Safety tool dynamic inventory optimization system based on operation data fusion

Abstract

The invention relates to the technical field of inventory management, and discloses a safety tool dynamic inventory optimization system based on operation data fusion, which comprises an operation data fusion module, an operation step table generation module, a tool mapping module, an inventory attribute analysis module and a dynamic optimization strategy generation module. According to the method, deep binding of the inventory and the operation time sequence is realized through a collaborative architecture generated by operation data fusion, step time sequence analysis, tool dynamic mapping, multi-dimensional inventory attribute analysis and a scenarized optimization strategy, so that the requirements of tools in each step are accurately matched to reduce resource waste; and the compliance and the emergency capability are guaranteed through multi-dimensional analysis of effectiveness, safety and position, and efficient and reliable inventory guarantee is provided for safe operation.

Description

Technical Field

[0001] This application relates to the field of inventory management technology, specifically a dynamic inventory optimization system for safety tools and equipment based on operational data fusion. Background Technology

[0002] In the field of inventory management for safety tools and equipment, traditional methods rely heavily on manual static inventory planning, which has significant technical shortcomings, specifically:

[0003] The failure to effectively integrate multi-source operational data, such as operation type, time sequence, and scenario, leads to a disconnect between inventory planning and actual operational needs, often resulting in shortages of tools and equipment for critical steps or excessive stockpiling of low-frequency tools and equipment.

[0004] The lack of correlation analysis of the operation sequence logic means that the scheduling of safety tools and equipment is based solely on experience, making it difficult to match the order of operation steps.

[0005] Isolated inventory attribute analysis, such as the analysis of inventory quantity, inventory validity, inventory security and location, is not integrated with the work process, which can easily lead to risks such as misuse of expired tools and equipment, delayed emergency response or low retrieval efficiency, seriously affecting work safety and resource utilization.

[0006] Chinese invention patent application CN117875874A discloses a method for managing safety tools based on big data, but the invention patent application is not good at responding to work steps.

[0007] In summary, there is an urgent need for a new technical solution for dynamic inventory optimization of safety tools and equipment based on operational data fusion. Summary of the Invention

[0008] The purpose of this application is to provide a dynamic inventory optimization system for safety tools and equipment based on operational data fusion, so as to solve the technical problems mentioned in the background art.

[0009] To achieve the above objectives, this application discloses the following technical solution: a dynamic inventory optimization system for safety tools and equipment based on operational data fusion, comprising:

[0010] The operation data fusion module is used to collect and fuse multi-source historical operation data, which includes operation type, operation time sequence and operation scenario information;

[0011] The job step table generation module is used to obtain a job step table with time sequence step attributes based on the fused multi-source historical job data. The job step table records the execution order of the jobs and the characteristic information of each job step.

[0012] The tool mapping module is used to map the feature information of each work step in the work step table to obtain a safety tool table with corresponding time sequence step attributes. The safety tool table records the types and corresponding relationships of the safety tools required for each work step.

[0013] The inventory attribute analysis module is used to analyze the inventory attributes of each safety tool in the safety tool table. The inventory attributes include inventory quantity, inventory validity, inventory safety, and inventory location.

[0014] The dynamic optimization strategy generation module is used to obtain a dynamic optimization strategy for the inventory of safety tools based on the inventory attributes and corresponding time sequence step attributes of each safety tool. The optimization strategy includes inventory quantity adjustment, inventory location allocation, failure warning and supplementary procurement plan.

[0015] Preferably, the job data fusion module includes:

[0016] The multi-source historical job data is cleaned, normalized, and time-series aligned; wherein, the time-series alignment is used to calibrate time-series data from different sources in the same job process according to the execution node.

[0017] Preferably, the job step table generation module includes:

[0018] The analysis includes the execution frequency, average interval duration, and dependencies of each task step. The execution frequency analysis is used to count the number of times the same task step appears in historical data to distinguish between core and optional steps. The average interval duration analysis is used to calculate the time difference distribution between adjacent task steps to determine the compactness between steps. The dependencies analysis is used to identify strong and weak dependencies between task steps, enabling the task step table to define the execution order of task steps and the temporal constraints between task steps.

[0019] Preferably, the inventory attribute analysis module analyzes the inventory quantity, including:

[0020] Extract the historical consumption data of each safety tool in the safety tool table in the corresponding work steps, and calculate the average consumption and consumption fluctuation coefficient within a unit period;

[0021] Based on the planned number of times and execution time of each work step in the work procedure table, predict the total demand for each safety tool and equipment within the future preset period.

[0022] Based on the total demand, current actual inventory, and inventory replenishment cycle, calculate the inventory gap value; associate the gap value with the urgency of the work steps, and assign priority replenishment weights to the safety tools and equipment corresponding to high-urgency work steps.

[0023] Preferably, the inventory attribute analysis module analyzes the inventory validity, including:

[0024] Obtain the most recent inspection time, inspection cycle, and cumulative usage time of each safety tool, and calculate the remaining time and remaining number of uses until the next inspection;

[0025] Based on the comparison between the remaining time and the planned execution time of the work steps, the effectiveness status of the tools and equipment during the execution of the corresponding work steps is determined.

[0026] The percentage of valid, pending inspection, and invalid safety tools and equipment is statistically analyzed to obtain an inventory validity distribution table. Safety tools and equipment with a valid percentage less than a preset threshold should be given priority for re-inspection or supplementary procurement.

[0027] Preferably, the inventory attribute analysis module analyzes the inventory security, including:

[0028] For each safety tool in the safety tool and equipment table, retrieve the emergency handling records of the sudden shortage or failure of the safety tool and equipment in the historical operation, and extract the effective alternative tool and equipment model, emergency allocation route and emergency response time.

[0029] Based on the current inventory quantity and availability of the safety equipment, assess the potential risk level, which includes low risk, medium risk and high risk.

[0030] A pre-set emergency response plan library is provided for the high-risk safety equipment. The emergency response plan library includes at least two emergency backup paths and the execution conditions and expected time consumption for each emergency backup path.

[0031] Preferably, the inventory attribute analysis module analyzes the inventory location, including:

[0032] Collect the current storage location information of each safety tool and equipment, including the storage warehouse number, storage location coordinates, and the corresponding work area;

[0033] Based on the execution location and sequence of each operation step in the operation step table, calculate the retrieval time of safety tools from the current storage location to the operation execution location. The retrieval time includes the preparation time for leaving the warehouse, the transportation time, and the on-site handover time.

[0034] Based on the sequence of work steps, the matching degree of the storage locations of safety tools required for adjacent work steps is analyzed. This matching degree analysis includes: when the storage locations of the safety tools required for the previous work step and the safety tools required for the next work step are the same or the distance is less than a preset distance, it is determined that the locations are matched; when the distance is greater than the preset distance, it is determined that the locations are mismatched, and an instruction to adjust the storage location is output.

[0035] Based on the instruction to adjust the storage location, an inventory location optimization suggestion table is obtained. The inventory location optimization suggestion table marks the safety tools whose retrieval time is longer than the interval between work steps as objects that need to have their storage location adjusted first.

[0036] Preferably, the tool mapping module includes:

[0037] Based on the correspondence between work steps and safety tools, the target safety tools are obtained;

[0038] The target safety tools are dynamically adjusted based on the results of inventory attribute analysis, including: when the current inventory validity ratio of the target safety tools corresponding to a certain work step is less than a preset value, an certified alternative tool model is automatically added to the safety tool table and the substitution priority is marked; when the retrieval time between the inventory location of the target safety tool and the work execution location is greater than a preset time threshold, the information of the same type of safety tools at the nearest storage point is associated in the safety tool table.

[0039] Preferably, the dynamic optimization strategy generation module includes:

[0040] When inventory is insufficient and the inventory availability ratio is greater than the preset threshold, the optimization strategy is to make emergency replenishment purchases. At the same time, based on the timing of the work steps, priority is given to ensuring the supply of safety tools and equipment required for the work steps to be executed first.

[0041] When the inventory is sufficient but the inventory effectiveness ratio is less than the preset threshold, the optimization strategy is to centrally re-inspect and schedule, and to reverse-engineer the re-inspection plan based on the execution time of the work steps, so as to ensure that the number of effective safety tools and equipment reaches the preset demand threshold before the work is executed.

[0042] When inventory security is at a high-risk level and inventory location is mismatched, the optimization strategy is to adjust emergency reserves and adjust their location. First, emergency inventory is allocated from outside to reduce risk, and then the normalized storage location is adjusted based on the long-term execution plan of the operation steps.

[0043] When all the inventory attributes are normal, the optimization strategy is to maintain the current inventory and perform dynamic inbound and outbound monitoring, triggering a reanalysis only when the work step plan changes.

[0044] Preferably, the dynamic optimization strategy generation module further includes a strategy priority sorting unit, which sorts the generated optimization strategies based on the safety level, time urgency, and inventory adjustment cost corresponding to the operation steps.

[0045] Beneficial Effects: The dynamic inventory optimization system for safety tools based on operational data fusion proposed in this application effectively solves the pain points of supply and demand mismatch, low efficiency, and uncontrollable safety risks in traditional safety tool inventory management through a collaborative architecture of operational data fusion, step sequence analysis, dynamic tool mapping, multi-dimensional inventory attribute analysis, and scenario-based optimization strategy generation. Through full-process data-driven operation, it achieves deep binding between inventory and operational sequence, accurately matching tool requirements at each step to reduce resource waste, and ensuring compliance and emergency response capabilities through multi-dimensional analysis of effectiveness, safety, and location. Simultaneously, dynamic strategies and priority ranking mechanisms improve scheduling flexibility and execution accuracy, significantly reducing inventory costs and shortening response time, providing efficient and reliable inventory support for safe operations. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 The structural block diagram of the dynamic inventory optimization system for safety tools and equipment based on operation data fusion provided in this application embodiment is shown. Detailed Implementation

[0048] The technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0049] In this document, the term "comprising" is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0050] In the field of safety equipment inventory management, traditional management methods often rely on manual experience to formulate static inventory plans, resulting in problems such as low matching between inventory and operational needs, and delayed scheduling of safety equipment. Specifically, on the one hand, due to the lack of linkage with operational time-series data, resource waste often occurs due to shortages or redundant reserves of equipment for critical steps; on the other hand, inventory attributes, such as inventory validity and location, are disconnected from operational processes, which can easily lead to safety hazards or efficiency losses.

[0051] The dynamic inventory optimization system for safety tools proposed in this embodiment, based on operation data fusion, achieves deep integration of inventory management and operation processes through the full-process collaboration of operation data fusion, step table generation, tool mapping, inventory attribute analysis, and dynamic strategy generation. It can accurately match the tool requirements of each operation step and ensure safety compliance through multi-dimensional inventory attribute analysis, significantly improving the utilization efficiency of inventory resources and the ability to ensure operational safety.

[0052] like Figure 1 As shown, this embodiment discloses a dynamic inventory optimization system for safety tools and equipment based on operational data fusion, including:

[0053] The operation data fusion module is used to collect and fuse multi-source historical operation data, which includes operation type, operation time sequence and operation scenario information;

[0054] The job step table generation module is used to generate a job step table with time sequence step attributes based on the fused multi-source historical job data. The job step table records the execution order of the jobs and the characteristic information of each job step.

[0055] The tool mapping module is used to map the feature information of each work step in the work step table to obtain a safety tool table with corresponding time sequence step attributes. The safety tool table records the types and corresponding relationships of the safety tools required for each work step.

[0056] The inventory attribute analysis module is used to analyze the inventory attributes of each safety tool in the safety tool table. The inventory attributes include inventory quantity, inventory validity, inventory safety, and inventory location.

[0057] The dynamic optimization strategy generation module is used to obtain dynamic optimization strategies for the inventory of safety tools based on the inventory attributes and corresponding time sequence step attributes of each safety tool. The optimization strategies include inventory quantity adjustment, inventory location allocation, failure warning and supplementary procurement plan.

[0058] Multi-source operational data, such as operational sequence and scenario information recorded by different systems, often suffers from inconsistencies in format, misaligned timing, or outlier interference, directly impacting the accuracy of subsequent operational step analysis. Traditional data processing methods lack standardized cleaning and alignment mechanisms, resulting in merged data that fails to accurately reflect the temporal logic of the operational process, creating data vulnerabilities for inventory optimization.

[0059] This embodiment effectively removes abnormal data and unifies the data format through cleaning, normalization, and time-series alignment. In particular, time-series alignment ensures the consistency of nodes in multi-source data within the same work process, providing a high-quality data foundation for the accurate generation of subsequent work step tables and avoiding inventory strategy deviations caused by data distortion.

[0060] Specifically, the task data fusion module includes:

[0061] The process involves cleaning, normalizing, and aligning multi-source historical operation data. The time alignment process is used to calibrate time-series data from different sources within the same operation process according to execution nodes, ensuring that the merged operation data accurately reflects the sequential logic of the operation steps.

[0062] In this embodiment, data cleaning and normalization are performed based on existing data preprocessing techniques. Data cleaning is used to remove abnormal job records, which include temporary job data that deviates from the regular job process by more than a preset threshold. Normalization is used to convert job time-series data of different formats into a unified timestamp format.

[0063] In practical applications, it has been found that traditional work step tables simply record the order of work without deeply analyzing the execution characteristics of the steps, such as frequency, interval and dependency. This results in a lack of specificity in the generated tool and equipment demand plan. For example, there is no difference in the tool and equipment reserve weight between core steps and optional steps, or the time constraints between steps are not considered, such as the time requirements for tool and equipment scheduling due to strong dependencies, resulting in misallocation of inventory resources.

[0064] This embodiment optimizes the analysis dimensions of the work step table generation module, not only clarifying the sequence of steps, but also distinguishing between core and optional steps, quantifying the compactness of steps, and identifying dependencies, so that the work step table has time-series constraint characteristics. This provides a precise time-dimensional reference for the dynamic scheduling of tool and equipment inventory, ensuring that inventory resources are tilted towards high-frequency and critical steps.

[0065] Specifically, the work step table generation module includes:

[0066] The analysis focuses on the execution frequency, average interval duration, and dependencies of each task step. Execution frequency analysis counts the number of times the same task step appears in historical data to distinguish between core and optional steps. Average interval analysis calculates the time difference distribution between adjacent task steps to determine the compactness between steps. Dependency analysis identifies strong and weak dependencies between task steps, enabling the task step table to define the execution order of task steps and the temporal constraints between them.

[0067] Traditional methods of calculating inventory levels typically use fixed thresholds, such as commonly set minimum reserves. These methods fail to consider the actual consumption patterns of work steps and the characteristics of planned execution, which can easily lead to inflated inventory levels. For example, if tools for high-urgency work steps are not prioritized, they may compete with tools for low-urgency work steps for replenishment resources, causing critical operations to be hindered.

[0068] This embodiment optimizes the inventory analysis process, achieving dynamic binding between inventory levels and operational characteristics. It accurately predicts demand through unit cycle consumption and fluctuation coefficients, and sets replenishment priorities by associating gap values ​​with urgency levels. This ensures priority supply of tools and equipment for high-urgency steps, avoiding operational delays caused by inventory imbalances.

[0069] Specifically, the inventory attribute analysis module analyzes inventory levels, including:

[0070] Extract historical consumption data of each safety tool in the safety tool table for the corresponding work steps, and calculate the average consumption and consumption fluctuation coefficient within a unit period.

[0071] Based on the planned number of times and execution time of each work step in the work procedure table, predict the total demand for each safety tool and equipment within the future preset period.

[0072] Calculate the inventory gap based on total demand, current actual inventory, and inventory replenishment cycle;

[0073] By associating the gap value with the urgency of the work steps, priority replenishment weights are assigned to the safety tools and equipment corresponding to high-urgency work steps.

[0074] To ensure operational safety, the availability of safety equipment in inventory, such as whether it is within its inspection period, directly impacts safety. However, traditional inventory management often relies on manual records to determine availability, which carries risks such as missed inspections and expired use. For example, directly assessing the remaining validity of equipment without considering the planned execution time of work steps could lead to the use of equipment that has exceeded its inspection period, potentially causing safety accidents.

[0075] This embodiment achieves precise matching between the effectiveness of safety tools and work plans based on inventory validity analysis. By comparing the remaining time with the work time, it identifies safety tools that need to be inspected or have expired in advance, and triggers re-inspection and / or replenishment mechanisms for safety tools with insufficient effective ratios. This prevents invalid tools from entering the work process from the source and significantly improves the safety compliance of the inventory.

[0076] Specifically, the inventory attribute analysis module analyzes inventory effectiveness, including:

[0077] Obtain the most recent inspection time, inspection cycle, and cumulative usage time of each safety tool, and calculate the remaining time and remaining number of uses until the next inspection;

[0078] Based on the comparison between the remaining time and the planned execution time of the work steps, the effectiveness status of the tools and equipment during the execution of the corresponding work steps is determined.

[0079] The percentage of valid, pending inspection, and invalid safety tools and equipment is statistically analyzed to obtain an inventory validity distribution table. Safety tools and equipment with a valid percentage less than a preset threshold should be given priority for re-inspection or supplementary procurement.

[0080] Furthermore, in the management of safety tools and equipment inventory, the ability to respond to sudden shortages or failures is crucial to ensuring the continuity of operations. However, traditional management methods lack systematic or non-manual risk assessment and contingency plan reserves. For example, if alternative tools or emergency allocation routes are not identified in advance, work may be interrupted due to tool and equipment shortages in the event of an emergency, or even safety risks may be triggered.

[0081] This embodiment constructs a full-process risk prevention and control mechanism by optimizing the analysis of inventory security. It extracts effective emergency strategies from historical data, assesses risks in a graded manner based on the current inventory status, and matches multi-path emergency plans for high-risk tools and equipment, ensuring rapid response in case of emergencies and reducing the probability of work interruption caused by tool and equipment problems.

[0082] Specifically, the inventory attribute analysis module analyzes inventory security, including:

[0083] For each safety tool in the safety tool and equipment table, retrieve the emergency handling records of the sudden shortage or failure of the safety tool and equipment in historical operations, and extract the effective alternative tool and equipment models, emergency deployment routes and emergency response durations.

[0084] Based on the current inventory and availability of the safety equipment, assess the potential risk level, which includes low risk, medium risk and high risk.

[0085] A pre-set emergency response plan library is provided for high-risk safety equipment. The emergency response plan library includes at least two emergency backup paths and the execution conditions and expected time for each emergency backup path.

[0086] In the actual requisition process, the rationality of the storage location of safety tools and equipment directly affects their scheduling efficiency. Traditional inventory layouts are mostly fixed and do not correspond to the execution location and sequence of work steps, resulting in frequent cross-regional transfers and excessively long retrieval times. For example, if the storage locations of tools and equipment for adjacent work steps are scattered, it will increase transportation time and costs and delay the progress of the work.

[0087] This embodiment achieves dynamic adaptation between inventory location and work process by optimizing the analysis of inventory location. By calculating the matching degree between retrieval time and step interval, it identifies tools with mismatched locations and generates adjustment suggestions. In particular, it prioritizes optimizing the location of tools with overdue retrieval time, which significantly improves the timeliness and economy of tool scheduling.

[0088] Specifically, the inventory attribute analysis module analyzes inventory location, including:

[0089] Collect the current storage location information of each safety tool and equipment. The storage location information includes the storage warehouse number, storage location coordinates, and the corresponding work area.

[0090] Based on the execution location and sequence of each operation step in the operation procedure table, calculate the retrieval time of safety tools from the current storage location to the operation execution location. The retrieval time includes the preparation time for leaving the warehouse, the transportation time, and the on-site handover time.

[0091] Based on the sequence of work steps, the matching degree of the storage locations of safety tools required for adjacent work steps is analyzed. This matching degree analysis includes: when the storage locations of the safety tools required for the previous work step and the safety tools required for the next work step are the same or the distance is less than a preset distance, it is determined that the locations are matched; when the distance is greater than the preset distance, it is determined that the locations are mismatched, and an instruction to adjust the storage location is output.

[0092] Based on the instruction to adjust the storage location, an inventory location optimization suggestion table is obtained. The inventory location optimization suggestion table marks safety tools whose retrieval time is longer than the interval between work steps as objects that need to have their storage location adjusted first.

[0093] In typical safety tool mapping, the mapping method is either manual selection or a static association between fixed work steps and safety tools. This does not take into account the real-time status of inventory, which may lead to a disconnect between the mapping results and the actual inventory capacity. For example, the target tool corresponding to a certain work step may be invalid, but the system still calls it according to the fixed mapping, causing the work to be interrupted.

[0094] This embodiment optimizes the dynamic adjustment logic of the tool mapping module, so that the mapping result can not only meet the functional requirements of the operation steps, but also adapt to the actual status of the current inventory. When the target tool is insufficient, it automatically supplements the alternative model, and when the location is unreasonable, it associates with the adjacent inventory, which enhances the flexibility and feasibility of tool scheduling and avoids supply and demand mismatch caused by static mapping.

[0095] Specifically, the tool mapping module includes:

[0096] Based on the correspondence between work steps and safety tools, the target safety tools are obtained;

[0097] The target safety tools are dynamically adjusted based on the results of inventory attribute analysis, including: when the current inventory validity ratio of the target safety tools corresponding to a certain work step is less than a preset value, an certified alternative tool model is automatically added to the safety tool table and the substitution priority is marked; when the retrieval time between the inventory location of the target safety tool and the work execution location is greater than a preset time threshold, the information of the same type of safety tools at the nearest storage point is associated in the safety tool table.

[0098] Traditional inventory optimization strategies often employ a uniform approach, triggering purchases based on inventory thresholds. This fails to differentiate between the fundamental characteristics of various inventory problems, resulting in insufficient strategy targeting and an inability to efficiently address core issues. Therefore, it is determined that the generation of dynamic optimization strategies must consider the specific scenarios of inventory attributes and operational sequences.

[0099] This embodiment achieves precise matching between inventory problems and solutions by refining the scenario-based strategies of the dynamic optimization strategy generation module. It formulates differentiated strategies for different combinations of inventory attributes and prioritizes key steps in the operation sequence, making optimization measures more effective and improving the efficiency and accuracy of inventory adjustments.

[0100] Specifically, the dynamic optimization strategy generation module includes:

[0101] When inventory is insufficient and the inventory availability ratio is greater than the preset threshold, the optimization strategy is to make emergency replenishment purchases. At the same time, based on the timing of the work steps, priority is given to ensuring the supply of safety tools and equipment required for the work steps to be executed first.

[0102] When the inventory is sufficient but the inventory effectiveness ratio is less than the preset threshold, the optimization strategy is to centrally re-inspect and schedule, and to reverse-engineer the re-inspection plan based on the execution time of the work steps, so as to ensure that the number of effective safety tools and equipment reaches the preset demand threshold before the work is executed.

[0103] When inventory security is at a high-risk level and inventory location is mismatched, the optimization strategy is to adjust emergency reserves and adjust their location. First, emergency inventory is allocated from outside to reduce risk, and then the normalized storage location is adjusted based on the long-term execution plan of the operation steps.

[0104] When all inventory attributes are normal, the optimization strategy is to maintain the current inventory and perform dynamic inbound and outbound monitoring, triggering a reanalysis only when the work step plan changes.

[0105] Furthermore, in practical applications, there are multiple inventory optimization strategies. Traditional management methods lack a clear priority ranking mechanism, which can easily lead to the problem of delayed execution of key strategies. For example, when a strategy to replenish safety tools for high-risk operations is carried out in parallel with a strategy to adjust inventory for low-urgency operations, disordered resource allocation may result in insufficient safety assurance for critical operations.

[0106] This embodiment adds a strategy priority sorting unit to sort strategies based on job safety level, time urgency, and adjustment cost. This ensures that resources are tilted towards high-priority tasks, prioritizing the execution of strategies with high safety risks, high urgency, and low cost. This avoids safety hazards or efficiency losses caused by disordered strategy execution order, further enhancing the application value of the dynamic optimization system.

[0107] Specifically, the dynamic optimization strategy generation module also includes a strategy priority sorting unit, which sorts the generated optimization strategies based on the safety level, time urgency, and inventory adjustment cost corresponding to the operation steps.

[0108] In this embodiment, the safety level is based on the risk coefficient involved in the work steps. For example, the risk coefficient of high-pressure operations and high-altitude operations is higher than that of routine inspections. The time urgency is based on the interval between the planned execution time of the work step and the current time. Inventory adjustment costs include procurement costs, allocation costs, and storage costs. The priority rule is as follows: the optimization strategy corresponding to the work step with the highest safety level is executed first. Under the same safety level, the strategy with high time urgency and low adjustment cost is executed first, so as to ensure that limited resources are used for inventory protection of critical operations.

[0109] In summary, the safety tool dynamic inventory optimization system based on operational data fusion in this embodiment effectively addresses the pain points of traditional safety tool inventory management, such as supply-demand mismatch, low efficiency, and uncontrollable safety risks, through a collaborative architecture that integrates operational data fusion, step-by-step sequence analysis, dynamic tool mapping, multi-dimensional inventory attribute parsing, and scenario-based optimization strategy generation. Driven by end-to-end data, it achieves deep integration of inventory and operational sequence, accurately matching tool requirements at each step to reduce resource waste, while ensuring compliance and emergency response capabilities through multi-dimensional analysis of effectiveness, safety, and location. Simultaneously, dynamic strategies and priority ranking mechanisms enhance scheduling flexibility and execution accuracy, significantly reducing inventory costs and shortening response time, providing efficient and reliable inventory support for safe operations.

[0110] In the embodiments provided in this application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor may be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments may be performed by a computer program instructing the associated hardware. During implementation, the program may be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible to a computer. Computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0111] Finally, it should be noted that the above description is only a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A dynamic inventory optimization system for safety tools and equipment based on operational data fusion, characterized in that, include: The operation data fusion module is used to collect and fuse multi-source historical operation data, which includes operation type, operation time sequence and operation scenario information; The job step table generation module is used to obtain a job step table with time sequence step attributes based on the fused multi-source historical job data. The job step table records the execution order of the jobs and the characteristic information of each job step. The tool mapping module is used to map the feature information of each work step in the work step table to obtain a safety tool table with corresponding time sequence step attributes. The safety tool table records the types and corresponding relationships of the safety tools required for each work step. The inventory attribute analysis module is used to analyze the inventory attributes of each safety tool in the safety tool table. The inventory attributes include inventory quantity, inventory validity, inventory safety, and inventory location. The dynamic optimization strategy generation module is used to obtain a dynamic optimization strategy for the inventory of safety tools based on the inventory attributes and corresponding time sequence step attributes of each safety tool. The optimization strategy includes inventory quantity adjustment, inventory location allocation, failure warning and supplementary procurement plan.

2. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 1, characterized in that, The operation data fusion module includes: The multi-source historical job data is cleaned, normalized, and time-series aligned; wherein, the time-series alignment is used to calibrate time-series data from different sources in the same job process according to the execution node.

3. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 1, characterized in that, The job step table generation module includes: The analysis includes the execution frequency, average interval duration, and dependencies of each task step. The execution frequency analysis is used to count the number of times the same task step appears in historical data to distinguish between core and optional steps. The average interval duration analysis is used to calculate the time difference distribution between adjacent task steps to determine the compactness between steps. The dependencies analysis is used to identify strong and weak dependencies between task steps, enabling the task step table to define the execution order of task steps and the temporal constraints between task steps.

4. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 1, characterized in that, The inventory attribute analysis module analyzes the inventory quantity, including: Extract the historical consumption data of each safety tool in the safety tool table in the corresponding work steps, and calculate the average consumption and consumption fluctuation coefficient within a unit period; Based on the planned number of times and execution time of each work step in the work procedure table, predict the total demand for each safety tool and equipment within the future preset period. Based on the total demand, current actual inventory, and inventory replenishment cycle, calculate the inventory gap value; The gap value is correlated with the urgency of the work steps, and priority replenishment weights are set for the safety tools and equipment corresponding to high-urgency work steps.

5. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 4, characterized in that, The inventory attribute analysis module analyzes the inventory validity, including: Obtain the most recent inspection time, inspection cycle, and cumulative usage time of each safety tool, and calculate the remaining time and remaining number of uses until the next inspection; Based on the comparison between the remaining time and the planned execution time of the work steps, the effectiveness status of the tools and equipment during the execution of the corresponding work steps is determined. The percentage of valid, pending inspection, and invalid safety tools and equipment is statistically analyzed to obtain an inventory validity distribution table. Safety tools and equipment with a valid percentage less than a preset threshold should be given priority for re-inspection or supplementary procurement.

6. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 5, characterized in that, The inventory attribute analysis module's analysis of inventory security includes: For each safety tool in the safety tool and equipment table, retrieve the emergency handling records of the sudden shortage or failure of the safety tool and equipment in the historical operation, and extract the effective alternative tool and equipment model, emergency allocation route and emergency response time. Based on the current inventory quantity and availability of the safety equipment, assess the potential risk level, which includes low risk, medium risk and high risk. A pre-set emergency response plan library is provided for the high-risk safety equipment. The emergency response plan library includes at least two emergency backup paths and the execution conditions and expected time consumption for each emergency backup path.

7. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 6, characterized in that, The inventory attribute analysis module analyzes the inventory location, including: Collect the current storage location information of each safety tool and equipment, including the storage warehouse number, storage location coordinates, and the corresponding work area; Based on the execution location and sequence of each operation step in the operation step table, calculate the retrieval time of safety tools from the current storage location to the operation execution location. The retrieval time includes the preparation time for leaving the warehouse, the transportation time, and the on-site handover time. Based on the sequence of work steps, the matching degree of the storage locations of safety tools required for adjacent work steps is analyzed. This matching degree analysis includes: when the storage locations of the safety tools required for the previous work step and the safety tools required for the next work step are the same or the distance is less than a preset distance, it is determined that the locations are matched; when the distance is greater than the preset distance, it is determined that the locations are mismatched, and an instruction to adjust the storage location is output. Based on the instruction to adjust the storage location, an inventory location optimization suggestion table is obtained. The inventory location optimization suggestion table marks the safety tools whose retrieval time is longer than the interval between work steps as objects that need to have their storage location adjusted first.

8. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 1, characterized in that, The tool mapping module includes: Based on the correspondence between work steps and safety tools, the target safety tools are obtained; The target safety tools are dynamically adjusted based on the results of inventory attribute analysis, including: when the current inventory validity ratio of the target safety tools corresponding to a certain work step is less than a preset value, an certified alternative tool model is automatically added to the safety tool table and the substitution priority is marked; when the retrieval time between the inventory location of the target safety tool and the work execution location is greater than a preset time threshold, the information of the same type of safety tools at the nearest storage point is associated in the safety tool table.

9. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 7, characterized in that, The dynamic optimization strategy generation module includes: When inventory is insufficient and the inventory availability ratio is greater than the preset threshold, the optimization strategy is to make emergency replenishment purchases. At the same time, based on the timing of the work steps, priority is given to ensuring the supply of safety tools and equipment required for the work steps to be executed first. When the inventory is sufficient but the inventory effectiveness ratio is less than the preset threshold, the optimization strategy is to centrally re-inspect and schedule, and to reverse-engineer the re-inspection plan based on the execution time of the work steps, so as to ensure that the number of effective safety tools and equipment reaches the preset demand threshold before the work is executed. When inventory security is at a high-risk level and inventory location is mismatched, the optimization strategy is to adjust emergency reserves and adjust their location. First, emergency inventory is allocated from outside to reduce risk, and then the normalized storage location is adjusted based on the long-term execution plan of the operation steps. When all the inventory attributes are normal, the optimization strategy is to maintain the current inventory and perform dynamic inbound and outbound monitoring, triggering a reanalysis only when the work step plan changes.

10. The dynamic inventory optimization system for safety tools and equipment based on operational data fusion according to claim 9, characterized in that, The dynamic optimization strategy generation module further includes a strategy priority sorting unit, which sorts the generated optimization strategies based on the safety level, time urgency, and inventory adjustment cost corresponding to the operation steps.

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