This paper describes the philosophy and architecture of a multi-objective design tool called modeFRONTIER. The paper explains the important concepts that lie behind the tool and demonstrates its use by tackling two multiple criteria design problems. Several technological components needs to be harmonised in order to do be able to face real multi-disciplinary and multi-criteria optimisation: IT infrastructure, efficient optimisation tools, decision making and statistical tools. The example problem deals with gas-assisted plastic injection moulding. The optimisation is done using CADMould for the simulation of the process. While the geometry of the component is fixed, the plastic and gas injection point and process parameters like pressure, temperature, timing of the process fases are automatically found by the optimiser. The two examples are related to different type of problems that can be faced by means of distributed computing: parallel execution of design tasks to improve the efficiency of the optimisation algorithms and handling of different simulation codes and platforms in the same design task.

Gas Assisted Injection Molding optimization with M.O.G.A.

POLONI, CARLO;
2001-01-01

Abstract

This paper describes the philosophy and architecture of a multi-objective design tool called modeFRONTIER. The paper explains the important concepts that lie behind the tool and demonstrates its use by tackling two multiple criteria design problems. Several technological components needs to be harmonised in order to do be able to face real multi-disciplinary and multi-criteria optimisation: IT infrastructure, efficient optimisation tools, decision making and statistical tools. The example problem deals with gas-assisted plastic injection moulding. The optimisation is done using CADMould for the simulation of the process. While the geometry of the component is fixed, the plastic and gas injection point and process parameters like pressure, temperature, timing of the process fases are automatically found by the optimiser. The two examples are related to different type of problems that can be faced by means of distributed computing: parallel execution of design tasks to improve the efficiency of the optimisation algorithms and handling of different simulation codes and platforms in the same design task.
2001
1852335343
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2545778
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