提升營建鋼構場生產智慧化系統之先進開發研究(2/3)

Project Details

Description

Artificial Intelligence (AI) technologies have been brought in order to enrich people’s lives for years. They have also affected most industries and made significant improvement for production. The objectives in the study are to establish (Year 1) the automatic recognition model for coating H-shape steel components, (Year 2) the coating thickness detection and optimal robotic coating path, and (Year 3) the optimal logistical routes for steel component shipping. A wide-ranging literature review in AI applications, pattern recognition, and steel component production provides the outline that constructs the methodology for the study including Convolution Neural Network (CNN), Fuzzy Hyper-Rectangular Composite Neural Networks (FHRCNN), and Self-Organizing feature Map Optimization (SOMO). Through the new facilities that has been completely set up in January 2020 at the Guan-yin (桃園市觀音區) industrial zoom, Taoyuan City, we can have an experimental and practical environment to fully support automatic steel component production by coating recognition, thickness detection, and optimal logistical routes for steel component shipping. The experiments will be conducted in the newly established facilities in order to check if they meet the industrial needs. The anticipated findings will benefit both academic and industrial practitioners by AI applications, cost efficiency, improved quality control, and occupational safety and health.
StatusFinished
Effective start/end date1/06/2131/05/22

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 8 - Decent Work and Economic Growth
  • SDG 11 - Sustainable Cities and Communities
  • SDG 17 - Partnerships for the Goals

Keywords

  • Artificial Intelligence (AI)
  • Automatic recognition model
  • Coating thickness detection
  • Optimal logistical routes
  • Fuzzy Hyper-Rectangular Composite Neural Networks
  • Self-Organizing feature Map Optimization

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