(untitled) (International Journal of Engineering and Computer Science, 2025)
This paper is motivated by the fact that Effective resource allocation is a vital factor in optimizing production processes in the paint manufacturing industry. This project aim to apply the Hungarian Algorithm in minimizing production time and costs by optimizing worker-task assignments and machine use. The methodologies used were the combination of structured system analysis and design Methodology (SSADM) with simple calculations via the Hungarian Algorithm, as the most dominated technique for resolving assignment problems, it is used to allocate workers to specific tasks based on skill levels, efficiency, and workload balance. The researcher modelled the assignment problem by describing cost matrices using the parameters such as worker proficiency, task complexity, and production deadlines. Putting the Algorithm into use, the best assignment of workers on tasks is determined, safeguarding minimal idle time and improved efficacy in the production of paint. Additionally, the algorithm is extended to machine allocation, where different production stages such as mixing, grinding, and packaging are assigned to accessible machines based on their ability and operational efficacy. An expected results gotten shows that the application of the Hungarian Algorithm meaningfully improves productivity by dropping delays and proper resource utilization. Thus integrating this algorithm into paint production can lead to better workforce management, reduced operational costs, and higher output adeptness.