Profit Maximizing Smart Manufacturing Over AI-Enabled Configurable Blockchains
Yinglei Teng, Lanlin Li, Luona Song, F. Richard Yu, Victor C. M. Leung
Abstract
Based on the trustless feature of blockchain, this article designs a general configurable blockchain-enabled smart manufacturing system to achieve flexible manufacturing in response to large-scale manufacturing services. With a transaction pool containing all the pending manufacturing tasks but aligning with the logic flow, the complex manufacturing structure can be uniformly tackled. Furthermore, in virtue of the contradiction between large-scale manufacturing and limited blockchain throughput, we formulate a joint optimization of the block size, task scheduling, and the supply-demand configuration to maximize the customers’ net profit with the probabilistic delay requirements, which addresses the critical issue of efficiency and latency in the blockchain-based live manufacturing process. Meanwhile, the production quality and price preference are involved. For solution, a mixed online bipartite matching-based DQN algorithm is proposed, which circumvents the high dimensionality by separating the task-manufacturer matching from the time-correlated problem. Simulation results show that the proposed flexible framework can well adopt to dynamic customer population, and achieves better convergence.