| Much research in Selective Laser Sintering (SLS) process is focused on improving the quality of built parts as well as the system performance, such as process speed. Shrinkage, curling, warpage, and growth (such as bottom surface growth called Bonus-Z) are quality detractors. Curling results in upward warping of the boundaries when the temperature gradient is too large in the process. Bonus-Z primarily refers to undesired downward growth of layers or partial layers. Bonus-Z growth is specifically limited to the initial sintering areas in a layer, i.e., which have not been sintered in a previous layer. Bonus-Z also includes rough surfaces on the bottom layers/regions. Part growth/shrinkage in x and y dimensions has been well studied and software is available for compensation. However, the compensation is limited, because both growth and shrinkage usually depend on specific geometry (shapes) of the layer. The problem is generally more severe when small but close features are present in a layer.; This work studies methods to reduce part curling, Bonus-Z and part shrinkage/growth, and to explore methods to build larger nylon parts within the current SLS stations. The research focuses on software issues to address these problems by developing intelligent scanning techniques, and then determining optimal values of laser parameters (such as laser power, scan step size and scan speed) for different layers and even different regions within the same layer. (In current SLS practice, these parameters are constant during a part build). A new Bonus-Z model has been developed in order to understand the problem and to compensate for bottom growth systematically.; In this dissertation, two kinds of powder, Nylon and TrueForm TM, are targeted for research in developing intelligent laser scanning methods. The goal is to make the SLS process ever better, cheaper, quicker, and more accurate (both in dimensions and geometric tolerances). The study also determines whether nylon parts can be built larger sizes within current SinterStations. |
