Optimizing conventional machining process parameters for A713 aluminum alloy using Taguchi method and passive optical network for data transmission
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Vikas Sharma
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Sachin Kumar
Abstract
This study focuses on optimizing machining parameters for A713 aluminum alloy, renowned for its high strength-to-weight ratio but challenging to machine with precision. Using the Taguchi method, key parameters – cutting speed, feed rate, and depth of cut – are optimized to improve surface finish, tool life, and dimensional accuracy. An L9 orthogonal array is applied to enhance experimental efficiency. Furthermore, the integration of Passive Optical Network (PON) technology facilitates real-time data monitoring and transmission, enabling continuous feedback and timely adjustments. This hybrid approach of Taguchi optimization and PON technology achieves superior machining performance, boosting surface quality and operational efficiency. The research highlights how modern data transmission solutions like PON can enhance traditional optimization methods, providing a scalable framework for advanced machining processes in industrial applications.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: I (Dr.Vikas Sharma) am accepted all the responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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