Abstract :

Present Automation In Welding ,milling, And Polishing Operations In Automobile And Aircraft Manufacturing , Not Able To Control , Optimise The Operations By The Robotic Machines, Arms, Legs, Stands, Tool Handlers, Positioners. The Present System Do Not Have The Dynamic Adaptive ,sensitiveness For Physical Mechanical Dynamics ,kinetics Like A Human Muscle Adaptiveness, Bio Mechanics As Per The Target Operation , Trajectory And Dynamic Environment With The Obstacles, Heat ,vibrations Resonance, Disturbed Machine Behaviour Action,reaction . Abstract : This Research Paper Presents An Advanced Automation Framework Using Modern AI ML DL , Behaviour Models , Transformers Architecture , Attention Mechanism For Welding, Milling, And Polishing Operations In Automobile And Aircraft Manufacturing Using Intelligent Robotic Arms. The System Integrates Hydraulic And Pneumatic Actuation, Adaptive PID Control Enhanced With Transform-based Modeling, And Reinforcement Learning. Multi-head Attention Mechanisms Process Real-time Sensor Data Such As Vibration, Dust, Thermal Variation, And Geometric Deviations. Classical Mathematical Foundations Including Lagrangian Dynamics, Laplace Transforms, Fourier Analysis, And Taylor Series Are Embedded Into The Control And Learning Pipeline To Achieve Precision, Stability, And Sustainability. Keywords: Industrial Automation, Robotic Arms, Adaptive PID, Reinforcement Learning, Multi-Head Attention, Lagrangian Dynamics, Laplace Transform, Fourier Transform, Taylor Series, ARL - Adaptive Reinforcement Learning, EMHA - Environment Multi Head Attention; FSS - Fusion Sensor Systems ; AI ML - Artificial Intelligence, Machine Learning; SDP - Sensor Data Parameters, SDPD- SPD Decriptor, OPV- Output Parameter Value;

Published:

09-2-2026

Issue:

Vol. 26 No. 2 (2026)

Page Nos:

19-21

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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