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Due to heavy competitions in manufacturing and marketing, the industries are prompted to manufacture products that are better, long-lasting and dependable and a new material revolution in this regard has become inevitable. As an impact of the revolution, the families of difficult-to machine materials like high carbon high chromium die steel, stainless steel and super alloys have expanded. Experimental results analysed by ANOVA indicate the improved performance of ECM. The developed mathematical models provide a good relationship between the selected influencing factors and the objectives due to higher values of R2. The confirmatory experiments were conducted for both GA and Firefly algorithm and the results reveal that the actual performance deviates from the predicted one by 2 to 4% only. Hence, the developed mathematical models can be used for obtaining maximum MRR and minimum surface roughness of HCHCr die steel. The performance of Firefly algorithm is better when compared to genetic algorithm. Firefly algorithm performs well in all the selected machining parameters on maximum MRR and minimum surface roughness condition.
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Improving the MRR of ECM Using Nano Particles Suspended Electrolytes
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LAP LAMBERT Academic Publishing Feb 2019, 2019
ISBN 10: 6139450608
ISBN 13: 9786139450602
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Due to heavy competitions in manufacturing and marketing, the industries are prompted to manufacture products that are better, long-lasting and dependable and a new material revolution in this regard has become inevitable. As an impact of the revolution, the families of difficult-to machine materials like high carbon high chromium die steel, stainless steel and super alloys have expanded. Experimental results analysed by ANOVA indicate the improved performance of ECM. The developed mathematical models provide a good relationship between the selected influencing factors and the objectives due to higher values of R2. The confirmatory experiments were conducted for both GA and Firefly algorithm and the results reveal that the actual performance deviates from the predicted one by 2 to 4% only. Hence, the developed mathematical models can be used for obtaining maximum MRR and minimum surface roughness of HCHCr die steel. The performance of Firefly algorithm is better when compared to genetic algorithm. Firefly algorithm performs well in all the selected machining parameters on maximum MRR and minimum surface roughness condition. 208 pp. Englisch. Codice articolo 9786139450602
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Varatharajan SathiyamoorthyDr. V. Sathiyamoorthy was born in Salem, Tamil Nadu, India on 5th May 1983. Received B.E., in Mechanical Engineering (2006), M.E., in CAD (2008) and Ph.D. in mechanical engineering (2015) from Anna Universi. Codice articolo 385858758
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Improving the MRR of ECM Using Nano Particles Suspended Electrolytes
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LAP LAMBERT Academic Publishing Feb 2019, 2019
ISBN 10: 6139450608
ISBN 13: 9786139450602
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Due to heavy competitions in manufacturing and marketing, the industries are prompted to manufacture products that are better, long-lasting and dependable and a new material revolution in this regard has become inevitable. As an impact of the revolution, the families of difficult-to machine materials like high carbon high chromium die steel, stainless steel and super alloys have expanded. Experimental results analysed by ANOVA indicate the improved performance of ECM. The developed mathematical models provide a good relationship between the selected influencing factors and the objectives due to higher values of R2. The confirmatory experiments were conducted for both GA and Firefly algorithm and the results reveal that the actual performance deviates from the predicted one by 2 to 4% only. Hence, the developed mathematical models can be used for obtaining maximum MRR and minimum surface roughness of HCHCr die steel. The performance of Firefly algorithm is better when compared to genetic algorithm. Firefly algorithm performs well in all the selected machining parameters on maximum MRR and minimum surface roughness condition.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 208 pp. Englisch. Codice articolo 9786139450602
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Improving the MRR of ECM Using Nano Particles Suspended Electrolytes
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Due to heavy competitions in manufacturing and marketing, the industries are prompted to manufacture products that are better, long-lasting and dependable and a new material revolution in this regard has become inevitable. As an impact of the revolution, the families of difficult-to machine materials like high carbon high chromium die steel, stainless steel and super alloys have expanded. Experimental results analysed by ANOVA indicate the improved performance of ECM. The developed mathematical models provide a good relationship between the selected influencing factors and the objectives due to higher values of R2. The confirmatory experiments were conducted for both GA and Firefly algorithm and the results reveal that the actual performance deviates from the predicted one by 2 to 4% only. Hence, the developed mathematical models can be used for obtaining maximum MRR and minimum surface roughness of HCHCr die steel. The performance of Firefly algorithm is better when compared to genetic algorithm. Firefly algorithm performs well in all the selected machining parameters on maximum MRR and minimum surface roughness condition. Codice articolo 9786139450602
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Improving the MRR of ECM Using Nano Particles Suspended Electrolytes
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Taschenbuch. Condizione: Neu. Improving the MRR of ECM Using Nano Particles Suspended Electrolytes | Sathiyamoorthy Varatharajan (u. a.) | Taschenbuch | 208 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139450602 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 115846920
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