4.5 Article

An experimental investigation of the surface roughness of parts produced by LOM process

Journal

RAPID PROTOTYPING JOURNAL
Volume 13, Issue 1, Pages 17-22

Publisher

EMERALD GROUP PUBLISHING LIMITED
DOI: 10.1108/13552540710719172

Keywords

surface texture; Taguchi methods; optimization techniques; modelling

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Purpose - To investigate the influence of different process parameters of the laminated object manufacturing (LOM) process on the roughness of vertical surfaces along Z-axis on ZX-plane of parts produced by LOM. Design/methodology/approach - The process parameters tested were layer thickness, heater temperature, platform retract, heater speed, laser speed, feeder speed and platform speed. A typical test part has been used, and matrix experiments were carried out based on Taguchi design. Optimal process parameter values were identified and finally, a regression model was applied onto the experimental results, and compared with bibliography models, using arbitrary experiments. Findings - The statistical analysis of the experimental results showed that the surface roughness depends mainly on the heater temperature, layer thickness, and laser speed. Moreover, the regression model gave good predictions when heater temperature values were within the initial experimental area and inaccurate predictions when heater temperature takes the value 200 degrees C. Research limitations/implications - Future work should involve extensive matrix experiments using parameters such as dimensions of test part (X(max), Y(max), Z(max)) hatch spacing in X and Y directions, and delay time between sequential layers. Practical implications - Using the extracted regression model, vertical surface roughness can be predicted and selected proprietary process parameter values. This means minimization of post processing time, easier disengagement between supporting frame and part, easier decubing, process optimization, and less finishing. Originality/value - This methodology could be easily applied on different materials and initial conditions for optimisation of LOM processes.

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