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Optimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition
Alternative TitleOptimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition
Katoch Sanjeev1; Sehgal Rakesh3; Singh Vishal1
2017
Source PublicationFriction
ISSN2223-7690
Volume5Issue:1Pages:66-86
AbstractAbstract Cryogenic treatment (CT) is a relatively new field, which has emerged during the last three decades of the twentieth century. However, its impact on material shaping and making tool life, and enhancement of their mechanical properties are quite remarkable. The selection of appropriate process parameters for CT is essential for cost reduction and optimum productivity. This study focuses on the influence of key parameters of CT cycles (i.e., soaking temperature and duration) on the friction and wear behavior of AISI H13 hot die steel under dry sliding conditions against hardened and tempered AISI D3 cold work tool steel (counter face) at varying sliding speeds and loads. Mathematical models have been developed for wear rate, the average coefficient of friction, and maximum contact temperature using the Box-Cox methodology. The developed mathematical models have been validated by comparing with the experimental results. Moreover, the optimum values of the process parameter have been employed to maximize the output and validate the same by confirmation of the experiments. To the best of our knowledge, this is the first study that demonstrates the modeling and optimization of sliding friction and wear characteristics of AISI H13 under varied CT cycles.
Other AbstractCryogenic treatment (CT) is a relatively new field, which has emerged during the last three decades of the twentieth century. However, its impact on material shaping and making tool life, and enhancement of their mechanical properties are quite remarkable. The selection of appropriate process parameters for CT is essential for cost reduction and optimum productivity. This study focuses on the influence of key parameters of CT cycles (i.e., soaking temperature and duration) on the friction and wear behavior of AISI H13 hot die steel under dry sliding conditions against hardened and tempered AISI D3 cold work tool steel (counter face) at varying sliding speeds and loads. Mathematical models have been developed for wear rate, the average coefficient of friction, and maximum contact temperature using the Box-Cox methodology. The developed mathematical models have been validated by comparing with the experimental results. Moreover, the optimum values of the process parameter have been employed to maximize the output and validate the same by confirmation of the experiments. To the best of our knowledge, this is the first study that demonstrates the modeling and optimization of sliding friction and wear characteristics of AISI H13 under varied CT cycles.
Keywordcryogenics treatment hot die steel friction wear modeling Box-Cox method Mechanical engineering and machinery TJ1-1570
Indexed ByCSCD
Language英语
Funding Project[National Institute of Technology, Hamirpur]
CSCD IDCSCD:6142117
Citation statistics
Document Type期刊论文
Identifierhttp://ir.imr.ac.cn/handle/321006/156033
Collection中国科学院金属研究所
Affiliation1.中国科学院金属研究所
2.Institute Auto Parts & Hand Tools Technol, A-9,Phase 5, Ludhiana 141010, Punjab, India
3.Natl Institute Technol, Dept Mech Engn, Hamirpur 177005, HP, India
Recommended Citation
GB/T 7714
Katoch Sanjeev,Sehgal Rakesh,Singh Vishal. Optimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition[J]. Friction,2017,5(1):66-86.
APA Katoch Sanjeev,Sehgal Rakesh,&Singh Vishal.(2017).Optimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition.Friction,5(1),66-86.
MLA Katoch Sanjeev,et al."Optimization of friction and wear characteristics of varied cryogenically treated hot die steel grade AISI-H13 under dry condition".Friction 5.1(2017):66-86.
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