Die shape optimisation for net-shape accuracy in metal forming using direct search and localised response surface methods

Lü, Bin; Ou, Hengan; Long, Hui

doi:10.1007/s00158-011-0635-x

Cited by 21 publications

(8 citation statements)

References 39 publications

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“…To maintain the hardness and toughness of hot forging die, nitriding is chosen as the heat treatment in which the depth of nitriding layer also plays an important role in strengthening die performance. [5][6][7][8] The whole forging process can be simulated and verified using finite element method (FEM) by applying various input parameters and then they can be optimized according to the process requirements.…”

Section: Die Characteristicsmentioning

confidence: 99%

A Systematic Review of Factors Affecting the Process Parameters and Various Measurement Techniques in Forging Processes

Sharma

Gupta

et al. 2023

steel research int.

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Forging is a primary manufacturing process used in several manufacturing industries. Aircraft and automobile industries are manufacturing products with high‐dimensional accuracy and quality that are highly precise or near the required shape. Customers require products that are free of cracks and fulfill their functional requirements. This leads to the advancement of the forging process due to its ability to form complicated and intricate shapes. Herein, a detailed review of the aspects of forging is given in which the optimization of factors like preform design, forging conditions, workpiece dimensions, die design, lubricant properties, and thermal treatment parameters are discussed, enhancing the tool life and forging quality of the product. The selection of die‐forging tool material and methods for enhancing the surface quality of forged products are also reviewed. The article also presents methods for measurement of forging quality, tool life, machine effectiveness, forging image acquisition, and forging parameters, which can significantly reduce the risk of error at every step of the forging process. This review serves as a reference for researchers to increase production rate, enhance the effectiveness of measurement system, and improve the quality of forged products with technological advancement.

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Section: Die Characteristicsmentioning

confidence: 99%

A Systematic Review of Factors Affecting the Process Parameters and Various Measurement Techniques in Forging Processes

Sharma

Gupta

et al. 2023

steel research int.

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“…Hence, thoroughly analysing the wear of forging tools and predicting their life is a very important issue and a huge challenge for technologists, tool designers, process engineers and forging companies, as well as many research centres [9,10]. Numerous studies described in the technical literature are devoted, on the one hand, to research works which make it possible to increase the tool life by various techniques of surface engineering [11][12][13][14][15][16] and, on the other, to improvements of the technical and technological process parameters [17], optimization of the tool shape [18], conversion of the tool material to a material more resistant to the effect of destructive mechanisms [19,20], or implementation of proper heat treatment [21].…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of the artificial neural networks in a system for durability prediction of forging tools to forgings made of C45 steel

Mrzygłód

Hawryluk

Janik

et al. 2020

Int J Adv Manuf Technol

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The article presents the results of a sensitivity analysis of artificial neural networks developed for a system which predicts the durability of forging tools used in the selected hot die forging process. The developed system makes it possible to calculate the geometric loss of the examined tool for the given values of its operating parameters (number of forgings, tool temperature at selected points, type of the applied protective layer, pressure and path of friction) and estimates the intensity of the occurrence of typical mechanisms of tool destruction, i.e. thermo-mechanical fatigue, mechanical wear, abrasive wear and plastic deformation. Nine neural networks operate in the developed system. Five of them determine the geometric loss of the material used for tools operating with protective layers, including a nitrided layer, a pad welded layer and three hybrid layers, i.e. AlCrTiSiN, Cr/CrN and Cr/AlCrTiN. Four networks make calculations determining the intensity of the occurrence of typical destructive mechanisms. The developed sensitivity analysis allows for each neural network to show which input parameters are most important and have the greatest impact on the explained variables. This is determined based on the network error analysis in the case of elimination of individual variables from the input data. The greater the network error calculated after rejecting an input variable relative to the error obtained for the network with all the input variables, the more sensitive the network to the lack of this variable. The best compliance was obtained for the first developed set of networks regarding the geometric loss of material, while the lowest compliance was obtained for the second developed set of networks regarding the applied protective layers, and in particular for plastic deformation and mechanical fatigue, probably due to the smallest size of these sets in the knowledge base. The obtained results of this analysis are important for the system operation, i.e. supporting the technologist's decision in the selection of such process parameter values that will increase the die's lifetime.

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“…Mutual, quantitative proportions of individual destructive mechanisms affecting forging tools vary greatly and mainly depend on the operational conditions present during the forging process. To a lesser extent, a tool's resistance to destructive mechanisms depends on its design (shape of the working surface), the tool material and its proper heat treatment, as well as treatment of the surface layer, while the shape of the forging preform has the least influence [9,27,28,32]. In the literature, lifetime is usually defined, from a production perspective, as the number of forgings that meet qualitative requirements manufactured by means of the given tool.…”

Section: Introductionmentioning

confidence: 99%

Wear Analysis of Die Inserts in the Hot Forging Process of a Forked Type Forging Using Reverse Scanning Techniques

Dworzak¹,

Hawryluk²,

Ziemba³

2017

Adv. Sci. Technol. Res. J.

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This article presents a wear analysis of die inserts used in the hot forging process of a forked forging (yoke), an element applied in steering systems of passenger vehicles. Studies involved the application of an original reverse scanning method intended for rapid and reliable wear analysis of forging tools (with complicated shape) affording easy assessment without the need to dismount tools from the forging unit. The developed method involves analysis of progressive wear of forging tools based on measurements (scanning) of forgings periodically collected from the process and constitutes a useful tool for measurement and testing. As the authors' earlier works have demonstrated, the proposed new approach to analysis of tool wear with the application of reverse 3D scanning has proven successful in multiple instances in the case of axially symmetrical objects. The presented results of studies indicate that it is possible to utilize the expanded method to analyze the lifetime of forging tools, including tools with complex geometry. Application of the reverse scanning method allows for continuous and practical monitoring of the condition of forging tools over the course of the forging process and should have a positive impact on improving production output and reducing production costs.

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Die shape optimisation for net-shape accuracy in metal forming using direct search and localised response surface methods

Cited by 21 publications

References 39 publications

A Systematic Review of Factors Affecting the Process Parameters and Various Measurement Techniques in Forging Processes

A Systematic Review of Factors Affecting the Process Parameters and Various Measurement Techniques in Forging Processes

Sensitivity analysis of the artificial neural networks in a system for durability prediction of forging tools to forgings made of C45 steel

Wear Analysis of Die Inserts in the Hot Forging Process of a Forked Type Forging Using Reverse Scanning Techniques

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