Exploring AI/ML approaches for CBR-enabled Knowledge Reuse in Sheet Metal Tooling Development

The sheet metal forming tooling industry is a highly specialized area. However, there seem to be similarities in the tasks executed and in the design solutions. This work has investigated what types of data are involved in the various steps in the design and manufacturing of sheet metal tooling in five different tooling firms. By analyzing these different types of data, the study explores possible avenues for employing AI/ML techniques for CBR-enabled knowledge reuse based on legacy data. The paper concludes that adopting AI/ML in knowledge reuse has the potential to significantly improve efficiency and innovation in tooling design and manufacturing.