On the extrusion stage of linear friction welding of Ti 6Al 4V

Vairis, Achilles; Frost, M.

doi:10.1016/s0921-5093(99)00449-9

Cited by 156 publications

(123 citation statements)

References 3 publications

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“…[2][3][4] The process has many advantages over traditional fusion welding methods, including excellent mechanical properties, avoidance of melting, and very low defect rates.…”

Section: Linear Friction Welding (Lfw) Is a Solid-statementioning

confidence: 99%

“…The process is said to occur over four phases: [3,5,6] Phase 1-Initial phase. During this phase asperity contact exists between the two surfaces to be joined and heat is generated due to friction-see Figure 1(a).…”

Section: Linear Friction Welding (Lfw) Is a Solid-statementioning

confidence: 99%

“…Equation [3] is less susceptible to noise when compared to the numerical differentiation method. [6] Since the motion of the workpieces in these experiments was sinusoidal, Eq.…”

Section: B Analysis Of the Force And Displacement Historymentioning

confidence: 99%

“…[6] Since the motion of the workpieces in these experiments was sinusoidal, Eq. [3] was used for the analyses presented in this paper.…”

Section: B Analysis Of the Force And Displacement Historymentioning

confidence: 99%

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Energy and Force Analysis of Ti-6Al-4V Linear Friction Welds for Computational Modeling Input and Validation Data

McAndrew

Colegrove

Addison

et al. 2014

Metall Mater Trans A

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The linear friction welding (LFW) process is finding increasing use as a manufacturing technology for the production of titanium alloy Ti-6Al-4V aerospace components. Computational models give an insight into the process, however, there is limited experimental data that can be used for either modeling inputs or validation. To address this problem, a design of experiments approach was used to investigate the influence of the LFW process inputs on various outputs for experimental Ti-6Al-4V welds. The finite element analysis software DEFORM was also used in conjunction with the experimental findings to investigate the heating of the workpieces. Key findings showed that the average interface force and coefficient of friction during each phase of the process were insensitive to the rubbing velocity; the coefficient of friction was not coulombic and varied between 0.3 and 1.3 depending on the process conditions; and the interface of the workpieces reached a temperature of approximately approximately 1273 K (1000°C) at the end of phase 1. This work has enabled a greater insight into the underlying process physics and will aid future modeling investigations.

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“…[2][3][4] The process has many advantages over traditional fusion welding methods, including excellent mechanical properties, avoidance of melting, and very low defect rates.…”

Section: Linear Friction Welding (Lfw) Is a Solid-statementioning

confidence: 99%

Section: Linear Friction Welding (Lfw) Is a Solid-statementioning

confidence: 99%

“…Equation [3] is less susceptible to noise when compared to the numerical differentiation method. [6] Since the motion of the workpieces in these experiments was sinusoidal, Eq.…”

Section: B Analysis Of the Force And Displacement Historymentioning

confidence: 99%

“…[6] Since the motion of the workpieces in these experiments was sinusoidal, Eq. [3] was used for the analyses presented in this paper.…”

Section: B Analysis Of the Force And Displacement Historymentioning

confidence: 99%

See 2 more Smart Citations

Energy and Force Analysis of Ti-6Al-4V Linear Friction Welds for Computational Modeling Input and Validation Data

McAndrew

Colegrove

Addison

et al. 2014

Metall Mater Trans A

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“…In the case of Ti6Al4V which is studied in this paper, the extruded material from the two specimens forms a single joined flash, and not separate flashes for each specimen [4]. This indicates that the plastic material at the rubbing interface has been joined together at this stage.…”

Section: Introductionmentioning

confidence: 87%

Designing experiments to study welding processes: using the Taguchi method

Vairis¹,

Petousis²

2009

JESTR

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Identification of significant process parameters using experiments needs to be carefully formulated as it can be a resource demanding process. Using appropriate statistical techniques such as the Taguchi method of factorial design of experiments, the number of necessary experiments can be reduced and the statistical significance of parameters can be safely identified. In the case of linear friction welding it was found that the frequency of oscillation, power input and forging pressure are statistically insignificant for the range of friction pressures studied.Keywords: taguchi method, factorial design of experiments, friction welding. An experiment can be considered as a process seeking to answer one or more carefully formulated questions. It should have carefully described goals which will be used to choose the appropriate factors and their range, as well as the relevant procedure. The factors studied should not be covered by other variables, with the chosen experimental sequence removing the effects of the uncontrolled variables. Replication of the experiments will help to randomise the results taken, to limit bias from the experiments. While replication ensures a measure of precision, randomisation provides validity of the measure of precision. By using this technique, many evaluations are usually needed to get sufficient information which can be a time-consuming process. Journal of EngineeringThe term "design of experiments" was originated around 1920 by Ronald A. Fisher, a British scientist who studied and proposed a more systematic approach in order to maximize the knowledge gained from experimental data [1] nce then, design of experiments has become an important methodology that maximizes the knowledge gained from experimental data by using a smart positioning of points in the space. This methodology provides a strong tool to design and analyze experiments; it eliminates redundant observations and reduces the time and resources to make experiments.In general, we can say that a good distribution of points achieved through a DOE (design of experiments) technique will extract as much information as possible from a system, based on as few data points as possible. Ideally, a set of points made with an appropriate DOE should have a good distribution of input parameter configurations. This equates to having a low correlation between inputs. The DOE approach is important to determine the behavior of the objective function we are examining because it is able to identify which factors are more important. The choice of DOE depends mainly on the type of objectives and on the number of variables involved. Usually, only linear or quadratic relations are detected. However and fortunately, higher-order interactions are rarely important and for most purposes it is only necessary to evaluate the main effects of each variable. This can be done with just a fraction of the runs, using only a "high" and "low" setting for each factor and some center points when necessary.Therefore DOE statistical techniques are especia...

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