A comparative investigation of Taguchi and full factorial design for machinability prediction in turning of a titanium alloy

Kechagias, John; Aslani, Κyriaki-Evangelia; Fountas, Nikolaos A.; Vaxevanidis, Nikolaos M.; Manolakos, D.E.

doi:10.1016/j.measurement.2019.107213

Cited by 102 publications

(59 citation statements)

References 22 publications

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“…Taguchi's experimental method was developed for single response optimization, but in the case of two or more responses optimization, this method is unsuitable [10][11][12]. Hence, Grey Taguchi approach can be used for creating a single response from different performance features [13].…”

Section: Resultsmentioning

confidence: 99%

Impact of process parameters on dimensional accuracy of PolyJet 3D printed parts using grey Taguchi method

et al. 2020

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In this study, the dimensional accuracy of parts fabricated with PolyJet 3D Printing Direct process is investigated. An L4 orthogonal array was utilized as the design of experiments, while the process parameters examined are layer thickness, build style and scale. A simple prototype was proposed and specified external and internal dimensions were measured using a digital vernier calliper. Grey-Taguchi method was applied for optimizing all dimensional measurements. The effect of each parameter on dimensional accuracy has been identified using ANOM (Analysis of Means), while ANOVA (Analysis of Variances) has been performed to determine each parameter’s dominance. Additionally, the results of this study were compared with the findings of a previous optimization study in which the usual Taguchi method was used. It was concluded that 16 μm of layer thickness, glossy style and 50% scale provide the optimum dimensional results, while scale is the most important factor.

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Section: Resultsmentioning

confidence: 99%

Impact of process parameters on dimensional accuracy of PolyJet 3D printed parts using grey Taguchi method

et al. 2020

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“…Materials harder to process are widely used in the aircraft, automotive, shipbuilding and energy industries for the production of complex and varied components; therefore, materials based on nickel, titanium and steels with improved mechanical properties have been investigated in order to understand the factors degrading the machining process thoroughly. In recent decades, various milling methods have been investigated and analysed to increase productivity [1,[13][14][15], the subject of the investigation also included the following aspects: high-speed machining with respect to the removed material [2,13,14]; simulation methods aiming to implement different control models and the real behaviour of machines to eliminate machine failure and downtime [16,17]; adjusting tool feeds aiming to optimize the production cycle time; process monitoring to evaluate tool wear for titanium or nickel-based alloys [1,18]. The possibilities of the predictive model are control of the machining process in order to reduce vibrations, increase the stability of the cut and efficiency of the cutting process [19]; and trochoidal milling in connection with finish operations in machining superalloys based on nickel [20][21][22].…”

Section: Research Of Trochoidal Millingmentioning

confidence: 99%

Analysis and Prediction of the Machining Force Depending on the Parameters of Trochoidal Milling of Hardened Steel

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Current demands on quality are the engine of searching for new progressive materials which should ensure enough durability in real conditions. Due to their mechanical properties, however, they cannot be applied to conventional machining methods. In respect to productivity, one of the methods is the finding of such machining technologies which allow achieving an acceptable lifetime of cutting tools with an acceptable quality of a machined surface. One of the mentioned technologies is trochoidal milling. Based on our previous research, where the effect of changing cutting conditions (cutting speed, feed per tooth, depth of cut) on tool lifetime was analysed, next, we continued with research on the influences of trochoid parameters on total machining force (step and engagement angle) as parameters adjustable in the CAM (computer-aided machining) system. The main contribution of this research was to create a mathematical-statistical model for the prediction of cutting force. This model allows setting up the trochoid parameters to optimize force load and potentially extend the lifetime of the cutting tool.

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“…The major signature of conventional machining is that there is direct contact between the cutting tool and the workpiece. As shown in Supplementary Table S1, the different machining operations under this category include turning, milling and drilling which are performed under dry or wet conditions [38][39][40]. These operations have other variants such as micro milling, face milling, planar milling, angular milling, horizontal drilling, directional drilling, ultra-precision machining to mention a few [41][42][43].…”

Section: Conventional Machiningmentioning

confidence: 99%

“…In fact, in most cases, only a few of the factors that influence machining are accommodated in experiments in order to avoid large experimental matrix and associated cost. Consequently, mathematical modelling, numerical simulation, Taguchi experimental design, full factorial experimental design and finite element modelling are now being utilised in studying the influence of machining parameters on the tool life and machinability of titanium alloys [20,38,67,[90][91][92]. These paved way for incorporating a large number of machining variables for modelling and simulations and the outcomes are validated experimentally.…”

Section: Summary Of Conventional Machining Processesmentioning

confidence: 99%

An overview of conventional and non-conventional techniques for machining of titanium alloys

et al. 2020

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Machining is one of the major contributors to the high cost of titanium-based components. This is as a result of severe tool wear and high volume of waste generated from the workpiece. Research efforts seeking to reduce the cost of titanium alloys have explored the possibility of either eliminating machining as a processing step or optimising parameters for machining titanium alloys. Since the former is still at the infant stage, this article provides a review on the common machining techniques that were used for processing titanium-based components. These techniques are classified into two major categories based on the type of contact between the titanium workpiece and the tool. The two categories were dubbed conventional and non-conventional machining techniques. Most of the parameters that are associated with these techniques and their corresponding machinability indicators were presented. The common machinability indicators that are covered in this review include surface roughness, cutting forces, tool wear rate, chip formation and material removal rate. However, surface roughness, tool wear rate and metal removal rate were emphasised. The critical or optimum combination of parameters for achieving improved machinability was also highlighted. Some recommendations on future research directions are made.

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A comparative investigation of Taguchi and full factorial design for machinability prediction in turning of a titanium alloy

Cited by 102 publications

References 22 publications

Impact of process parameters on dimensional accuracy of PolyJet 3D printed parts using grey Taguchi method

Impact of process parameters on dimensional accuracy of PolyJet 3D printed parts using grey Taguchi method

Analysis and Prediction of the Machining Force Depending on the Parameters of Trochoidal Milling of Hardened Steel

An overview of conventional and non-conventional techniques for machining of titanium alloys

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