Modelling, simulation and experimental validation of the milling operation of titanium alloy (Ti6Al4V)

Daniyan, Ilesanmi; Fameso, Festus; Ale, Felix; Bello, Kazeem Aderemi; Tlhabadira, Isaac

doi:10.1007/s00170-020-05714-y

Cited by 23 publications

(5 citation statements)

References 27 publications

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“…The feasible combination of the process parameters was done using the Response Surface Methodology (RSM). The choice of the RSM was based on its ability to iteratively study the cross-effect of process parameters [33][34][35]. The numerical experimentation comprises a four factor experimental design, which varied at different levels in the following ranges; feed rate (250 − 350 mm/rev), spindle speed (1000 − 3000 rpm), cutting speed (100 − 300 m/min) and depth of cut (0.3 − 0.9 mm).…”

Section: The Response Surface Methodologymentioning

confidence: 99%

DEVELOPMENT OF NUMERICAL MODELS FOR THE PREDICTION OF TEMPERATURE AND SURFACE ROUGHNESS DURING THE MACHINING OPERATION OF TITANIUM ALLOY (Ti6Al14V)

et al. 2020

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Temperature and surface roughness are important factors, which determine the degree of machinability and the performance of both the cutting tool and the work piece material. In this study, numerical models obtained from the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques were used for predicting the magnitude of the temperature and surface roughness during the machining operation of titanium alloy (Ti6Al4V). The design of the numerical experiment was carried out using the Response Surface Methodology (RSM) for the combination of the process parameters while the Artificial Neural Network (ANN) with 3 input layers, 10 sigmoid hidden neurons and 3 linear output neurons were employed for the prediction of the values of temperature. The ANN was iteratively trained using the Levenberg-Marquardt backpropagation algorithm. The physical experiments were carried out using a DMU80monoBLOCK Deckel Maho 5-axis CNC milling machine with a maximum spindle speed of 18 000 rpm. A carbide-cutting insert (RCKT1204MO-PM S40T) was used for the machining operation. A professional infrared video thermometer with an LCD display and camera function (MT 696) with infrared temperature range of −50−1000 °C, was employed for the temperature measurement while the surface roughness of the work pieces were measured using the Mitutoyo SJ – 201, surface roughness machine. The results obtained indicate that there is high degree of agreement between the values of temperature and surface roughness measured from the physical experiments and the predicted values obtained using the ANN and RSM. This signifies that the developed RSM and ANN models are highly suitable for predictive purposes. This work can find application in the production and manufacturing industries especially for the control, optimization and process monitoring of process parameters.

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Section: The Response Surface Methodologymentioning

confidence: 99%

DEVELOPMENT OF NUMERICAL MODELS FOR THE PREDICTION OF TEMPERATURE AND SURFACE ROUGHNESS DURING THE MACHINING OPERATION OF TITANIUM ALLOY (Ti6Al14V)

et al. 2020

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“…The guidelines for the bearings for jet engines were considered for the identification of the product's properties in relation to the service requirements [32]. The emphasis on the Ti-6Al-4V alloy is due to its main features, which are light weight, high strength (yield strength of approximately 1000 MPa), high temperature characteristics (maximum melting point for grade 5 is at 1933 K), thermal processability, fracture toughness, workability, and superior formability [33][34][35][36]. This alloy is currently the most preferred for aircraft manufacturing owing to its theo- retical chemical composition properties, good hightemperature properties and high strength-to-weight ratio [37,38].…”

Section: Mesh Generation and Geometric Modelmentioning

confidence: 99%

Design and simulation of a bearing housing aerospace component from titanium alloy (Ti6Al4V) for additive manufacturing

et al. 2022

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In evaluating emerging technology, such as additive manufacturing, it is important to analyse the impact of the manufacturing process on efficiency in an objective and quantifiable manner. This study deals with the design and simulation of a bearing housing made from titanium alloy (Ti6Al4V) using the selective laser melting (SLM) technique. The Finite Element Analysis (FEA) method was used for assessing the suitability of Ti6Al4V for aerospace application. The choice of Ti6Al4V is due to the comparative advantage of its strength-to-weight ratio. The implicit and explicit modules of the Abaqus software were employed for the non-linear and linear analyses of the component part. The results obtained revealed that the titanium alloy (Ti6Al4V) sufficiently meets the design, functional and service requirements of the bearing housing component produced for aerospace application. The designed bearing is suitable for a high speed and temperature application beyond 1900 K, while the maximum stress induced in the component during loading was 521 kPa. It is evident that the developed stresses do not result in a distortion or deformation of the material with yield strength in the region of 820 MPa. This work provides design data for the development of a bearing housing for AM under the technique of SLM using Ti6Al4V by reflecting the knowledge of the material behaviour under the operating conditions.

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“…The validation of the numerical experiments was done via physical experiments as well as the Analysis of Variance (ANOVA). The indicators for determining the validity of a numerical experiments include the: "p-value Prob > F" (which should be less than 0.050), "Lack of Fit" (which should be statistically insignificant compared to the pure error) as well as the correlation coefficients, namely the predicted R square, R squared and the adjusted R Squared (which should be close to 1) for a statistically significant model [39].…”

Section: Optimization Of the Conversion Processmentioning

confidence: 99%

Process optimization and performance evaluation of a downdraft gasifier for energy generation from wood biomass

Daniyan

Ale²,

Uchegbu

et al. 2021

Acta Polytech

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In recent time, due to the increasing demand for energy and the need to address environment-related issues, a great deal of focus has been given to alternative sources of energy, which are green, sustainable and safe. This work considers the process optimization and performance evaluation of a downdraft gasifier, suitable for energy generation using wood biomass. The assessment of the performance of the downdraft gasifier was based on the amount of output energy generated as well as the emission characteristics of the output. The Response Surface Methodology (RSM) was employed for the determination of the optimum range of the process parameters that will yield the optimum conversion of the biomass to energy. The optimum process parameters that produced the highest rate of conversion of biomass to energy (2.55 Nm3/kg) during the physical experiments were: temperature (1000 °C), particle size (6.0 mm) and residence time (35 min). The produced gas indicated an appreciable generation of methane gas (10.04 % vol.), but with a significant amount of CO (19.20 % vol.) and CO2 (22.68 % vol.). From the numerical results obtained, the gas yield was observed to increase from 1.86908 Nm3/kg to 2.40324 Nm3/kg as the temperature increased from 800 °C to 1200 °C. The obtained results indicate the feasibility for the production of combustible gases from the developed system using wood chips. It is envisaged that the findings of this work will assist in the development of an alternative and renewable energy source in an effort to meet the growing energy requirements.

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Modelling, simulation and experimental validation of the milling operation of titanium alloy (Ti6Al4V)

Cited by 23 publications

References 27 publications

DEVELOPMENT OF NUMERICAL MODELS FOR THE PREDICTION OF TEMPERATURE AND SURFACE ROUGHNESS DURING THE MACHINING OPERATION OF TITANIUM ALLOY (Ti6Al14V)

DEVELOPMENT OF NUMERICAL MODELS FOR THE PREDICTION OF TEMPERATURE AND SURFACE ROUGHNESS DURING THE MACHINING OPERATION OF TITANIUM ALLOY (Ti6Al14V)

Design and simulation of a bearing housing aerospace component from titanium alloy (Ti6Al4V) for additive manufacturing

Process optimization and performance evaluation of a downdraft gasifier for energy generation from wood biomass

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