# On the Design and Implementation of a Blockchain-Based Data Management System for ETO Manufacturing
## 3 Blockchain network layer (BNL)
### Smart Contract Logic
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Sales** & **Product** & **Production** & **Discrete** & **Assembly** & **Inspection** \\  & **Department** & **Design** & **Management** & **Processing** & **Line** & **Inspection** \\ \hline _Ta\({}^{\prime}\)_ & 0.399s & 0.399s & 0.388s & 0.474s & 0.485s & 0.447s \\ _Tq\({}^{\prime}\)_ & 0.322s & 0.365s & 0.356s & 0.398s & 0.381s & 0.374s \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The average value of _Ta_ and _Tq_ for each channel. Figure 9: Network throughput testing of blockchain channel. ### Performance Comparison

In order to more objectively evaluate the performance of the proposed scheme, a comparison is made with the data traceability scheme proposed by [PERSON] et al. [36]. First, a comparison is made of the throughput rate of write data and query data of the channel in the blockchain network. The design department channel of BPDMS and a single chain in [PERSON]'s scheme is taken as an example. The experiment takes 25 transactions as a group, and adopts the method of gradually increasing the number of transactions. The results are shown in Figures 11 and 12, respectively. When the number of processing transactions is between 25 and 100, the write throughput increases linearly, and gradually flattens after reaching 100; when the number of processed transactions is between 25 and 200, the query throughput increases linearly, and gradually flattens after reaching 200. Compared with [PERSON]'s solution, the throughput performance of BPDMS is slightly poorer in terms of write performance, but superior in terms of query performance. Figure 11: The throughput rate of write data. Figure 12: The throughput rate of query data. Figure 10: Efficiency of sequential aggregate signatures. In addition, the accounting time and query delay time of the blockchain network channels of the two systems are compared. The design department channel of BPDMS and a single chain in [PERSON]'s scheme are again taken as an example. The test of uploading 60 data blocks to the chain is used, and the results of the accounting time are shown in Figure 13. Similarly, 60 non-repeated queries are selected on the design department channel, and the results of the delay time are shown in Figure 14. Compared with [PERSON]'s solution, the accounting performance of BPDMS is better, and the query performance is similar. ## 5 Conclusions

ETO-type production is the main production method used in the current manufacturing field. In this process, the production process data of the product are difficult to trace, and the production status data of the product are difficult to monitor in real-time. A production process traceability model based on blockchain technology is proposed, which can be applied to ETO-type production. By analyzing each data entity generated in the production process and the relationship between the data, the smart contracts for uploading data to the blockchain and data traceability are written. After integrating the sequential aggregate signature technology, the proposed scheme can be used to verify whether the production process is executed according to the designed process route. Based on the Hyperledger Fabric framework, the production process traceability system was designed and implemented. The experimental results show that the system can solve the problem of data traceability in the production process, and improve the security and traceability of data between each step of collaborative manufacturing of ETO-type production enterprises. In future research, other parts of manufacturing, such as procurement of production materials, material management, product logistics, and after-sales service can be added, so

Figure 14: The comparison of query delay. Figure 13: The comparison of accounting performance. that the data management of ETO manufacturing can be studied from a more systematic perspective. Conceptualization, Z.J., N.H. and Y.S. ; methodology, Z.J., N.H. and Y.S. ; software, N.H., B.S. ; validation, Z.J. ; formal analysis, Z.J.