Abstract

This study deals with the optimization of the injection moulding process parameters in the production of the FR (Forward Reverse) Lever, using the Grey Relational Analysis (GRA) and Desirability Function Approach (DFA) and the results are validated by ANN. The FR lever is used to control the direction of the rotation of spindles in conventional machines. Parameters such as injection pressure, injection speed and injection temperature, which influence the quality of the final product of the injection moulding process, are called the input parameters. Parameters such as Shrinkage and Surface Roughness, which are considered as the quality characteristics of this product, are called the output parameters. FR levers are produced using a fabricated Injection moulding tool, according to Taguchi’s experimental design and the response data are recorded. The recorded experimental data are analyzed and the optimum process parameters combinations have been found, by using the GRA and DFA. An ANN has been developed using the experimental data and the responses (output data) are predicted for the corresponding optimal parameters combination. Finally, the obtained optimum parameter combinations are tested by both ANN and the experiment and the results are found to be satisfactory.

Keywords:

Desirability function approach, FR lever, grey relational analysis, injection moulding,

References

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.