Characterization and recognition of particles for improving cleanability in automotive production

The complicated systems for casting, anodizing, machining (drilling, milling, turning), high-pressure water jet (HPWJ) deburring, and brushing processes create many different kinds of particles: burr, cast and chip. These particles lodge inside the transmission, engine and crankshaft, and then damage the functions of these components, posing risks to drivers. Many researchers have endeavored to minimize these negative effects without clear understanding of the main sources. This investigation aims at clear recognition of these problems and suggests solutions to minimize or remove each kind of particle with high reliability based on experimental databases. By understanding the formation mechanism of each particle, a particle classification algorithm is developed and verified by comparison between the results from simulation and experiment. This research contributes to building a classification algorithm for specific parts like transmissions and engines by suggesting the source of each particle which is very important in cleanability.