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CN-120634406-B - Modularized logistics system data analysis method and system

CN120634406BCN 120634406 BCN120634406 BCN 120634406BCN-120634406-B

Abstract

The application provides a data analysis method and a data analysis system for a modularized logistics system, which relate to the technical field of data analysis of logistics systems, can accurately understand the influence of the change on the functions and the performances of upper equipment when the parameters of bottom components are changed, and dynamically adjust calculation logic according to the specific relation between the components and the equipment, thereby ensuring that the changes of the bottom parameters can be accurately conducted and reflected in the performance indexes of the upper equipment, and realizing the accurate maintenance of the authenticity of the cross-level data.

Inventors

  • ZHANG KUNMING
  • PENG HUANRONG

Assignees

  • 深圳市智佳能自动化有限公司

Dates

Publication Date
20260512
Application Date
20250714

Claims (10)

  1. 1. A method of modular logistics system data analysis, comprising: Creating a device function template, wherein the device function template comprises a plurality of component role slots, and each slot prescribes a component type and key input and output parameters to be received; encapsulating a logical relation script in the equipment function template, wherein the logical relation script defines the operation relation of parameters among the component role slots; creating an equipment instance based on the equipment function template, and binding at least one component instance with a component role slot contained in the equipment function template associated with the equipment instance, wherein the component instance is a function forming unit of the equipment instance, and the performance parameters of the component instance participate in the calculation of equipment performance indexes through a logic relationship script bound by the equipment instance; and in response to the modification of the performance parameter of the first component instance, invoking the logical relation script to recalculate the device performance index and updating the calculation result to the performance index of the device instance, wherein the first component instance is one of the device instances.
  2. 2. The method of claim 1, wherein the step of invoking the logical relationship script to recalculate the device performance index in response to a modification to the performance parameter of the first component instance and updating the calculation to the performance index of the device instance comprises: detecting a first component role slot bound by a first component instance in response to modification of a performance parameter of the first component instance; and calling a corresponding logical relation script according to the first component role slot to recalculate the performance index of the equipment, and updating the calculation result into the performance index of the equipment instance.
  3. 3. The method of claim 1, wherein the step of invoking the logical relationship script to recalculate the device performance index in response to a modification to the performance parameter of the first component instance and updating the calculation to the performance index of the device instance comprises: An early warning sensing area is arranged at the upstream of the equipment instance and is used for acquiring early warning information carrying the identity information of the logistics object before the logistics object reaches the equipment instance; responding to the early warning information, calling the logic relation script to execute pre-calculation according to the modified performance parameter and the identity information of the logistics object, and obtaining and caching a first equipment performance index bound with the logistics object; And responding to a data query request sent for the logistics object, extracting the first equipment performance index from a cache, and updating the performance index of the equipment instance by adopting the first equipment performance index.
  4. 4. The method of claim 3, wherein the step of calling the logic relationship script to perform a pre-calculation in response to the pre-warning information according to the modified performance parameter and the identity information of the logistic object to obtain and cache a first device performance index bound to the logistic object comprises: generating a pre-calculation task associated with the logistics object identity information in response to the pre-warning information; Inquiring service priority associated with the logistics object according to the identity information of the logistics object; Binding the pre-calculation task and the service priority, and placing the pre-calculation task and the service priority into a calculation task queue; Scheduling a plurality of pre-calculation tasks in the calculation task queue according to the service priority by a calculation module, and extracting the pre-calculation tasks to be executed from the calculation task queue; And calling the logic relation script aiming at the pre-calculation task to be executed to execute pre-calculation according to the modified performance parameter and the identity information of the logistics object, so as to obtain and cache a first equipment performance index bound with the logistics object.
  5. 5. The method of claim 4, wherein the step of scheduling, by the computing module, a plurality of pre-computing tasks in the computing task queue according to the traffic priority and extracting pre-computing tasks to be performed from the computing task queue comprises: Monitoring the business attribute change of a logistics object associated with a pre-calculation task which is placed in the calculation task queue to acquire business attribute change information containing the identity information of the logistics object and new business priority; Responding to the service attribute change information, and searching a corresponding first pre-calculation task in the calculation task queue according to the logistics object identity information; updating the processing priority bound by the first pre-computing task according to the new service priority indicated by the service attribute change information; And scheduling a plurality of pre-calculation tasks in the calculation task queue by the calculation module according to the updated processing priority, and extracting the pre-calculation tasks to be executed from the calculation task queue.
  6. 6. The method of claim 5, wherein the step of scheduling, by the computing module, a plurality of pre-computing tasks in the computing task queue according to the updated processing priority, and extracting the pre-computing tasks to be performed from the computing task queue comprises: Configuring resource consumption attributes representing the calculated amount of each pre-calculation task in the calculation task queue for each pre-calculation task; acquiring a real-time load state of the computing module; selecting a pre-calculation task to be checked from the calculation task queue by the calculation module according to the processing priority; Comparing the resource consumption attribute of the pre-computing task to be checked with the real-time load state of the computing module to generate a comparison result; And when the comparison result shows that the real-time load state of the computing module meets the resource consumption attribute, extracting the pre-computing task to be checked from the computing task queue as the pre-computing task to be executed.
  7. 7. The method of claim 6, wherein the step of scheduling, by the computing module, a plurality of pre-computing tasks in the computing task queue according to the updated processing priority and extracting pre-computing tasks to be performed from the computing task queue comprises: When the comparison result shows that the real-time load state of the computing module does not meet the resource consumption attribute of the pre-computing task to be checked, setting a priority checking identification for the pre-computing task to be checked; After the real-time load state of the computing module is changed, checking whether a pre-computing task provided with the priority checking mark exists in the computing task queue; If the pre-calculation task provided with the priority check mark exists, the resource consumption attribute of the pre-calculation task provided with the priority check mark is preferentially compared with the real-time load state of the changed calculation module to generate a new comparison result; if the pre-calculation task with the priority checking mark does not exist, or the new comparison result shows that the real-time load state of the changed calculation module still does not meet the resource consumption attribute, other pre-calculation tasks are selected from the calculation task queue to serve as the pre-calculation task to be checked according to the processing priority.
  8. 8. The method according to claim 7, wherein the step of extracting the pre-calculation task to be inspected from the calculation task queue as the pre-calculation task to be executed when the comparison result indicates that the real-time load state of the calculation module satisfies the resource consumption attribute comprises: judging whether a plurality of pre-calculation tasks to be checked with the same highest service priority exist or not; If judging that a plurality of pre-calculation tasks to be checked with the same highest service priority exist, determining the plurality of pre-calculation tasks to be checked with the same highest service priority as a task group to be selected; For each pre-computing task in the task group to be selected, acquiring the current running state of the equipment instance associated with the pre-computing task and the target running state required by executing the pre-computing task; determining the state switching cost corresponding to each pre-calculation task in the task group to be selected according to the current running state and the target running state; Selecting a pre-calculation task from the task group to be selected as a pre-calculation task to be executed according to the state switching cost; Extracting the pre-calculation task to be executed from the calculation task queue; and if the fact that a plurality of pre-calculation tasks to be checked with the same highest service priority do not exist is judged, taking the pre-calculation tasks to be checked as pre-calculation tasks to be executed, and extracting the pre-calculation tasks to be executed from the calculation task queue.
  9. 9. The method for analyzing data of a modular logistics system of claim 8, wherein the step of determining a state switching cost corresponding to each pre-computed task of the set of tasks to be selected based on the current operating state and the target operating state comprises: Acquiring dynamic factor data affecting the state switching cost; combining the dynamic factor data with the current running state and the target running state to obtain a basis for determining the state switching cost; And determining the state switching cost corresponding to each pre-computing task in the task group to be selected according to the basis for determining the state switching cost.
  10. 10. A modular logistics system data analysis system, comprising: the template creation module is used for creating a device function template, the device function template comprises a plurality of component role slots, and each slot prescribes the type of a component to be received and key input and output parameters; The script packaging module packages a logical relation script in the equipment function template, wherein the logical relation script defines the operation relation of parameters among the role slots of each component; An instance management module, configured to create an equipment instance based on the equipment function template, and bind at least one component instance with a component role slot included in the equipment function template associated with the equipment instance, where the component instance is a function forming unit of the equipment instance, and a performance parameter of the component instance participates in calculation of an equipment performance index through a logical relationship script bound by the equipment instance; And the performance updating module is used for responding to the modification of the performance parameters of the first component instance, calling the logic relation script to recalculate the equipment performance index, and updating the calculation result into the performance index of the equipment instance, wherein the first component instance is one of the equipment instances.

Description

Modularized logistics system data analysis method and system Technical Field The application relates to the technical field of data analysis of logistics systems, in particular to a data analysis method and system of a modularized logistics system. Background In a large logistics hub, the operation management often depends on a logistics twinning scene constructed based on computer aided design software. This scenario typically employs a hierarchical data structure in which the underlying physical units are represented as component-level dynamic blocks, encapsulating technical specification parameters. The plurality of component level dynamic blocks combine to form a functionally complete device level dynamic block, which in turn combines to form a higher level functional area dynamic block. This hierarchical structure allows staff of different roles to view information of different granularity as required. However, existing data analysis systems suffer from deficiencies in handling such hierarchical data structures. When a core performance parameter of a bottom-layer, nested component-level dynamic block is modified, the existing analysis system often adopts preset and solidified calculation logic when data aggregation and upper-layer device performance index calculation are performed. Such solidified logic fails to fully understand and exploit the pre-established functional role binding relationships between components and their parent devices, as well as the specific physical constraint logic involved therein. For example, for an equipment-level dynamic block (e.g., a linear conveyor belt), the calculation of its critical performance index (e.g., maximum conveying speed) may depend only on the parameters of certain components (e.g., rollers) within it, while ignoring the decisive impact of parameter changes of other critical components (e.g., drive motors) on overall performance. Thus, even if the key performance parameters of the underlying components have changed, the upper device performance indicators calculated by the existing system may still be based on old or irrelevant parameters, resulting in inconsistent results from the actual situation. The distortion of the bottom data can be transferred to the upper layer by layer, and the accuracy of performance evaluation and prediction of a higher-level functional area and even the whole system is affected. Erroneous performance assessment may lead to operational decision errors, such as excessive task load allocation in case of insufficient actual capacity, eventually leading to operational interruptions or inefficiencies. Disclosure of Invention The application aims to provide a data analysis method and a data analysis system for a modularized logistics system, which have the advantages of accurately reflecting the influence of the parameter change of a bottom layer assembly on the performance of upper equipment and improving the accuracy of data analysis. In one aspect, the application provides a method for analyzing data of a modularized logistics system, comprising the following steps: Creating a device function template, wherein the device function template comprises a plurality of component role slots, and each slot prescribes a component type and key input and output parameters to be received; encapsulating a logical relation script in the equipment function template, wherein the logical relation script defines the operation relation of parameters among the component role slots; creating an equipment instance based on the equipment function template, and binding at least one component instance with a component role slot contained in the equipment function template associated with the equipment instance, wherein the component instance is a function forming unit of the equipment instance, and the performance parameters of the component instance participate in the calculation of equipment performance indexes through a logic relationship script bound by the equipment instance; And in response to the modification of the performance parameter of the first component instance, invoking the logical relation script to recalculate the device performance index and updating the calculation result to the performance index of the device instance, wherein the first component instance is one of the device instances. Optionally, the step of calling the logical relationship script to recalculate the device performance index in response to the modification of the performance parameter of the first component instance and updating the calculation result to the performance index of the device instance includes: detecting a first component role slot bound by a first component instance in response to modification of a performance parameter of the first component instance; and calling a corresponding logical relation script according to the first component role slot to recalculate the performance index of the equipment, and updating the calculation result into the perfor