Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis. (December 2018)

• Record Type: Journal Article
• Authors: Rajamani, D; Ziout, Aiman; Balasubramanian, E; Velu, R; Sachin, Salunkhe; Mohamed, Hussein
• Is Part Of: Advances in mechanical engineering. Volume 10:Number 12(2018)
• Publication Date: 2018-12
• Subjects: Additive manufacturing -- surface roughness -- selective inhibition sintering -- grey relational analysis -- analysis of variance; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/1687814018820994
• Languages: English
• ISSNs: 1687-8132

Abstract

Selective inhibition sintering (SIS) process intends to produce near-net-shape components through sintering of specific region of powder particles. The prediction of surface quality in SIS parts is a challenging task due to its complex part building mechanism and influence of abundant process parameters. Therefore, this study investigates the key contributing parameters such as layer thickness, heater energy, heater feedrate and printer feedrate on the surface quality characteristics ( Ra, Rz and Rq ) of high-density polyethylene specimens fabricated through selective inhibition sintering process. The SIS system is custom built and experiments are conducted based on four-factor, three-level Box–Behnken design. The empirical models have been developed for predicting the influence of selected parameters on surface quality. The optimal process parameters such as the layer thickness of 0.1 mm, heater energy of 28.48 J/mm 2, heater feedrate of 3.25 mm/s and printer feedrate of 110 mm/min are attained using grey relational multi-criteria decision-making approach. Furthermore, response surface analysis revealed that surface quality of sintered components is influenced significantly with heater energy and heater feedrate, followed by layer thickness. The confirmation experiments based on optimal process variables validate the developed grey relational analysis strategy.