Improving the Aluminium Rolling Ingot Recovery using Tqm Technique
Ritesh S. Fegade1, Rajendrakumar G. Tated2, Rupendra S. Nehete3
1Prof. R. S. Fegade*, Department of Mechanical Engineering, Genba Sopanrao Moze College of Engineering, Balewadi, Pune, India.
2Dr. R. G. Tated, Department of Mechanical Engineering, Matoshri College of Engineering & Research Center Eklahare, Nashik, India.
3Dr. R. S. Nehete, Department of Mechanical Engineering, SIES Graduate School of Technology, Navi Mumbai, India.
Manuscript received on September 15, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 282-289 | Volume-8 Issue-12, October 2019. | Retrieval Number: L37791081219/2019©BEIESP | DOI: 10.35940/ijitee.L3779.1081219
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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: To improve productivity and profitability in Aluminium continuous casting industry the main action is to reduce losses due to defects resulting into revenue losses. Improving Rolling Ingot Recovery is possible by reducing the rejections & using the resources effectively (resources MAN, MACHINE, MATERIAL & CAPITAL) by applying TQM technique. This study presents a case about minimizing defects in aluminium continuous casting using Total Quality Management (TQM) techniques in which why-why analysis, Standard Operating Procedures (SOPs),and Cause and Effect analysis is used. It can be concluded from study that rejections, shell zone & inclusion can be reduced by, Continuous monitoring the health of the moulds, quality & quantity of water, the metal casting temperature, metal head in mould, water impingement angle, use of Ceramic foam filter plates, awareness & the adherence towards the guidelines.
Keywords: Aluminium Casting, Aluminium Rolling Ingot, Cause and Effect, Rolling Ingot defect, Standard Operating Procedures (SOPs), Why-Why Analysis.
Scope of the Article: Predictive Analysis