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Powder Metallurgy Volume 43, 2000 - Issue 1
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Articles

Experimental analysis and neural network modelling of the rheological behaviour of powder injection moulding feedstocks formed with bimodal powder mixtures

L. V. Dihoru
,
L. N. Smith
&
R. M. German
Pages 31-36 | Published online: 19 Jul 2013

Citations (11)

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Seyed Mohammad Majdi, Atefeh Ayatollahi Tafti, Vincent Demers, Guillem Vachon & Vladimir Brailovski. (2022) Effect of powder particle shape and size distributions on the properties of low-viscosity iron-based feedstocks used in low-pressure powder injection moulding. Powder Metallurgy 65:2, pages 170-180.
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Articles from other publishers (10)

Atefeh A. Tafti, Vincent Demers, Guillem Vachon & Vladimir Brailovski. (2023) Influence of powder size on the moldability and sintered properties of irregular iron-based feedstock used in low-pressure powder injection molding. Powder Technology 420, pages 118395.
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Senthil Kumaran Selvaraj, Aditya Raj, R. Rishikesh Mahadevan, Utkarsh Chadha & Velmurugan Paramasivam. (2022) A Review on Machine Learning Models in Injection Molding Machines. Advances in Materials Science and Engineering 2022, pages 1-28.
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O. S. Zvereva, V. A. Dovydenkov, S. Ya. Alibekov & O. I. Razinskaya. (2021) Technology of Producing Pseudo Alloys of System Fine Porous Powder Steel-Copper Alloy by the Infiltration Method. Inorganic Materials: Applied Research 12:4, pages 922-927.
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A A Abdullah, H Norita, H N Azlina, A B Sulong & N N Mas’ood. (2018) Preparation of SS316L MIM feedstock with biopolymer as a binder. IOP Conference Series: Materials Science and Engineering 290, pages 012076.
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Dong Yong Park, Youngmin Oh, Hyung Ju Hwang & Seong Jin Park. (2017) An experimental approach to powder-binder separation of feedstock. Powder Technology 306, pages 34-44.
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Bhimasena Nagaraj Mukund, Berenika Hausnerova & Tirumani Srinivasan Shivashankar. (2015) Development of 17-4PH stainless steel bimodal powder injection molding feedstock with the help of interparticle spacing/lubricating liquid concept. Powder Technology 283, pages 24-31.
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Ahmad Nizam bin AbdullahNurhaslina binti JohariMuhammad Jabir bin Suleiman AhmadRosdi Ibrahim & Abdul Rahim Abu Talib. (2014) Analysis of the Rheological Behavior and Stability of Inconel 718 Powder Injection Molding (PIM) Feedstock. Advanced Materials Research 879, pages 63-72.
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Julien Bricout, Jean-Claude Gelin, Carine Ablitzer, Pierre Matheron & Meryl Brothier. (2013) Influence of powder characteristics on the behaviour of PIM feedstock. Chemical Engineering Research and Design 91:12, pages 2484-2490.
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Drago Torkar, Saša Novak & Franc Novak. (2008) Apparent viscosity prediction of alumina–paraffin suspensions using artificial neural networks. Journal of Materials Processing Technology 203:1-3, pages 208-215.
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L.N. Smith, R.M. German & M.L. Smith. (2002) A neural network approach for solution of the inverse problem for selection of powder metallurgy materials. Journal of Materials Processing Technology 120:1-3, pages 419-425.
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