Federated-Learning-based Decision Support for Industrial Internet of Things (IIoT)-based Printed Circuit Board Assembly Process

Y. P. Tsang, C. H. Wu (Corresponding Author), W. H. Ip, C. K.M. Lee

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Solder paste printing (SPP) is one of the critical processes for the printed circuit board assembly to reliably apply the solder paste on raw PCBs for the component placement through surface mount technology. Although computerised SPP machines have been developed in the past few years, the reliance on domain experts cannot be neglected to fine-tune corresponding process parameters so as to maintain productivity and quality. This study exploits federated learning on the industrial internet of things (IIoT) paradigm to establish an intelligent decision support system across various networked machines. The IIoT-based squeegee blade is deployed in the SPP machines for better machine-to-machine communication and interconnectivity. In contrast, a global machine intelligence model is aggregated in a decentralised and privacy-preserving manner. Consequently, the automated and sustainable manufacturing management for PCBA is achieved, where wastes from trial production runs are eliminated.

Original languageEnglish
Article number43
Number of pages22
JournalJournal of Grid Computing
Issue number4
Publication statusPublished - Dec 2022


  • Assembly
  • Decision support
  • Federated learning
  • Industrial internet of things
  • Printed circuit board

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications


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