Abstract
The increasing complexity of modern manufacturing systems demands advanced decision support app; iDSS-ProLean, that can process vast amounts of real-time data for optimal performance. This paper introduces a modular sensor architecture aimed at enhancing decision support systems (DSS) revolving a manufacturing environment through the seamless interchange of IoT data. The proposed architecture enables flexible integration of multiple sensor types to capture critical operational parameters, such as cycle time and total processing time, in a semiconductor production line. By modularizing sensor configurations, the system ensures the adaptability, allowing it to respond dynamically to changing production requirements. The interchangeability of sensors further supports the system's ability to collect data from diverse sources, facilitating comprehensive data analysis for an informed decision-making. Through integration with a cloud-based DSS, this architecture provides real-time minitoring into production efficiency, resource allocation, and process optimization. The paper demonstrates the utility of this approach based on the semiconductor manufacturing setting, highlighting its potential to optimize lean manufacturing processes through DSS, improving operational efficiency via the data-driven decision-making.
