scholarly journals Prediction and analysis of surface roughness in selective inhibition sintered high-density polyethylene parts: A parametric approach using response surface methodology–grey relational analysis

2018 ◽  
Vol 10 (12) ◽  
pp. 168781401882099 ◽  
Author(s):  
D Rajamani ◽  
Aiman Ziout ◽  
E Balasubramanian ◽  
R Velu ◽  
Salunkhe Sachin ◽  
...  
Keyword(s):  
Layer Thickness ◽  
Surface Quality ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
High Density Polyethylene ◽  
Selective Inhibition ◽  
Optimal Process ◽  
Relational Analysis ◽  
Selective Inhibition Sintering ◽  
Grey Relational

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/mm2, 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.

Mechanical Behaviour of Polylactic Acid Parts Fabricated via Material Extrusion Process: A Taguchi-Grey Relational Analysis Approach

2020 ◽  
Vol 46 ◽  
pp. 32-44
Author(s):  
Peter Kayode Farayibi ◽  
Babatunde Olamide Omiyale
Keyword(s):  
Mechanical Properties ◽  
Tensile Strength ◽  
Impact Strength ◽  
Layer Thickness ◽  
Polylactic Acid ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Extrusion Temperature ◽  
Relational Analysis ◽  
Grey Relational

The acceptance and application of functional parts produced via additive manufacturing technologies is faced with challenges of poor surface finish, dimensional accuracy and mechanical properties among other which is mostly dependent on process parameters employed. In this study, the effect of infill density, layer thickness and extrusion temperature on mechanical properties of polylactic acid (PLA) part manufactured using fused deposition modelling process was investigated to obtain optimum process parameters to achieve the best properties. Solid cuboid bars were produced from which tensile, impact and hardness test specimens were obtained. A statistical approach based on Taguchi design of experiment was employed with process parameters varied and grey relational analysis coupled with principal component analysis was employed to obtain the unified optimum parameter. The single optimisation results showed that 50% infill density, 220°C extrusion temperature and 0.4 mm layer thickness resulted in best tensile strength; 30% density, 210°C temperature and 0.2 mm layer thickness is required to achieve the best impact strength, while 50% density, 215°C temperature and 0.3 mm thickness is required for highest hardness. The multi-response optimisation indicated that for the best of all the three properties to be achieved at once in a PLA built part, 50% infill density, 220°C extrusion temperature and 0.3 mm is required which yielded tensile strength of 30.02±2.15 MPa, impact strength 4.20±0.12 J and hardness of 76.80±0.38 BHN.

scholarly journals Analysis and optimization of laser drilling process during machining of AISI 303 material using grey relational analysis approach

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
V. Chengal Reddy ◽  
Thota Keerthi ◽  
T. Nishkala ◽  
G. Maruthi Prasad Yadav
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Pulse Frequency ◽  
Laser Drilling ◽  
Simultaneous Optimization ◽  
Fibre Laser ◽  
Drilling Process ◽  
Relational Analysis ◽  
Grey Relational

AbstractSurface roughness and heat-affected zone (HAZ) are the important features which influence the performance of the laser-drilled products. Understanding the influence of laser process parameters on these responses and identifying the cutting conditions for simultaneous optimization of these responses are a primary requirement in order to improve the laser drilling performance. Nevertheless, no such contribution has been made in the literature during laser drilling of AISI 303 material. The aim of the present work is to optimize the surface roughness (Ra) and HAZ in fibre laser drilling of AISI 303 material using Taguchi-based grey relational analysis (GRA). From the GRA methodology, the recommended optimum combination of process parameters is flushing pressure at 30 Pa, laser power at 2000 W and pulse frequency at 1500 Hz for simultaneous optimization of Ra and HAZ, respectively. From analysis of variance, the pulse frequency is identified as the most influenced process parameters on laser drilling process performance.

Multi-Response Optimization of Wire-EDM Process Parameters of Titanium Alloy Using Taguchi Method and Grey Relational Analysis

2015 ◽  
Vol 772 ◽  
pp. 245-249
Author(s):  
A. Ramamurthy ◽  
R. Sivaramakrishnan ◽  
S. Venugopal ◽  
T. Muthuramalingam
Keyword(s):  
Titanium Alloy ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Wire Edm ◽  
Relational Analysis ◽  
Response Optimization ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

It is very important and complexity to find the optimum values of wire EDM process parameters and contribution of each parameter to attain the better performance characteristics. In this study, an attempt has been made to optimize those parameters while machining the titanium alloy. Since the process involves more one than one response parameter, it is essential to carry out the multi-response optimization methodology .The experiments have been conducted with different levels of input factors such as pulse on time,pulse off time and wire tension based on Taguchi L9 orthogonal table.Wire EDM optimal process parameter has been identified using grey relational analysis and significant parameter has been determined by analysis of variance. Experimental results have indicated that the multi-response characteristic such as material removal rate and surface roughness can be improved effectively through grey relational analysis.

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