Taguchi’s Approach: Design optimization of process parameters in selective inhibition sintering

2018 ◽  
Vol 5 (2) ◽  
pp. 4778-4786 ◽  
Author(s):  
Sagar M. Baligidad ◽  
U. Chandrasekhar ◽  
K. Elangovan ◽  
S. Shankar
Keyword(s):  
Design Optimization ◽  
Process Parameters ◽  
Selective Inhibition ◽  
Selective Inhibition Sintering ◽  
Optimization Of Process Parameters

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.

Optimization of Process Parameters for Production of Pectinase using Bacillus Subtilis MF447840.1

2019 ◽  
Vol 13 (1) ◽  
pp. 69-73 ◽  
Author(s):  
Ram Balak Mahto ◽  
Mukesh Yadav ◽  
Soumya Sasmal ◽  
Biswnath Bhunia
Keyword(s):  
Bacillus Subtilis ◽  
Process Parameters ◽  
Volume Ratio ◽  
Optimum Process ◽  
Agitation Rate ◽  
Fermentation Condition ◽  
Optimization Of Process Parameters ◽  
Food And Beverage ◽  
Pectinase Production ◽  
Sterile Product

Background: Pectinase enzyme has immense industrial prospects in the food and beverage industries. </P><P> Objective: In our investigation, we find out the optimum process parameters suitable for better pectinase generation by Bacillus subtilis MF447840.1 using submerged fermentation. </P><P> Method: 2% (OD600 nm = 0.2) of pure Bacillus subtilis MF447840.1 bacterial culture was inoculated in sterile product production media. The production media components used for this study were 1 g/l of pectin, 2 g/l of (NH4)2SO4, 1 g/l of NaCl, 0.25 g/l of K2HPO4, 0.25 g/l of KH2PO4 and 1 g/l of MgSO4 for pectinase generation. We reviewed all recent patents on pectinase production and utilization. The various process parameters were observed by changing one variable time method. </P><P> Results: The optimum fermentation condition of different parameters was noticed to be 5% inoculums, 25% volume ratio, temperature (37°C), pH (7.4) and agitation rate (120 rpm) following 4 days incubation. </P><P> Conclusion: Maximum pectinase generation was noticed as 345 ± 12.35 U following 4 days incubation.

Recent trends in approaches for optimization of process parameters for the production of microbial cellulase from wastes

2021 ◽  
Author(s):  
Dibyajit Lahiri ◽  
Moupriya Nag ◽  
Dipro Mukherjee ◽  
Sayantani Garai ◽  
Ritwik Banerjee ◽  
...  
Keyword(s):  
Process Parameters ◽  
Optimization Of Process Parameters ◽  
Recent Trends
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