基於影像辨識技術的自動化手機殼加工與種類判別系統

Abstract

本研究旨在開發一套基於影像辨識技術的自動化手機殼加工系統，以解決傳統手工檢測與加工方法中因操作人員疲勞、經驗不足或技能限制所導致的生產效率低下及品質不穩定問題。研究目標為提升手機殼加工過程的高精度與高效率，並確保產品品質的一致性與可靠性。 本研究設計了一套多模組協作的自動化生產流程，包括進料感測、外殼種類檢測、標識印刷、孔位加工與最終質量檢查。影像辨識模組使用高分辨率相機與人工智慧演算法進行特徵提取及分類，並透過數位處理單元精準比對加工參數。標識印刷與孔位加工模組則利用高精度氣壓缸與感測器實現即時監控與自動調整，以滿足不同型號手機殼的加工需求。 實驗結果顯示，該系統顯著提升了生產效率與產品品質，減少人為誤差與不良品率，為手機殼全流程自動化生產奠定了技術基礎。未來，本系統可進一步整合客製化生產功能，讓使用者選擇特定材質及設計，並優化進料異常處理機制，進一步提升生產過程的智能化與可靠性。

This study aims to develop an automated smartphone case processing system based on image recognition technology to address the inefficiencies and quality instability associated with traditional manual inspection and processing methods. These issues often arise from operator fatigue, lack of experience, or skill limitations. The research objective is to enhance the precision and efficiency of smartphone case processing while ensuring product quality consistency and reliability. The study designed a multi-module collaborative automated production process, including material sensing, case type detection, label printing, hole processing, and final quality inspection. The image recognition module employs high-resolution cameras and artificial intelligence algorithms for feature extraction and classification, accurately matching processing parameters through a digital processing unit. The label printing and hole processing modules utilize high-precision pneumatic cylinders and sensors for real-time monitoring and automatic adjustments, meeting the processing requirements of different smartphone case models. Experimental results show that the system significantly improves production efficiency and product quality, reducing human errors and defective rates. This lays a technical foundation for fully automated production of smartphone cases. In the future, the system could integrate customized production functionalities, allowing users to select specific materials and designs, as well as optimize abnormal material handling mechanisms to further enhance the intelligence and reliability of the production process.