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Development of Multi-fidelity AI based Algorithm for precision machining of bi-metallic materials for Automobile Applications

Implementing Organization

Indian Institute of Technology (IIT)
Principal Investigator
Dr. Prithviraj Mukhopadhyay
Department Of Physics, Indian Institute of Technology (IIT) Delhi
CO-Principal Investigator
Dr. sudarsan Ghosh
Department Of Physics, Indian Institute of Technology (IIT) Delhi
CO-Principal Investigator
Prof. souvik Chakraborty
Department Of Physics, Indian Institute of Technology (IIT) Delhi

Project Overview

Precision machining of the crankshaft bearing bore and cylinder block is a major challenge in the manufacturing of an engine block. Cylindricity and superior surface topography are two most required aspects that industries are thriving to achieve for ameliorating the performance of engines. The crankshaft bearing bore consists of a housing made up of aluminium and the bearing caps are often cast iron or in some cases powdered (sintered) metal. In similar light, cylinder blocks consist of grey cast iron liner casted together with aluminium. Machining of such bores and cylindrical blocks require special class of customized tools that can effectively remove material from the bimetal at same time. Machining of bi-metal aluminium-cast iron blocks often exhibit higher machining vibrations, poor hole cylindricity and smeared metal giving rise to potential galvanic corrosion. such problems are largely a consequence of the differences in material properties. In the present proposal, diamond based abrasive tools will be indigenously developed for machining of bimetallic blocks along with application of a suitable metal working fluid (MWF) via twin-jet technique. It is believed that the use of MWFs along with these abrasives will minimize machining vibrations by effectively reducing the stick-slip friction. To assess the performance, a test part will be created to simulate the pairing of a cast aluminium alloy engine block with a cast iron cap. Furthermore, the proposal commits to develop a next generation intelligent Multi-Fidelity (MF) Artificial Intelligence (AI) based Algorithm that will enable to monitor and control the machining process. The promise in this direction crucially hinges on in-depth know-how, insight, and exhaustive comprehension of pivotal issues, namely, stochasticity, dynamic material behavior, active abrasive grit-work interaction and critical protrusion height. The combined challenges will be addressed using novel theoretical algorithms in conjunction with extensive experimental investigations. The outcome of this proposal will cater to immediate need of automobile manufacturing industries associated with machining bi-metal crankshaft bores. The proposed project idea is highly inter-disciplinary in nature wherein expertise of PIs' from manufacturing, and applied mechanics will be scouted.
Funding Organization
Funding Organization
Anusandhan National Research Foundation (ANRF)
Quick Information
Area of Research
Engineering Sciences
Focus Area
Mechanical Engineering
Start Year
2024
End Year
2027
Sanction Amount
₹ 37.36 L
Status
Ongoing
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
N/A
Startup (If Any)
00
No. of Patents
Filed :00
Grant :00
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