產線離子濃度之線上分析系統

Project: Government MinistryMinistry of Science and Technology

Project Details

Description

The ion concentration on the production line of many manufacturing industries has an impact on product quality or wastewater treatment, so the ion concentration on the production line must be quickly sensed. However, currently, the main methods for detecting ion concentration in liquids on production lines are mostly manual detection. Due to not only no real-time detection system on the production line but also the too long chemical pretreatment, it resulted in unstable quality and slow feedback control, affecting the production fluency. To achieve smart manufacturing, this research developed the production online analytic system of ion concentrations (copper, nickel, iron) by integrating optical detection technology, IoT system, cloud construction, and AI algorithm. Through the anti-acid and alkali, simple, developed fiber optic probe, without any labor, pre-processing preparation, time and material cost, the UV absorption spectrum of metal ions could be obtained in real time. Consequently, the main characteristic and non-characteristic bands can be dynamically analyzed through AI algorithm. With the dynamic analyzing the component concentration of the electroplating solution during the electroplating process (such as nickel ion: 10~100000 ppm, copper ion: 5~5000 ppm, iron ion: 5-100000 ppm, boric acid: 7000~150000 ppm), it is use to determine the replacement of electroplating solution. Besides, the cloud platform is beneficial for direct feedback or control of data visualization. The platform linked to the production line could achieve rapid and multi-smart platform monitoring and control of multi-slot dynamics. Eventually, to improving quality and efficiency, reducing the impact on the environment, it also could enhance the safety of production line personnel. In the long-term, the overall industrial competitiveness and drive economic growth increase.
StatusFinished
Effective start/end date2020/06/012021/05/31

Keywords

  • ion concentration
  • IoT
  • AI
  • UV
  • rapid

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