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DOE Applied To Optimization of Steel Casting Gong Xuedan1, 2, Liao Dunming1, Zhou Jianxin1, Shen Xu1 1State Key Laboratory of Materials Processing and Die & Mould Technology Huazhong University of Science and Technology, Wuhan, Hubei, China, 430074 2 School of Mechanical Engineering, Hubei University of Technology, Wuhan, Hubei, China, 430068 Keywords: Steel Casting; DOE; Numerical Simulation; Process Parameters Optimization Abstract.
Acknowledgements This work was supported by the following foundations: (1) New Century Excellent Talents in University (NCET) 2010-2012 (2) National Science & Technology Key Projects of Numerical control (2012ZX04014-052) 2011-2013 (3) Fundamental Research Funds for the Central Universities (2011TS039) 2011-2012 (4) Foundation for Innovative Research Groups of the Natural Science Foundation of Hubei Province, China (2010CDA067) 2011-2013 (5) National Science & Technology Key Projects of Numerical control (2012ZX04012-011) 2012-2015 (6) National Science & Technology Key Projects of Numerical control (2012ZX04010-031) 2012-2015 (7) Natural Science Foundation of Hubei Province (2011CDB279) 2012-2013 References [1] HUANG Tian-you, LIU Xiao-gang, KANG Jin-wu, SHEN Hou-fa, LIU Bai-cheng,The Review of the Production Status of Heavy Steel Castings and Key Technologies for Their Manufacturing in China [J].
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Acknowledgment This work was supported in part by the National Natural Science Foundation of China (60774036) and Projects of Special Fund of the Hubei Province Natural Science Foundation (2008CDA063).
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Hirankumar2, b*, A.Maheswaran1 ,c, R.S.Daries Bella1, d and C.Sanjeeviraja3, e 1 Energy Materials Research Laboratory, Department of Physics, Kalasalingam University, Krishnankoil – 626 126, India. 2 Centre for Scientific and Applied Research, School of Basic Engineering and Sciences, PSN College of Engineering and Technology, Melathediyoor – 627 152, TN, India 3Department of Physics, Alagappa chettiar college of Engineering and Technology, Karaikudi, India.
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The Establishment of Comprehensive Evaluation Model of Manufacturing Process Resources and Environmental Attributes Based on Artificial Neural Network The entire manufacturing process that transforms raw materials into finished products is shown in Fig. 1.
Input the raw materials, auxiliary raw materials (such as cutter, cutting fluid, etc.), energy (electricity, etc.), after the course of roughcast shaping, parts machining, materials modification and processing, assembly, to produce qualified products or parts, at the same time, solid waste such as waste products, by-products and emissions such as waste gas, waste fluid, noise, vibration, radiation will generate during the production process, which is harmful to the ecological environment, human health and safety, workshop environment and manufacturing safety.
The resources and environmental parameters involved in manufacturing process can be divided into: the consumption of raw materials and auxiliary raw materials, energy consumption, gas waste, liquid waste, solid waste, other pollution (noise, radiation, etc.), occupational health and safety hazards, each classification guidelines has specific targets, the frame structure as shown in Fig. 3.
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Acknowledgements The research is supported by grants from Science and Technology Demonstration Project of Hebei Transportation Department (H-2014-1); Science and Technology Projects of Hebei Transportation Department: Application of Waterborne Polymer Materials in Longitudinal Slope Pavement.
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All the other materials are kept constant.
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If these waste materials can be used, not only greatly reduce waste emissions, but also can reduce the rocks, sand mining, to improve the ecological environment can be described as dual.
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