Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

Autor: Syed Wasim Hassan Zubair, Syed Muhammad Arafat, Sarmad Ali Khan, Sajawal Gul Niazi, Muhammad Rehan, Muhammad Usama Arshad, Nasir Hayat, Tauseef Aized, Ghulam Moeen Uddin, Fahid Riaz

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-28 (2024)

Abstract The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (61

Externí odkaz: https://doaj.org/article/cddc82ea4bc744f5b98f4b9394be24c3

Computational structural analysis of 3D printed hip joint implant and comparison of bio-compatible coating materials for design parameters: Coating thickness, hardness, and adhesion requirements

Autor: Ghulam Moeen Uddin, Muhammad Waqar Nasir, Syed Muhammad Arafat, Syed Wasim Hassan Zubair, Abdul Rehman, Muhammad Arslan Younis, Sara Moazam, Muhammad Shazad Khan, Sajawal Gul Niazi, Waqar Muhammad Ashraf, Muhammad Taimoor Adil

Publikováno v: Advances in Mechanical Engineering, Vol 11 (2019)

This research article presents a design parameter assessment technique for three-dimensional printed hip joint implants. A coupled experimental-simulation-based design technique, addressing minimum coating thickness, hardness, and adhesion requiremen

Externí odkaz: https://doaj.org/article/3a478946507f41608b97ded14227e31b

Optimization of a 660 MWe Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management. Part 2. Power Generation

Autor: Waqar Muhammad Ashraf, Ghulam Moeen Uddin, Ahmad Hassan Kamal, Muhammad Haider Khan, Awais Ahmad Khan, Hassan Afroze Ahmad, Fahad Ahmed, Noman Hafeez, Rana Muhammad Zawar Sami, Syed Muhammad Arafat, Sajawal Gul Niazi, Muhammad Waqas Rafique, Ahsan Amjad, Jawad Hussain, Hanan Jamil, Muhammad Shahbaz Kathia, Jaroslaw Krzywanski

Publikováno v: Energies, Vol 13, Iss 21, p 5619 (2020)

Modern data analytics techniques and computationally inexpensive software tools are fueling the commercial applications of data-driven decision making and process optimization strategies for complex industrial operations. In this paper, modern and re

Externí odkaz: https://doaj.org/article/d8a004df158e47fa95eb37a7ef41efc1

Artificial intelligence-based Monte-Carlo numerical simulation of aerodynamics of tire grooves using computational fluid dynamics

Autor: Ali Hussain Kazim, Nasir Hayat, Syed Muhammad Arafat, Ibrahim Zeid, Muhammad Farhan, Ghulam Moeen Uddin, Sajawal Gul Niazi, Sagar Kamarthi

Publikováno v: Artificial Intelligence for Engineering Design, Analysis and Manufacturing. 33:302-316

In the current work, the effects of design (groove depth and groove width) and operational (temperature and velocity) parameters on aerodynamic performance parameters (coefficient of drag and coefficient of lift) of an isolated passenger car tire hav

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::30d9780f50a73a944c40a4f2fd9be216
https://doi.org/10.1017/s0890060419000039

Optimization of a 660 MWe Supercritical Power Plant Performance—A Case of Industry 4.0 in the Data-Driven Operational Management Part 1. Thermal Efficiency

Autor: Sajawal Gul Niazi, Sher Afghan, Uwe Naumann, Ashfaq Ahmad, A. Jamil, Nasir Hayat, Ahmad Kamal, Muhammad Waqas Rafique, Muhammad Asim, Muhammad Haider Khan, Ijaz Ahmad Chaudhary, Ghulam Moeen Uddin, Shao Changkai, Hanan Jamil, Jaroslaw Krzywanski, Syed Muhammad Arafat, Waqar Muhammad Ashraf, Liu Bin Xiang

Publikováno v: Energies; Volume 13; Issue 21; Pages: 5592
Energies, Vol 13, Iss 5592, p 5592 (2020)
Energies : open-access journal of related scientific research, technology development and studies in policy and management 13(21), 5592 (2020). doi:10.3390/en13215592 special issue: "Special Issue "Novel Combustion Techniques for Clean Energy" / Special Issue Editors Prof. Dr. Wojciech Nowak, Dr. Jaroslaw Krzywanski, Dr. Karol Sztekler"

Energies 13(21), 5592 (2020). doi:10.3390/en13215592
Published by MDPI, Basel

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec2ce113164d4ceeee8b81e952bfa27f