Paper Contents
Abstract
QMS In the rapidly evolving landscape of smartphone manufacturing, ensuring high-quality production standards is Paramount. This paper presents an intelligent quality management system (IQMS) that leverages linear regression analysis to Enhance quality control in smartphone assembly lines. The proposed system integrates real-time data acquisition from various stages Of the assembly process, including component fitting, soldering, and testing. By employing linear regression, we identify critical Quality determinants and predict potential defects based on historical data patterns. The models predictive capabilities enable Proactive decision-making, allowing for timely interventions and reducing the incidence of defective products. Our results indicate A significant improvement in production quality metrics, showcasing the effectiveness of data-driven approaches in quality Management. This IQMS not only streamlines the manufacturing process but also aligns with industry 4.0 principles, promoting Efficiency and sustainability in smartphone production. The findings highlight the potential for linear regression as a powerful tool For quality assurance in manufacturing environments, paving the way for future research and advancements in intelligent quality Systems.
Copyright
Copyright © 2024 S. Nikhitha. This is an open access article distributed under the Creative Commons Attribution License.
