Casting Design Through Multi-Objective Optimization

Kor, Jean; Chen, Xiang; Sun, Zhi‐zhong; Hu, Henry

doi:10.3182/20110828-6-it-1002.01726

“…The Pareto front obtained by the MOEA can provide a trade-off between objectives and support decision-makers in choosing the final optimal solution [ 13 ]. Kor [ 14 ] proposed an optimization strategy for the gating system using the elitist non-dominated sorting GA II (NSGA-II) [ 15 ], in which the objectives included no shrinkage porosity, minimized flow velocity, and maximized casting yields. However, expressing the shrinkage porosity mathematically is difficult; consequently, the individual fitness in NSGA II cannot be evaluated.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of the Gating and Riser System for Complex Casting Using an Evolutionary Algorithm

He

¹

,

Lei

²

,

Mengqi

³

et al. 2022

Materials

4

0

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The gating and riser system design is essential for both quality and cost in large-scale casting and is expected to reach several objectives simultaneously. However, even with the help of commercial simulation software, the design of gating and riser systems is still the result of a long-term trial-and-error optimal process owing to the conflict between the objectives. Several evolutionary algorithms (EAs) have been reported to be helpful in the selection of the geometrical dimensions of gating and riser systems. In this study, a route with sequential use of a multi-objective EA and single-objective optimization algorithm was developed to help design gating and riser systems, respectively. This route was applied in an actual case and verified using commercial simulation software. The results showed a dramatic decrease in the time cost in design and acceptable casting quality. Thus, the proposed design method is time-saving.

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“…To maximise the effectiveness of casting simulation and improve the likelihood of an operator achieving an optimal solution, automatic optimisation algorithms for casting process development are being researched, [1][2][3][4][5] and commercial software such as MAGMAfrontier, [6][7][8][9] OPTICast 10 and AutoCAST-X 4,11,12 have been developed. The most common application found in all of these automatic process optimisation tools is the solution to the problem of casting feeding system optimisation.…”

Section: Introductionmentioning

confidence: 99%

Reliability based casting process design optimisation

Hardin

¹

,

Choi

²

,

Gaul

³

et al. 2014

International Journal of Cast Metals Research

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Deterministic optimum designs are unreliable without consideration of the statistical and physical uncertainties in the casting process. In the present research, casting simulation is integrated with a general purpose reliability based design optimisation (RBDO) software tool that considers uncertainties in both the input variables as well as in the model itself. The output consists of an optimal design that meets a specified reliability. An example casting process design is presented where the shape of a riser is optimised while considering uncertainties in the fill level and riser diameter. It is shown that RBDO provides a much different optimum design than a traditional deterministic approach. The deterministic optimal solution offers a 12% increase in casting yield over typical safety margin design practice, but has an unacceptable 61% probability of failure. The RBDO design has a 7% increase in casting yield over the safety margin approach and a probability of failure of 4?6%.

show abstract

“…To maximise the effectiveness of casting simulation and improve the likelihood of an operator achieving an optimal solution, automatic optimisation algorithms for casting process development are being researched, [1][2][3][4][5] and commercial software such as MAGMAfrontier, [6][7][8][9] OPTICast 10 and AutoCAST-X 4,11,12 have been developed. The most common application found in all of these automatic process optimisation tools is the solution to the problem of casting feeding system optimisation.…”

Section: Introductionmentioning

confidence: 99%

Reliability‐Based Casting Process Design Optimization

Hardin¹,

and²,

Beckermann³

2014

Shape Casting: 5th International Symposium 2014

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Deterministic optimum designs are unreliable without consideration of the statistical and physical uncertainties in the casting process. In the present research, casting simulation is integrated with a general purpose reliability based design optimisation (RBDO) software tool that considers uncertainties in both the input variables as well as in the model itself. The output consists of an optimal design that meets a specified reliability. An example casting process design is presented where the shape of a riser is optimised while considering uncertainties in the fill level and riser diameter. It is shown that RBDO provides a much different optimum design than a traditional deterministic approach. The deterministic optimal solution offers a 12% increase in casting yield over typical safety margin design practice, but has an unacceptable 61% probability of failure. The RBDO design has a 7% increase in casting yield over the safety margin approach and a probability of failure of 4?6%.

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Casting Design Through Multi-Objective Optimization

Cited by 10 publications

References 11 publications

Optimal Design of the Gating and Riser System for Complex Casting Using an Evolutionary Algorithm

Optimal Design of the Gating and Riser System for Complex Casting Using an Evolutionary Algorithm

Reliability based casting process design optimisation

Reliability‐Based Casting Process Design Optimization

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