Development of a Smart Mechanized Kuih Ros Production System with Integrated Yield Monitoring and Process Optimization
Abstract
The traditional production of Kuih Ros, a deep-fried Southeast Asian delicacy, is predominantly manual, resulting in inconsistent product quality, low production efficiency, and significant yield variability. In response to increasing demand for standardized traditional foods and the need for food manufacturing modernization, this study proposes the development of a smart mechanized Kuih Ros production system integrated with real-time yield monitoring and process optimization capabilities. The research focuses on designing an automated forming-frying mechanism, embedding sensor-based yield tracking, and implementing a data-driven control framework to enhance production consistency and operational efficiency.
The system architecture combines mechanical automation with IoT-enabled monitoring modules that capture temperature stability, frying time, batter consistency, and output yield rate. Inspired by innovation frameworks in food product development (Guiné et al., 2016), the system is designed to address consumer demand for quality consistency while preserving traditional food identity. The mechanization approach aligns with broader agricultural and food processing modernization trends highlighted in prior mechanization studies (Azman & Ruwaida, 2016; Folaranmi, 2014).
A hybrid optimization model is introduced to improve frying efficiency and reduce material wastage through adaptive feedback control. Results from simulated operational modeling indicate improved yield efficiency, reduced production variability, and enhanced scalability. The proposed system demonstrates strong potential for small-to-medium food enterprises seeking industrial transformation of traditional snack production.
Overall, the study contributes a novel integration of mechanical engineering, food processing automation, and smart monitoring systems for traditional food manufacturing modernization.
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