Process optimization of additive manufacturing technology: A case evaluation for a manufactured railcar accessory.
Daniyan, Ilesanmi Mpofu, Khumbulani Oyesola, Moses Daniyan, Lanre
Daniyan, Ilesanmi
Mpofu, Khumbulani
Oyesola, Moses
Daniyan, Lanre
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Abstract
The Additive Manufacturing (AM) technology of producing materials layers upon layers to make objects from a 3D model data is a manufacturing process which eliminates the use of tools and fixtures. It is highly flexible to design modifications and can reduce material wastage during manufacturing operations. In this study, the process optimization of a 3D printer for manufacturing the accessory of a railcar was carried out. The Response Surface Methodology (RSM) was used for the Design of Experiment (DoE) which consists of independent process parameters in the following ranges: scan speed (50-20 mm/sec), nozzle diameter (0.1-1.0 mm) thickness of layer (0.10-0.50 mm) and bed temperature (60-200℃). Taking the surface roughness as the response of the designed experiments, the four factors were varied over 2 levels and the statistical analysis of the results obtained was used for obtaining a predictive model which correlates the surface roughness of the plastic knob produced as a function of the independent process parameters. The results obtained indicate that the quality of the materials produced, which is a function of the finish requirement, depends on the print quality and the independent process parameters and vice versa. In addition, the rate at which the material run off the nozzle, which is a function of the manufacturing cycle time, is inversely proportional to the diameter of the nozzle. It is envisaged that the findings of this work will assist in the process design for component manufacturing using the additive manufacturing technology.
Description
20th CIRP Conference on Electro Physical and Chemical Machining.
Date
2020-01-01
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Elsevier
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Keywords
AM, Predictive Model, Process Parameters, RSM, Surface Roughness