CN112529594B - Material quality inspection method and related device - Google Patents
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Abstract
The application provides a material quality inspection method and a material quality inspection device, which are applied to a block chain service platform, wherein the block chain service platform comprises the following components: the system comprises a provider node, a buyer node, a quality inspection node and a gateway node; the gateway node is used for storing production data and quality inspection data; the method comprises the following steps: acquiring a test report stored on a blockchain service platform by a provider node and a quality inspection report stored on the blockchain service platform by a quality inspection node; calculating the credibility range of the product parameter statistical index on the test report and calculating the credibility range of the product quality inspection statistical index on the quality inspection report; and judging whether the statistical index of the product test value in the production data exceeds the credible range of the product parameter statistical index on the corresponding test report, and whether the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report. The application can ensure the authenticity of the detection report and the quality inspection report.
Description
Technical Field
The application relates to the field of material quality inspection, in particular to a material quality inspection method and a related device.
Background
The quality inspection management is to manage performance certification, quality inspection report and qualification certification of suppliers through informatization means, so as to realize full life cycle management and control of quality of the materials, and is generally based on an enterprise production management system.
At present, a material quality inspection management system based on ERP generally starts from ERP, and in material purchasing and internal and external quality inspection links, external detection reports are transmitted to a server through a Web system for storage and processing, all detection reports are associated with material products, and data are generally stored through a relational database and a centralized file system. The quality inspection agency typically provides paper quality certificates, and the suppliers pass the quality certificate scans to the materials quality management system, which the user performs quality validation by inspecting the paper or the scans.
Due to the significant benefits associated with materials, there is a potential for certain modifications to the detection report and the quality control report. Moreover, the paper version detection report and the quality inspection report cannot prevent the supplier from doing falsification, i.e. the authenticity of the detection report and the quality inspection report cannot be guaranteed.
Disclosure of Invention
The application provides a material quality inspection method and a related device, and aims to solve the problem that the authenticity of a detection report and a quality inspection report cannot be guaranteed.
In order to achieve the above object, the present application provides the following technical solutions:
The application provides a material quality inspection method, which is applied to a block chain service platform, wherein the block chain service platform comprises the following components: the system comprises a provider node, a buyer node, a quality inspection node and a gateway node; the gateway node is used for storing production data and quality inspection data; the production data are obtained by sampling and collecting product test values of all suppliers by preset internet of things equipment; the product test value of any provider is the product parameter value measured in the process of testing the product by the provider; the quality inspection data are obtained by sampling and collecting product quality inspection values of all quality inspection units by the internet of things equipment; the product quality inspection value of any quality inspection unit is a product parameter value measured in the quality inspection process of the quality inspection unit on the product of the supplier; the method comprises the following steps:
acquiring a test report stored on the blockchain service platform by the provider node and a quality inspection report stored on the blockchain service platform by the quality inspection node;
Calculating the credibility range of the product parameter statistical index on the test report and calculating the credibility range of the product quality inspection statistical index on the quality inspection report;
and judging whether the statistical index of the product test value in the production data exceeds the credible range of the product parameter statistical index on the corresponding test report, and judging whether the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report.
Optionally, after the determining whether the statistical index of the product test value in the production data exceeds the trusted range of the statistical index of the product parameter on the corresponding test report, and whether the statistical index of the product quality inspection value in the quality inspection data exceeds the trusted range of the statistical index of the product quality inspection on the corresponding quality inspection report, the method further includes:
Under the condition that the statistical index of the product test value in the production data exceeds the credible range of the product parameter statistical index on the corresponding test report, carrying out preset processing operation on the provider node corresponding to the corresponding test report; the processing operations include: reducing weight, adding at least one of blacklist and notification;
and under the condition that the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report, carrying out the processing operation on the quality inspection node corresponding to the corresponding quality inspection report.
Optionally, the method further comprises:
acquiring historical data respectively stored by the provider node, the buyer node and the quality inspection node; the history data includes: enterprise registration scale parameters, historical number of deals, and historical credit points;
Calculating credit scores corresponding to the provider node, the buyer node and the quality inspection node respectively according to the historical data;
According to a preset corresponding relation between a preset node role and a credit value interval, respectively determining node roles of the provider node, the buyer node and the quality inspection node; the preset node roles include: the public node comprises a consensus node, a trust node and a common node;
and selecting one trust node from all the trust nodes as a master node by taking the ratio of the credit score of the credit node to the total credit score of all the credit nodes as the selection probability.
Optionally, after the determining whether the product test value in the production data exceeds the trusted range of the product parameter value on the corresponding test report and the product quality inspection value in the quality inspection data exceeds the trusted range of the product quality inspection value on the corresponding quality inspection report, the method further includes:
under the condition that the product test value of the production data does not exceed the credible range of the product parameter value on the corresponding test report, the corresponding test report is stored in a preset test report library;
and under the condition that the product quality inspection value in the quality inspection data does not exceed the credible range of the product quality inspection value on the corresponding quality inspection report, storing the corresponding quality inspection report in a preset quality inspection report library.
The application also provides a material quality inspection device which is applied to the block chain service platform,
The blockchain service platform includes: the system comprises a provider node, a buyer node, a quality inspection node and a gateway node; the gateway node is used for storing production data and quality inspection data; the production data are obtained by sampling and collecting product test values of all suppliers by preset internet of things equipment; the product test value of any provider is the product parameter value measured in the process of testing the product by the provider; the quality inspection data are obtained by sampling and collecting product quality inspection values of all quality inspection units by the internet of things equipment; the product quality inspection value of any quality inspection unit is a product parameter value measured in the quality inspection process of the quality inspection unit on the product of the supplier; the device comprises:
The acquisition module is used for acquiring a test report stored on the blockchain service platform by the provider node and a quality inspection report stored on the blockchain service platform by the quality inspection node;
the calculating module is used for calculating the credibility range of the product parameter statistical index on the test report and calculating the credibility range of the product quality inspection statistical index on the quality inspection report;
the judging module is used for judging whether the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report and whether the statistical index of the product quality inspection value in the quality inspection data exceeds the credibility range of the product quality inspection statistical index on the corresponding quality inspection report.
Optionally, the method further comprises:
The processing module is used for carrying out preset processing operation on the provider node corresponding to the corresponding test report when the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report after the judging module judges whether the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report and whether the statistical index of the product quality check value in the quality check data exceeds the credibility range of the product quality check statistical index on the corresponding quality check report; the processing operations include: reducing weight, adding at least one of blacklist and notification;
and under the condition that the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report, carrying out the processing operation on the quality inspection node corresponding to the corresponding quality inspection report.
Optionally, the method further comprises:
the consensus module is used for acquiring historical data respectively stored by the supplier node, the buyer node and the quality inspection node; the history data includes: enterprise registration scale parameters, historical number of deals, and historical credit points; calculating credit scores corresponding to the provider node, the buyer node and the quality inspection node respectively according to the historical data; according to a preset corresponding relation between a preset node role and a credit value interval, respectively determining node roles of the provider node, the buyer node and the quality inspection node; the preset node roles include: the public node comprises a consensus node, a trust node and a common node; and selecting one trust node from all the trust nodes as a master node by taking the ratio of the credit score of the credit node to the total credit score of all the credit nodes as the selection probability.
Optionally, the method further comprises:
The storage module is used for storing the corresponding test report in a preset test report library under the condition that the product test value of the production data does not exceed the credible range of the product parameter value on the corresponding test report after judging whether the product test value in the production data exceeds the credible range of the product parameter value on the corresponding test report and whether the product quality check value in the quality check data exceeds the credible range of the product quality check value on the corresponding quality check report; and under the condition that the product quality inspection value in the quality inspection data does not exceed the credible range of the product quality inspection value on the corresponding quality inspection report, storing the corresponding quality inspection report in a preset quality inspection report library.
The application also provides a storage medium comprising a stored program, wherein the program executes the material quality inspection method according to any one of the above.
The application also provides a device comprising at least one processor, and at least one memory and a bus connected with the processor; the processor and the memory complete communication with each other through the bus; the processor is configured to invoke the program instructions in the memory to perform the method of quality of goods as described in any of the preceding claims.
The application discloses a material quality inspection method and a related device, which are applied to a block chain service platform, wherein the block chain service platform comprises the following components: the system comprises a provider node, a buyer node, a quality inspection node and a gateway node; the gateway node is used for storing production data and quality inspection data; the method comprises the following steps: the method comprises the steps of obtaining a test report stored on a blockchain service platform by a provider node and a quality inspection report stored on the blockchain service platform by a quality inspection node. Because the production data are obtained by sampling and collecting the product parameter values measured in the testing process of each supplier by the preset internet of things equipment; the quality inspection data are obtained by sampling and collecting the quality inspection values of the products measured in the quality inspection process of each quality inspection unit by the internet of things equipment, namely, the production data and the quality inspection data are actual measurement data in the test process and the quality inspection process, and are real data.
In one aspect, because the blockchain is non-tamper-resistant, production data, quality inspection data, test reports, and quality inspection reports stored on the blockchain are non-tamper-resistant. On the other hand, the blockchain can determine the authenticity of the test report and the quality inspection report by judging whether the production data exceeds the credibility range of the product parameter values on the test report of the corresponding supplier and whether the quality inspection data exceeds the credibility range of the product quality inspection values on the quality inspection report of the corresponding quality inspection unit, so that the test report and the quality inspection report which are inspected by the quality inspection method can be ensured to be authentic.
In addition, in the application, the gateway is used as a node in the blockchain service platform, so that the nodes for storing the production data and the quality inspection data sampled and collected by the Internet of things equipment are not required to be arranged in the blockchain service platform, and the pressure of the blockchain service platform can be reduced.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a block chain service platform according to an embodiment of the present application;
FIG. 2 is a flowchart of a method for determining node roles according to an embodiment of the present application;
FIG. 3 is a flow chart of a method for quality inspection of materials according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a material quality inspection device according to an embodiment of the present application;
Fig. 5 is a schematic structural diagram of an apparatus according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Fig. 1 is a block chain service platform according to an embodiment of the present application, including: cloud infrastructure layer, basic function layer, block management layer, business domain management layer, cross-chain management layer, block chain display layer, network management layer and monitoring management layer. The cloud infrastructure layer is used for providing basic resources required by operation for the blockchain service platform, and specifically can comprise cloud services, networks, storage, cluster management and automatic operation and maintenance. The basic function layer is used for realizing basic services of the blockchain service platform, and specifically can comprise: consistency verification, trust verification, privacy services, intelligent contracts, block construction, block synchronization, national encryption algorithms and consensus algorithms. The block management layer is used for managing the full life cycle of the block, and specifically can comprise: block initialization policies, block generation and distribution, block state management, and the like. The service domain management layer has the function of performing configuration management on the service domain, and specifically can include: business domain registration management, business domain authority configuration management and business domain data privacy management. The function of the cross-chain management layer is to realize the cross-chain interaction of the blockchain service platform and other blockchain platforms, which can specifically include: inter-chain service registration management, inter-chain interaction request management and inter-chain interaction log management. The function of the blockchain display layer is to realize the visual display function of the blockchain service platform, and specifically can comprise visual display of data, user management, transaction management and terminal access management. The network management layer is used for realizing management of the state of the common node and node communication, and specifically comprises the following steps: node configuration management, node operation management, node abnormality management and data transceiving management. The monitoring management layer is used for monitoring the operation process of the blockchain service platform, and specifically can comprise the following steps: network node monitoring, blockchain running state, service call statistics, running log management and data interface management.
Specifically, the blockchain service platform provided by the embodiment of the application can be developed by adopting a JAVA technology, uses a relational database as a bottom layer for storage, stores the original data and the hash value of the last data block, adopts a consensus algorithm based on credibility to carry out algorithm consensus of nodes on the chain, and ensures that the data on the whole chain cannot be tampered.
In the embodiment of the application, the blockchain service nodes are allocated to each supplier, each purchasing unit and each quality inspection unit in the blockchain service platform, and are called a supplier node, a purchasing unit node and a quality inspection node for convenience of description. And each node stores the whole data, so that the safety and the credibility of the data are guaranteed together. And the control right of each node is in the unit to which the node belongs, so that other people can not change the control right at will.
In the embodiment of the application, the gateway is also called a gateway node and accesses to the blockchain service platform. The gateway is used as a lightweight consensus node, the gateway node does not store the whole data, only stores the data provided by the gateway subordinate internet of things equipment, and stores the hash values of other nodes, so that the nodes for storing the data sampled and collected by the internet of things equipment do not need to be redistributed on the blockchain service platform, and the pressure of the blockchain platform is reduced. The gateway node stores production data and quality inspection data acquired by subordinate internet of things equipment. The production data are obtained by sampling and collecting product parameter values measured in the testing process of each supplier by the Internet of things equipment; the quality inspection data are obtained by sampling and collecting the quality inspection values of the products measured in the quality inspection process of each quality inspection unit by the internet of things equipment.
In an embodiment of the application, the blockchain determines node roles for the supplier node, the buyer node, and the quality assurance node, respectively. The specific determination process is shown in fig. 2, and may include the following steps:
S201, historical data respectively stored by a provider node, a buyer node and a quality inspection node are obtained.
In this step, the history data may include: enterprise registration scale parameters, historical number of deals, and historical credit points.
S202, calculating credit scores corresponding to the provider node, the buyer node and the quality inspection node respectively according to the historical data.
In this step, the specific implementation process of calculating the credit score of each node is the prior art, and will not be described herein.
S203, according to a preset corresponding relation between a preset node role and a credit score interval, determining node roles of a provider node, a buyer node and a quality inspection node respectively.
In this embodiment, the preset node roles include: common nodes, trust nodes and common nodes.
In this step, the correspondence between node roles and the credit score interval includes: one node character corresponds to one credit score interval. For example, 80 minutes or more serves as a trust node, 60 minutes or less serves as a consensus node, and the other sections serve as normal nodes.
S204, selecting one trust node from all the trust nodes as a master node by taking the ratio of the credit scores of the credit nodes to the total credit scores of all the credit nodes as the selection probability.
In this embodiment, among the provider node, the buyer node, the quality inspection node, and the gateway node, there may be a plurality of nodes all being credit nodes, i.e., the number of credit nodes may be a plurality.
In this step, one credit node is selected from all the credit nodes as a master node, wherein the specific selection mode includes: and selecting by taking the ratio of the credit score of the credit node to the total credit score of all the credit nodes as the selection probability.
In this step, the ratio of the credit score of the credit node to the total credit score (sum of the credit scores) of all the nodes is referred to as the credit ratio of the credit node.
In this step, from all the trust nodes, the duty ratio of any one trust node is the probability of selecting that trust node as the master node. In the embodiment of the application, the higher the duty ratio of any trust node is, the larger the probability that the trust node is selected as the master node is, but the trust node with the highest duty ratio is the master node, so that the problem that a single high-trust node is always used as the master node is avoided, the inefficiency problem caused by the fact that a large number of nodes are needed to participate in the traditional consensus algorithm is solved, and the problem that the master node of the traditional Bayesian and the busy-court algorithm is invalid is solved.
The intelligent contract execution material quality inspection method in the blockchain of the embodiment of the application has transparent verification rules, is disclosed as being unable to be tampered, and can upgrade the verification rules only after the approval of a plurality of consensus nodes, and a specific material quality inspection flow is shown in a figure 3 and can comprise the following steps:
S301, acquiring a test report stored on the blockchain service platform by the provider node and a quality inspection report stored on the blockchain service platform by the quality inspection node.
In this embodiment, the vendor produces products and tests the products to obtain test reports, where each product corresponds to a test report. And the quality inspection unit performs quality inspection on products produced by the suppliers to obtain quality inspection reports. The test report of the supplier node is maintained on the blockchain, as is the quality report of the quality inspection node.
In this step, a test report of the provider node and a quality inspection report of the quality inspection node are obtained for quality inspection.
In this embodiment, the test report records the statistical index of the product parameter value, and the quality inspection report records the statistical index of the product quality inspection value. In this embodiment, the product parameters and the product quality inspection parameters need to be determined according to actual situations, for example, for a cable, the product parameters may be an inner diameter parameter and an outer diameter parameter. The product quality inspection parameters may be an inner diameter quality inspection parameter and an outer diameter quality inspection parameter.
The statistical index may include a maximum value, a minimum value, an average value, and the like, and of course, in practice, the statistical index may also include other indexes, which are not limited to the specific meaning of the statistical index in this embodiment.
In this embodiment, taking a cable as an example, the maximum value, the minimum value, and the average value of the inner diameter, and the maximum value, the minimum value, and the average value of the outer diameter may be recorded on the test report. The maximum value, the minimum value and the average value of the inner diameter quality inspection can be recorded on the quality inspection report, and the maximum value, the minimum value and the average value of the outer diameter quality inspection can be recorded.
S302, calculating the credibility range of the product parameter statistical index on the test report and calculating the credibility range of the product quality inspection statistical index on the quality inspection report.
The embodiment performs reliability verification according to the statistical idea. In this step, the trusted ranges of the product parameter statistical indicators on each test report are calculated respectively, and the trusted ranges of the product quality inspection statistical indicators on each quality inspection report are calculated respectively. For example, the trusted ranges for the inside diameter maximum, minimum, average, outside diameter maximum, minimum, and average, respectively, on the test report are calculated. And calculating the credible ranges respectively corresponding to the maximum value, the minimum value, the average value, the maximum value, the minimum value and the average value of the inner diameter quality inspection on the quality inspection report. The calculation manner of the trusted range is the prior art, and is not described herein.
S303, judging whether the statistical index of the product test value in the production data exceeds the credible range of the product parameter statistical index on the corresponding test report, and judging whether the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report, if so, executing S304, and if not, executing S305.
The production data are obtained by sampling and collecting the product test values of all suppliers by the external connection equipment, wherein the product test value of any supplier is a product parameter value measured in the process of testing the product by the supplier. In the present embodiment, since the product test value in the production data is a parameter test value of a certain product, the product corresponds to a test report, there is a correspondence between the product test value in the production data and the test report provided by the supplier.
Taking a product as a cable, and taking product parameters as an inner diameter parameter and an outer diameter parameter as examples, the production data can comprise: and respectively sampling and collecting the obtained inner diameter test value and the obtained outer diameter test value in the test process of each supplier.
The quality inspection data are obtained by sampling and collecting product quality inspection values of all quality inspection units by the internet of things equipment; the product quality inspection value of any quality inspection unit is a product parameter value measured in the quality inspection process of the quality inspection unit on the product of the supplier. Taking the product quality inspection parameter as an inner diameter quality inspection parameter and an outer diameter quality inspection parameter as an example, the quality inspection data may include an inner diameter quality inspection value and an outer diameter quality inspection value respectively corresponding to products of each supplier.
In this embodiment, since the quality inspection value of the product in the quality inspection data is a parameter quality inspection value of a certain product, the product corresponds to a quality inspection report, and therefore, there is a correspondence between the quality inspection value of the product in the quality inspection data and the quality inspection report provided by the quality inspection unit.
In this step, the product test value of each product in the production data is determined separately, wherein the manner of determining each product is the same, and any product is described here as an example. Specifically, whether the statistical indexes of the product test values of the product respectively belong to the product test statistical indexes in the corresponding test reports is judged, if so, the test reports are determined to be credible, and if not, the test reports are determined to be not credible.
For example, it is determined whether the statistical indicator of the inner diameter test value of the product belongs to the trusted ranges of the maximum value, the minimum value and the average value of the inner diameter in the corresponding test report, respectively, if both belong to the trusted ranges, the test report is determined to be trusted, and if either does not belong to the trusted ranges, the test report is determined to be untrusted. And judging whether the statistical index of the outer diameter test value of the product belongs to the credible ranges of the maximum value, the minimum value and the average value of the outer diameter in the corresponding test report respectively, if so, determining that the maximum value, the minimum value and the average value of the outer diameter recorded in the test report are credible, and if not, determining that the test report is unreal.
In this step, the product quality inspection value of each product in the quality inspection data is respectively determined, where the manner of determining the product quality inspection value of each product is the same, and any product is described here as an example. Specifically, whether the statistical index of the product quality inspection value of the product in the quality inspection data is in the credible range of the product quality inspection statistical index in the corresponding quality inspection report is judged.
For example, it is determined whether the maximum value, the minimum value, and the average value of the inside diameter quality inspection values of the product in the quality inspection data correspond to trusted ranges belonging to the maximum value, the minimum value, and the average value of the inside diameter in the corresponding quality inspection report, respectively, if both belong to the trusted ranges, the quality inspection report is determined to be trusted, and if either does not belong to the trusted ranges, the quality inspection report is determined to be untrusted. And judging whether the maximum value, the minimum value and the average value in the outer diameter quality inspection value of the product in the quality inspection data respectively belong to the credible ranges of the maximum value, the minimum value and the average value of the outer diameter in the corresponding quality inspection report, if so, determining that the quality inspection report is credible, and if not, determining that the quality inspection report is not credible.
And S304 is executed under the condition that the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report, and S304 is executed under the condition that the statistical index of the product quality inspection value in the quality inspection data exceeds the credibility range of the product quality inspection statistical index on the corresponding quality inspection report.
S304, carrying out preset processing operation on the provider node corresponding to the corresponding test report, and carrying out processing operation on the quality inspection node corresponding to the corresponding quality inspection report.
In this embodiment, the processing operation may include: and at least one of weight reduction, blacklist addition and notification.
And S305, storing the test report in a preset test report library, and storing the quality inspection report in a preset quality inspection report library.
And executing the step under the condition that the statistical index of the product test value in the production data does not exceed the credibility range of the product parameter statistical index on the corresponding test report, and executing the step under the condition that the statistical index of the product quality inspection value in the quality inspection data does not exceed the credibility range of the product quality inspection statistical index on the corresponding quality inspection report.
In this step, the specific implementation manner of the saving is the prior art, and will not be described herein.
In this embodiment, the buyer node in the blockchain service platform can verify whether the product provided by the provider passes the detection through the embodiment, thereby avoiding the phenomenon of falsification and ensuring the quality of material supply.
Fig. 4 is a schematic diagram of a material quality inspection device according to an embodiment of the present application, where the blockchain service platform includes: the system comprises a provider node, a buyer node, a quality inspection node and a gateway node; the gateway node is used for storing production data and quality inspection data; the production data are obtained by sampling and collecting product test values of all suppliers by preset internet of things equipment; the product test value of any provider is the product parameter value measured in the process of testing the product by the provider; the quality inspection data are obtained by sampling and collecting product quality inspection values of all quality inspection units by the internet of things equipment; the product quality inspection value of any quality inspection unit is a product parameter value measured in the quality inspection process of the quality inspection unit on the product of the supplier;
the apparatus may include: an acquisition module 401, a calculation module 402, and a judgment module 403, wherein,
An obtaining module 401, configured to obtain a test report stored on the blockchain service platform by the provider node, and a quality inspection report stored on the blockchain service platform by the quality inspection node;
a calculating module 402, configured to calculate a trusted range of product parameter statistics indexes on the test report, and calculate a trusted range of product quality inspection statistics indexes on the quality inspection report;
The judging module 403 is configured to judge whether the statistical index of the product test value in the production data exceeds the trusted range of the statistical index of the product parameter on the corresponding test report, and whether the statistical index of the product quality inspection value in the quality inspection data exceeds the trusted range of the statistical index of the product quality inspection on the corresponding quality inspection report.
Optionally, the apparatus may further include:
The processing module is used for carrying out preset processing operation on the provider node corresponding to the corresponding test report when the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report after the judging module judges whether the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report and whether the statistical index of the product quality check value in the quality check data exceeds the credibility range of the product quality check statistical index on the corresponding quality check report; the processing operations include: reducing weight, adding at least one of blacklist and notification;
and under the condition that the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report, carrying out the processing operation on the quality inspection node corresponding to the corresponding quality inspection report.
Optionally, the apparatus may further include:
the consensus module is used for acquiring historical data respectively stored by the supplier node, the buyer node and the quality inspection node; the history data includes: enterprise registration scale parameters, historical number of deals, and historical credit points; calculating credit scores corresponding to the provider node, the buyer node and the quality inspection node respectively according to the historical data; according to a preset corresponding relation between a preset node role and a credit value interval, respectively determining node roles of the provider node, the buyer node and the quality inspection node; the preset node roles include: the public node comprises a consensus node, a trust node and a common node; and selecting one trust node from all the trust nodes as a master node by taking the ratio of the credit score of the credit node to the total credit score of all the credit nodes as the selection probability.
Optionally, the apparatus may further include:
The storage module is used for storing the corresponding test report in a preset test report library under the condition that the product test value of the production data does not exceed the credible range of the product parameter value on the corresponding test report after judging whether the product test value in the production data exceeds the credible range of the product parameter value on the corresponding test report and whether the product quality check value in the quality check data exceeds the credible range of the product quality check value on the corresponding quality check report; and under the condition that the product quality inspection value in the quality inspection data does not exceed the credible range of the product quality inspection value on the corresponding quality inspection report, storing the corresponding quality inspection report in a preset quality inspection report library.
The material quality inspection device comprises a processor and a memory, wherein the acquisition module 401, the calculation module 402, the judgment module 403 and the like are all stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The kernel can be provided with one or more than one kernel, and the problem that the authenticity of the detection report and the quality inspection report cannot be guaranteed is solved by adjusting kernel parameters.
The embodiment of the invention provides a storage medium, on which a program is stored, which when executed by a processor, implements the material quality inspection method.
The embodiment of the invention provides a processor which is used for running a program, wherein the program runs to execute the material quality inspection method.
The embodiment of the invention provides equipment, as shown in fig. 5, which comprises at least one processor, at least one memory and a bus, wherein the at least one memory is connected with the processor; the processor and the memory complete communication with each other through a bus; the processor is used for calling the program instructions in the memory to execute the material quality inspection method. The device herein may be a server, PC, PAD, cell phone, etc.
The application also provides a computer program product adapted to perform, when executed on a data processing device, a program initialized with the method steps of:
acquiring a test report stored on the blockchain service platform by the provider node and a quality inspection report stored on the blockchain service platform by the quality inspection node;
Calculating the credibility range of the product parameter statistical index on the test report and calculating the credibility range of the product quality inspection statistical index on the quality inspection report;
and judging whether the statistical index of the product test value in the production data exceeds the credible range of the product parameter statistical index on the corresponding test report, and judging whether the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, the device includes one or more processors (CPUs), memory, and a bus. The device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip. Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
The functions of the methods of embodiments of the present application, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored on a computing device readable storage medium. Based on such understanding, a part of the present application that contributes to the prior art or a part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Features described in the various embodiments of the present disclosure may be interchanged or combined, each having a particular emphasis on illustrating differences from other embodiments, and the same or similar elements of the various embodiments may be used in conjunction with each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for quality inspection of materials, applied to a blockchain service platform, the blockchain service platform comprising: the system comprises a provider node, a buyer node, a quality inspection node and a gateway node; the gateway node is used for storing production data and quality inspection data; the production data are obtained by sampling and collecting product test values of all suppliers by preset internet of things equipment; the product test value of any provider is the product parameter value measured in the process of testing the product by the provider; the quality inspection data are obtained by sampling and collecting product quality inspection values of all quality inspection units by the internet of things equipment; the product quality inspection value of any quality inspection unit is a product parameter value measured in the quality inspection process of the quality inspection unit on the product of the supplier; the method comprises the following steps:
acquiring a test report stored on the blockchain service platform by the provider node and a quality inspection report stored on the blockchain service platform by the quality inspection node;
Calculating the credibility range of the product parameter statistical index on the test report and calculating the credibility range of the product quality inspection statistical index on the quality inspection report;
judging whether the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report, and judging whether the statistical index of the product quality inspection value in the quality inspection data exceeds the credibility range of the product quality inspection statistical index on the corresponding quality inspection report; the product test value in the production data and the test report provided by the supplier have a corresponding relation, and the product quality test value in the quality test data and the quality test report provided by the quality test unit have a corresponding relation.
2. The method of claim 1, further comprising, after said determining whether the statistical indicator of the product test value in the production data exceeds the confidence level of the statistical indicator of the product parameter on the corresponding test report and whether the statistical indicator of the product quality control value in the quality control data exceeds the confidence level of the statistical indicator of the product quality control on the corresponding quality control report:
Under the condition that the statistical index of the product test value in the production data exceeds the credible range of the product parameter statistical index on the corresponding test report, carrying out preset processing operation on the provider node corresponding to the corresponding test report; the processing operations include: reducing weight, adding at least one of blacklist and notification;
and under the condition that the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report, carrying out the processing operation on the quality inspection node corresponding to the corresponding quality inspection report.
3. The method as recited in claim 1, further comprising:
acquiring historical data respectively stored by the provider node, the buyer node and the quality inspection node; the history data includes: enterprise registration scale parameters, historical number of deals, and historical credit points;
Calculating credit scores corresponding to the provider node, the buyer node and the quality inspection node respectively according to the historical data;
According to a preset corresponding relation between a preset node role and a credit value interval, respectively determining node roles of the provider node, the buyer node and the quality inspection node; the preset node roles include: the public node comprises a consensus node, a trust node and a common node;
and selecting one trust node from all the trust nodes as a master node by taking the ratio of the credit score of the credit node to the total credit score of all the credit nodes as the selection probability.
4. The method of claim 1, further comprising, after said determining whether a product test value in said production data is outside a trusted range of product parameter values on a corresponding test report and a product quality control value in said quality control data is outside a trusted range of product quality control values on a corresponding quality control report:
under the condition that the product test value of the production data does not exceed the credible range of the product parameter value on the corresponding test report, the corresponding test report is stored in a preset test report library;
and under the condition that the product quality inspection value in the quality inspection data does not exceed the credible range of the product quality inspection value on the corresponding quality inspection report, storing the corresponding quality inspection report in a preset quality inspection report library.
5. A material quality inspection device is characterized in that the device is applied to a block chain service platform,
The blockchain service platform includes: the system comprises a provider node, a buyer node, a quality inspection node and a gateway node; the gateway node is used for storing production data and quality inspection data; the production data are obtained by sampling and collecting product test values of all suppliers by preset internet of things equipment; the product test value of any provider is the product parameter value measured in the process of testing the product by the provider; the quality inspection data are obtained by sampling and collecting product quality inspection values of all quality inspection units by the internet of things equipment; the product quality inspection value of any quality inspection unit is a product parameter value measured in the quality inspection process of the quality inspection unit on the product of the supplier; the device comprises:
The acquisition module is used for acquiring a test report stored on the blockchain service platform by the provider node and a quality inspection report stored on the blockchain service platform by the quality inspection node;
the calculating module is used for calculating the credibility range of the product parameter statistical index on the test report and calculating the credibility range of the product quality inspection statistical index on the quality inspection report;
The judging module is used for judging whether the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report and whether the statistical index of the product quality inspection value in the quality inspection data exceeds the credibility range of the product quality inspection statistical index on the corresponding quality inspection report; the product test value in the production data and the test report provided by the supplier have a corresponding relation, and the product quality test value in the quality test data and the quality test report provided by the quality test unit have a corresponding relation.
6. The apparatus as recited in claim 5, further comprising:
The processing module is used for carrying out preset processing operation on the provider node corresponding to the corresponding test report when the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report after the judging module judges whether the statistical index of the product test value in the production data exceeds the credibility range of the product parameter statistical index on the corresponding test report and whether the statistical index of the product quality check value in the quality check data exceeds the credibility range of the product quality check statistical index on the corresponding quality check report; the processing operations include: reducing weight, adding at least one of blacklist and notification;
and under the condition that the statistical index of the product quality inspection value in the quality inspection data exceeds the credible range of the product quality inspection statistical index on the corresponding quality inspection report, carrying out the processing operation on the quality inspection node corresponding to the corresponding quality inspection report.
7. The apparatus as recited in claim 5, further comprising:
the consensus module is used for acquiring historical data respectively stored by the supplier node, the buyer node and the quality inspection node; the history data includes: enterprise registration scale parameters, historical number of deals, and historical credit points; calculating credit scores corresponding to the provider node, the buyer node and the quality inspection node respectively according to the historical data; according to a preset corresponding relation between a preset node role and a credit value interval, respectively determining node roles of the provider node, the buyer node and the quality inspection node; the preset node roles include: the public node comprises a consensus node, a trust node and a common node; and selecting one trust node from all the trust nodes as a master node by taking the ratio of the credit score of the credit node to the total credit score of all the credit nodes as the selection probability.
8. The apparatus as recited in claim 5, further comprising:
The storage module is used for storing the corresponding test report in a preset test report library under the condition that the product test value of the production data does not exceed the credible range of the product parameter value on the corresponding test report after judging whether the product test value in the production data exceeds the credible range of the product parameter value on the corresponding test report and whether the product quality check value in the quality check data exceeds the credible range of the product quality check value on the corresponding quality check report; and under the condition that the product quality inspection value in the quality inspection data does not exceed the credible range of the product quality inspection value on the corresponding quality inspection report, storing the corresponding quality inspection report in a preset quality inspection report library.
9. A storage medium comprising a stored program, wherein the program performs the method of quality control of materials of any one of claims 1 to 4.
10. An apparatus comprising at least one processor, and at least one memory, bus coupled to the processor; the processor and the memory complete communication with each other through the bus; the processor is configured to invoke program instructions in the memory to perform the material quality inspection method of any of claims 1-4.
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