Design of Experiment in the Milling Process of Aluminum Alloys in the Aerospace Industry

Țîțu, Aurel Mihail; Sandu, Andrei Victor; Pop, Alina Bianca; Țîțu, Ștefan; Frățilă, Dragos Nicolae; Ceocea, Costel; Boroiu, Alexandru

doi:10.3390/app10196951

Cited by 22 publications

(12 citation statements)

References 17 publications

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“…Table 2 shows the parametric conditions for conducting the experimental t controlling parameters pulse on-time (Ton) and pulse current (I) each was va four levels. The steel was usually cut in the range of 150 V to 250 V [29,30]; there specific parameter was varied over only two levels so that the number of tests minimized. The other parameters were set as: machining gap = 2 mm; duty cycle polarity = positive.…”

Section: Methodsmentioning

confidence: 99%

The Performance Prediction of Electrical Discharge Machining of AISI D6 Tool Steel Using ANN and ANFIS Techniques: A Comparative Study

et al. 2022

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AISI-D6 steel is widely used in the creation of dies and molds. In the present paper, first the electrical discharge machining (EDM) of the aforementioned material is performed with a testing plan of 32 trials. Then, artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were applied to predict the outputs. The effects of some significant operational parameters—specifically pulse on-time (Ton), pulse current (I), and voltage (V)—on the performance measures of EDM processes such as the material removal rate (MRR), tool wear ratio (TWR), and average surface roughness (Ra) are extracted. To lead the process operators, process plans (i.e., parameter–effect correlations) are created. The outcomes exposed the upper values of pulse on-time caused by higher amounts of MRR and Ra, and likewise lower volumes of TWR. Furthermore, growing the pulse current resulted in upper volumes of the material removal rate, tool wear ratio, and surface roughness. Besides, the higher input voltage resulted in a lower amount of MRR, TWR, and Ra. The estimation models developed by using experimental data recounting MRR, TWR, and Ra. The root means the square error was used to determine the error of training models. Furthermore, the estimated outcomes based on the models have been proven with an unseen validation set of experiments. They are found to be in decent agreement with the experimental issues. The investigation shows the powerful learning capability of an ANFIS model and its advantage in terms of modeling complex linear machining processes.

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Section: Methodsmentioning

confidence: 99%

The Performance Prediction of Electrical Discharge Machining of AISI D6 Tool Steel Using ANN and ANFIS Techniques: A Comparative Study

et al. 2022

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“…In this study, full factorial design was used to observe and identify any changes in the response due to the changes made to the variables [ 26 ]. This is a reliable and efficient approach due to its ability to discover the main effect of each factor as well as the interaction between all factors of the process, thereby achieving the optimal conditions [ 23 , 24 , 25 ].…”

Section: Modeling and Simulationmentioning

confidence: 99%

“…DoE is a statistical tool including a set of techniques such as factorial design, fractional factorial design and response surface method that is widely used to investigate the relationships between the factors affecting a process and their effects on one or multiple outputs [ 26 ]. It is considered an efficient and cost-effective tool to determine these relationships and to optimize process parameters [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Optimization of a Patient-Specific External Fixation Device for Lower Limb Injuries

et al. 2021

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The use of external fixation devices is considered a valuable approach for the treatment of bone fractures, providing proper alignment to fractured fragments and maintaining fracture stability during the healing process. The need for external fixation devices has increased due to an aging population and increased trauma incidents. The design and fabrication of external fixations are major challenges since the shape and size of the defect vary, as well as the geometry of the human limb. This requires fully personalized external fixators to improve its fit and functionality. This paper presents a methodology to design personalized lightweight external fixator devices for additive manufacturing. This methodology comprises data acquisition, Computer tomography (CT) imaging analysis and processing, Computer Aided Design (CAD) modelling and two methods (imposed predefined patterns and topology optimization) to reduce the weight of the device. Finite element analysis with full factorial design of experiments were used to determine the optimal combination of designs (topology optimization and predefined patterns), materials (polylactic acid, acrylonitrile butadiene styrene, and polyamide) and thickness (3, 4, 5 and 6 mm) to maximize the strength and stiffness of the fixator, while minimizing its weight. The optimal parameters were found to correspond to an external fixator device optimized by topology optimization, made in polylactic acid with 4 mm thickness.

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“…The statistical approach, also known as design of experiment (DOE), allows researchers to evaluate the independent and interacting effect of various process variables under consideration. Therefore, statistical models were developed that aid in process optimization [ 88 , 89 , 90 ].…”

Section: Trends For Target Metal Ionmentioning

confidence: 99%

Donnan Membrane Process for the Selective Recovery and Removal of Target Metal Ions—A Mini Review

et al. 2021

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Membrane-based water purification technologies contribute significantly to water settings, where it is imperative to use low-cost energy sources to make the process economically and technically competitive for large-scale applications. Donnan membrane processes (DMPs) are driven by a potential gradient across an ion exchange membrane and have an advantage over fouling in conventional pressure driven membrane technologies, which are gaining attention. DMP is a removal, recovery and recycling technology that is commonly used for separation, purification and the concentrating of metals in different water and waste streams. In this study, the principle and application of DMP for sustainable wastewater treatment and prospects of chemical remediation are reviewed and discussed. In addition, the separation of dissolved metal ions in wastewater settings without the use of pressure driven gradients or external energy supply membrane technologies is highlighted. Furthermore, DMP distinctive configurations and operational factors are explored and the prospects of integrating them into the wastewater treatment plants are recommended.

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Design of Experiment in the Milling Process of Aluminum Alloys in the Aerospace Industry

Cited by 22 publications

References 17 publications

The Performance Prediction of Electrical Discharge Machining of AISI D6 Tool Steel Using ANN and ANFIS Techniques: A Comparative Study

The Performance Prediction of Electrical Discharge Machining of AISI D6 Tool Steel Using ANN and ANFIS Techniques: A Comparative Study

Optimization of a Patient-Specific External Fixation Device for Lower Limb Injuries

Donnan Membrane Process for the Selective Recovery and Removal of Target Metal Ions—A Mini Review

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