Optimization algorithm for indivisible products to improve the packaging process in multi-head batch weighers

The utilization of multi-head packaging systems improves packages production processes, minimizing margins of error in their content. This paper proposes an exact enumerative algorithm for packaging indivisible products using multi-head batch weighers. The optimization algorithm and its translation into programming language are presented. Validation experiments involved calculating process variability measures and conducting an experimental analysis with real data. The results indicate that adjusting the label’s target weight value and considering the probability distribution of process data can significantly reduce variability. This approach minimizes overweight packages while enhancing productivity and overall process efficiency compared to random packaging methods. Additionally, it was observed that the number of hoppers in the weigher does not influence process variability when only a few hoppers are used during packaging. Consequently, machines with fewer hoppers can reduce both acquisition and operational costs. In summary, the proposed enumerative algorithm significantly improves operating conditions and ensures product savings.