Resource efficiency is one of the greatest challenges for sustainable manufacturing. Material flow in manufacturing systems directly influences resource efficiency, financial cost and environmental impact. A framework for material flow assessment in manufacturing systems (MFAM) was applied to a complex multi-product manufacturing case study. This supported the identification of options to alter material flow through changes to the product assembly design, to improve overall resource efficiency through eliminating resource intensive changeovers. Alternative assembly designs were examined using a combination of intelligent computation techniques: k-means clustering, genetic algorithm and ant colony algorithm. This provided recommendations balancing improvement potential with extent of process modification impact.