Socio-Economic Impact Research of Foundry Industry By using Neural Network
Ranjitsinh A. Deshmukh1, Rahul Hiremath2, Gurudas Nulkar3
1Ranjitsinh A Deshmukh, Department of Mechanical Engineering, Walchand Institute of Technology, Solapur (Maharashtra), India.
2Dr. Rahul Hiremath, Faculty of Management, SCMHRD, SIU Pune (Maharashtra), India.
3Gurudas Nulkar, Faculty of Management, SCMHRD, SIU Pune (Maharashtra), India.
Manuscript received on 10 September 2019 | Revised Manuscript received on 19 September 2019 | Manuscript Published on 11 October 2019 | PP: 401-404 | Volume-8 Issue-11S September 2019 | Retrieval Number: K107109811S19/2019©BEIESP | DOI: 10.35940/ijitee.K1071.09811S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Global casting production reached 104.4 million tons in 2016. The top ten casting production nation produces 91.6 million metric tons of the total production of 104.4 million metric tons. Nearly 47.2 million metric tons of casting produces by China. Casting production increases from 5.4% to 11.35% million metric tons. USA, Japan, Germany, Russia, Korea, Mexico, Brazil and Italy are the top ten nations. Almost 6500 foundry units are in country out of which 90% can be categorized as small scale units, medium scale units as 8% and large scale units as 2%. Foundry industry includes several critical aspects related to social, economic and environmental aspect need to assess. The results gained by these models are compared with regression model. Socio- economic foundry industry complex relationship between different parameters can be modeled by using neural network and regression model. It can also study running such program lead to substantial improvements in socio-economic circumstances of targeted industry and make it sustainable industry.
Keywords: Neural Network, Regression Analysis, Sustainability etc.
Scope of the Article: Operational Research