CN115907456A - Material management method and device - Google Patents
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Abstract
The application relates to a material management method and device. The method comprises the following steps: based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model; monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule; comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result; updating the state attribute of the material corresponding to the material model based on the state attribute of the material model; and finally realizing the management of the materials.
Description
Technical Field
The present application relates to the field of material management technologies, and in particular, to a method and an apparatus for material management.
Background
With the rapid development of the fields of internet technology, big data, cloud computing, artificial intelligence and the like, the configuration of the server in each application scene is more and more complex, more and more intelligent and more precise. The product development complexity and the frequency of product maintenance are also correspondingly improved. In the life cycle Of the product, the BOM (Bill Of Material; chinese: bill Of materials) changes along with the change Of the product, and the BOM data Of the server product is increasingly huge. For a server product BOM, common expressions are a modular BOM, a fixed BOM, and the like, where the bill of materials represents a bill containing a plurality of materials, and it should be understood that the modular bill of materials may be understood that the bill of materials contains a plurality of materials, and the materials are composed of modules; or it may be understood that the bill of materials is made up of modules.
For the modular bill of materials, when the modules in the modular bill of materials are changed, the abnormal state of the materials is likely to occur, that is, the situation that the materials have application risks is likely to occur. If the material at risk of application is applied directly, irreparable losses may occur. In the prior art, the risk identification means for the materials is single, and the risk evaluation can be performed on the materials only through material application experiments; the method for evaluating the material risk based on the application experiment not only has low efficiency, but also can cause resource waste.
In view of the above, there is a need for a material management method and device that can solve the above technical problems.
Disclosure of Invention
In view of the above, it is necessary to provide a material management method and device capable of improving effectiveness of material risk identification.
In one aspect, a method for material management is provided, the method comprising:
based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model;
monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule;
comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result;
and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
In one embodiment, the hierarchical division of the modules in the material based on the parent-child relationship among the modules in the material to generate the material model includes: responding to a material model generation request, and generating a binary tree root node based on the in-material module, wherein the material model generation request contains the category information of the root node; generating a sub-structure of a binary tree based on parent-child relationship among modules in the material, wherein the sub-structure at least comprises a node; assigning a risk grade and a risk coefficient of each node in the binary tree, wherein each node in the binary tree corresponds to one module; and traversing the binary tree in a hierarchical manner, and performing hierarchical division on the binary tree to generate the material model.
In one embodiment, the preset risk identification rule includes: defining a module with changed attribute information in the material model as a first module, wherein the first module is at least one; defining a node corresponding to the first module as a reference node based on the first module and the binary tree; based on the reference nodes, traversing the substructures of the reference nodes in a reverse order hierarchy until the root nodes; acquiring all nodes from the root node to the reference node, wherein the number of the nodes is at least one; and acquiring the risk coefficient of each node and the product of the risk grades of the sub-nodes to acquire a first risk value.
In one embodiment, obtaining the risk value of the material model according to a preset risk identification rule includes: when the first module is one, the first risk value is the risk value of the material model; and when the first modules are not one, the sum of the first risk values corresponding to each first module is the risk value of the material model.
In one embodiment, the risk value of the material model is obtained based on the following formula:
wherein N is a risk value of the material model; a is a risk value of a substructure where a junction corresponding to the first module is located; the risk level value of the module corresponding to the root node of the P substructure; l is a risk coefficient of a module corresponding to a child node of the substructure; i is the number of substructures; m is the maximum value of the number of substructures; j is the number of substructure layers; n is the maximum value of the number of layers of the substructure.
In one embodiment, after updating the state attribute of the material model based on the comparison result, the method further includes: acquiring state attributes of the material model, wherein the state attributes of the material model comprise forbidden and available states; when the state attribute of the material model is forbidden, positioning a module which causes the state attribute of the material model to be forbidden; judging whether the module is replaceable; and if the module can be replaced, replacing the module to generate the material model.
In one embodiment, if the module is not replaceable, the method further comprises: defining nodes corresponding to the modules as reference nodes based on the modules and the substructures where the modules are located; traversing the sub-structure in reverse order based on the reference node, and sequentially judging whether the module corresponding to the father node of the reference node can be replaced layer by layer; and when the module corresponding to the father node can be replaced, replacing the module corresponding to the father node to generate the material model.
In one embodiment, when the module is replaceable, the method further comprises: acquiring attribute information of the module, and judging whether bridging attributes exist in the attribute information of the module; if the module exists, acquiring a bridged module bridged by the module based on the bridging property of the module; determining whether the bridging module is replaceable; if the bridging module can be replaced, replacing the bridging module and the module to generate a material model; otherwise, the module is prohibited from being replaced.
In one embodiment, the method further comprises: obtaining a replaced module; changing a state attribute of the replaced module to disabled.
In another aspect, there is provided a material management apparatus, the apparatus comprising:
the material model generation unit is used for carrying out hierarchical division on the modules in the material based on the parent-child relationship among the modules in the material to generate a material model;
the risk monitoring unit is used for monitoring the attribute information of the modules in the material model in real time, and if the attribute information of the modules is changed, the risk value of the material model is obtained according to a preset risk identification rule;
the state attribute updating unit is used for comparing the risk value with a preset risk threshold value and updating the state attribute of the material model based on the comparison result; and the state attribute updating module is also used for updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
In another aspect, a computer device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to perform the following steps:
based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model;
monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule;
comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result; and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
In yet another aspect, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, performs the steps of:
based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model;
monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule;
comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result;
and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
The material management method, the material management device and the computer equipment comprise the following steps: based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model; monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule; comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result; and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model. Based on the method, the timeliness of material risk detection is improved, the management of the materials is realized, and the resource consumption is avoided.
The internal material modules are hierarchically divided based on parent-child relations among the internal material models to generate the material models, so that the relations among the internal material modules are more visual, and the internal material modules are more convenient to maintain;
monitoring the attribute information of the modules in the material model in real time, and if the attribute information of the modules is changed, acquiring the risk value of the material model according to a preset risk identification rule to realize the real-time monitoring of the attribute information of the modules in the material model; acquiring a risk value of the material model according to a preset risk identification rule, standardizing a material model risk identification process, and improving the accuracy of the acquired risk value of the material model;
and updating the state attribute of the material model based on the comparison result, and setting the state attribute of the material model as forbidden in time when the risk value of the material model exceeds a preset risk threshold value so as to prevent economic loss caused by misuse of the risky material model.
Drawings
FIG. 1 is a diagram of an application environment of a method for material management in one embodiment;
FIG. 2 is a diagram illustrating a result of verification of a material model according to an embodiment;
FIG. 3 is a diagram illustrating a result of verification of a material model according to an embodiment;
FIG. 4 is a schematic flow chart diagram of a method for material management in one embodiment;
FIG. 5 is a schematic view of a material model in one embodiment;
FIG. 6 is a block diagram of an embodiment of a material model apparatus;
FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The material management method provided by the application can be applied to the application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. A technician sends a material management request to the server 104 through the terminal 102, and the server 104 executes a material management method in response to the material management request, so as to manage the material. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, a material management method is provided, which is described by taking an electronic board as an example, and includes the following steps:
naming the electronic board according to a preset material naming rule; wherein the naming rule is as follows: "electronic board English abbreviation-electronic board material number";
carrying out module division on the electronic board according to a preset module type; the preset module types comprise but are not limited to appearance size, labels, materials, technical specification performance parameters and characteristics, and the definition A represents an appearance size module, the definition B represents a label module, the definition C represents a material module, the definition D represents a technical specification performance parameter module and the definition E represents a characteristic module;
subdividing the modules based on preset module subdivision rules; the preset module subdivision rule includes, but is not limited to, subdividing the tag module B into B1, B2, B3 and B4 sub-modules, wherein the B1 sub-module is a QID sub-module, the B2 sub-module is a MAC sub-module, the B3 sub-module is a version tag sub-module, and the B4 sub-module is a SAS tag sub-module; the module D is subdivided into D1, D2 and D3 8230and D6 sub-modules according to different parameter types, wherein D1 is defined as a processor sub-module, D2 is defined as a chipset sub-module, D3 is defined as an interface and expansion slot sub-module, D4 is defined as a Jumper and dial switch definition sub-module, D5 is defined as an FW module, and D6 is defined as a power control module. The preset module subdivision rule further comprises: a lower-order module subdivision rule, which is used for dividing the sub-modules, and takes the sub-modules included in the module D as an example for description, where the lower-order module subdivision rule includes, but is not limited to, subdividing the sub-module D2 into lower-order modules D21, D22, and D23, where the lower-order module D21 is defined as a BMC chip, the lower-order module D22 is defined as a BIOS chip, and the lower-order module D23 is defined as an X710 chip; the sub-module D3 can be subdivided into lower-order modules D31, D32, D33 and D34, the lower-order module D31 is defined as a slot interface, the lower-order module D32 is defined as an audio and video interface, the lower-order module D33 is defined as a network cable interface, and the lower-order module D34 is defined as an SATA interface; the sub-module D5 can be subdivided into lower-order modules D51, D52, D53 and D35, the lower-order module D51 being defined as BIOS FW, the lower-order module D52 being defined as BMC FW, the lower-order module D53 being defined as CPLD, and the lower-order module D54 being defined as VR Code. It should be understood that, a person skilled in the art can determine whether the module needs to be further subdivided to obtain the sub-modules or not and whether the sub-modules need to be subdivided to obtain the next-order module or not by combining with the actual application scenario; and judging that the modules need to be further subdivided to obtain sub-modules, and further subdividing the sub-modules to obtain next-order modules. Similarly, a person skilled in the art can also determine whether to subdivide the lower-order module to obtain a lower-order module sub-module and which lower-order modules need to be further subdivided to obtain a lower-order module sub-module based on the actual application scenario.
Assigning a risk grade and a risk coefficient of each module in the material, wherein the risk grade comprises from low to high: p1, P2, P3 \8230; P10 ten grades, with risk grades from low to high including: 0.1, 0.2, 0.3, 823060, (82301) ten grades.
And when the module in the material is changed, correspondingly changing the risk grade and the risk coefficient corresponding to the module before the change into the risk grade and the risk coefficient of the module after the change, and generating a new material. It should be understood that the new material described in the present application indicates that a new material has been generated when any module in the material and its corresponding information change.
Calculating the risk value of the new material according to a preset material risk calculation method; the preset material risk calculation method comprises the following steps: acquiring a changed module, and sequentially indexing upper modules of the module until the module is indexed to the uppermost module; acquiring risk levels and risk coefficients of all modules based on the module indexes; calculating the risk value of each level of module in sequence from the top level module until the risk value of the changed module is calculated; the sum of the risk values of the modules at each level is obtained. And the sum of the risk values of the modules of each stage is the risk value of the new material.
Specifically, based on the uppermost module, obtaining a risk coefficient of a module belonging to the uppermost module until the module to be changed is located, obtaining a risk level of the module to be changed, and obtaining a risk value of the material model based on the following formula:
wherein N is a risk value of the material model; a is a risk value corresponding to all modules from the top module to a new module to be changed; p is a risk level value of the uppermost module; l is the risk coefficient of the module subordinate to the uppermost module; i is the number of the uppermost module; m is the maximum value of the number of the modules at the uppermost stage; j is the number of modules from the top module to the module; n is the number of modules between the top module and the module to be changed.
Specifically, the risk value of the material model is obtained by taking the hard disk as an example for forbidding. If in an actual application scene, the hard disk has a problem of the quality of a dropped connection at a client, research and development technicians analyze that the positioning reason is that FW and power supply control have problems, so that the FW and the power supply control need to be correspondingly changed, and after the change, the risk value of the material model is obtained through the material model risk value calculation method; wherein, the FW is the top module, the corresponding risk value is 10, and the corresponding risk coefficient is 0.7; the power supply control is the next-order module of the uppermost module M, the risk coefficient corresponding to the uppermost module M is 0.8, the risk value corresponding to the power supply control is 7, and the corresponding risk coefficient is 0.6. Then calculate to obtain A 1 =10 × 0.7=7; calculating to obtain A 2 =1 × 0.08 × 7 × 0.6=3.36; n =10.36 was calculated.
Judging whether the risk value of the new material meets the requirement or not based on a preset risk threshold, and if the risk value of the new material meets the requirement, changing corresponding modules in the material to generate the new material; otherwise, the corresponding module in the material is not changed, and the material is forbidden. When the calculated risk value of the new material is not less than 10, changing a corresponding module in the material and forbidding the material; and when the calculated risk value of the new material is less than 10, changing the corresponding module in the material to generate the new material for production use.
Taking the above change FW and power supply control as examples, if the calculated risk value of the hard disk after the change is 10.36 and is greater than the preset risk threshold value, the hard disk is disabled without changing FW and power supply control.
Before changing the modules in the material, whether the current module to be changed has an association relation with other modules in the material is judged, and if the current module to be changed has the association relation with other modules in the material, the modules having the association relation with the current module are synchronously changed.
In one embodiment, when the state attribute of the material model is detected to be forbidden, a module which causes the state attribute of the material model to be forbidden is positioned, whether the module can be replaced or not is judged, and if the module can be replaced and the module is not bridged with a bridging module, the module is directly replaced; and if the module is not replaceable, sequentially traversing the previous-level modules of the module based on the module until the topmost-level module.
In some special service scenarios, the old PN needs to be processed with a purchase order to meet the service requirements, and when the prohibition is completed, the order cannot be placed normally. It should be understood that, in an actual application scenario, in order to prevent a conflict from being brought to a normal service, when the material is temporarily disabled, a special time period is opened to establish a storage medium for temporarily disabling the material, which avoids a time period in which a normal usage flow value is high.
The material check in the prior art is carried out according to the traditional specification, and is inefficient and has large error. In order to overcome the defects of large material inspection error, easy error detection and missing detection in the prior art, the material management method further comprises the following steps: generating a material model resource library, wherein the material model resource library comprises at least one material model; matching the material model to be detected with material models in a material model resource library; and checking whether the module to be detected meets the requirements or not based on the material model in the material model resource library. As shown in fig. 2 and fig. 3, which are schematic diagrams of material model verification. When all the modules, sub-modules and lower-order modules in the material model to be detected are '8230' \8230 '\ 8230'; check values are 'TRUE', obtaining a detection result PASS; and obtaining a detection result Fail when one or more of the check values of the modules, the sub-modules and the lower-order modules in the material model to be detected are '8230' \8230 '\ 8230'. The test result Fail is obtained. Based on the method, the material checking efficiency can be improved to a great extent, and abnormal conditions such as missing detection, error detection and the like are avoided.
In one embodiment, as shown in fig. 4, a method for managing materials is provided, which is described by taking the method as an example applied to the server in fig. 1, and includes the following steps:
based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model;
monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule;
comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result;
and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
Specifically, as shown in fig. 5, the method is a schematic diagram of a material model generated by hierarchically dividing modules in a material based on a parent-child relationship between the modules in the material, taking an electronic board card X as an example.
In one embodiment, the hierarchical division of the modules in the material based on the parent-child relationship among the modules in the material to generate the material model includes: responding to a material model generation request, and generating a binary tree root node based on the in-material module, wherein the material model generation request contains the category information of the root node; generating a sub-structure of a binary tree based on parent-child relationship among modules in the material, wherein the sub-structure at least comprises a node; assigning a risk grade and a risk coefficient of each node in the binary tree, wherein each node in the binary tree corresponds to one module; and traversing the binary tree in a hierarchical manner, and performing hierarchical division on the binary tree to generate the material model.
According to the material management method, the material management is realized by monitoring the attribute information of the modules in the material in real time, and the timeliness of the material management is improved; and when the attribute information of the modules in the material is changed, namely when the modules in the material are changed, calculating and acquiring the risk value of the material model in real time according to a preset risk identification rule, so that the usability of the material corresponding to the material model is ensured, and the condition of economic loss caused by using the risk material is prevented.
In one embodiment, the preset risk identification rule includes: defining a module with changed attribute information in the material model as a first module, wherein the first module is at least one; defining a node corresponding to the first module as a reference node based on the first module and the binary tree; based on the reference nodes, traversing the substructures of the reference nodes in a reverse order hierarchy until the root nodes; acquiring all nodes from the root node to the reference node, wherein the number of the nodes is at least one; and acquiring the risk coefficient of each node and the product of the risk grades of the sub-nodes to acquire a first risk value.
In one embodiment, obtaining the risk value of the material model according to a preset risk identification rule includes: when the first module is one, the first risk value is the risk value of the material model; and when the first modules are not one, the sum of the first risk values corresponding to each first module is the risk value of the material model.
In one embodiment, the risk value of the material model is obtained based on the following formula:
wherein N is a risk value of the material model; a is a risk value of a substructure where a junction corresponding to the first module is located; the risk level value of the module corresponding to the root node of the P substructure; l is a risk coefficient of a module corresponding to a child node of the substructure; i is the number of substructures; m is the maximum value of the number of substructures; j is the number of substructure layers; n is the maximum value of the number of layers of the substructure.
In one embodiment, after updating the state attribute of the material model based on the comparison result, the method further includes: acquiring state attributes of the material model, wherein the state attributes of the material model comprise forbidden and available states; when the state attribute of the material model is forbidden, locating a module which causes the state attribute of the material model to be forbidden; judging whether the module is replaceable; and if the module can be replaced, replacing the module to generate the material model.
In one embodiment, if the module is not replaceable, the method further comprises: defining nodes corresponding to the modules as reference nodes based on the modules and the substructures where the modules are located; traversing the sub-structure in reverse order based on the reference node, and sequentially judging whether the module corresponding to the father node of the reference node can be replaced layer by layer; and when the module corresponding to the father node can be replaced, replacing the module corresponding to the father node to generate the material model.
In one embodiment, when the module is replaceable, the method further comprises: acquiring attribute information of the module, and judging whether bridging attributes exist in the attribute information of the module; if the module exists, acquiring a bridged module bridged by the module based on the bridging property of the module; determining whether the bridge module is replaceable; if the bridging module can be replaced, replacing the bridging module and the module to generate a material model; otherwise, the module is prohibited from being replaced.
Specifically, as shown in fig. 2, since the lower module D21 and the lower module D52 are in a bridging relationship, when either the lower module D21 or the lower module D52 is replaced, the other module needs to be adaptively changed.
In one embodiment, the method further comprises: obtaining a replaced module; changing a state attribute of the replaced module to disabled.
It should be understood that, although the steps in the flowchart of fig. 4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 6, there is provided a material management apparatus including: material model generation unit, risk monitoring unit and state attribute update unit, wherein:
the material model generation unit is used for carrying out hierarchical division on the modules in the material based on the parent-child relationship among the modules in the material to generate a material model;
the risk monitoring unit is used for monitoring the attribute information of the modules in the material model in real time, and acquiring the risk value of the material model according to a preset risk identification rule if the attribute information of the modules is changed;
the state attribute updating unit is used for comparing the risk value with a preset risk threshold value and updating the state attribute of the material model based on the comparison result; and the state attribute updating module is also used for updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
In one embodiment, the material model generation module is further configured to generate a binary tree root node based on the in-material module in response to a material model generation request, where the material model generation request includes information about a type of the root node; generating a substructure of a binary tree based on parent-child relationship among modules in the material, wherein the substructure at least comprises a node; assigning a risk grade and a risk coefficient of each node in the binary tree, wherein each node in the binary tree corresponds to one module; and traversing the binary tree in a hierarchy manner, and performing hierarchy division on the binary tree to generate the material model.
In one embodiment, the risk monitoring unit is further configured to define a module in which the attribute information in the material model changes as a first module, where the first module is at least one; defining a node corresponding to the first module as a reference node based on the first module and the binary tree; based on the reference node, traversing the substructure in which the reference node is positioned in a reverse order hierarchy until the root node; acquiring all nodes from the root node to the reference node, wherein the number of the nodes is at least one; acquiring a risk coefficient of each node and a product of risk grades of the sub-nodes to acquire a first risk value; when the first module is one, the first risk value is the risk value of the material model; and when the first modules are not one, the sum of the first risk values corresponding to each first module is the risk value of the material model.
In one embodiment, the risk monitoring unit is further configured to obtain a risk value of the material model based on the following formula:
wherein N is a risk value of the material model; a is a risk value of a substructure where a junction corresponding to the first module is located; the risk level value of the module corresponding to the root node of the P substructure; l is a risk coefficient of a module corresponding to a child node of the substructure; i is the number of substructures; m is the maximum value of the number of substructures; j is the number of substructure layers; n is the maximum value of the number of layers of the substructure.
In one embodiment, the apparatus further includes a module replacing unit, and the state attribute updating unit is further configured to obtain state attributes of the material model, where the state attributes of the material model include disabled and available; when the state attribute of the material model is forbidden, locating a module which causes the state attribute of the material model to be forbidden; judging whether the module is replaceable; and if the module can be replaced, the module replacing unit replaces the module to generate the material model.
In one embodiment, the module replacing unit is further configured to define a node corresponding to the module as a reference node based on the module and the substructure where the module is located; traversing the sub-structure based on the reference node in a reverse order, and sequentially judging whether a module corresponding to a parent node of the reference node can be replaced layer by layer; and when the module corresponding to the father node can be replaced, replacing the module corresponding to the father node to generate the material model.
In one embodiment, the module replacing unit is further configured to obtain attribute information of the module, and determine whether a bridging attribute exists in the attribute information of the module; if the module exists, acquiring a bridged module bridged by the module based on the bridging property of the module; determining whether the bridging module is replaceable; if the bridging module can be replaced, replacing the bridging module and the module to generate a material model; otherwise, the module is prohibited from being replaced.
In one embodiment, the state attribute updating unit is further configured to obtain a replaced module; changing a state attribute of the replaced module to disabled.
For specific limitations of the material management apparatus, reference may be made to the above limitations of the material management method, which is not described herein again. All or part of each module in the material management device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 7. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of material management. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:
based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model;
monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule;
comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result;
and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
responding to a material model generation request, and generating a binary tree root node based on the in-material module, wherein the material model generation request contains the category information of the root node; generating a sub-structure of a binary tree based on parent-child relationship among modules in the material, wherein the sub-structure at least comprises a node; assigning a risk level and a risk coefficient of each node in the binary tree, wherein each node in the binary tree corresponds to one module; and traversing the binary tree in a hierarchical manner, and performing hierarchical division on the binary tree to generate the material model.
In one embodiment, the processor when executing the computer program further performs the steps of:
defining a module with changed attribute information in the material model as a first module, wherein the first module is at least one; defining a node corresponding to the first module as a reference node based on the first module and the binary tree; based on the reference nodes, traversing the substructures of the reference nodes in a reverse order hierarchy until the root nodes; acquiring all nodes from the root node to the reference node, wherein the number of the nodes is at least one; and acquiring the risk coefficient of each node and the product of the risk grades of the sub-nodes to acquire a first risk value.
In one embodiment, the processor when executing the computer program further performs the steps of:
when the first module is one, the first risk value is the risk value of the material model; and when the first modules are not one, the sum of the first risk values corresponding to each first module is the risk value of the material model.
In one embodiment, the processor when executing the computer program further performs the steps of:
obtaining a risk value of the material model based on the following formula:
wherein N is a risk value of the material model; a is a risk value of a substructure where a junction corresponding to the first module is located; the risk level value of the module corresponding to the root node of the P substructure; l is a risk coefficient of a module corresponding to a child node of the substructure; i is the number of substructures; m is the maximum value of the number of substructures; j is the number of substructure layers; n is the maximum value of the number of layers of the substructure.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring state attributes of the material model, wherein the state attributes of the material model comprise forbidden and available states; when the state attribute of the material model is forbidden, locating a module which causes the state attribute of the material model to be forbidden; judging whether the module can be replaced; and if the module can be replaced, replacing the module to generate the material model.
In one embodiment, the processor when executing the computer program further performs the steps of:
defining nodes corresponding to the modules as reference nodes based on the modules and the substructures of the modules; traversing the sub-structure in reverse order based on the reference node, and sequentially judging whether the module corresponding to the father node of the reference node can be replaced layer by layer; and when the module corresponding to the father node can be replaced, replacing the module corresponding to the father node to generate a material model.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring attribute information of the module, and judging whether bridging attributes exist in the attribute information of the module; if so, acquiring a bridged module bridged by the module based on the bridging property of the module; determining whether the bridging module is replaceable; if the bridging module can be replaced, replacing the bridging module and the module to generate a material model; otherwise, the module is prohibited from being replaced.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
obtaining a replaced module; changing a state attribute of the replaced module to disabled.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model;
monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule;
comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result;
and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
responding to a material model generation request, and generating a binary tree root node based on the in-material module, wherein the material model generation request contains the category information of the root node; generating a sub-structure of a binary tree based on parent-child relationship among modules in the material, wherein the sub-structure at least comprises a node; assigning a risk level and a risk coefficient of each node in the binary tree, wherein each node in the binary tree corresponds to one module; and traversing the binary tree in a hierarchy manner, and performing hierarchy division on the binary tree to generate the material model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
defining a module with changed attribute information in the material model as a first module, wherein the first module is at least one; defining a node corresponding to the first module as a reference node based on the first module and the binary tree; based on the reference nodes, traversing the substructures of the reference nodes in a reverse order hierarchy until the root nodes; acquiring all nodes from the root node to the reference node, wherein the number of the nodes is at least one; and acquiring the risk coefficient of each node and the product of the risk grades of the sub-nodes to acquire a first risk value.
In one embodiment, the computer program when executed by the processor further performs the steps of:
when the first module is one, the first risk value is the risk value of the material model; and when the first modules are not one, the sum of the first risk values corresponding to each first module is the risk value of the material model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
obtaining a risk value of the material model based on the following formula:
wherein N is a risk value of the material model; a is a risk value of a substructure where a junction corresponding to the first module is located; the risk level value of the module corresponding to the root node of the P substructure; l is a risk coefficient of a module corresponding to a child node of the substructure; i is the number of substructures; m is the maximum value of the number of substructures; j is the number of substructure layers; n is the maximum value of the number of layers of the substructure.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring state attributes of the material model, wherein the state attributes of the material model comprise forbidden and available states; when the state attribute of the material model is forbidden, locating a module which causes the state attribute of the material model to be forbidden; judging whether the module can be replaced; and if the module can be replaced, replacing the module to generate the material model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
defining nodes corresponding to the modules as reference nodes based on the modules and the substructures where the modules are located; traversing the sub-structure in reverse order based on the reference node, and sequentially judging whether the module corresponding to the father node of the reference node can be replaced layer by layer; and when the module corresponding to the father node can be replaced, replacing the module corresponding to the father node to generate a material model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring attribute information of the module, and judging whether bridging attributes exist in the attribute information of the module; if so, acquiring a bridged module bridged by the module based on the bridging property of the module; determining whether the bridging module is replaceable; if the bridging module can be replaced, replacing the bridging module and the module to generate a material model; otherwise, the module is prohibited from being replaced.
In one embodiment, the computer program when executed by the processor further performs the steps of:
obtaining a replaced module; changing a state attribute of the replaced module to disabled.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of material management, the method comprising:
based on the parent-child relationship among the modules in the material, carrying out hierarchical division on the modules in the material to generate a material model;
monitoring attribute information of a module in the material model in real time, and if the attribute information of the module is changed, acquiring a risk value of the material model according to a preset risk identification rule;
comparing the risk value with a preset risk threshold value, and updating the state attribute of the material model based on the comparison result;
and updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
2. The material management method according to claim 1, wherein the hierarchical division of the modules in the material based on parent-child relationships among the modules in the material to generate the material model comprises:
responding to a material model generation request, and generating a binary tree root node based on the in-material module, wherein the material model generation request contains the category information of the root node;
generating a sub-structure of a binary tree based on parent-child relationship among modules in the material, wherein the sub-structure at least comprises a node;
assigning a risk grade and a risk coefficient of each node in the binary tree, wherein each node in the binary tree corresponds to one module;
and traversing the binary tree in a hierarchy manner, and performing hierarchy division on the binary tree to generate the material model.
3. The material management method according to claim 2, wherein the preset risk identification rule comprises:
defining a module with changed attribute information in the material model as a first module, wherein the first module is at least one;
defining a node corresponding to the first module as a reference node based on the first module and the binary tree;
based on the reference nodes, traversing the substructures of the reference nodes in a reverse order hierarchy until the root nodes;
acquiring all nodes from the root node to the reference node, wherein the number of the nodes is at least one;
and acquiring the risk coefficient of each node and the product of the risk grades of the sub-nodes to acquire a first risk value.
4. The material management method according to claim 3, wherein obtaining the risk value of the material model according to a preset risk identification rule comprises:
when the first module is one, the first risk value is the risk value of the material model;
and when the first modules are not one, the sum of the first risk values corresponding to each first module is the risk value of the material model.
5. The material management method according to claim 4, wherein the risk value of the material model is obtained based on the following formula:
wherein N is a risk value of the material model; a is a risk value of a substructure where a junction corresponding to the first module is located; the risk level value of the module corresponding to the root node of the P substructure; l is a risk coefficient of a module corresponding to a child node of the substructure; i is the number of substructures; m is the maximum value of the number of substructures; j is the number of substructure layers; n is the maximum value of the number of layers of the substructure.
6. The material management method according to any one of claims 1 to 5, wherein after updating the state attribute of the material model based on the comparison result, the method further comprises:
acquiring state attributes of the material model, wherein the state attributes of the material model comprise forbidden and available states;
when the state attribute of the material model is forbidden, positioning a module which causes the state attribute of the material model to be forbidden;
judging whether the module is replaceable;
and if the module can be replaced, replacing the module to generate the material model.
7. The material management method of claim 6, wherein if the module is not replaceable, the method further comprises:
defining nodes corresponding to the modules as reference nodes based on the modules and the substructures where the modules are located;
traversing the sub-structure in reverse order based on the reference node, and sequentially judging whether the module corresponding to the father node of the reference node can be replaced layer by layer;
and when the module corresponding to the father node can be replaced, replacing the module corresponding to the father node to generate the material model.
8. The material management method of claim 7, wherein when the module is replaceable, the method further comprises:
acquiring attribute information of the module, and judging whether bridging attributes exist in the attribute information of the module;
if the module exists, acquiring a bridged module bridged by the module based on the bridging property of the module;
determining whether the bridging module is replaceable;
if the bridging module can be replaced, replacing the bridging module and the module to generate a material model; otherwise, the module is prohibited from being replaced.
9. The material management method of claim 8, further comprising:
obtaining a replaced module;
changing a state attribute of the replaced module to disabled.
10. An apparatus for managing materials, the apparatus comprising:
the material model generation unit is used for carrying out hierarchical division on the modules in the material based on the parent-child relationship among the modules in the material to generate a material model;
the risk monitoring unit is used for monitoring the attribute information of the modules in the material model in real time, and acquiring the risk value of the material model according to a preset risk identification rule if the attribute information of the modules is changed;
the state attribute updating unit is used for comparing the risk value with a preset risk threshold value and updating the state attribute of the material model based on the comparison result; and the state attribute updating module is also used for updating the state attribute of the material corresponding to the material model based on the state attribute of the material model.
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