[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Lin et al., 2011 - Google Patents

Application of the fuzzy-based Taguchi method for the structural design of drawing dies

Lin et al., 2011

Document ID
3895339419772922456
Author
Lin B
Kuo C
Publication year
Publication venue
The International Journal of Advanced Manufacturing Technology

External Links

Snippet

In the sheet metal stamping process for automobiles, the drawing process requires the greatest stamping force, and thus the structure of the drawing dies is the thickest and heaviest among all stamping dies. This study describes how the fuzzy-based Taguchi …
Continue reading at link.springer.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • G06F17/5018Computer-aided design using simulation using finite difference methods or finite element methods

Similar Documents

Publication Publication Date Title
Lin et al. Application of the fuzzy-based Taguchi method for the structural design of drawing dies
Mohanty et al. A particle swarm approach for multi-objective optimization of electrical discharge machining process
Fei et al. Springback prediction for incremental sheet forming based on FEM-PSONN technology
Yildiz Optimization of multi-pass turning operations using hybrid teaching learning-based approach
Li et al. Modeling and multi-objective optimization of cutting parameters in the high-speed milling using RSM and improved TLBO algorithm
CN106096127A (en) Robust error estimator method containing interval parameter uncertainty structure
Maji et al. Inverse analysis and multi-objective optimization of single-point incremental forming of AA5083 aluminum alloy sheet
Chan et al. An integrated FEM and ANN methodology for metal-formed product design
Muñoz-Escalona et al. Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351
Bologa et al. Using the Analytic Hierarchy Process (AHP) and fuzzy logic to evaluate the possibility of introducing single point incremental forming on industrial scale
CN110502779B (en) Intelligent design method of injection molding mold based on fuzzy reasoning
Cica et al. Intelligent process modeling and optimization of porosity formation in high-pressure die casting
Abolghasema et al. Optimization of machining parameters for product quality and productivity in turning process of aluminum
Altan et al. Design for forming and other near net shape manufacturing processes
Vukman et al. Application of fuzzy logic in the analysis of surface roughness of thin-walled aluminum parts
Banabic et al. Computer-aided tool path optimization for single point incremental sheet forming
Kuo et al. Optimization of microridge punch design for deep drawing process by using the fuzzy Taguchi method
Azhiri et al. Optimization of single point incremental forming process using ball nose tool
Pan et al. Lightweight design of vehicle front–end structure: contributions of multiple surrogates
Li et al. Structural Design and Optimization in the Beam of a Five-axis Gantry Machining Center.
Naeimi et al. Optimum designing of forging preform die for the H-shaped parts using backward deformation method and neural networks algorithm
Qin et al. High precision judgment method for milling stability based on Bernoulli distribution and hybrid-drive model
Ramnath et al. A Comparative Design Study of Topologically Dissimilar Automotive Structures
CN109033512A (en) A kind of determination method of the optimal blade shape of fine blanking die
JP2006031488A (en) Design support method