Sivasrinivasu Devadula

Employment

• Indian Institute of Technology Madras Associate Professor

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (25)

• A new approach for product reliability prediction by considering the production factory lifecycle information
  Reliability Engineering & System Safety 2025 DOI: 10.1016/j.ress.2025.110915
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• Identifying Joint Dynamics in Bolted Cantilevered Systems Under Varying Tightening Torques and Torsional Excitations
  Journal of Vibration Engineering and Technologies 2022 DOI: 10.1007/s42417-021-00386-8
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• Modeling of abrasive waterjet generated kerf on the top layer of a multi-layered structure
  CIRP Journal of Manufacturing Science and Technology 2022 DOI: 10.1016/j.cirpj.2022.06.010
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• Optimal number of thermal hotspots selection on motorized milling spindle to predict its thermal deformation
  Materials Today: Proceedings 2022 DOI: 10.1016/j.matpr.2022.04.267
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• A novel iterative-based field search technique for roundness evaluation
  Procedia Manufacturing 2021 DOI: 10.1016/j.promfg.2021.06.030
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• Machining Thin-walled 2 1/2 D Structure in a Novel Aluminium Carbon Fiber Composite Material by the Abrasive Waterjets–an experimental investigation
  Advances in Materials and Processing Technologies 2021 DOI: 10.1080/2374068X.2021.1927650
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• Modelling of abrasive waterjet kerf in a double-layered structure
  Journal of Manufacturing Processes 2021 DOI: 10.1016/j.jmapro.2021.07.053
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• A study on the interaction of jet with constituent layers of multilayered structure in through kerfing with abrasive waterjets
  Journal of Manufacturing Processes 2020 DOI: 10.1016/j.jmapro.2020.10.046
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• Experimental investigations on the surface characteristics of abrasive waterjet-milled pockets in aluminium 6061-T6 alloy
  Advances in Materials and Processing Technologies 2020 DOI: 10.1080/2374068X.2020.1815136
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• Image Data-Based Surface Texture Characterization and Prediction Using Machine Learning Approaches for Additive Manufacturing
  Journal of Computing and Information Science in Engineering 2020 DOI: 10.1115/1.4045719
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