HICA: A MATLAB-based hierarchical image clustering algorithm for classifying parts suitable for additive and traditional manufacturing technologies

Abstract

This paper presents an image clustering algorithm that classifies parts to be fabricated using traditional and additive manufacturing (AM) technologies. The proposed algorithm is a MATLAB-based software tool that clusters 3D CAD models of parts considering their geometry only. The algorithm can classify image datasets, CAD datasets, and combined datasets that contain both images and CAD models. The software tool reduces the time and effort spent during process selection by offering a preselected set of parts that are more suitable for AM. The software tool is aimed at supporting decision-making for traditional manufacturing companies that consider expanding their production capability by introducing AM processes in their production facilities. The HICA software tool expands the scope of scientific applications in manufacturing process selection by providing an unsupervised approach that does not require data labelling. The tool is made available as a MATLAB function through a permanent link.

Keywords

• MATLAB
• Hierarchical clustering
• Image processing
• Additive manufacturing
• Process selection
• SolidWorks