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The flame was always ignited at low velocities (approximately 33 cmVs) with an alcohol burner. The field was then turned on and the methane and air flow rates increased simultaneously up to the total velocity at which the blowoff limits were to be determined. Blowoff points were obtained by maintaining a constant flow of either the methane or air, while varying the other flow until the flame left the burner port.By decreasing the gas flow rates, the lower blowoff limits were obtained, with and without electric fields. The upper blowoff points could not be obtained by increasing the gas flow rates because the flame picked up more air from the open surroundings at higher rates. As a result, another set of lower blowoff limits were obtained by keeping the gas flow rate constant and increasing the airflow rate. Figure 2 represents the configuration for the second geometry. A longitudinal electric field was obtained by placing an aluminum foil ring around the glass tube for one electrode and making the brass burner the other electrode. Following the procedures of the first geometry, lower blowoff limits were obtained, with and without electric fields.

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Rapid prototyping turns a three‐dimensional CAD drawing into an actual part that can be tested for form, fit, and function. Therefore, accuracy of the prototype is important. The goal of this research was to improve in‐plane dimensional accuracy for the Stratasys FDM 1650 rapid prototyping machine. The CHRISTMAS‐TREE™ test procedure developed by 3D Systems, Inc., was used to arrive at a new shrinkage compensation factor (SCF) for the Stratasys machine. It was found that an SCF of 1.010 will produce a 53% reduction in mean error of the dimensions. More test procedures could be implemented to further refine accuracy. © 1999 John Wiley & Sons, Inc. Comput Appl Eng Educ 7: 186–195, 1999

The objective of this research was to find the best combination of factor levels that minimized the surface roughness of prototyped samples from Fused Deposition Modeling (FDM). Two sets of experiments were conducted for that purpose; a two-level three-factor full factorial experiment and a three-level two-factor full factorial experiment. The parameters chosen for this research were model temperature, layer thickness and part fill style. The results obtained from both experiments were compared and analyzed in order to determine the best combination of factors that minimized the surface roughness of the specimens. The significant factors, their interactions and the optimum setting are presented in this paper

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3D Printing (3DP) is an additive manufacturing technology used to rapidly build parts that are designed using 3D modeling software. 3DP builds a part by adding one layer of the working material at a time until the process is complete. One main concern with 3D printed samples is the high levels of surface roughness, which can result in the rejection of parts by many precision manufacturing companies. The objective of this research is to use the Design of Experiment (DOE) to analyze which factors influence the surface roughness of the part built from a 3D printer. In this research, a two-level, three-factor, full factorial design of experiment is used to select the best combination of factors that will minimize the surface roughness of parts made from Polylactic Acid (PLA) materials. The selected factors are printing orientation, nozzle diameter, and infill percentage. Based on the preliminary result, it is determined all the factors and their two-factor interactions are shown to significantly affect the surface roughness. However, it is shown that the nozzle diameter has had the most effect on surface roughness. These results will be explained in terms of the optical microscopy of the processed PLA test specimens.