Profit Maximizing Smart Manufacturing Over AI-Enabled Configurable Blockchains

被引:6
|
作者
Teng, Yinglei [1 ]
Li, Lanlin [1 ]
Song, Luona [2 ]
Yu, F. Richard [3 ]
Leung, Victor C. M. [4 ]
机构
[1] Beijing Univ Posts & Telecommun, Beijing Key Lab Spaceground Interconnect & Conver, Beijing 100876, Peoples R China
[2] Beijing Informat Sci & Technol Univ, Sch Econ & Management, Beijing 100101, Peoples R China
[3] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada
[4] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V6T 1Z4, Canada
基金
中国国家自然科学基金;
关键词
Blockchain; deep Q network (DQN); Industrial Internet of Things (IIoT); smart manufacturing (SM); INDUSTRIAL INTERNET; CLOUD; OPTIMIZATION; ASSIGNMENT; KNOWLEDGE; SERVICES; PLATFORM; SYSTEMS; THINGS;
D O I
10.1109/JIOT.2021.3098917
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:346 / 358
页数:13
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