Predictive modelling of surface roughness in fused deposition modelling using data fusion

2018 ◽  
Vol 57 (12) ◽  
pp. 3992-4006 ◽  
Author(s):  
Dazhong Wu ◽  
Yupeng Wei ◽  
Janis Terpenny
Keyword(s):  
Surface Roughness ◽  
Data Fusion ◽  
Predictive Modelling ◽  
Fused Deposition Modelling ◽  
Fused Deposition ◽  
Using Data

Effect of cold vapour treatment on geometric accuracy of fused deposition modelling parts

2017 ◽  
Vol 23 (6) ◽  
pp. 1226-1236 ◽  
Author(s):  
Ashu Garg ◽  
Anirban Bhattacharya ◽  
Ajay Batish
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Fused Deposition Modelling ◽  
Curved Surfaces ◽  
Geometric Accuracy ◽  
Content Type ◽  
Fused Deposition ◽  
Cold Vapour ◽  
Side Face ◽  
Functional Components

Purpose The purpose of this paper is to investigate the influence of low-cost chemical vapour treatment process on geometric accuracy and surface roughness of different curved and freeform surfaces of fused deposition modelling (FDM) specimens build at different part building orientations. Design/methodology/approach Parts with different primitive and curved surfaces are designed and modelled to build at three different part orientations along X orientation (vertical position resting on side face), Y orientation (horizontal position resting on base) and Z orientation (upright position). Later, the parts are post-processed by cold vapours of acetone. Geometric accuracy and surface roughness are measured both before and after the chemical treatment to investigate the change in geometric accuracy, surface roughness of FDM parts. Findings The results indicate that surface roughness is reduced immensely after cold vapour treatment with minimum variation in geometric accuracy of parts. Parts build vertically over its side face (X orientation) provides the overall better surface finish and geometric accuracy. Originality/value The present study provides an approach of post-built treatment for FDM parts and observes a significant improvement in surface finish of the components. The present approach of post-built treatment can be adopted to enhance the surface quality as well as to achieve desired geometric accuracy for different primitive, freeform/curved surfaces of FDM samples suitable for functional components as well as prototypes.

A Decision-Level Data Fusion Approach to Surface Roughness Prediction

2019 ◽  
Author(s):  
Yupeng Wei ◽  
Dazhong Wu ◽  
Janis Terpenny
Keyword(s):  
Surface Roughness ◽  
Data Fusion ◽  
Process Monitoring ◽  
Predictive Models ◽  
Sensor Data ◽  
Fused Deposition ◽  
Decision Level ◽  
Level Data ◽  
Fusion Approach

Abstract To improve the quality of additively manufactured parts, it is crucial to develop real-time process monitoring systems and data-driven predictive models. While various sensor- and image-based process monitoring methods have been developed to improve the quality of additively manufactured parts, very limited research has been conducted to predict surface roughness. To fill this gap, this paper presents a decision-level data fusion approach to predicting surface roughness in the fused deposition modeling (FDM) process. The predictive models are trained by the random forests method using multiple sensor signals. A decision-level data fusion method is introduced to integrate sensor data sources. Experimental results have shown that the decision-level data fusion approach can predict surface roughness in FDM with high accuracy.

Parametric Study on Surface Roughness of Metallized Parts Manufactured by Additive Manufacturing

2019 ◽  
Vol 821 ◽  
pp. 137-143 ◽  
Author(s):  
Pavan Kumar Gurrala ◽  
Brijesh Tripathi
Keyword(s):  
Surface Roughness ◽  
Additive Manufacturing ◽  
Acrylonitrile Butadiene Styrene ◽  
Etching Time ◽  
Fused Deposition Modelling ◽  
Technological Evolution ◽  
Fused Deposition ◽  
Copper Electroplating ◽  
Optimal Value ◽  
Butadiene Styrene

In the current technological evolution, additive manufacturing is taking a lead role in manufacturing of components for both prototyping as well as finished products. Metallization of the polymer parts has high potential to add value in-terms of metallic luster, improved strength, long shelf-life and better radiation resistance. Standard acid copper plating process has been adopted for deposition of copper on polymer parts manufactured by fused deposition modelling (FDM) technique. The parameters namely the etching time, voltage and the surface finish of the manufactured FDM parts are studied for their influence on the surface quality. Experiments have been designed using design of experiments strategy. Experiments have been conducted and surface roughness has been measured. Influence of each of the three parameters has been discussed in detail. For the reported process the optimal value of etching time of Acrylonitrile Butadiene Styrene (ABS) has been found in the range of 30 to 60 minutes along with applied voltage in the range of 1.5 to 2.5 Volts for copper electroplating.

scholarly journals Mechanical and Physical Properties of Recycled-Carbon-Fiber-Reinforced Polylactide Fused Deposition Modelling Filament

Materials ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 190
Author(s):  
Nur’ain Wahidah Ya Omar ◽  
Norshah Aizat Shuaib ◽  
Mohd Haidiezul Jamal Ab Hadi ◽  
Azwan Iskandar Azmi ◽  
Muhamad Nur Misbah
Keyword(s):  
Surface Roughness ◽  
Carbon Fiber ◽  
Physical Properties ◽  
Tensile Properties ◽  
Fused Deposition Modelling ◽  
Fiber Reinforced ◽  
Porosity Level ◽  
Fused Deposition ◽  
Mechanical And Physical Properties ◽  
Carbon Fiber Reinforced

Carbon-fiber-reinforced plastic materials have attracted several applications, including the fused deposition modelling (FDM) process. As a cheaper and more environmentally friendly alternative to its virgin counterpart, the use of milled recycled carbon fiber (rCF) has received much attention. The quality of the feed filament is important to avoid filament breakage and clogged nozzles during the FDM printing process. However, information about the effect of material parameters on the mechanical and physical properties of short rCF-reinforced FDM filament is still limited. This paper presents the effect of fiber loading (10 wt%, 20 wt%, and 30 wt%) and fiber size (63 µm, 75 µm, and 150 µm) on the filament’s tensile properties, surface roughness, microstructure, porosity level, density, and water absorptivity. The results show that the addition of 63 µm fibers at 10 wt% loading can enhance filament tensile properties with minimal surface roughness and porosity level. The addition of rCF increased the density and reduced the material’s water intake. This study also indicates a clear trade-off between the optimized properties. Hence, it is recommended that the optimization of rCF should consider the final application of the product. The findings of this study provide a new manufacturing strategy in utilizing milled rCF in potential 3D printing-based applications.

scholarly journals Effects of CNC Machining on Surface Roughness in Fused Deposition Modelling (FDM) Products

Materials ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2608 ◽  
Author(s):  
Mohammadreza Lalegani Dezaki ◽  
Mohd Khairol Anuar Mohd Ariffin ◽  
Mohd Idris Shah Ismail
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
High Surface ◽  
Great Influence ◽  
Cnc Machining ◽  
Numerical Control ◽  
Fused Deposition Modelling ◽  
High Surface Quality ◽  
Complex Products ◽  
Fused Deposition

Fused deposition modelling (FDM) opens new ways across the industries and helps to produce complex products, yielding a prototype or finished product. However, it should be noted that the final products need high surface quality due to their better mechanical properties. The main purpose of this research was to determine the influence of computer numerical control (CNC) machining on the surface quality and identify the average surface roughness (Ra) and average peak to valley height (Rz) when the specimens were printed and machined in various build orientations. In this study, the study samples were printed and machined to investigate the effects of machining on FDM products and generate a surface comparison between the two processes. In particular, the block and complex specimens were printed in different build orientations, whereby other parameters were kept constant to understand the effects of orientation on surface smoothness. As a result, wide-ranging values of Ra and Rz were found in both processes for each profile due to their different features. The Ra values for the block samples, printed samples, and machined samples were 21, 91, and 52, respectively, whereas the Rz values were identical to Ra values in all samples. These results indicated that the horizontal surface roughness yielded the best quality compared to the perpendicular and vertical specimens. Moreover, machining was found to show a great influence on thermoplastics in which the surfaces became smooth in the machined samples. In brief, this research showed that build orientation had a great effect on the surface texture for both processes.

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