Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

100
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
100

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Wettability-Driven void suppression and enhanced mechanical performance in Si₃N₄-Reinforced bamboo Fiber epoxy composites using COCOSO and ANN modeling.

Scientific reports·2025
Same author

An automated AI-powered IoT algorithm with data processing and noise elimination for plant monitoring and actuating.

PeerJ. Computer science·2024
Same author

Assessment of consolidative multi-criteria decision making (C-MCDM) algorithms for optimal mapping of polymer materials in additive manufacturing: A case study of orthotic application.

Heliyon·2024
Same author

EEGDepressionNet: A Novel Self Attention-Based Gated DenseNet With Hybrid Heuristic Adopted Mental Depression Detection Model Using EEG Signals.

IEEE journal of biomedical and health informatics·2024
Same author

Advanced Machining Technology for Modern Engineering Materials.

Materials (Basel, Switzerland)·2024
Same author

Predicting Mechanical Properties of Polymer Materials Using Rate-Dependent Material Models: Finite Element Analysis of Bespoke Upper Limb Orthoses.

Polymers·2024

Related Experiment Video

Updated: Sep 3, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K

Multiobjective Optimization of Heat-Treated Copper Tool Electrode on EMM Process Using Artificial Bee Colony (ABC)

Geethapriyan Thangamani1,2, Muthuramalingam Thangaraj3, Khaja Moiduddin4

  • 1Department of Mechanical Engineering, Indian Institute of Technology Indore, Indore 453552, India.

Materials (Basel, Switzerland)
|July 27, 2022
PubMed
Summary

Heat-treated copper electrodes enhance electrochemical micromachining (EMM) of aluminum alloys. Annealed electrodes yield high material removal rates with low overcut, while quenched electrodes improve precision for components like turbine blades.

Keywords:
ABCEMMmachiningoptimizationsurface

More Related Videos

Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

1.2K
Author Spotlight: Computing the Effects of a Local Radiofrequency Hyperthermia Intervention on Tumor Biomechanics
10:23

Author Spotlight: Computing the Effects of a Local Radiofrequency Hyperthermia Intervention on Tumor Biomechanics

Published on: December 1, 2023

533

Related Experiment Videos

Last Updated: Sep 3, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

1.7K
Surrogate Model Development for Digital Experiments in Welding
09:17

Surrogate Model Development for Digital Experiments in Welding

Published on: March 28, 2025

1.2K
Author Spotlight: Computing the Effects of a Local Radiofrequency Hyperthermia Intervention on Tumor Biomechanics
10:23

Author Spotlight: Computing the Effects of a Local Radiofrequency Hyperthermia Intervention on Tumor Biomechanics

Published on: December 1, 2023

533

Area of Science:

  • Manufacturing Engineering
  • Materials Science
  • Surface Engineering

Background:

  • Electrochemical micromachining (EMM) is vital for high-precision microcomponent fabrication.
  • Applications include manufacturing turbine blades for automotive and aerospace industries.
  • Optimizing EMM parameters is crucial for material-specific performance.

Purpose of the Study:

  • To investigate the impact of heat-treated copper tool electrodes on EMM of aluminum 8011 alloy.
  • To analyze the effects of varying process parameters on material removal rate (MRR), overcut, conicity, and circularity.
  • To determine optimal EMM parameters using artificial bee's colony (ABC) and TOPSIS algorithms.

Main Methods:

  • EMM process performed on aluminum 8011 alloy using heat-treated (annealed, quenched) copper electrodes.
  • Systematic variation of process parameters: voltage, electrolyte concentration, frequency, and duty factor.
  • Optimization using Artificial Bee's Colony (ABC) algorithm and TOPSIS; confirmation tests conducted.

Main Results:

  • Annealed electrodes achieved high MRR with reduced overcut.
  • Quenched electrodes demonstrated superior conicity and circularity compared to other treatments.
  • Optimal parameters identified: e.g., 14V, 30g/L electrolyte, 60Hz, 33% duty cycle for annealed electrodes.

Conclusions:

  • Heat treatment of copper electrodes significantly influences EMM performance on aluminum alloys.
  • Specific heat treatments (annealing, quenching) are beneficial for different performance metrics (MRR vs. precision).
  • Optimized parameters achieve high accuracy, with confirmation tests validating 95% response accuracy.