Automatic Virtual Metrology for Carbon Fiber Manufacturing

Yu Ming Hsieh, Chin Yi Lin, Yu Ru Yang, Min Hsiung Hung, Fan Tien Cheng

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


Carbon fiber is currently one of the most popular composite materials in the world, with its wide applications ranging from bikes to space shuttles. However, there is no comprehensive method for the total quality inspection of carbon fiber products so far due to its feature of continuous production and destructive examination of quality inspection. Through years of development, the Automatic Virtual Metrology (AVM) technology has been applied to various industries to turn the offline sampling inspection with metrology delay into online and real-time total inspection. With AVM, every workpiece of the carbon fiber products can be examined to ensure total quality inspection. The biggest issue of continuous production is that it can neither accurately define each unit nor label on the products. To solve this problem, a production data traceback (PDT) mechanism is proposed in this letter. The PDT mechanism can provide a virtual label to each unit for referring back to the process parameters of the production. With PDT, the process data of each workpiece of a complete spin can be acquired so as to accomplish the work-in-process (WIP) tracking requirement of applying AVM. Also, the Advanced Manufacturing Cloud of Things (AMCoT) platform is adopted in this letter to fulfill all the smart manufacturing requirements for achieving the goal of zero defects of carbon fiber manufacturing.

Original languageEnglish
Article number8716511
Pages (from-to)2730-2737
Number of pages8
JournalIEEE Robotics and Automation Letters
Issue number3
Publication statusPublished - 2019 Jul

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence


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