Abstract

The selection of optimal process parameters is essential while machining thin-wall parts since it influences the quality of the product and affects productivity. Dimensional accuracy affects the product quality, whereas the material removal rate alters the process productivity. Therefore, the study investigated the effect of tool diameter, feed per tooth, axial and radial depth of cut on wall deflection, and material removal rate. The selected process parameters were found to significantly influence the in-process deflection and thickness deviation due to the generation of unfavorable cutting forces. Further, an increase in the material removal rate resulted in chatter, thus adversely affecting the surface quality during the final stages of machining. Considering the conflicting nature of the two performance measures, Non-dominated Sorting Genetic Algorithm-II was adopted to solve the multi-objective optimization problem. The developed model could predict the optimal combination of process variables needed to lower the in-process wall deflection and maintain a superior surface finish while maintaining a steady material removal rate.

Highlights

  • Improving fuel efficiency is of prime importance in aircraft industries

  • The analysis revealed that tool diameter was a crucial parameter that influenced the cutting forces and surface finish while machining thin-wall parts

  • The dimensional accuracy of machined low rigidity parts is affected by the in-process wall deflection

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Summary

Introduction

Improving fuel efficiency is of prime importance in aircraft industries. For this purpose, modern aircraft manufacturers incorporate thin monolithic structures designed to have high rigidity with minimal thickness of 1–2.5 mm [1]. Modern aircraft manufacturers incorporate thin monolithic structures designed to have high rigidity with minimal thickness of 1–2.5 mm [1] These monolithic thin-wall structures are fabricated by removing approximately 90–95% of the material from the blanks using the machining operation [2]. Since a large volume of material needs to be machined, the thin-wall machining process productivity needs to be significantly improved by increasing the Material Removal Rate (MRR). The determination of the optimal process parameters is essential to effectively machine the low rigidity parts without affecting the surface and dimensional quality

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