Multi-characteristic optimization of wax patterns in the investment casting process using grey–fuzzy logic

The present investigation focuses on optimizing the injection process parameters with multiple performance characteristics in the investment casting process using the orthogonal array with grey–fuzzy logics. A grey–fuzzy reasoning grade obtained from the grey–fuzzy logics analysis is used as a performance index to determine the optimal injection process parameters. The selected injection process parameters are injection temperature, injection time, and injection pressure, while the considered performance characteristics are linear shrinkage and surface finish. The response table, response graph, and analysis of variance are used to find the optimal setting and the influence of injection process parameters on the multiple performance characteristics. The results of confirmation experiments reveal that grey–fuzzy logics can effectively acquire an optimal combination of the process parameters. Hence, quality of wax patterns in the investment casting process can be significantly improved through this approach.

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