Intelligent chemical product supply chain management system and management method

Abstract

The invention discloses an intelligent chemical product supply chain management system and management method, and relates to the technical field of supply chain management, and the system comprises a chemical product transportation supervision module, an early warning terminal, a warehouse management module, an optimization strategy generation module and a total data warehouse. According to the method, the real-time traffic restriction data, the meteorological data and the chemical product characteristic parameters are integrated to form a multi-dimensional risk assessment model, so that the adaptability of a push path is improved, and meanwhile, the problem of path failure caused by traffic restriction change in chemical product transportation is also solved; aiming at the characteristics of the chemical products, the chemical products are stored in a targeted manner in combination with the adjustment precision grades of the control system of the storage end in a plurality of internal areas, so that the suitability of the storage areas of the chemical products is guaranteed, and the damage to the storage end is avoided while the quality of the chemical products is guaranteed; the validity period of the chemical product is corrected, the validity period of the chemical product is closer to reality, and resource waste is avoided.

Description

Technical Field

[0001] This invention relates to the field of supply chain management technology, specifically to an intelligent chemical product supply chain management system and management method. Background Technology

[0002] The quality and safety of chemical products is another key consideration in supply chain management. Many chemical products, such as food additives, pharmaceutical raw materials, and pesticides, are directly related to public health and environmental safety. At every stage of the supply chain, from raw material procurement and production to warehousing and transportation, even minor quality issues can be amplified and lead to serious consequences. Furthermore, failure to adhere to specific environmental requirements during warehousing and transportation can result in product spoilage or contamination. Therefore, managing the transportation and warehousing of chemical products is extremely necessary.

[0003] Existing technologies rely on preset traffic restriction rules and fixed route libraries, making it impossible to adjust to real-time weather or cargo characteristics, thus reducing the adaptability of push routes. Furthermore, there is a lack of targeted storage for the characteristics of chemical products. Since the warehouse control system regulates the entire warehouse environment, inconsistencies in control precision are inevitable in different internal areas. The neglect of this aspect in existing technologies makes it difficult to guarantee the adaptability of chemical product storage areas, reducing product quality and posing risks to the warehouse. Additionally, most technologies adhere to the nominal expiration date of chemical products. However, during transportation, factors such as driver habits, road conditions, and environmental factors affect the actual shelf life of chemical products. The neglect of this aspect in existing technologies makes it difficult to accurately determine the actual shelf life of chemical products, thus hindering the provision of strong data support for subsequent use and resulting in resource waste. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent chemical product supply chain management system and method, which solves the problems existing in the background technology.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The first aspect of the present invention provides an intelligent chemical product supply chain management system, including: a chemical product transportation supervision module, used to crawl industry requirements, dynamically update a dedicated navigation map for chemical products, and intelligently push the transportation route of the current batch of chemical products when the current batch of chemical products is being transported, and to perform real-time monitoring during the transportation of the current batch of chemical products, and generate a data package for the current batch of chemical products.

[0006] The early warning terminal is used to track risk events during transportation in real time based on the data package of this batch of chemical products, and trigger early warnings through data logic.

[0007] The warehouse management module is used to collect environmental monitoring data at the warehouse, process the data to create a table of warehouse control accuracy levels, store the chemical products in a targeted manner for this batch, monitor the storage data of this batch of chemical products in real time, and dynamically supplement the data package of this batch of chemical products.

[0008] The optimization strategy generation module is used to dynamically correct the predicted actual shelf life of this batch of chemical products based on the data package of this batch of chemical products.

[0009] The second aspect of the present invention provides a management method for implementing the intelligent chemical product supply chain management system of the present invention, comprising: T1, crawling industry requirements, dynamically updating a dedicated navigation map for chemical products, and intelligently pushing the transportation route of the current batch of chemical products when the current batch of chemical products is being transported, and performing real-time monitoring during the transportation of the current batch of chemical products, and generating a data package for the current batch of chemical products.

[0010] T2. Based on the data package of this batch of chemical products, track risk events during transportation in real time and trigger early warnings through data logic.

[0011] T3. Collect environmental monitoring data at the storage end, process the data to create a table of actual control accuracy levels at the storage end, store the chemical products of this batch in a targeted manner, monitor the storage data of the chemical products of this batch in real time, and dynamically supplement the data package of the chemical products of this batch.

[0012] T4. Based on the data package of this batch of chemical products, dynamically adjust the predicted actual shelf life of this batch of chemical products.

[0013] The beneficial effects of the present invention are as follows: (1) The present invention integrates real-time traffic restriction data, meteorological data and chemical product characteristic parameters to form a multi-dimensional risk assessment model. Compared with the prior art, it achieves personalized adaptation of route planning through dynamic data superposition. For example, it can avoid high-temperature areas for flammable liquids or plan light-avoiding routes for photosensitive substances, thereby improving the adaptability of the push route. At the same time, it also solves the problem of route failure caused by changes in traffic restrictions (such as the addition of hazardous chemical traffic restriction areas) in the transportation of chemical products.

[0014] (2) Based on the characteristics of chemical products, this invention combines the control system at the storage end with the adjustment accuracy level of several internal areas to store chemical products in a targeted manner, ensuring the adaptability of the chemical product storage area, ensuring the quality of chemical products, and avoiding harm to the storage end.

[0015] (3) The present invention corrects the shelf life of chemical products, making the shelf life of chemical products closer to reality, providing strong data support for the subsequent use of chemical products, and avoiding resource waste. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0018] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Reference Figure 1 As shown, the first aspect of the present invention provides an intelligent chemical product supply chain management system, including: a chemical product transportation monitoring module, used to crawl industry requirements, dynamically update a dedicated navigation map for chemical products, and intelligently push the transportation route of the current batch of chemical products when the current batch of chemical products is being transported, and to perform real-time monitoring during the transportation of the current batch of chemical products, and generate a data package for the current batch of chemical products.

[0021] In a specific embodiment of the present invention, the process of crawling industry requirements and dynamically updating the navigation map for chemical products is as follows: ST1. Using a data collection tool, based on industry keywords stored in the database, automatically crawl official websites and local announcements such as those from the Ministry of Transport and the Ministry of Ecology and Environment to ensure that the latest industry requirements are obtained in real time.

[0022] ST2. Store the crawled industry requirements in MySQL or MongoDB by region, time, and restriction type, and create related indexes. The restriction types include restricted time periods and vehicle types.

[0023] ST3: Crawl a bridge database. Use Python to parse PDF or HTML files, extract bridge names, set real-time load limits, and crawl meteorological data from the meteorological management center.

[0024] The aforementioned real-time load limit is specifically calculated using a rapid calculation system for bridge passage by transport vehicles, which is already documented in existing technologies and will not be elaborated upon here.

[0025] ST4. Use Apache InLong to build a data pipeline, extract and clean traffic restriction data, bridge data and meteorological data from various data sources, perform real-time calculations through Flink or Spark, and output structured data for map system calls.

[0026] In a specific embodiment of the present invention, the intelligent push method for the transportation route of this batch of chemical products is as follows: obtaining relevant information of this batch of chemical products, including type, weight, and type of transport vehicle.

[0027] The navigation map for chemical products is abstracted as a directed graph G = (V, E), where V represents nodes, specifically key locations such as intersections, bridge endpoints, and entrances / exits of chemical industrial parks, with coordinates and regional attributes (such as whether traffic restrictions apply), and E represents edges, specifically roads and bridges, with attributes including:

[0028] Distance d: Physical length.

[0029] Travel time t: calculated based on real-time traffic conditions.

[0030] Load-bearing limit: The bridge has a real-time limit on the weight it can bear.

[0031] Weather sensitivity: Sensitivity level coefficient to weather type. The specific sensitivity level of the weather type is jointly determined by the sensitivity level of the road section and this batch of chemical products to the weather type.

[0032] It should be noted that the weather sensitivity coefficient of this batch of chemical products is specifically obtained by storing sensitive chemical products and their sensitivity coefficients under several weather types in the data warehouse. The weather sensitivity coefficient of the road segment is specifically obtained by storing the sensitivity coefficient of the road segment under several weather types in the data warehouse. When the weather sensitivity coefficients of the road segment and this batch of chemical products are different, the highest sensitivity coefficient is taken. The larger the sensitivity coefficient, the less suitable the weather type of the current road segment is for passing through.

[0033] The sensitivity coefficients of the aforementioned sensitive chemical products under certain weather types are specifically optimized using machine learning (such as random forest and gradient descent) by utilizing actual transportation accident data and laboratory accelerated aging test results.

[0034] Restricted periods [t_start,t_end]: Restricted periods for different types of transport vehicles.

[0035] A multidimensional cost function is introduced to evaluate the merits of a path, with the formula: Cost = α*d + β*t + γ*penalty(constraints). Where the base costs are distance d and travel time t, and α and β are the weights of distance and travel time, respectively. (The weights can be configured; for example, if prioritizing time, then β = 0.6).

[0036] Constraints and penalties:

[0037] Violation of traffic restrictions: penalty_ylimit = t_0 * 1000 (forced prohibition of passage, cost set to infinity).

[0038] Bridge load-bearing capacity insufficient: penalty_yweight = (weight of this batch of chemical products + weight of transport vehicles - real-time load-bearing capacity limit of the bridge) * 500.

[0039] Weather violation: penalty_yweather = duration of weather * weather sensitivity level coefficient * 300.

[0040] The transportation route for this batch of chemical products is intelligently pushed based on the multidimensional cost function, and the location of the transport vehicles for this batch of chemical products is obtained in real time through GPS, and the transportation route for this batch of chemical products is dynamically updated at set intervals.

[0041] It should be noted that the method of intelligently pushing the transportation route of this batch of chemical products based on the multidimensional cost function is relatively mature in the existing technology, and will not be elaborated here.

[0042] It should be noted that the real-time monitoring of this batch of chemical products during transportation specifically involves arranging several data acquisition devices on the transport vehicle to monitor the transportation of this batch of chemical products in real time. The monitoring method is relatively mature in the existing technology and will not be elaborated here.

[0043] This invention integrates real-time traffic restriction data, meteorological data, and chemical product characteristic parameters to form a multi-dimensional risk assessment model. Compared with existing technologies, it achieves personalized adaptation of route planning through dynamic data overlay. For example, it can avoid high-temperature areas for flammable liquids or plan light-avoiding routes for photosensitive substances, thereby improving the adaptability of the push route. It also solves the problem of route failure caused by changes in traffic restrictions (such as the addition of new restricted areas for hazardous chemicals) in the transportation of chemical products.

[0044] The early warning terminal is used to track risk events during transportation in real time based on the data package of this batch of chemical products, and trigger early warnings through data logic.

[0045] In a specific embodiment of the present invention, the real-time tracking of risk events during transportation and the triggering of early warnings through data logic are implemented as follows: extract the real-time location of the transport vehicle from the data package of this batch of chemical products, set up an electronic fence based on the transportation route of this batch of chemical products, and provide a voice reminder to the driver of the transport vehicle when the real-time location of the transport vehicle is not within the electronic fence.

[0046] Driving habit data of transport vehicles is extracted from the data package of this batch of chemical products, risky driving events of transport vehicles are identified, and voice reminders are given to the drivers of transport vehicles. The set of risky driving events of transport vehicles is statistically obtained and updated into the data package of this batch of chemical products.

[0047] Environmental data of transport vehicles are extracted from the data package of this batch of chemical products, and risky environmental events of transport vehicles are identified. Voice reminders are given to the drivers of transport vehicles, and a set of risky environmental events of transport vehicles is obtained and updated into the data package of this batch of chemical products.

[0048] In a specific embodiment of the present invention, the method for identifying risky driving events of transport vehicles is as follows: based on the driving habit data of transport vehicles, which includes a time-series dataset of facial images, driving speed, lane changes, following distance, emergency braking, and bump amplitude, and combined with the feature mapping table of risky driving events and driving habit data stored in data warehouse 1, the risky driving events of transport vehicles are identified. The risky driving events specifically include fatigue driving, distracted driving, speeding, frequent lane changes, following too closely, bumpy driving, and frequent emergency braking.

[0049] For example, the mapping table between risky driving events and driving habit data features is shown in Table 1:

[0050] Table 1. Mapping Table of Risky Driving Events and Driving Habits Data Features

[0051]

[0052]

[0053] It should be noted that the appropriate range of eyelid closure frequency and the threshold for the duration of gaze deviation from the road ahead in the driving habit data features are specifically defined as risk driving events and corresponding feature thresholds based on industry standards and historical accident data.

[0054] In a specific embodiment of the present invention, the method for identifying risky environmental events of transport vehicles is as follows: based on the environmental data of the transport vehicle, which includes a time series dataset of temperature, humidity, pressure, ultraviolet exposure intensity, various gas concentrations, container electrostatic voltage, container wall thickness, container lateral acceleration, container tilt angle, and container liquid level drop height, and combined with a risky environmental event and environmental data feature mapping table of several chemical product types stored in data warehouse 2, the risky environmental events of the transport vehicle are identified. The risky environmental events include abnormal temperature, abnormal humidity, abnormal pressure, decomposition of photosensitive substances, abnormal accumulation of container static electricity, container structural failure, abnormal container displacement, and container leakage.

[0055] It is also necessary to deploy AI chips (such as NVIDIA Jetson) in transport vehicles to distinguish between road bumps (low frequency) and spontaneous container displacement (high frequency resonance).

[0056] For example, taking this batch of chemical products as an example, the mapping table between the risk environmental events and environmental data characteristics is shown in Table 2:

[0057] Table 2 Mapping Table of Risky Environmental Events and Environmental Data Characteristics

[0058]

[0059]

[0060] It should be noted that the environmental data characteristics, such as the temperature threshold and the temperature change rate threshold, are specifically defined based on industry standards and historical accident data, and are the risk environmental events and corresponding characteristic thresholds for this batch of chemical products.

[0061] The warehouse management module is used to collect environmental monitoring data at the warehouse, process the data to create a table of warehouse control accuracy levels, store the chemical products in a targeted manner for this batch, monitor the storage data of this batch of chemical products in real time, and dynamically supplement the data package of this batch of chemical products.

[0062] It should be noted that the collection of environmental monitoring data at the warehouse end specifically involves deploying several data acquisition devices at the warehouse end to monitor the environmental monitoring data at the warehouse end in real time. The monitoring method is relatively mature in the existing technology and will not be described in detail here.

[0063] In a specific embodiment of the present invention, the environmental monitoring data collected at the storage end is processed to create a table of actual control accuracy levels at the storage end, and the batch of chemical products is stored in a targeted manner. The specific implementation method is as follows: based on the environmental monitoring data at the storage end, which includes time-series datasets of each environmental monitoring indicator in several regions, combined with the actual control amount of each environmental monitoring indicator in several regions by the control system at the storage end, the actual control accuracy of each environmental monitoring indicator in several regions by the control system at the storage end is obtained through data processing, and a table of actual control accuracy levels at the storage end is created.

[0064] It should be noted that the actual control accuracy refers specifically to the deviation between the average value of the environmental monitoring indicators and the actual control amount.

[0065] For example, the creation of the warehouse end control accuracy level table also includes defining control accuracy levels. For instance, for temperature, Level 1 control accuracy corresponds to ±0.5℃, Level 2 control accuracy corresponds to ±1℃, and Level 3 control accuracy corresponds to ±2℃. For humidity, Level 1 control accuracy corresponds to ±3%RH, and Level 2 control accuracy corresponds to ±5%RH. For light intensity, Level 1 control accuracy corresponds to UV < ±2μW / cm². 2 The actual control accuracy corresponding to the second-level actual control accuracy is ±5μW / cm. 2 .

[0066] The storage environment accuracy requirements for this batch of chemical products are obtained from the central data warehouse. Specifically, the storage environment accuracy requirements include the required accuracy level for each environmental monitoring indicator. The storage area for this batch of chemical products is obtained by traversing the actual control accuracy level table at the storage end.

[0067] For example, if the storage environment precision requirements for this batch of chemical products are: temperature at level 1 precision, humidity at level 2 precision, and light intensity at level 2 precision, the following areas are available:

[0068] Area A: Temperature is controlled with Level 1 accuracy, humidity is controlled with Level 1 accuracy, and light intensity is controlled with Level 1 accuracy.

[0069] Area B: Temperature is controlled with Level 1 accuracy, humidity with Level 2 accuracy, and light intensity with Level 2 accuracy.

[0070] Area C: Temperature is controlled with Level 2 accuracy, humidity with Level 1 accuracy, and light intensity with Level 1 accuracy.

[0071] If both Region A and Region B meet the storage environment precision requirements for this batch of chemical products, then Region B will be selected as the storage region for this batch of chemical products (due to its better cost).

[0072] This invention addresses the characteristics of chemical products by combining a control system at the storage end with adjustable precision levels in several internal areas to enable targeted storage of chemical products. This ensures the adaptability of the storage areas for chemical products, guarantees their quality, and avoids harm to the storage end.

[0073] The optimization strategy generation module is used to dynamically correct the predicted actual shelf life of this batch of chemical products based on the data package of this batch of chemical products.

[0074] In a specific embodiment of the present invention, the specific correction process for dynamically correcting the predicted actual shelf life of this batch of chemical products is as follows: based on the environmental data of the transport vehicle, extract several quantitative indicators of environmental stress corresponding to this batch of chemical products. The quantitative indicators of environmental stress include vibration energy (RMS acceleration * duration) of bumps and vibrations, deceleration peak value * number of times during emergency braking, temperature exposure duration of abnormal temperature, humidity exceeding the standard duration * relative humidity difference of abnormal humidity, pressure fluctuation amplitude * frequency of abnormal pressure, and ultraviolet dose of photosensitive substance decomposition.

[0075] The quantitative indicators of several environmental stresses of this batch of chemical products are incorporated into the shelf life correction formula T_X=T*(1-∑δ p *L p In the output, the predicted actual shelf life T_X of this batch of chemical products is output.

[0076] In the formula, T represents the nominal shelf life of this batch of chemical products, and δ p L is the weighting factor for the p-th environmental stress stored in the overall data warehouse. p is the equivalent aging coefficient corresponding to the p-th environmental stress.

[0077] It should be noted that the equivalent aging coefficients corresponding to each environmental stress are specifically determined based on the quantitative indicators of several environmental stresses, combined with the equivalent relationships between several environmental stresses and laboratory standard conditions stored in the total data warehouse. The equivalent relationships between these environmental stresses and laboratory standard conditions are specifically established based on accelerated aging test data, which are relatively mature in the existing technology and will not be elaborated here.

[0078] It should be noted that the weighting factors for each environmental stress are specifically defined based on the characteristics of this batch of chemical products. High-pressure liquefied gas, solid oxidant, liquid corrosives, and photosensitive liquids are used as reference examples. The weighting factors for each environmental stress are shown in Table 3.

[0079] Table 3. Weighting factors for each environmental stress corresponding to product type.

[0080]

[0081]

[0082] It should be noted that the total weight can exceed 1, reflecting the superposition effect of multiple stress coupling, which can be achieved through normalization or adjustment of independent coefficients.

[0083] This invention corrects the shelf life of chemical products, making the shelf life of chemical products more realistic, providing strong data support for the subsequent use of chemical products, and avoiding resource waste.

[0084] Reference Figure 2 As shown, the second aspect of the present invention provides a management method for implementing the intelligent chemical product supply chain management system of the present invention, including: T1, crawling industry requirements, dynamically updating a dedicated navigation map for chemical products, and intelligently pushing the transportation route of the current batch of chemical products when the current batch of chemical products is being transported, and performing real-time monitoring during the transportation of the current batch of chemical products, and generating a data package for the current batch of chemical products.

[0085] T2. Based on the data package of this batch of chemical products, track risk events during transportation in real time and trigger early warnings through data logic.

[0086] T3. Collect environmental monitoring data at the storage end, process the data to create a table of actual control accuracy levels at the storage end, store the chemical products of this batch in a targeted manner, monitor the storage data of the chemical products of this batch in real time, and dynamically supplement the data package of the chemical products of this batch.

[0087] T4. Based on the data package of this batch of chemical products, dynamically adjust the predicted actual shelf life of this batch of chemical products.

[0088] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. An intelligent chemical product supply chain management system, characterized in that, include: The chemical product transportation monitoring module is used to crawl industry requirements, dynamically update the dedicated navigation map for chemical products, and intelligently push the transportation route of the current batch of chemical products when the current batch of chemical products is being transported. It also performs real-time monitoring during the transportation of the current batch of chemical products and generates a data package for the current batch of chemical products. The early warning terminal is used to track risk events during transportation in real time based on the data package of this batch of chemical products, and trigger early warnings through data logic. The warehouse management module is used to collect environmental monitoring data at the warehouse, process the data to create a table of warehouse control accuracy levels, store the chemical products in a targeted manner for this batch, monitor the storage data of this batch of chemical products in real time, and dynamically supplement the data package of this batch of chemical products. The optimization strategy generation module is used to dynamically correct the predicted actual shelf life of this batch of chemical products based on the data package of this batch of chemical products.

2. The intelligent chemical product supply chain management system according to claim 1, characterized in that, The process of crawling industry requirements and dynamically updating a dedicated navigation map for chemical products is as follows: ST1. Using data collection tools, based on industry keywords stored in the database, automatically crawl official websites and local announcements from sources such as the Ministry of Transport and the Ministry of Ecology and Environment to ensure real-time access to the latest industry requirements; ST2. Store the crawled industry requirements in MySQL or MongoDB according to region, time, and restriction type, and create related indexes. The restriction types include restricted time periods and vehicle types. ST3: Crawling bridge databases, using Python to parse PDF or HTML files, extracting bridge names, real-time load limits, and crawling meteorological data from the meteorological management center; ST4. Use Apache InLong to build a data pipeline, extract and clean traffic restriction data, bridge data and meteorological data from various data sources, perform real-time calculations through Flink or Spark, and output structured data for map system calls.

3. The intelligent chemical product supply chain management system according to claim 2, characterized in that, The specific method for intelligently pushing the transportation route of this batch of chemical products is as follows: Obtain relevant information about this batch of chemical products, including type, weight, and type of transport vehicle; The navigation map for chemical products is abstracted as a directed graph G = (V, E), where V represents a node with coordinates and region attributes, and E represents an edge, specifically a road or bridge, with attributes including: Distance d: physical length; Travel time t: calculated based on real-time traffic conditions; Load-bearing limits: The bridge has real-time weight-bearing limits; Weather sensitivity: Sensitivity level coefficient to weather type, wherein the specific sensitivity level of the weather type is jointly determined by the sensitivity level of the road section and this batch of chemical products to the weather type; Traffic restriction periods [t_start, t_end]: Restricted periods for different types of transport vehicles; A multidimensional cost function is introduced to evaluate the quality of a path, with the formula: Cost = α*d + β*t + γ*penalty(constraints); where the basic costs are distance d and travel time t, and α and β are the weights of distance and travel time, respectively. Constraints and penalties: Violation of traffic restrictions: penalty_ylimit = t_0 * 1000; Bridge load-bearing capacity insufficient: penalty_yweight = (weight of this batch of chemical products + weight of transport vehicle - real-time load-bearing capacity limit of bridge) * 500; Weather violation: penalty_yweather = duration of weather * weather sensitivity level coefficient * 300; The transportation route for this batch of chemical products is intelligently pushed based on the multidimensional cost function, and the location of the transport vehicles for this batch of chemical products is obtained in real time through GPS, and the transportation route for this batch of chemical products is dynamically updated at set intervals.

4. The intelligent chemical product supply chain management system according to claim 1, characterized in that, The real-time tracking of risk events during transportation and the triggering of early warnings through data logic are specifically implemented as follows: Extract the real-time location of the transport vehicle from the data package of this batch of chemical products, set up an electronic fence based on the transport route of this batch of chemical products, and give a voice reminder to the driver of the transport vehicle when the real-time location of the transport vehicle is not within the electronic fence. The driving habit data of the transport vehicles is extracted from the data package of this batch of chemical products, and the risk driving events of the transport vehicles are identified. Voice reminders are given to the drivers of the transport vehicles. The set of risk driving events of the transport vehicles is obtained and updated into the data package of this batch of chemical products. Environmental data of transport vehicles are extracted from the data package of this batch of chemical products, and risky environmental events of transport vehicles are identified. Voice reminders are given to the drivers of transport vehicles, and a set of risky environmental events of transport vehicles is obtained and updated into the data package of this batch of chemical products.

5. The intelligent chemical product supply chain management system according to claim 4, characterized in that, The specific method for identifying risky driving events of transport vehicles is as follows: Based on the driving habit data of transport vehicles, which includes time-series datasets of facial images, driving speed, lane changes, following distance, emergency braking, and bump amplitude, and combined with the risk driving event and driving habit data feature mapping table stored in data warehouse 1, risk driving events of transport vehicles are identified. The risk driving events specifically include fatigue driving, distracted driving, speeding, frequent lane changes, following too closely, bumpy driving, and frequent emergency braking.

6. The intelligent chemical product supply chain management system according to claim 4, characterized in that, The specific identification method for identifying risky environmental events involving transport vehicles is as follows: Based on the environmental data of the transport vehicle, including time-series datasets of temperature, humidity, pressure, ultraviolet exposure intensity, various gas concentrations, container electrostatic voltage, container wall thickness, container lateral acceleration, container tilt angle, and container liquid level drop height, and combined with the risk environmental event and environmental data feature mapping table of several chemical product types stored in data warehouse 2, risk environmental events of the transport vehicle are identified. These risk environmental events include abnormal temperature, abnormal humidity, abnormal pressure, decomposition of photosensitive substances, abnormal accumulation of container static electricity, container structural failure, abnormal container displacement, and container leakage.

7. The intelligent chemical product supply chain management system according to claim 1, characterized in that, The environmental monitoring data collected at the storage facility is processed to create a table of the actual control accuracy levels at the storage facility. This table is then used to target the storage of this batch of chemical products. The specific implementation method is as follows: Based on the environmental monitoring data at the warehouse, which includes time-series datasets of each environmental monitoring indicator in several regions, and combined with the actual control amount of each environmental monitoring indicator in several regions by the control system at the warehouse, the actual control accuracy of each environmental monitoring indicator in several regions by the control system at the warehouse is obtained through data processing, and a table of actual control accuracy levels at the warehouse is created. The storage environment accuracy requirements for this batch of chemical products are obtained from the central data warehouse. Specifically, the storage environment accuracy requirements include the required accuracy level for each environmental monitoring indicator. The storage area for this batch of chemical products is obtained by traversing the actual control accuracy level table at the storage end.

8. The intelligent chemical product supply chain management system according to claim 1, characterized in that, The specific correction process for dynamically adjusting the predicted actual shelf life of this batch of chemical products is as follows: Based on the environmental data of the transport vehicle, a number of quantitative indicators of environmental stress corresponding to this batch of chemical products are extracted. The quantitative indicators of environmental stress include vibration energy of bumps and vibrations, deceleration peak value*number of emergency braking, temperature exposure duration of abnormal temperature, humidity exceeding the standard duration*relative humidity difference of abnormal humidity, pressure fluctuation amplitude*frequency of abnormal pressure, and ultraviolet dose of photosensitive substance decomposition. The quantitative indicators of several environmental stresses of this batch of chemical products are incorporated into the shelf life correction formula T_X=T*(1-∑δ p *L p In the output, the predicted actual shelf life T_X of this batch of chemical products is output; In the formula, T represents the nominal shelf life of this batch of chemical products, and δ p L is the weighting factor for the p-th environmental stress stored in the overall data warehouse. p is the equivalent aging coefficient corresponding to the p-th environmental stress.

9. A management method for implementing the intelligent chemical product supply chain management system according to any one of claims 1-8, characterized in that, include: T1. Crawling industry requirements, dynamically updating the dedicated navigation map for chemical products, and intelligently pushing the transportation route of this batch of chemical products during transportation, and conducting real-time monitoring during the transportation of this batch of chemical products, generating data packages for this batch of chemical products. T2. Based on the data package of this batch of chemical products, track risk events during transportation in real time and trigger early warnings through data logic; T3. Collect environmental monitoring data at the storage end, process the data to create a table of actual control accuracy levels at the storage end, store the chemical products of this batch in a targeted manner, monitor the storage data of the chemical products of this batch in real time, and dynamically supplement the data package of the chemical products of this batch. T4. Based on the data package of this batch of chemical products, dynamically adjust the predicted actual shelf life of this batch of chemical products.

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