Detection system for cover tape offset in tap and reel process with predictive analysis

Rosli, Muhammad Irfan (2024) Detection system for cover tape offset in tap and reel process with predictive analysis. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

This thesis presents a comprehensive study on the detection of cover tape offset or misalignment during the tape and reel process, crucial for packaging electronic components into individual pockets of carrier tape. The research aims to develop an efficient system utilizing the Raspberry Pi Camera Module for detecting and analysing cover tape misalignment. The methodology involves integrating the Raspberry Pi Camera Module with a microcontroller to capture and process images of the carrier tape, employing image processing techniques for misalignment detection. The resulting data is displayed in a user-friendly dashboard format using Node-RED. Additionally, the data is analysed in MATLAB for predictive analysis. The findings of this research, including the analysis of training results, demonstrate the successful implementation of a reliable cover tape misalignment detection system. Notably, Bayesian Regularization (BR) training algorithm outperformed Scaled Conjugate Gradient (SCG) training algorithm for cover tape offset’s predictive analysis, exhibiting lower Mean Squared Error (MSE) with 0.0015874 for BR compared to 0.0017839 for SCG, consistently lower Mean Absolute Error values, stronger linear correlations, and superior overall performance, emphasizing its effectiveness for accurate predictions.

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