Blockchain performance optimization in manufacturing service collaboration with improved Grey Wolf Optimizer

With the integration of information technology and manufacturing industries, manufacturing is expected to enter the stage of service collaboration on platform. 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 platform. Therefore, this paper proposes a blockchain-enabled MSC framework based on Hyperledger Fabric's multi-chain architecture. A platform chain Org allocation mechanism based on enterprise operation data is designed, and services are grouped based on QoS to ensure consistency in each service chain. Additionally, Generalized Stochastic Petri Nets is employed to model the relevant stages of services execution and log recording process on blockchain to analyze system performance, and an improved Grey 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 paper, 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.