A chip yield detection system for distribution sources in a zoned distribution network

Abstract

The present invention proposes a chip yield rate detection system for distribution sources of a regional distribution network, including building a distribution network through a digital collaborative platform, and constructing a shipment statistics unit in the distribution network to record the entire process of chip production, transportation and sales in the distribution network; the distribution network is built through a docker microserver architecture, and distributors interact with the docker microserver through blockchain nodes, and retain each transaction data through the nodes; the statistics unit classifies distributors by region through the distribution network, and counts the transaction data of distributors to form regional statistical data; distributors perform parabolic curve sampling on chips of the same specification of chip manufacturers in batch order through a sampling unit, and feed back the sampling data to the blockchain node for recording; the chip manufacturer determines the terminal yield rate and regional yield rate threshold of the distributor before each batch of chips is shipped, and the distributor feeds back the sampling yield rate of each batch of chips.

Description

Technical Field

[0001] The present invention belongs to the field of evaluation systems, and in particular relates to a chip yield rate detection system for distribution sources in a zoned distribution network. Background Art

[0002] At present, the biggest challenge to the development of enterprises in the era of e-commerce is that the traditional mass manufacturing must be transformed into a mass customization model, that is, from making products first and then finding users to selecting users first and then making products. The traditional enterprise's "production-inventory-sales" model must be transformed into a user-driven "supply-on-demand" model. Supply chain management plays an increasingly important role in the mass customization of enterprises. The supply chain involves many participants and is closely linked to each other. Sudden problems in any link may have adverse effects on the entire supply chain upstream and downstream. Therefore, the supply chain system has great uncertainty and fragility, and is vulnerable to various risks.

[0003] The sales model of the chip industry can be divided into two models: direct sales and distribution, depending on whether the original manufacturer signs a contract directly with the customer.

[0004] The direct sales model is suitable for products with large projects, clear customer targets, high product technology complexity and complex project delivery. In this case, it is most appropriate for the original manufacturer to directly arrange sales personnel to connect with customers. Distribution is to establish sales channels, implement a channel sales model, develop agents, and let the agents connect with customers, fulfill contracts and provide after-sales services. Because the chip industry has a large market and many projects, it is unrealistic to rely solely on the original manufacturer to recruit people for direct sales to cover the market.

[0005] During the long-distance transportation of chip products, due to the large number of products, they are generally transported in sealed boxes and stacked. During the transportation process, due to long-distance travel, stacking of goods, humidity changes, etc., although it is not easy to cause problems with the entire batch of products, it will increase the defective rate during transportation. Because the unit price of chips is relatively high among bulk commodities, distributors need to conduct random inspections on different batches of chips received during distribution to ensure the quality of the entire batch.

[0006] However, after arriving at the destination area, due to the problem of unstable sales, sales in different regions are unstable, and the shipment volume varies in different regions. Long-term storage also has a certain impact on the quality of the chip.

[0007] Therefore, there is an urgent need for a chip yield detection system for distribution sources in a regional distribution network. Summary of the invention

[0008] The present invention proposes a chip yield detection system for distribution sources in a zoned distribution network, which solves the problem in the prior art that distributors cannot conveniently and timely provide feedback on chip quality, and chip manufacturers cannot timely, accurately and safely understand the quality of distributed products and maintain processes and assembly lines in a timely manner.

[0009] The technical solution of the present invention is implemented as follows: a chip yield rate detection system for distribution sources of a zoned distribution network, including building a distribution network through a digital collaborative platform, and constructing a shipment statistics unit in the distribution network to record the entire process of chip production, transportation and sales in the distribution network;

[0010] The distribution network is built through the docker microserver architecture. Distributors interact with the docker microserver through blockchain nodes and retain each transaction data through the nodes.

[0011] The statistical unit classifies distributors by region through the distribution network and compiles statistics on the distributors’ transaction data to form regional statistical data;

[0012] Distributors use sampling units to perform parabolic sampling of chips of the same specification from chip manufacturers in batch order, and feed the sampling data back to the blockchain node for recording;

[0013] Before shipping each batch of chips, the chip manufacturer determines the distributor's terminal yield and regional yield threshold. The distributor will provide feedback on the yield of each batch of chips sampled and warn the chip manufacturer when the yield is lower than the set terminal yield threshold. The chip manufacturer monitors the yield in all areas in the statistical unit. When the yield in a certain area is lower than the regional yield threshold, the factory double quality inspection is initiated. When the yield in all areas is lower than the regional yield threshold, the production water flow line is shut down for inspection.

[0014] At present, distributors rarely conduct quality assessment on the source of goods, and they only conduct random inspections after receiving the goods. Most distributors only distribute chips. Therefore, for chip manufacturers, the only way to understand the yield rate of chips after transportation and before installation is through after-sales links and consumer feedback. This is controllable for chip manufacturers under normal circumstances, because in most cases the quality of the chips themselves is guaranteed and has passed factory quality inspection. However, in some special environments, such as sea transportation, seawater may penetrate into the container. Although waterproof and rust-proof measures are taken, if there is a problem, it may be a batch of bad products, which may have a great impact on public opinion of the chip brand. To avoid this situation, a quality assessment system is adopted to allow distributors to participate in the quality assessment of the source of goods entering the distribution, improve the overall product yield rate among users, and enable chip manufacturers to discover and rectify batch problems in a timely manner.

[0015] As a preferred implementation, after calculating the regional statistical data, the statistical unit backs up the data in the blockchain node. The chip manufacturer reads the regional statistical data generated by the statistical unit by calling the data in the blockchain node, and the blockchain node records the reading record.

[0016] As a preferred implementation, when the distributor enters the blockchain node, a dedicated address is formed through a public key encryption algorithm, and the distributor exchanges data with the docker microserver through the address through its own terminal. The dedicated address formed by the blockchain has the characteristics of encryption, and after data backup and upload, based on the characteristics that the content of the blockchain node cannot be changed, data traceability can be conveniently performed, and the uploaded data can be replaced in the greatest case, which is convenient for chip manufacturers to understand the real data in a timely and accurate manner.

[0017] As a preferred implementation, the digital collaboration platform uses HPC and HPG to build graphics, and stores the distribution network data in the platform. HPC and HPG are high-performance computing and high-performance graphics, respectively. The two are used to build graphics to form a UI interface, and users can perform real-time operations through the UI interface. The data generated by the distribution network is stored, which is convenient for comparison and detection with the data in the blockchain node in the later stage.

[0018] As a preferred implementation, the distributor and the blockchain node are encrypted using an encryption algorithm, and the encryption algorithm uses RSA-1024 to encrypt the data channel.

[0019] As a preferred implementation, the parabolic curve sampling is based on the batch number of chips of the same specification determined between the chip manufacturer and the distributor. The sampling quantity increases first according to the batch number, and the sampling quantity decreases after reaching the agreed intermediate batch. The sampling quality can be effectively improved by this parabolic curve sampling method. By adopting this method of sampling, a good detection efficiency can be maintained in different cycles of chips of the same specification.

[0020] As a preferred implementation, if the chip manufacturer has an extra batch that is not planned, the maximum sampling quantity of chips of this specification is used for sampling inspection. When distributing extra batches, the product quality needs to be fully guaranteed to avoid the situation where the overall distribution efficiency is affected by quality problems when the shipment volume is large.

[0021] As a preferred implementation, the factory double quality inspection is to conduct the first quality inspection after the assembly line packaging is completed, and then conduct another random inspection on the shipped chips when the batch is determined to be shipped to the regional distributor. The double quality inspection is because quality problems occur in regional distribution. In order to avoid being caused by transportation to the region, the next batch of shipments to the region is subjected to repeated quality inspection, and the quality of shipments to the region is monitored to understand the transportation defect rate of shipments to the region.

[0022] After adopting the above technical solution, the beneficial effect of the present invention is: by incorporating distributors into the product quality management system, the yield rate at the user terminal can be effectively improved, and the chip manufacturer can timely understand the yield rate data when the chip reaches the distributor, which is convenient for them to adjust the factory and assembly line in the later stage. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 This is a system framework diagram of the present invention.

[0025] Figure 2 It is a schematic diagram of parabolic sampling of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] Example:

[0028] like Figures 1-2 As shown, a chip yield rate detection system for distribution sources in a zoned distribution network includes building a distribution network through a digital collaborative platform, and constructing a shipment statistics unit in the distribution network to record the entire process of chip production, transportation and sales in the distribution network;

[0029] The distribution network is built through the docker microserver architecture. Distributors interact with the docker microserver through blockchain nodes and retain each transaction data through the nodes.

[0030] The statistical unit classifies distributors by region through the distribution network and compiles statistics on the distributors’ transaction data to form regional statistical data;

[0031] Distributors use sampling units to perform parabolic sampling of chips of the same specification from chip manufacturers in batch order, and feed the sampling data back to the blockchain node for recording;

[0032] Before shipping each batch of chips, the chip manufacturer determines the distributor's terminal yield and regional yield threshold. The distributor will provide feedback on the yield of each batch of chips sampled and warn the chip manufacturer when the yield is lower than the set terminal yield threshold. The chip manufacturer monitors the yield in all areas in the statistical unit. When the yield in a certain area is lower than the regional yield threshold, the factory double quality inspection is initiated. When the yield in all areas is lower than the regional yield threshold, the production water flow line is shut down for inspection.

[0033] At present, in the actual chip distribution, distributors pay little attention to product quality, because all quality issues are guaranteed by chip manufacturers. However, in the current increasingly fierce market competition, in order to ensure the yield rate of products delivered to customers, distributors need to actively cooperate. Chip manufacturers, because they control the supply and distribution channels and can control the shipment volume, can promote the entire detection system, through distributors to conduct centralized goods quality sampling close to user terminals, test the yield rate, and when the sampling yield rate is within the set threshold, there is no need to interfere with production. When the yield rate of a certain distributor is below the threshold, If the yield rate of the entire region is lower than the threshold, it can be solved by subsidies or by sending regional engineers for re-inspection. If the overall yield rate of the entire region is lower than the threshold, it may be caused by problems during transportation, which in turn affects the yield rate. Because conventional chip products are quality-checked when they leave the factory, and after transportation from the factory to the distributor, there are few problems because the chip itself is tightly packaged. Therefore, only the next batch of chips needs to be shipped again for quality inspection of the chips shipped to the region. After arriving at the region, the distributors in the region will conduct quality inspection. By comparing the quality inspections before and after the two transportations, the transportation loss can be obtained. It is convenient for chip manufacturers to replace the transportation channels in the region or choose other transportation methods. If the quality inspections of distributors in all regions exceed the threshold, the entire assembly line may have precision loss, and the assembly line needs to be maintained and adjusted. In this way, the quality of the products produced by the entire chip manufacturer to the user terminal can be effectively improved.

[0034] The blockchain node method used for data storage is to avoid data leakage and subsequent data tampering. Relying on the encryption and anti-modification characteristics of the blockchain itself, the data uploaded by the distributor can be recorded. In order to prevent distributors from abusing the chip manufacturer's subsidy mechanism, the inspection results of the distributors can be reviewed by engineers in the region, and the illegal distributors can be punished by adjusting the shipment volume of the distributors.

[0035] After calculating the regional statistical data, the statistical unit backs up the data in the blockchain node. The chip manufacturer reads the regional statistical data generated by the statistical unit by calling the data in the blockchain node, and the blockchain node records the reading record.

[0036] When the distributor enters the blockchain node, a dedicated address is formed through the public key encryption algorithm, and the distributor exchanges data with the docker microserver through its own terminal through this address. The digital collaboration platform is built through HPC and HPG for graphics, and the distribution network data is stored in the platform. The parabolic curve sampling is based on the number of batches of chips of the same specification determined between the chip manufacturer and the distributor. The sampling quantity first increases according to the batch quantity, and the sampling quantity decreases after reaching the agreed intermediate batch.

[0037] If the chip manufacturer has an extra batch that is not planned, the maximum sampling quantity of chips of this specification will be used for sampling inspection. The double quality inspection before delivery is the first quality inspection after the assembly line packaging is completed, and then the shipped chips will be sampled again when the batch is determined and shipped to the distributor in the region.

[0038] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A chip yield rate detection system for distribution sources in a regional distribution network, characterized in that: This includes building a distribution network through a digital collaborative platform and establishing a shipment statistics unit within the distribution network to record the entire process of chip production, transportation and sales in the distribution network; The distribution network is built through the docker microserver architecture. Distributors interact with the docker microserver through blockchain nodes and retain each transaction data through the nodes. The statistical unit classifies distributors by region through the distribution network and compiles statistics on the distributors’ transaction data to form regional statistical data; Distributors use sampling units to perform parabolic sampling of chips of the same specification from chip manufacturers in batch order, and feed the sampling data back to the blockchain node for recording; Before shipping each batch of chips, the chip manufacturer determines the terminal yield rate and regional yield rate threshold of the distributor. The distributor will provide feedback on the sampling yield rate of each batch of chips and warn the chip manufacturer when the yield rate is lower than the set terminal yield rate threshold. The chip manufacturer monitors the yield rate in all areas of the statistical unit. When the yield rate of a certain area is lower than the regional yield rate threshold, the factory double quality inspection is initiated. When the yield rate of all areas is lower than the regional yield rate threshold, the production water flow line is shut down for inspection. The double quality inspection before delivery is the first quality inspection after the assembly line packaging is completed, and then when the batch is determined to be shipped to the distributor in the region, the shipped chips are sampled again.

2. The chip yield rate detection system for distribution sources in a zoned distribution network as claimed in claim 1, characterized in that: After calculating the regional statistical data, the statistical unit backs up the data in the blockchain node, and the chip manufacturer reads the regional statistical data generated by the statistical unit by calling the data in the blockchain node.

3. The chip yield rate detection system for distribution sources in a zoned distribution network as claimed in claim 1, characterized in that: When the distributor enters the blockchain node, a dedicated address is formed through the public key encryption algorithm, and the distributor interacts with the docker microserver through its own terminal through this address.

4. The chip yield rate detection system for distribution sources in a zoned distribution network as claimed in claim 1, characterized in that: The digital collaboration platform is constructed through HPC and HPG for graphics construction, and the distribution network data is backed up within the platform.

5. The chip yield rate detection system for distribution sources in a zoned distribution network as claimed in claim 1, characterized in that: The distributor and the blockchain node are encrypted through an encryption algorithm, and the encryption algorithm uses RSA-1024 to encrypt the data channel.

6. The chip yield rate detection system for distribution sources in a zoned distribution network as claimed in claim 1, characterized in that: The parabolic sampling is based on the number of chip batches of the same specification determined between the chip manufacturer and the distributor. The sampling quantity first increases according to the batch quantity, and then decreases after reaching the agreed middle batch.

7. The chip yield rate detection system for distribution sources in a zoned distribution network as claimed in claim 6, characterized in that: If the chip manufacturer has unplanned additional batches, the maximum sampling quantity of chips of the same specification will be used as a reference for random inspection during quality inspection.

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