Advances in Real-Time Data-Driven Scheduling and Optimisation in Dairy Manufacturing: Insights from Smart Yoghurt Production at Kefalos Cheese Pvt Ltd in Zimbabwe

Abstract

This review paper synthesizes recent research and practical developments in real-time data-driven scheduling and optimisation within the dairy manufacturing sector, with a particular focus on smart yoghurt production processes. Emphasis is placed on critical operational parameters such as machine utilisation, changeover times, demand variability, and batch size management and their influence on key production performance indicators. The integration of Industry 4.0 technologies, including IoT sensor networks, OPC UA data acquisition protocols, and advanced simulation- optimisation frameworks built in MATLAB/Simulink, is examined as enabling pillars of adaptive scheduling. Practical case studies from dairy manufacturers worldwide share quantified improvements in production efficiency and schedule robustness. Attention is given to challenges and opportunities for implementing such data-driven scheduling techniques in emerging economies, highlighting the case of Kefalos Cheese Pvt Ltd in Zimbabwe. Gaps for future research and technology adoption are outlined to guide continued advancements in smart dairy manufacturing systems.