Multi-objective optimization of green sand mould system using evolutionary algorithms

@article{Surekha2012MultiobjectiveOO,
  title={Multi-objective optimization of green sand mould system using evolutionary algorithms},
  author={B. Surekha and Lalit Kaushik and Abhishek K. Panduy and Pandu Ranga Vundavilli and Mahesh B. Parappagoudar},
  journal={The International Journal of Advanced Manufacturing Technology},
  year={2012},
  volume={58},
  pages={9-17}
}
The quality of cast products in green sand moulds is largely influenced by the mould properties, such as green compression strength, permeability, hardness and others, which depend on the input (process) parameters (that is, grain fineness number, percentage of clay, percentage of water and number of strokes). This paper presents multi-objective optimization of green sand mould system using evolutionary algorithms, such as genetic algorithm (GA) and particle swarm optimization (PSO). In this… 

Multi Response Optimization of Green Sand Moulding Parameters Using Taguchi-DEAR Method

Green sand casting is treated as the most versatile casting process due to their excellent design flexibility that offer complex shapes and ability to reclaim silica sand. The modern foundries are

Optimization of green sand mould system using Taguchi based grey relational analysis

The strength of the mould cavity in sand casting is very much significant to attain high-quality castings. Optimization of green sand process parameters plays a vital role in minimizing casting

Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization

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

Parametric Optimization of Permeability of Green Sand Mould Using ANN and ANFIS Methods

In foundry industries, various additives are used to increase the sand mould properties such as green strength and permeability number. In the present paper, camphor has been used as additive to

Multiobjective Optimization of Green Sand Mould System Using Chaotic Differential Evolution

In this work, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms; differential evolution, chaotic differential evolution and gravitational search algorithm (GSA) to generate the approximate Pareto frontier to the green sand mould system problem.

Multi-Objective Optimization of Squeeze Casting Process using Evolutionary Algorithms

The performance of PSO is found to be comparable with that of GA for identifying optimal process variable combinations, however, PSO outperformed GA with regard to computation time.

Optimization of Aluminum Sand Casting process parameters on RSM and ANN methods

Sand casting is one of the best processes to produce a product to satisfy the customer requirements. The prime advantages of choosing the sand casting technique are perfect dimensional geometry,

OPTIMIZATION IN GREEN SAND CASTING PROCESS FOR EFFICIENT , ECONOMICAL AND QUALITY CASTING

Among the industrial activities sand casting process still remains as one of the most complex and indefinite activities. Due to the complex relationship between casting defects and green sand

Multi-Objective Optimization of process parameters during solidification of Hypoeutectic Al-Si alloy casting using Genetic Algorithm

The properties of Al-Si alloy are dependent on the grain size and distribution of silicon particles. Grain size and distribution of silicon particles can be affected by grain refinement and

Multiobjective optimization of green sand mould system using DE and GSA

The weighted sum scalarization approach is used in conjunction with two meta-heuristic algorithms; differential evolution (DE) and gravitational search algorithm (GSA) to generate the approximate Pareto frontier to the green sand mould system problem.

References

SHOWING 1-10 OF 14 REFERENCES

Optimization of turning process parameters using Multi-objective Evolutionary algorithm

The Pareto-optimal front of the bi-objective problem is obtained using Non-dominated Sorting Genetic Algorithm (NSGA-II) and the performance of NSGA- II is found to be more effective and efficient as compared to micro-GA.

An Investigation of Grinding Process Optimization via Evolutionary Algorithms

Numerical results show that PSO is comparatively superior in comparison with DE and GA algorithms for grinding process optimization in terms of its accuracy and convergent capability.

Multi-objective optimization of electrochemical machining process parameters using a particle swarm optimization algorithm

The selection of optimum values of important process parameters of electrochemical machining processes such as the tool feed rate, electrolyte flow velocity, and applied voltage play a significant

Non-linear modelling using central composite design to predict green sand mould properties

A Pareto optimal front of solutions was developed for strength and permeability, using a multiobjective optimization tool - the so-called non-dominated sorting genetic algorithm (NSGA).

Optimization of green sand casting process parameters of a foundry by using Taguchi’s method

An optimization technique for process parameters of green sand casting of a cast iron differential housing cover based on the Taguchi parameter design approach is proposed in this paper. The process

MULTI-OBJECTIVE OPTIMIZATION OF ABRASIVE FLOW MACHINING PROCESSES USING POLYNOMIAL NEURAL NETWORKS AND GENETIC ALGORITHMS

It is shown that some interesting and important relationships as useful optimal design principles involved in the performance of AFM can be discovered by the Pareto-based multi-objective optimization of the obtained polynomial models.

Linear and non-linear statistical modelling of green sand mould system

Abstract In the present work, design of experiments (DOE) technique with response surface methodology was used to develop both linear and non-linear models, to establish the input–output