PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

This study presents iDSS-ProLean, an IoT-enabled Decision Support System (DSS) developed to enhance line balancing in semiconductor production. Traditional methods lack real-time adaptability, while iDSS-ProLean integrates sensor-based data acquisition, Firebase cloud analytics, and a mobile app to support responsive, data-driven decisions. The system architecture includes ESP32 modules, multiple sensors, cloud processing, and an Android interface for the operation feedback. A feasibility study was conducted using 60 production runs, where Line Balancing Efficiency (LBE) served as the main performance metric. Paired t-tests revealed p-values above 0.05 and t-values near zero, indicating consistent data transmission and system stability. These results affirm the reliability of the mobile DSS and its real-time performance under varying production conditions. The study demonstrates how integrating Lean Manufacturing (LM) tools with IoT technologies enables dynamic line optimisation. It's proven that LBE is highly correlated with NoM (0.96), TPT (0.97), and CT (0.93), confirming that machine count, processing time, and cycle time strongly influence LBE. Overall, the IDSS-ProLean framework proves to be an effective and adaptive decision support tool for LM applications, showcasing the value of IoT-enabled models in replacing static, time-consuming methods with real-time, intelligent systems.