Computer Vision Techniques in Manufacturing

  • Longfei Zhou
  • , Lin Zhang*
  • , Nicholas Konz
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Computer vision (CV) techniques have played an important role in promoting the informatization, digitization, and intelligence of industrial manufacturing systems. Considering the rapid development of CV techniques, we present a comprehensive review of the state of the art of these techniques and their applications in manufacturing industries. We survey the most common methods, including feature detection, recognition, segmentation, and three-dimensional modeling. A system framework of CV in the manufacturing environment is proposed, consisting of a lighting module, a manufacturing system, a sensing module, CV algorithms, a decision-making module, and an actuator. Applications of CV to different stages of the entire product life cycle are then explored, including product design, modeling and simulation, planning and scheduling, the production process, inspection and quality control, assembly, transportation, and disassembly. Challenges include algorithm implementation, data preprocessing, data labeling, and benchmarks. Future directions include building benchmarks, developing methods for nonannotated data processing, developing effective data preprocessing mechanisms, customizing CV models, and opportunities aroused by 5G.

Original languageEnglish
Pages (from-to)105-117
Number of pages13
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume53
Issue number1
DOIs
StatePublished - 1 Jan 2023

Keywords

  • Assembly
  • computer vision (CV)
  • deep learning
  • inspection
  • machine intelligence
  • machine learning
  • manufacturing
  • production
  • robotics
  • survey

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