Parametric analysis of wear behaviour on fused deposition modelling build parts

Swayam Bikash Mishra, Rashmi Pattnaik and Siba Sankar Mahapatra

International Journal of Productivity and Quality Management, 2017, vol. 21, issue 3, 375-391

Abstract: Fused deposition modelling (FDM) is one of the proficient technologies among all rapid prototyping (RP) processes due to its capability to build durable end-use parts with reasonable mechanical strength. FDM process has the ability to develop 3D complex geometry accurately with less time and material waste as compared to other RP processes. However, mechanical wear unfavourably affects the durability and lifespan of the FDM build part when used as an end-use part. It has been observed that few important FDM process parameters significantly determine the mechanical strength, wear resistance and surface roughness of build parts. Since wear is an important phenomenon influencing functionality of a part, effect of six FDM build parameters viz. contour number, layer thickness, raster width, part orientation, raster angle and air gap on sliding wear of the specimen is experimentally investigated in this research work. Using analysis of variance (ANOVA), effect of each process parameter on wear of the build specimen is analysed. From the scanning electron microscope (SEM) images, wear surfaces and internal structures of the specimens are evaluated. Finally, a model based on least square support vector machine (LSSVM) technique is proposed to predict the wear performance of the FDM build parts.

Keywords: additive manufacturing; fused depositing modelling; rapid prototyping; analysis of variance; ANOVA; response surface methodology; RSM; least square support vector machine. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=84461 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:21:y:2017:i:3:p:375-391

Access Statistics for this article

More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().