Six sigma optimization in sheet metal forming based on dual response surface model

2006 ◽  
Vol 19 (02) ◽  
pp. 251 ◽  
Author(s):  
Yuqiang LI
Keyword(s):  
Response Surface ◽  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Six Sigma ◽  
Metal Forming ◽  
Response Surface Model ◽  
Surface Model ◽  
Dual Response

scholarly journals Influence of process parameters on surface roughness and forming time of Al-1100 sheet in incremental sheet metal forming

2019 ◽  
Vol 13 (2) ◽  
pp. 4911-4927
Author(s):  
Swagatika Mohanty ◽  
Srinivasa Prakash Regalla ◽  
Yendluri Venkata Daseswara Rao
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Sheet Metal ◽  
Process Parameters ◽  
Sheet Metal Forming ◽  
Feed Rate ◽  
Metal Forming ◽  
Wall Angle ◽  
Surface Method ◽  
Incremental Sheet Metal Forming

Product quality and production time are critical constraints in sheet metal forming. These are normally measured in terms of surface roughness and forming time, respectively. Incremental sheet metal forming is considered as most suitable for small batch production specifically because it is a die-less manufacturing process and needs only a simple generic fixture. The surface roughness and forming time depend on several process parameters, among which the wall angle, step depth, feed rate, sheet thickness, and spindle speed have a greater impact on forming time and surface roughness. In the present work, the effect of step depth, feed rate and wall angle on the surface roughness and forming time have been investigated for constant 1.2 mm thick Al-1100 sheet and at a constant spindle speed of 1300 rpm. Since the variable effects of these parameters necessitate multi-objective optimization, the Taguchi L9 orthogonal array has been used to plan the experiments and the significance of parameters and their interactions have been determined using analysis of variance (ANOVA) technique. The optimum response has been brought out using response surfaces. Finally, the findings of response surface method have been validated by conducting additional experiments at the intermediate values of the parameters and these results were found to be in agreement with the predictions of Taguchi method and response surface method.

Multi-Objective Optimization for High Strength Steel Sheet Metal Forming Process Based on Response Surface Methodology

2010 ◽  
Vol 154-155 ◽  
pp. 1223-1227 ◽  
Author(s):  
Zhi Guo An ◽  
Yu Zhang
Keyword(s):  
Response Surface Methodology ◽  
Response Surface ◽  
Sheet Metal ◽  
Sheet Metal Forming ◽  
Metal Forming ◽  
High Strength Steel ◽  
High Strength ◽  
Forming Process ◽  
Multi Objective ◽  
Metal Forming Process

In sheet metal forming process, the input process parameters scatter and considerably result in unreliablity in practical production. Optimization for sheet metal forming process is often considered as a multi-objective problem. An optimizition strategy for high strength steel (HSS) sheet metal forming process was suggested based on response surface methodology (RSM). Latin Hypercube Sampling (LHS) method was introduced to design the rational experimental samples; the objective function was defined based on cracking factor wrinkle factor and severe thinning factor; the accurate response surface for sheet metal forming problem was built by Least Square Method; Multi-objective Genetic Algorithm(MOGA) was adoped in optimization and Pareto solution was selected. The strategy was applied to analyze a HSS auto-part, the result has proved this method suitable for optimization design of HSS sheet metal forming process.

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