Prototyping Method for Developing a Product Barcode Validation System in Manufacturing Industry

Abstract

Manual validation of product barcode labels within industrial manufacturing production lines is highly vulnerable to human errors and completely lacks an automated audit trail system for quality assurance. This study aims to design, implement, and evaluate a specialized desktop-based barcode validation scanning application to eliminate operational labeling risks and ensure absolute data traceability. The Prototyping method was utilized to iteratively develop the application using React.js and Electron.js frameworks, seamlessly integrating hardware components including a 125-kilohertz Radio Frequency Identification reader for authentication security and a barcode scanner connected to a centralized database. This robust integration ensures that all scanning transactions are instantly verified against the master data without experiencing any system latency or connectivity issues. Furthermore, the usability of the developed system was quantitatively evaluated using the standard System Usability Scale approach by involving 35 active respondents directly from the manufacturing quality inspection department. The empirical implementation results demonstrated that the software successfully automated the highly accurate verification of four distinct production label types and comprehensively enforced secure role-based access control. The quantitative usability evaluation yielded an exceptional average score of 80.57, which strategically positions the desktop application within the highly acceptable category with a good performance rating. The absence of complex terminologies and the straightforward navigation flow were key factors contributing to this positive user reception. In conclusion, the developed scanning system effectively eliminates manual verification defects, guarantees operational report data integrity, and offers a highly intuitive interface that minimizes the users' cognitive workload, thereby significantly enhancing quality control standards in the manufacturing environment.