Detectiverse: Advancing Supply Chain Efficiencywith Ai- Enhanced Screw Counting
Aaron Sam A. S., Shanmuga Pradeepan R., Sobana R. S., S. Rathnamala, A. Karthick Kumar, DOI : 10.37591
[This article belongs to Journal of Image Processing & Pattern Recognition Progress(joipprp)]
Keywords
Computer Vision, Image Processing, Object detection, pre-trained models, Screw Counting
Abstract
In the manufacturing industry, accurate screw counting is crucial for effective inventory management and quality control. Manual counting processes are prone to errors and lack the ability to identify the origin of missing screws. To address this challenge, we propose an automated screw counting system implemented at Indo Metal Tech in Ambattur, Chennai. Using sophisticated image processing and machine learning algorithms, the system identifies and enumerates screws in trays captured by cameras. The algorithm incorporates user- triggered actions, real-time feedback, and user verification, ensuring accuracy and adaptability to changing manufacturing conditions. This novel method not only improves productivity and precision but also lays the groundwork for cooperative manufacturing methodologies.
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