Papers by Keyword: Hardened Material

Abstract: In order to ascertain the superior characteristics of PCBN tool for hardened material machining, to promote the cutting performance and efficiency of a mold manufacturing, to investigate the wear mechanism of the cutting tool, and to investigate the dimensional accuracy and surface finish of the machined molds, SKD11 die steel and the polycrystalline cubic boron nitride are used as the workpiece and tool materials, respectively, in this study for turning experiments. After some proper surface layers removed from the workpiece in the experiment, the tool wear was measured through the toolmaker’s microscope and the roughness of the machined surface was measured by the roughness measuring instruments. So that, the associated sampling data prepared for training pattern of a neural network can be obtained. Besides, the noise-mediator was used to detect cutting noise during each surface layer removal for the cutting performance judgment in the machining processes additionally. An assessment model of cutting process is thus developed using a neural network system if the reliable and sufficient data is taken from the experiments. Based on the developed neural network, the complicated relationships between the cutting parameters (cutting speed, depth of cut and feed rate) and the cutting performance (surface roughness, tool wear and cutting temperature) can be clearly clarified. The best surface roughness of 0.29μm Ra is obtained from these experiments under the cutting conditions of d =0.2mm, f =0.05mm/rev and V=120m/min. This surface quality is equivalent to the manufacturing process of chemical-mechanical polishing (CMP), and the surface roughness of 0.2~0.5μm Ra may be attained by CMP. The CMP is always applied to high precision surface processing such as the valve piping and connector components in semiconductor/LED manufacturing.

Abstract: To enhance the fatigue resistance of mechanical components, different surface treatment processes are often applied to put the near surface layer into compression. Surface treatment processes are typically associated with deformation and work-hardening of the material. When applying x-ray diffraction techniques to the characterization of such surfaces, the work-hardening will cause the x-ray diffraction peak width to increase. When peak widths reach high values, the peak tail may extend beyond the active area or window of the multichannel x-ray detector, in which case the peak is truncated. Subsequent analytical treatment of broad diffraction peaks is troublesome and advanced numerical methods are required to accurately determine the peak position. The following work indicates that when a wider detector is used it is possible to collect the full, non-truncated peak, determine the peak position with a high level of confidence and subsequently, to calculate the residual stress with much improved repeatability and reproducibility.