Blockchain Performance Optimization in Manufacturing Service Collaboration With Improved Gray Wolf Optimizer

Abstract With the integration of information technology and manufacturing industries, manufacturing is expected to enter the stage of service collaboration on platforms. The immutability and decentralization of blockchain can provide a trustworthy environment for manufacturing service collaboration (MSC). Manufacturing services with varying processes and standards lead to significant quality of service (QoS) differences, making single-chain networks unable to meet diverse ledger demands, potentially delaying subsequent manufacturing procedures on platforms. Therefore, this article proposes a blockchain-enabled MSC framework based on the Hyperledger Fabric's multichain architecture. A platform chain Org allocation mechanism based on the enterprise operation data is designed, and manufacturing services are grouped based on the QoS to ensure consistency in each service chain. Additionally, generalized stochastic Petri nets is employed to model the relevant stages of manufacturing service execution and log recording process on blockchain to analyze the system performance, and an improved gray wolf optimizer (GWO) is adopted to identify the most suitable parameters of the blockchain. The proposed optimizer achieves significant enhancements in exploration performance and stability. In addressing the problem proposed in the article, the optimizer obtains comparable solutions while reducing iterations by approximately 9%, significantly lowering simulation costs. Experiments validate the effectiveness of the proposed mechanism and algorithms.