Ultraprecision aspheric cutting process using a monocrystalline diamond tool is widely used in the manufacturing process of the optical components and their molds/dies. Plastic lenses are molded by the injection molding using an amorphous electroless Ni-P plated molds/dies and decreasing of the lens surface roughness is required. Generally, the oblique cutting is one of the methods to decrease the cutting force and the burr, and to decrease the surface roughness. In this study, the oblique cutting was applied to aspheric mold materials to decrease the surface roughness. In the experiments, plunge cut by oblique cutting was applied to the electroless Ni-P plated molds, aluminum, oxygen free copper, and brass to clarify the burr behaviors. Finally, flat surface was diamond-turned by changing the oblique angle of the tool, the cut surface was evaluated, and the effects of the oblique angle to the surface roughness were evaluated.

The visual tracking problem can be solved by performing template matching on each frame, which can be treated as a dynamic optimization problem. On the other hand, Charged Particle Swarm Optimization (CPSO) is a PSO variant for dynamic optimization, which maintains swarm diversity by introducing charged particles and repulsion vectors into the velocity update step. CPSO uses a unified pre-determined amount of charge for all particles, which is difficult to deal with various moves of the optimal solution. Instead of a unified value, in this paper, we propose introducing diverse charged particles into CPSO, referred to as Multi-swarm CPSO (MCPSO). Specifically, MCPSO employs multiple sub-swarms and assigns different amounts of charge to particles in each sub-swarm, which leads to diverse moving characteristics of particles. Moreover, each particle is limited to receiving repulsion force only from other particles in the same sub-swarm, which results in various sub-swarms with different behaviors. The optimization performance of MCPSO is assessed by a numerical experiment using five benchmark functions compared with standard PSO and CPSO. In addition, the effectiveness of MCPSO for visual tracking using template matching is verified by a comparison experiment with nine synthetic sequences.

Electrochemical machining (ECM) technology has witnessed several research and development breakthroughs since its introduction in early 1900s. The ECM process serves as one of the key production processes in aerospace, die-moulds, tooling and automotive industries. Over time, the demands on precision have increased and this has resulted in several developments focusing specifically on improving precision in ECM processing. However, the existing review papers have not extensively focused on the methods and parameters controlling precision in the ECM process. Therefore, this article reviews the aspects of precision of ECM processes. This article will serve as a quick-read reference for researchers/engineers looking for precision ECM. An attempt is made to answer the main question posed by industry and academia “How can we control precision in the ECM process”?