Robust and fast part traceability in a production chain exploiting inherent, individual surface patterns

Abstract

Abstract Traceability of single parts is essential in automated manufacturing, especially considering recent developments in Industry 4.0 or Smart Manufacturing. In some cases, however, conventional traceability methods, e.g. barcode, DMC or RFID, are not sufficient to track individual components through their entire production chain. One solution is the exploitation of an object’s inherent, individual surface patterns. This work demonstrates label-/tag-free traceability of approx. 1000 components in a molded interconnect device (MID) production chain. The parts’ surface patterns are photographed several times along the MID production chain. Based on the captured images nearly 3300 successful identification processes were performed without any failure. Using a hash algorithm to compress the relevant data of the surface pattern images reduces the required disk space and the runtime significantly. Since the results demonstrate the robustness against surface alterations, this work gives the proof of concept regarding to a method for fast label-/tag-free part tracking that is applicable in an industrial production line.