Please login to be able to save your searches and receive alerts for new content matching your search criteria.
The demand for better tools for machining printed circuit boards (PCBs) is increasing due to the extensive usage of these boards in digital electronic products. This paper is aimed at optimizing coating type on micro drills in order to extend their lifetime in PCB machining. First, the tribotests involving micro crystalline diamond (MCD), nano crystalline diamond (NCD) and bare tungsten carbide (WC-Co) against PCBs show that NCD–PCB tribopair exhibits the lowest friction coefficient (0.35) due to the unique nano structure and low surface roughness of NCD films. Thereafter, the dry machining performance of the MCD- and NCD-coated micro drills on PCBs is systematically studied, using diamond-like coating (DLC) and TiAlN-coated micro drills as comparison. The experiments show that the working lives of these micro drills can be ranked as: NCD>TiAlN>DLC>MCD>bare WC-Co. The superior cutting performance of NCD-coated micro drills in terms of the lowest flank wear growth rate, no tool degradation (e.g. chipping, tool tipping) appearance, the best hole quality as well as the lowest feed force may come from the excellent wear resistance, lower friction coefficient against PCB as well as the high adhesive strength on the underneath substrate of NCD films.
This paper discusses commonly used reverse engineering methods to illegally recreate printed circuit board (PCB) designs. A solution using transformative electronics is presented to prevent the discussed reverse engineering methods by obfuscating the design. The transformative electronics solution is employed in a specific application that results in a reverse engineered board to be incorrectly recreated, where the signals would be distorted due to added electromagnetic interference (EMI). The nonconductive vias that are part of the obfuscation would allow the inclusion of EMI generators that would not affect the circuit in an original design but would prevent copied designs from working correctly. A machine learning algorithm is being designed to optimize the placement of the EMI sources in an original PCB.