scholarly journals Optimization of Process Parameters during Flow Forming Process and its Verification

Mechanika ◽  
2017 ◽  
Vol 23 (4) ◽  
Author(s):  
Ravi J Bhatt ◽  
Harit K. Raval
Keyword(s):  
Process Parameters ◽  
Forming Process ◽  
Flow Forming ◽  
Optimization Of Process Parameters

Application of Regression Trees in Optimization of Metal Forming Process

2014 ◽  
Vol 622-623 ◽  
pp. 749-755 ◽  
Author(s):  
Krzysztof Regulski ◽  
Danuta Szeliga ◽  
Jan Kusiak
Keyword(s):  
Sensitivity Analysis ◽  
Process Parameters ◽  
Dual Phase Steel ◽  
Deterministic Model ◽  
Computational Cost ◽  
Regression Trees ◽  
Dual Phase ◽  
Forming Process ◽  
Optimization Of Process Parameters ◽  
Thermomechanical Processes

Application of sensitivity analysis in optimization of process parameters of production processes for innovative materials, e.g. dual phase steel, requires deterministic model of thermomechanical processes and large datasets that covers whole surface of results. Difficulties in optimization of process parameters correspond with large number of control variables, which should be considered in the technology design. Furthermore, conduction of such analysis takes the great computational cost. Presented work concerns possibility of application of regression trees, especially CART model, in preliminary analysis for sensitivity analysis. Use of data mining algorithms enables acquiring of preliminary, rough results: relationships among parameters of the hot rolling process of dual phase steel strips and rules of optimization of this process, it also does not require any apriori knowledge about thermomechanical processes.

scholarly journals Optimization of Process Parameters of Stamping Forming of the Automotive Lower Floor Board

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Guoying Ma ◽  
Binbing Huang
Keyword(s):  
Process Parameters ◽  
Production Efficiency ◽  
Simulation Analysis ◽  
Orthogonal Experiment ◽  
Production Costs ◽  
Main Process ◽  
Forming Process ◽  
Optimization Of Process Parameters ◽  
Automobile Panel ◽  
Thinning Rate

There are many process parameters which have great effect on the forming quality of parts during automobile panel stamping forming process. This paper took automotive lower floor board as the research object; the forming process was analyzed by finite element simulation using Dynaform. The influences of four main process parameters including BHF (blank holder force), die corner radius, friction coefficient, and die clearance on the maximum thinning rate and the maximum thickening rate were researched based on orthogonal experiment. The results show that the influences of each value of various factors on the target are not identical. On this basis, the optimization of the four parameters was carried out, and the high quality product was obtained and the maximum thinning rate and maximum thickening rate were effectively controlled. The results also show that the simulation analysis provides the basis for the optimization of the forming process parameters, and it can greatly shorten the die manufacturing cycles, reduce the production costs, and improve the production efficiency.

scholarly journals Optimization of flow forming process parameters of al-8014 using genetic algorithm

2018 ◽  
Vol 7 (2) ◽  
pp. 868
Author(s):  
T Mahender ◽  
Bellam Venkatesh
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Process Parameters ◽  
Optimum Process ◽  
Forming Process ◽  
Flow Forming ◽  
Spinning Process ◽  
Evolutionary Technique ◽  
Metal Spinning ◽  
Advanced Version

Flow forming is an advanced version of the metal spinning process in which the metal is formed into the desired shape without formation of a chip. There are many flow forming process parameters that will influence the surface roughness of the material. In the current study, three process parameters are considered in the flow forming of AA8014. The process parameters are speed of the mandrel, longitudinal feed and the flow rate of the coolant and the response is surface roughness. Design of experiments based response surface method (RSM) is used to study the effect of process parameters on the response. A quadratic mathematical model was developed by RSM is used for optimization of surface roughness by using an evolutionary technique Genetic Algorithm. The surface roughness obtained at optimum process parameters from Genetic Algorithm is in good agreement with the experimental results.  

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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