Continuous Dry Cylindrical and Rectangular Deep Drawing by Electroconductive Ceramic Dies

Tamaoki, Kenji; Manabe, Katsushi; Kataoka, Seiji; Aizawa, Tatsuhiko

doi:10.1115/1.4023720

Cited by 10 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For deep drawing of stainless steel using an alumina ceramic die, the drawing load was significantly reduced (Kataoka et al, 2004). Tamaoki et al (2010) proposed the electroconductive ceramic die for deep drawing, and the cups were successfully deep drawn over 10,000 times (Tamaoki et al, 2013). However, it is not easy to apply the brittle ceramic die to ironing of stainless steel cups.…”

Section: Introductionmentioning

confidence: 98%

Improvement of Formability in Ironing of Stainless Steel Drawn Cups Using Low Friction Cermet Dies

Abe¹,

Fujita²,

Mori³

et al. 2014

Procedia Engineering

View full text Add to dashboard Cite

A TiCN-based cermet die was utilised to improve the formability in ironing of stainless steel drawn cups. By employing the cermet die, additional coating was not required because it was made of hard TiCN having low friction. As a comparison, TiCcoated WC-Co, non-coated WC-Co and tool steel dies were used. The effects of the viscosity of a lubricant and the ironing speed on the formability for the cermet die were examined. The cermet die exhibited the largest seizure resistance. The performance of the cermet die in repeated ironing was evaluated. For repeated ironing using the cermet die, the occurrence of seizure was prevented up to 100 strokes. It was found that the cermet die with low friction was effective in ironing stainless steel drawn cups.

show abstract

Section: Introductionmentioning

confidence: 98%

Improvement of Formability in Ironing of Stainless Steel Drawn Cups Using Low Friction Cermet Dies

Abe¹,

Fujita²,

Mori³

et al. 2014

Procedia Engineering

View full text Add to dashboard Cite

show abstract

“…When retracted, the punch's elastic construction allows it to partially revert to its original form. [2][3][4][5] The angle of the punch, the radius of the die nose, and the punch all affect the spring-back effect. The size of a drawn component must be accurately predicted, as must the spring-back effect.…”

Section: Introductionmentioning

confidence: 99%

A study on deep drawn cups and the selection of optimal settings deploying ANN training and architectural parameters using the Taguchi ARAS approach

Sivam

Rajendran

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

In recent years, the use of artificial neural networks (ANN) for modeling and optimizing metal forming processes has gained popularity. Numerous benefits are provided by ANNs, which can only be attained by constructing a high-performance ANN model. However, selecting an ANN’s appropriate training and architectural parameters remains challenging. Typically, these parameters are chosen using a trial-and-error approach in which many ANN models are produced and evaluated. This article describes the use of the Taguchi method for optimizing an ANN model trained on architectural parameters by the Levenberg–Marquardt algorithm and the additive ratio assessment method for selecting the optimized parameter. The method’s operation is demonstrated using the Altair Inspire form, the Forming Limit Diagram, and the Maximum Thinning Rate. The ANN model was trained using the orthogonal array, and its prediction performance was compared to the experimental validation. Analysis of variance assisted in determining whether the model was significant. The analysis of means helped us in deciding the appropriate ANN level for each parameter. Taguchi orthogonal array, ANN optimized for additive ratio assessment method. This model was developed and was found to be the most accurate. Through learning and testing, it was demonstrated that a systematic method for selecting the optimal ANN training and architecture parameters saves time and money by avoiding trial and error. The Taguchi-based additive ratio assessment method algorithm can then be used to determine the ideal processing parameters.

show abstract

“…The effect of wet and dry lubrication can make a distinct difference in coefficient of friction. 2 The component achieved by maintaining above conditions will have a uniform thickness and better mechanical strength which has vast application in mechanical and electrical devices.…”

Section: Introductionmentioning

confidence: 99%

A review on effect of thinning, wrinkling and spring-back on deep drawing process

Babu

2018

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

There are various processes practiced in a market for manufacturing axisymmetrical cup with significant forming depth among which deep drawing process is most prompt. The deep drawing process is a forming process with ongoing interest which will have a major impact on industries in coming years. This article focuses on the current status and potential of future development of technology in the deep drawing process. First, it describes various types of approaches and techniques used in the deep drawing of different materials. This is followed by brief reviews of advantages and limitations of these technologies with its application in industries. The details of these technologies are just referred rather than explaining in detail. The further part of this article focuses on advanced methods for predicting defects like thinning, wrinkling and spring-back in deep drawing process which are mostly responsible for rejection of the components. The opportunity in the development of flexibility in deep drawing process is covered with an observed barrier in the prediction of defects such as thinning, wrinkling and spring-back. The obtained evidence indicates that deep drawing process may not be applicable for all materials, but represents an excellent opportunity in the drawing of multilayer metal and composite material sheets to complex shapes.

show abstract

Continuous Dry Cylindrical and Rectangular Deep Drawing by Electroconductive Ceramic Dies

Cited by 10 publications

References 5 publications

Improvement of Formability in Ironing of Stainless Steel Drawn Cups Using Low Friction Cermet Dies

Improvement of Formability in Ironing of Stainless Steel Drawn Cups Using Low Friction Cermet Dies

A study on deep drawn cups and the selection of optimal settings deploying ANN training and architectural parameters using the Taguchi ARAS approach

A review on effect of thinning, wrinkling and spring-back on deep drawing process

Contact Info

Product

Resources

About