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Jing, Z.;  Hu, N.;  Song, Y.;  Song, B.;  Gu, C.;  Pan, L. Blockchain-Based Data Management System for ETO Manufacturing. Encyclopedia. Available online: https://encyclopedia.pub/entry/28248 (accessed on 12 August 2024).
Jing Z,  Hu N,  Song Y,  Song B,  Gu C,  Pan L. Blockchain-Based Data Management System for ETO Manufacturing. Encyclopedia. Available at: https://encyclopedia.pub/entry/28248. Accessed August 12, 2024.
Jing, Zhengjun, Niuping Hu, Yurong Song, Bo Song, Chunsheng Gu, Lei Pan. "Blockchain-Based Data Management System for ETO Manufacturing" Encyclopedia, https://encyclopedia.pub/entry/28248 (accessed August 12, 2024).
Jing, Z.,  Hu, N.,  Song, Y.,  Song, B.,  Gu, C., & Pan, L. (2022, October 04). Blockchain-Based Data Management System for ETO Manufacturing. In Encyclopedia. https://encyclopedia.pub/entry/28248
Jing, Zhengjun, et al. "Blockchain-Based Data Management System for ETO Manufacturing." Encyclopedia. Web. 04 October, 2022.
Blockchain-Based Data Management System for ETO Manufacturing
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This entry is adapted from the peer-reviewed paper 10.3390/app12189184

Engineer-to-order (ETO) is a currently popular production model that can meet customers’ individual needs, for which the orders are primarily non-standard parts or small batches. This production model has caused many management challenges, including the difficulty of tracing the production process data of products and the inability to monitor order status in real-time. 

blockchain-enabled ETO-type production sequential aggregate signature data management

1. Introduction

Engineer-to-order (ETO) production means that products are engineered and produced after orders have been received. This production method helps to meet the exact specifications of customers [1]. With the increasing personalized needs of customers, more and more enterprises have adopted the production model of ETO for their development, which accounts for an increasing proportion in the manufacturing industry. The ETO production mode is a highly discrete production type and is the most complex in the manufacturing environment. ETO manufacturing faces many challenges in production [2][3][4][5]. Customers’ needs are personalized and diversified, making it impossible to reuse the manufacturing process of the produced products. Furthermore, the relevant information about the new product can only be determined after the design drawings are released, including material code, BOM, and process route. This delay also directly leads to the lack of effective control of the collaborative cost of production. In addition, enterprises in the ETO production model have many discrete workshops for processing semi-finished products. Therefore, to meet the customer’s customized needs for products and the traceability of the production process, it is necessary to ensure the accuracy of product processing and the credibility of the production process information after the product is completed.
Through production process data management, not only can the production process of orders be tracked in real-time, but production problems can also be found in time and improved through data analysis. Therefore, the validity of data in manufacturing is crucial to improving production quality and efficiency. Due to the above reasons, each change in the process data or transformation event should be traceable in a record that cannot be deleted or changed. Building efficient multi-department collaboration to achieve credible and traceable production process data, and traceability of the production process, has always been a key research issue in the manufacturing field. The blockchain has the characteristic that data cannot be tampered with in a distributed environment, and is thus highly suitable for data management scenarios in manufacturing [6][7][8][9][10][11].

2. Blockchain in Engineering and Manufacturing

Blockchain is an electronic distributed ledger with the features of decentralization, data immutability, consensus mechanism, and many more [12][13][14][15][16]. Blockchain technology, as a new model of data sharing, provides a means for parties to build mutual trust without the need for a trusted third party. This mechanism records data changes in a block as a transaction and uploads them to the chain. Since all participants jointly maintain the ledger, any party’s changes to the data can only be recognized through consensus; otherwise, the transaction will be rejected. Most importantly, when smart contracts are integrated into the blockchain, the application scenarios of blockchain technology become more and more extensive. Smart contracts are a computer protocol linking multiple parties to complete a dedicated contract. Smart contracts are supported by major blockchain development platforms, such as Ethereum and Hyperledger [17][18].
To date, many studies have shown that the application of blockchain in production scenarios has many advantages, and its distributed storage structure greatly ensures the security of data, which are extremely difficult to tamper with [19][20][21][22][23][24][25]. The storage structure ensures the data are immutable and facilitates the traceability of the data. Thus, it helps to achieve transparent tracking of the production process. Kasten [26] undertook a detailed review of the application of blockchain technology in engineering and manufacturing in terms of achieving three outcomes: protecting data validity [27][28][29][30][31][32], enhancing communication within an organization [33][34][35][36][37][38], and improving manufacturing production efficiency [39][40][41][42][43]. Kumar et al. [44] discussed in detail the use of an Ethereum-based distributed ledger technology to improve information trustworthiness and access control in cloud-based manufacturing. To solve the data sharing problem of the production supply chain in the Industrial Internet of Things (IIoT), Wen et al. [45] proposed a new blockchain-based supply chain structure, which integrates attribute encryption to make data access more fine-grained. At the same time, it further improves the reliability and traceability of IIoT data. Rathee G. et al. [46] proposed a hybrid blockchain mechanism to provide security for multinational IIoT data with offices in multiple countries. A blockchain-based resource-sharing collaboration framework was designed by Agrawal et al. [47], which can support ecosystems with established collaborations and hierarchies. While blockchain technology has provided many benefits for smart manufacturing, there are still many problems in applying it to ETO-type manufacturing, especially in ensuring the validity of production chain data when the production process route is uncertain.

3. Sequential Aggregate Signature

An aggregate signature is a cryptographic primitive that can aggregate different signatures of multiple signers into a single signature [48]. Since the size of the aggregate signature remains the same as that of a single signature, it can effectively reduce the communication cost when an authenticated message must be forwarded from one partner to another. A sequential aggregate signature is a variant that supports data aggregation that depends on the order of the parties. It relies not only on the public data but also on the order of all previously aggregated data. The sequential aggregate signatures play a key role in situations such as verifying routing information or certificate chains, where the verification of the order of signature steps is important.
In the ETO-type production model, the sequential execution of discrete production process routes needs to be guaranteed. By integrating the sequential aggregate signature into the blockchain, verification and traceability of the execution steps of the production process route is ensured. Generally, a sequential aggregate signature scheme consists of three parts: key generation algorithm, signature aggregation algorithm, and aggregate verification algorithm. Specifically, when the signer receives an ordered set of public keys PK=(pk1,...pki) and messages M=(m1,...mi), and an aggregate signature corresponding to the sequence, the signer uses its own private key, sk, to derive a new aggregate signature on its message, m, using an aggregation algorithm, which takes m#M and pk#PK as input parameters. In the proposed scheme, the sequential aggregate signature designed by Fischilin M. in [49] is adopted; this is mainly constructed based on bilinear mapping, and its security has been proved theoretically [49][50].

4. Blockchain-Based Production Process Management for ETO Manufacturing

Due to the diverse and discrete process steps in ETO-type production, the traditional method of tracing data stored in the centralized database of the enterprise will result in low timeliness of data verification and the risk of data tampering and loss. The blockchain uses distributed ledgers instead of a central database to store enterprise production data. This approach can record product information positively in real-time, enhance the validity and reliability of the data, and improve the traceability of the production process.
A blockchain-based product data management system (BPDMS) is constructed for ETO-type production, as shown in Figure 1. The BPDMS can be divided into three levels from top to bottom: business logic, data acquisition, and the blockchain network. The three layers are interrelated.
Applsci 12 09184 g002 550
Figure 1. The architecture of BPDMS.
1. Business logic layer (BLL). This layer represents the business process of ETO-type manufacturing production. In the BLL, the business starts with contract orders, decomposes into product designs, and forms production work orders and their production process routes. Next, according to the production process route, the semi-finished product processing and finished product assembly are completed in the manufacturing center. Finally, the quality inspection of the product needs to be completed.
Compared to the business process described in Figure 1, a supervisory role is added to the process, primarily responsible for the production process supervision and traceability query through the deployed smart contracts. In addition, the purchasing step is also ignored in this process because the framework focuses on the production process data. In the actual enterprise management, this layer mainly includes some related application software, such as ERP, 3D design software, and the MES system.
2. Data acquisition layer (DAL). The DAL is the middle layer, and uses a variety of IoT devices to collect data on each business viewpoint of the business logic layer. For example, specific products can be identified by scanning the QR code corresponding to the work order generated in the ERP system with a barcode gun at the production station. Similarly, the operation data of various equipment with different functions are also collected through IoT terminals, such as sensors, industrial robots, and edge gateways.
In the DAL, the data collected on each business node can be stored and queried on the chain by calling the deployed smart contract. It should be noted that data such as production drawings and operation videos are stored off-chain, and the stored address index is then uploaded to the chain. This combination of on-chain and off-chain storage helps save blockchain storage resources and improve query efficiency.
3. Blockchain network layer (BNL). The BNL adopts Hyperledger Fabric as the blockchain platform, which is a permissioned blockchain. In this type of blockchain, all participants who can trace the data must first register and obtain a legal identity; otherwise, they cannot access the blockchain. Since managers can control the size of the network by controlling the number of nodes, permissioned chains usually have a high transaction throughput.
In BPDMS, the channel technology of the Fabric blockchain is used to create a channel for each department in the production process, and each channel has an independent ledger, which ensures that each department’s data are isolated from each other. In each channel, the production data collected by the DAL are packaged into transaction events and then uploaded to the blockchain network by calling the smart contract that stores the data to generate new blocks. The information of these transaction events is stored in the leaf node of the Merkle tree of the block body for block accounting, and then the returned transaction hash and block height are stored in the current state index database, CouchDB. Authorized users of each department can call smart contracts that query data to trace or track production data. Since the supervisory role has supervisory authority over the product production process, it can simultaneously call the smart contracts of one or more departments in the production chain to supervise the entire production process status regarding the specific product in real-time.

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Subjects: Computer Science, Information Systems
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Zhengjun Jing
,
Niuping Hu
,
Yurong Song
,
Bo Song
,
Chunsheng Gu
,
Lei Pan
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Update Date: 08 Oct 2022
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