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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Chandrashekarappa, Manjunath Patel Gowdru
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2022Effect of Pin Geometry and Orientation on Friction and Wear Behavior of Nickel-Coated EN8 Steel Pin and Al6061 Alloy Disc Paircitations
- 2021Corrosion behaviour of high-strength Al 7005 alloy and its composites reinforced with industrial waste-based fly ash and glass fibre: comparison of stir cast and extrusion conditionscitations
- 2021Experimental investigation of selective laser melting parameters for higher surface quality and microhardness propertiescitations
- 2021Image processing of Mg-Al-Sn alloy microstructures for determining phase ratios and grain size and correction with manual measurementcitations
- 2021The effect of Zn and Zn–WO3 composites nano-coatings deposition on hardness and corrosion resistance in steel substratecitations
- 2016Multi-Objective Optimization of Squeeze Casting Process using Evolutionary Algorithmscitations
- 2016Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimizationcitations
- 2015Prediction of Secondary Dendrite Arm Spacing in Squeeze Casting Using Fuzzy Logic Based Approachescitations
- 2014Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches
- 2014Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approachescitations
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article
Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization
Abstract
<jats:title>Abstract</jats:title> <jats:p>The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.). It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature) combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength) due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA), particle swarm optimization (PSO) and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD) methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.</jats:p>