Article
Engineering, Mechanical
Ramasubbu Narasimmalu, Ramabalan Sundaresan, Rajmohan Murugesan
Summary: This study mainly analyzes the influencing factors of using EDM, WEDM, and LBM processes to produce square holes on Hastelloy B2 material. Square holes of different sizes were created on a 1.8mm thick Hastelloy B2 sheet, and multiple response variables were considered. The study found that wire electrical discharge machining performs better than laser machining, and a square electrode can cause unstable spark phenomena in the EDM process. The use of MOORA method enhances performance measurement.
JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING
(2022)
Article
Automation & Control Systems
Huan Liu, Jicheng Bai, Bo Zhang, Yan Cao, Shaojie Hou, Zimu Zhou
Summary: The micro-hole array machined by micro-EDM has been widely used in various industrial fields, but the accuracy of electrode breakthrough detection and servo tracking performance are often poor, negatively impacting efficiency and quality. A three-dimensional flow field model was developed to analyze gap flow before and after electrode breakthrough, proposing an online detection scheme and segmented servo strategy to improve machining efficiency and quality. Experiment results showed a 36% reduction in machining time for micro-hole array and ensured machining quality.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Automation & Control Systems
Benjamin Pereira, Christian Andrew Griffiths, Benjamin Birch, Andrew Rees
Summary: This research investigates the capability of a highly flexible industrial robot modified with a high-speed spindle for drilling aluminum. By identifying the optimal robot pose and settings, it shows potential for surpassing a traditional CNC machine in drilling experiments and further optimization.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Energy & Fuels
Rahman Ashena, Minou Rabiei, Vamegh Rasouli, Amir H. Mohammadi, Siamak Mishani
Summary: Proper selection of drilling parameters and dynamic behavior is crucial for improving drilling performance. Development of an efficient AI method to predict control parameters is critical for drilling optimization. The AI approach presented in the paper utilizes optimized ANNs to model non-linear, multi-input/output drilling system behavior, providing quantified recommendations on optimal drilling parameters.
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME
(2021)
Article
Chemistry, Multidisciplinary
Hany Gamal, Ahmed Abdelaal, Salaheldin Elkatatny
Summary: This study utilized machine learning techniques to predict ECD based on drilling parameters, constructed models, and validated them through key performance indices. The results showed that both models performed well in ECD estimation application.
Review
Computer Science, Information Systems
Yusra Abdulrahman, Edin Arnautovic, Vladimir Parezanovic, Davor Svetinovic
Summary: This paper extensively investigates the possibilities of integrating blockchain and Artificial Intelligence (AI) technologies in the field of aerospace engineering, with a focus on supply chain management and operational efficiency. The decentralized nature of blockchain has the potential to greatly improve various aspects of aircraft lifecycle management, while AI can revolutionize predictive supply chain models and detection of structural faults. The paper presents a comprehensive overview of the current state, potential applications, challenges, and future research directions in this field, comparing blockchain technology with traditional record management systems in terms of data storage, security, transparency, and traceability advantages. However, legal, regulatory, and technological readiness issues need to be addressed for wider acceptance in the industry. The findings emphasize the importance of targeted research and development to unlock new applications and drive innovation in aerospace engineering. This paper serves as a comprehensive survey for researchers, practitioners, policymakers, and industry stakeholders, illustrating the transformative potential of AI and blockchain in the aerospace sector.
Article
Automation & Control Systems
Wazed Ibne Noor, Tanveer Saleh, Mir Akmam Noor Rashid, Azhar Mohd Ibrahim, Mohamed Sultan Mohamed Ali
Summary: A sequential process combining LBMM and μEDM methods was developed to improve machining efficiency and hole quality. Studies suggest strong correlations between input and output parameters, leading to the development of an artificial neural network-based dual-stage modeling method for predicting the sequential process outputs. Evaluation of the model showed high accuracy levels for predicting μEDM time, short circuit/arcing count, and tool wear.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Multidisciplinary Sciences
Ahmed Abdelaal, Salaheldin Elkatatny, Abdulazeez Abdulraheem
Summary: Two models were developed using artificial neural networks and adaptive neuro-fuzzy inference system to estimate formation pressure gradient in real-time through drilling data. The models showed good accuracy in predicting pressure gradient, proving their reliability.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Industrial
Afzaal Ahmed, Jibin Boban, Mustafizur Rahman
Summary: The effectiveness of the novel tool geometry for debris evacuation in EED drilling is validated through CFD simulations and experiments.
CIRP ANNALS-MANUFACTURING TECHNOLOGY
(2021)
Article
Chemistry, Analytical
Long Ye, Krishna Kumar Saxena, Jun Qian, Dominiek Reynaerts
Summary: This study proposes the use of micro-EDM as a potential technique for fabricating artificial defects on bearing raceways. A methodology is developed to achieve full control of defect dimension and distribution and to characterize the defect surface efficiently. A linear regression model with two-way interactions based on ANOVA is presented to optimize the process parameters. Verification experiments show a good fit for approximately 80% of the observed data. The combination of optical microscopy and confocal microscopy is used to measure and compare the morphology and topography of the artificial defects. Micro-EDM shows great potential in terms of machining efficiency and dimensional controllability for achieving desired defect shapes on bearings.
Article
Automation & Control Systems
Peng Yu, Jinkai Xu, Yonggang Hou, Huadong Yu
Summary: Micro-EDM technology was used for deep hole drilling on flexible bellows, discussing key technologies and designing solutions, the results show that the designed devices and process can meet the drilling requirements of the deep hole, achieving an aspect ratio of 44:1.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Automation & Control Systems
Maren David Dangut, Zakwan Skaf, Ian K. Jennions
Summary: This paper explores the application of predictive maintenance in the aerospace industry and methods to address data imbalance issues. By utilizing a hybrid machine learning approach, it successfully predicts extremely rare aircraft component failures.
Article
Chemistry, Multidisciplinary
Kamonpong Jamkamon, Pichai Janmanee
Summary: In this study, a modified electrode with a step cylindrical shape was designed to improve the performance of electrical discharge machining for deep hole drilling. The experimental results showed significant increases in material removal rate and decreases in electrode wear ratio with the step cylindrical electrode compared to a conventional electrode. Additionally, the electrode design led to reduced gap clearance and concavity on the side wall of the drilled hole, as well as an increase in debris escape area and a decrease in machining time.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Alexey Osipov, Ekaterina Pleshakova, Artem Bykov, Oleg Kuzichkin, Dmitry Surzhik, Stanislav Suvorov, Sergey Gataullin
Summary: The purpose of this article is to develop an effective method for monitoring the state of the drill string and the bit in low-time delay mode. A experimental setup was created based on the phase-metric control method to continuously monitor the drilling process. By analyzing the electrical characteristics of the probing signal, the authors used deep learning methods to identify the state of the drill string and the bit. The WFT-2D-CapsNet method showed high accuracy in detecting transitions between rock layers and the condition of the bit.
Article
Mathematical & Computational Biology
Li Chen
Summary: The application of support vector machine regression prediction function in predicting drilling fluid performance parameters can reduce experimental workload, improve drilling fluid formulation design efficiency, and verify the prediction accuracy of the model through experiments.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Review
Engineering, Manufacturing
Recep Halicioglu, L. Canan Dulger, A. Tolga Bozdana
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2016)
Article
Engineering, Manufacturing
Adnan A. Ugla, Oguzhan Yilmaz, Ahmed R. J. Almusawi
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2018)
Article
Automation & Control Systems
Recep Halicioglu, L. Canan Dulger, A. Tolga Bozdana
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2017)
Article
Engineering, Mechanical
Oguzhan Yilmaz, Adnan A. Ugla
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2017)
Article
Engineering, Manufacturing
Hasan Demirtas, Oguzhan Yilmaz, Bahattin Kanber
MACHINING SCIENCE AND TECHNOLOGY
(2017)
Article
Computer Science, Interdisciplinary Applications
Recep Halicioglu, Late Canan Dulger, Ali Tolga Bozdana
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2018)
Article
Engineering, Mechanical
Ali Tolga Bozdana, Nazar Kais Al-Kharkhi
STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING
(2018)
Article
Engineering, Industrial
Hasan Demirtas, Oguzhan Yilmaz, Bahattin Kanber
JOURNAL OF MATERIALS PROCESSING TECHNOLOGY
(2018)
Review
Engineering, Multidisciplinary
Ismail Fidan, Orkhan Huseynov, Mohammad Alshaikh Ali, Suhas Alkunte, Mithila Rajeshirke, Ankit Gupta, Seymur Hasanov, Khalid Tantawi, Evren Yasa, Oguzhan Yilmaz, Jennifer Loy, Vladimir Popov, Ankit Sharma
Summary: This paper summarizes recent inventions in the field of Additive Manufacturing (AM), including factors affecting their development and commercialization, breakthroughs in materials and AM technologies, and their integration with emerging technologies. It explores the impact of AM in various sectors since the 1970s and discusses challenges and future directions, such as hybrid manufacturing and bio-printing, as well as socio-economic and environmental implications. This collaborative study provides a concise understanding of the latest inventions in AM, offering valuable insights for researchers, practitioners, and decision makers in diverse industries and institutions.
Proceedings Paper
Engineering, Manufacturing
Sadik Olguner, Ali Tolga Bozdana
ADVANCES IN DESIGN, SIMULATION AND MANUFACTURING II
(2020)
Article
Multidisciplinary Sciences
Adnan A. Ugla, Oguzhan Yilmaz
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2017)
Article
Engineering, Mechanical
Ali Tolga Bozdana, Nazar Kais Al-Karkhi
MECHANICAL SCIENCES
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Recep Halicioglu, L. Canan Dulger, A. Tolga Bozdana
2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP)
(2017)
Article
Engineering, Manufacturing
Ali Tolga Bozdana, Tugba Ulutas
MATERIALS AND MANUFACTURING PROCESSES
(2016)
Article
Physics, Multidisciplinary
S. Olguner, A. Tolga Bozdana
ACTA PHYSICA POLONICA A
(2017)
