are excluded, and the remaining paths without contraindications are selected as second paths. These second paths become candidate paths. This step ensures that chemical co-location does not pose safety risks during the transfer process. The candidate paths provide the basis for subsequent selection of the optimal transfer path. They are all feasible paths that meet chemical compatibility requirements. The risk score for all areas along the candidate path is derived from a quantitative assessment of their risk profiles in terms of chemical compatibility, environment, equipment, and operations. Each area's risk score reflects its current safety level and potential risk. When selecting the optimal transfer path, paths with lower-risk areas are prioritized. This is because lower risk scores indicate that the areas along the path are relatively safer, and the probability of risk occurring during the transfer is lower. For example, if one potential path passes through multiple areas with lower risk scores, while another potential path passes through areas with higher risk scores, then, all other things being equal, the former will be prioritized. In actual transfer paths, there may be areas with equipment failures.Equipment failures can affect chemical transportation safety. For example, a faulty pipeline could cause a chemical leak, or a faulty lifting device could cause an accident during handling. Therefore, it's important to avoid the faulty area whenever possible. This increases the length of the transfer route, potentially increasing transportation time and cost. When selecting the optimal transfer route, it's important to comprehensively consider the distance around the faulty area. A route with a shorter detour, minimal impact on overall transportation time and cost, and effective avoidance of the faulty area is preferred. By comprehensively considering the risk scores of all areas along the candidate route and the distance around the faulty area, a decision-making method (such as a weighted scoring method or the analytic hierarchy process) is used to comprehensively evaluate and rank the candidate routes. The route with the best overall evaluation result is selected as the optimal transfer route. For example, weights are assigned to the risk score and detour distance, and a comprehensive score is calculated for each candidate route. The route with the highest score is the optimal transfer route.

[0118] Optionally, determining the optimal warehouse transfer path according to the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area includes:

[0119] The optimal transfer path is determined by the following formula:

[0120] ;

[0121] in, R i Indicates the first i The comprehensive risk value of the target area, D j Indicates detour j The distance to the equipment failure area, Indicates the weight corresponding to the comprehensive risk value, The weight representing the distance to avoid the equipment failure area.

[0122] For each candidate path, determine the comprehensive risk value of all target areas on the path R i , as well as the number of equipment fault areas that need to be detoured and the detour distance corresponding to each fault area D j Reasonably set the weight corresponding to the comprehensive risk value based on the company's security strategy, cost budget, time requirements and other actual conditions. Weight of the distance to the bypass equipment failure area The above formula multiplies the sum of the comprehensive risk values ​​of all target areas on the path by the weight of the comprehensive risk value, and then adds the sum of the distances to all bypass equipment failure areas multiplied by the weight of the bypass distance to obtain the final score of the path. This calculation process is repeated for all candidate paths to obtain the score of each path. The scores of each path are compared. The path with the lower score indicates that the path performs better when considering the risk and bypass distance. Therefore, the path with the lowest score is selected as the optimal warehouse transfer path.

[0123] This embodiment also discloses a cloud-edge collaborative hazardous chemicals management and control system. Figure 2 This is a module diagram of a cloud-edge collaborative hazardous chemicals management system disclosed in an embodiment of the present application, such as Figure 2 As shown, the system includes a collection module 201, a calculation module 202, a prediction module 203 and a suggestion module 204, wherein:

[0124] Acquisition module 201 is configured to acquire chemical data, environmental data, equipment data, and operation data of the first target area, wherein the chemical data includes name, expiration date, and chemical properties; the environmental data includes temperature, humidity, and light; the equipment data includes operating status data of the ventilation system, fire protection facilities, shelf load, and explosion-proof electrical appliances; and the operation data includes operator authority and protective equipment wearing status;

[0125] a calculation module 202 configured to construct a taboo substance matrix based on a preset material safety data sheet and the chemical data, determine a chemical compatibility risk value for the first target area based on the taboo substance matrix, determine an environmental out-of-control risk value based on a degree of deviation between the environmental data and a preset safety threshold, determine an equipment failure risk value based on historical equipment failure data and the equipment data, determine an operational risk value based on the operational data, and perform a weighted summation of the chemical compatibility risk value, the environmental out-of-control risk value, the equipment failure risk value, and the operational risk value to obtain a comprehensive risk value;

[0126] The prediction module 203 is configured to, when the comprehensive risk value is less than a preset first threshold, use a preset prediction algorithm in combination with seasonal factors and event factors to generate a local demand forecast value for the target chemical, calculate a local safety stock based on the service level and demand volatility, determine a local shortfall value based on the current inventory of the first target area, the local demand forecast value, and the local safety stock, and upload the local shortfall value to the cloud;

[0127] The suggestion module 204 is configured to generate a cross-warehouse allocation suggestion and a purchase suggestion for the target chemical in the cloud according to the multiple local gap values.

[0128] Optionally, the calculation module 202 is configured to:

[0129] Extracting chemical properties of all chemicals in the first target area from the preset material safety data sheet, and using any two combinations of all chemicals in the first target area as row and column indexes of the prohibited substance matrix;

[0130] If a taboo relationship exists between the first chemical and the second chemical, the conflict probability between the first chemical and the second chemical is marked at the corresponding position of the taboo substance matrix;

[0131] Traversing all storage locations of chemicals in the first target area, and checking whether there is a target combination with a mark greater than a preset second threshold in the taboo substance matrix in adjacent storage locations;

[0132] The chemical compatibility risk value is determined based on the conflict probability and conflict severity of all target combinations.

[0133] Optionally, the calculation module 202 is configured to:

[0134] The chemical compatibility risk value is calculated using the following formula:

[0135] ;

[0136] in, R 相容 Indicates the chemical compatibility risk value, P i Indicates the i The conflict probability of target combinations, S i Indicates the i The conflict severity of the target combination, i ∈[1, n ];

[0137] The risk value of environmental loss of control is calculated by the following formula:

[0138] ;

[0139] in, R 环境 Indicates the risk value of environmental loss of control, W j Indicates the j The weight of the environmental factors, T j Indicates the j The preset safety threshold of each environmental factor, V j Indicates the j The actual value of the environmental factor, j ∈[1, m ];

[0140] The equipment failure risk value is calculated using the following formula:

[0141] ;

[0142] in, R 设备 represents the equipment failure risk value, represents the failure rate, t Indicates the running time;

[0143] The operational risk value is calculated using the following formula:

[0144] ;

[0145] in, R 操作 Indicates the operation risk value. Illegal operations include inconsistent operator authority and incomplete wearing of protective equipment.

[0146] Optionally, the prediction module 203 is configured to:

[0147] Determine an initial demand forecast value using the preset forecast algorithm;

[0148] Calculate the ratio of the average demand data of the current month to the average demand data of other months in the historical data, calculate the average of the ratio as the seasonal factor, and determine the event type and impact coefficient of the event that occurs within a preset time from the current moment, and determine the event factor based on the event type and the impact coefficient;

[0149] Correcting the initial demand forecast value according to the seasonal factor and the event factor to obtain a local demand forecast value;

[0150] Determine a service level coefficient based on a normal distribution table and the service level, calculate demand volatility using a standard deviation formula, and determine a local safety stock based on a replenishment cycle, the service level coefficient, and the demand volatility;

[0151] The local gap value is calculated by the following formula:

[0152] G=max(0,D−(I−S));

[0153] Where G represents the local gap value, D represents the local demand forecast value, I represents the current inventory of the first target area, S represents the local safety stock, and max(0, D−(I−S)) represents the maximum value between 0 and D−(I−S).

[0154] Optionally, the suggestion module 204 is configured to:

[0155] screening a first target warehouse having redundant inventory in a cloud database based on the plurality of local gap values;

[0156] Generate multiple potential cross-warehouse transfer plans based on the spatial distance between the first target warehouse and the second target warehouse with a shortage, transportation costs, transportation time, and storage and transportation safety requirements of the chemicals;

[0157] For each potential cross-depot transfer plan, we screen target suppliers that meet the requirements based on the type and quantity of the missing chemicals and market dynamics data. We then use a pre-set cost-benefit analysis model to calculate the cost of direct procurement and, taking into account delivery times, generate multiple potential direct procurement plans.

[0158] A multi-attribute decision-making method is used to comprehensively evaluate the potential cross-warehouse transfer plan and the potential direct procurement plan to generate a cross-warehouse transfer suggestion and a procurement suggestion.

[0159] Optionally, the method further includes a library transfer module configured to:

[0160] When the comprehensive risk value is greater than or equal to a preset first threshold, a second target area with the lowest current comprehensive risk value is determined, and the compatibility of the chemicals to be transferred in the first target area with all chemicals on the first path is checked to determine whether there is any taboo mixing, where the first path is any path from the first target area to the second target area;

[0161] A second path without taboo mixing is selected from the first path as a candidate path, and an optimal warehouse transfer path is determined based on the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area.

[0162] Optionally, the library transfer module is configured to:

[0163] The optimal transfer path is determined by the following formula:

[0164] ;

[0165] in, R i Indicates the first i The comprehensive risk value of the target area, D j Indicates detour j The distance to the equipment failure area, Indicates the weight corresponding to the comprehensive risk value, The weight representing the distance to avoid the equipment failure area.

[0166] It should be noted that the device and method embodiments provided in the above embodiments belong to the same concept, and their specific implementation processes are detailed in the method embodiments, which will not be repeated here.

[0167] This embodiment also discloses an electronic device, referring to Figure 3 The electronic device may include: at least one processor 301 , at least one communication bus 302 , a user interface 303 , a network interface 304 , and at least one memory 305 .

[0168] The communication bus 302 is used to implement the connection and communication between these components.

[0169] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0170] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0171] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts within the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. As Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for a cloud-edge collaborative hazardous chemicals management method.

[0172] exist Figure 3 In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call an application program stored in the memory 305 for a cloud-edge collaborative hazardous chemical management method. When executed by one or more processors 301, the electronic device executes one or more methods in the above embodiments.

[0173] It should be noted that, for the aforementioned method embodiments, the sequences of the described actions are not necessarily required to practice the present application and embodiments of the present application can be practiced in other sequences than the one described, and even at the same time. Furthermore, some of the actions can be left out or replaced by other actions involving far- out processing hardware. The description as such is a description of the preferred embodiment and does not limit the present application.

[0174] In the above embodiments, the description of each embodiment focuses on different aspects, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0175] The above descriptions are merely exemplary embodiments of the present disclosure, and cannot limit the scope of the present disclosure. Any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. Other embodiments of the present disclosure will be readily apparent to those skilled in the art upon considering the disclosure herein, with the present application intended to cover any variations, uses, or adaptations of the present disclosure following, in general, the principles of the present disclosure and including such modifications and features as are within the scope of the present disclosure.

Claims

1. A cloud-edge collaborative hazardous chemicals management method, characterized by: Applied to a hazardous chemicals management and control platform, the method includes: Obtain chemical data, environmental data, equipment data, and operational data for the first target area. The chemical data includes the chemical name and expiration date. The environmental data includes temperature, humidity, and light. The equipment data includes operational status data for the ventilation system, fire protection facilities, shelf load-bearing capacity, and explosion-proof electrical appliances. The operational data includes operator authority and protective equipment wearing status. Constructing a taboo substance matrix based on a preset material safety data sheet and the chemical data, determining a chemical compatibility risk value for the first target area based on the taboo substance matrix, determining an environmental out-of-control risk value based on a degree of deviation between the environmental data and a preset safety threshold, determining an equipment failure risk value based on historical equipment failure data and the equipment data, determining an operational risk value based on the operational data, and performing a weighted summation of the chemical compatibility risk value, the environmental out-of-control risk value, the equipment failure risk value, and the operational risk value to obtain a comprehensive risk value; When the comprehensive risk value is less than a preset first threshold, a preset forecasting algorithm is used to combine seasonal factors and event factors to generate a local demand forecast value for the target chemical, calculate a local safety stock based on the service level and demand volatility, determine a local gap value based on the current inventory of the first target area, the local demand forecast value, and the local safety stock, and upload the local gap value to the cloud; Generate cross-warehouse transfer suggestions and purchase suggestions for the target chemical in the cloud based on the multiple local gap values, The step of constructing a taboo substance matrix according to a preset material safety data sheet and the chemical data, and determining the chemical compatibility risk value of the first target area according to the taboo substance matrix includes: Extracting chemical properties of all chemicals in the first target area from the preset material safety data sheet, and using any two combinations of all chemicals in the first target area as row and column indexes of the prohibited substance matrix; If a taboo relationship exists between the first chemical and the second chemical, the conflict probability between the first chemical and the second chemical is marked at the corresponding position of the taboo substance matrix; Traversing all storage locations of chemicals in the first target area, and checking whether there is a target combination with a mark greater than a preset second threshold in the taboo substance matrix in adjacent storage locations; The chemical compatibility risk value is determined based on the conflict probability and conflict severity of all target combinations. Determining the chemical compatibility risk value of the first target area based on the taboo substance matrix, determining the environmental out-of-control risk value based on the degree of deviation between the environmental data and a preset safety threshold, determining the equipment failure risk value based on historical equipment failure data and the equipment data, and determining the operation risk value based on the operation data include: The chemical compatibility risk value is calculated using the following formula: ； in, R 相容 Indicates the chemical compatibility risk value, P i Indicates the i The conflict probability of target combinations, S i Indicates the i The conflict severity of the target combination, i ∈[1, n ]; The risk value of environmental loss of control is calculated by the following formula: ； in, R 环境 Indicates the risk value of environmental loss of control, W j Indicates the j The weight of the environmental factors, T j Indicates the j The preset safety threshold of each environmental factor, V j Indicates the j The actual value of the environmental factor, j ∈[1, m ]; The equipment failure risk value is calculated using the following formula: ； in, R 设备 represents the equipment failure risk value, represents the failure rate, t Indicates the running time; The operational risk value is calculated using the following formula: ； in, R 操作 Indicates the operation risk value. Illegal operations include operator authority violations and incomplete wearing of protective equipment. The method further comprises: When the comprehensive risk value is greater than or equal to a preset first threshold, a second target area with the lowest current comprehensive risk value is determined, and the compatibility of the chemicals to be transferred in the first target area with all chemicals on the first path is checked to determine whether there is any taboo mixing, where the first path is any path from the first target area to the second target area; A second path without taboo mixing is selected from the first path as a candidate path, and an optimal warehouse transfer path is determined based on the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area.

2. The cloud-edge collaborative hazardous chemicals management method according to claim 1 is characterized in that: The method of generating a local demand forecast value of the target chemical using a preset forecasting algorithm in combination with seasonal factors and event factors, calculating a local safety stock based on a service level and a demand volatility, and determining a local gap value based on a current inventory in the first target area, the local demand forecast value, and the local safety stock comprises: Determine an initial demand forecast value using the preset forecast algorithm; Calculate the ratio of the average demand data of the current month to the average demand data of other months in the historical data, calculate the average of the ratio as the seasonal factor, and determine the event type and impact coefficient of the event that occurs within a preset time from the current moment, and determine the event factor based on the event type and the impact coefficient; Correcting the initial demand forecast value according to the seasonal factor and the event factor to obtain a local demand forecast value; Determine a service level coefficient based on a normal distribution table and the service level, calculate demand volatility using a standard deviation formula, and determine a local safety stock based on a replenishment cycle, the service level coefficient, and the demand volatility; The local gap value is calculated by the following formula: G=max(0,D−(I−S)); Where G represents the local gap value, D represents the local demand forecast value, I represents the current inventory of the first target area, S represents the local safety stock, and max(0, D−(I−S)) represents the maximum value between 0 and D−(I−S).

3. The cloud-edge collaborative hazardous chemicals management method according to claim 2 is characterized in that: Generating the cross-warehouse allocation suggestion and the procurement suggestion of the target chemical in the cloud according to the plurality of local gap values ​​includes: screening a first target warehouse having redundant inventory in a cloud database based on the plurality of local gap values; Generate multiple potential cross-warehouse transfer plans based on the spatial distance between the first target warehouse and the second target warehouse with a shortage, transportation costs, transportation time, and storage and transportation safety requirements of the chemicals; For each potential cross-depot transfer plan, we screen target suppliers that meet the requirements based on the type and quantity of the missing chemicals and market dynamics data. We then use a pre-set cost-benefit analysis model to calculate the cost of direct procurement and, taking into account delivery times, generate multiple potential direct procurement plans. A multi-attribute decision-making method is used to comprehensively evaluate the potential cross-warehouse transfer plan and the potential direct procurement plan to generate a cross-warehouse transfer suggestion and a procurement suggestion.

4. The cloud-edge collaborative hazardous chemicals management method according to claim 1 is characterized in that: The determining of the optimal warehouse transfer path according to the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area includes: The optimal transfer path is determined by the following formula: ； in, R i Indicates the first i The comprehensive risk value of the target area, D j Indicates detour j The distance to the equipment failure area, Indicates the weight corresponding to the comprehensive risk value, The weight representing the distance to avoid the equipment failure area.

5. A cloud-edge collaborative hazardous chemicals management and control system, characterized by: It includes acquisition module, calculation module, prediction module and suggestion module, among which: a collection module configured to acquire chemical data, environmental data, equipment data, and operation data of the first target area, wherein the chemical data includes name, expiration date, and chemical properties; the environmental data includes temperature, humidity, and light; the equipment data includes operating status data of the ventilation system, fire protection facilities, shelf load-bearing capacity, and explosion-proof electrical appliances; and the operation data includes operator authority and protective equipment wearing status; a calculation module configured to construct a taboo substance matrix based on a preset material safety data sheet and the chemical data, determine a chemical compatibility risk value for the first target area based on the taboo substance matrix, determine an environmental loss of control risk value based on a degree of deviation between the environmental data and a preset safety threshold, determine an equipment failure risk value based on historical equipment failure data and the equipment data, determine an operational risk value based on the operational data, and perform a weighted summation of the chemical compatibility risk value, the environmental loss of control risk value, the equipment failure risk value, and the operational risk value to obtain a comprehensive risk value; a forecasting module configured to, when the comprehensive risk value is less than a preset first threshold, use a preset forecasting algorithm in combination with seasonal factors and event factors to generate a local demand forecast value for the target chemical, calculate a local safety stock based on a service level and a demand volatility, determine a local gap value based on a current inventory level in the first target area, the local demand forecast value, and the local safety stock, and upload the local gap value to the cloud; A suggestion module is configured to generate cross-warehouse transfer suggestions and purchase suggestions for the target chemical in the cloud based on the multiple local gap values. The computing module is configured to: Extracting chemical properties of all chemicals in the first target area from the preset material safety data sheet, and using any two combinations of all chemicals in the first target area as row and column indexes of the prohibited substance matrix; If a taboo relationship exists between the first chemical and the second chemical, the conflict probability between the first chemical and the second chemical is marked at the corresponding position of the taboo substance matrix; Traversing all storage locations of chemicals in the first target area, and checking whether there is a target combination with a mark greater than a preset second threshold in the taboo substance matrix in adjacent storage locations; The chemical compatibility risk value is determined based on the conflict probability and conflict severity of all target combinations. Determining the chemical compatibility risk value of the first target area based on the taboo substance matrix, determining the environmental out-of-control risk value based on the degree of deviation between the environmental data and a preset safety threshold, determining the equipment failure risk value based on historical equipment failure data and the equipment data, and determining the operation risk value based on the operation data include: The chemical compatibility risk value is calculated using the following formula: ； in, R 相容 Indicates the chemical compatibility risk value, P i Indicates the i The conflict probability of target combinations, S i Indicates the i The conflict severity of the target combination, i ∈[1, n ]; The risk value of environmental loss of control is calculated by the following formula: ； in, R 环境 Indicates the risk value of environmental loss of control, W j Indicates the j The weight of the environmental factors, T j Indicates the j The preset safety threshold of each environmental factor, V j Indicates the j The actual value of the environmental factor, j ∈[1, m ]; The equipment failure risk value is calculated using the following formula: ； in, R 设备 represents the equipment failure risk value, represents the failure rate, t Indicates the running time; The operational risk value is calculated using the following formula: ； in, R 操作 Indicates the operation risk value. Illegal operations include operator authority violations and incomplete wearing of protective equipment. The system further includes a library transfer module configured to: When the comprehensive risk value is greater than or equal to a preset first threshold, a second target area with the lowest current comprehensive risk value is determined, and the compatibility of the chemicals to be transferred in the first target area with all chemicals on the first path is checked to determine whether there is any taboo mixing, where the first path is any path from the first target area to the second target area; A second path without taboo mixing is selected from the first path as a candidate path, and an optimal warehouse transfer path is determined based on the risk scores of all areas on the candidate path and the distance to the bypass equipment failure area.

6. An electronic device, characterized in that: The electronic device comprises a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 4 is executed.

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