Desirability Function Analysis (DFA) in Multiple Responses Optimization of Abrasive Water Jet Cutting Process

Perec, Andrzej

doi:10.31181/rme200103011p

Cited by 18 publications

(4 citation statements)

References 7 publications

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“…The arched machining traces (Fig. 13a) in this material are much clearer than in the case of metal materials, for example, nickel-based superalloy [39], cooper [40] or steel [41], and are visible on the entire surface, although slightly in its upper part weaker than at the bottom. The surface is not dull.…”

Section: Fig 12mentioning

confidence: 77%

Process Optimization by Applying the Response Surface Methodology (Rsm) to the Abrasive Suspension Water Jet Cutting of Phenolic Composites

Perec,

Radomska-Zalas,

Fajdek-Bieda

et al. 2023

FU Mech Eng

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The paper introduces the study on the cutting of the industrial composite phenolic resin, based on the thermoset materials reinforced with cotton cloth by the Abrasive Water Suspension Jet (AWSJ). The size reduction of abrasive grains during the formation of the jet and the erosion phenomenon are shown. The results of the machining process's critical factors as nozzle length, nozzle diameter, and abrasive mass flow rate on the maximal cutting depth, are indicated. To build a model of the process, the method of the response surface (RSM) was applied. The second-degree multinomial equation is selected for creating the cutting model. The research indicates the optimal control factors of the process, to achieve the best cutting depth performance.

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Section: Fig 12mentioning

confidence: 77%

Process Optimization by Applying the Response Surface Methodology (Rsm) to the Abrasive Suspension Water Jet Cutting of Phenolic Composites

Perec,

Radomska-Zalas,

Fajdek-Bieda

et al. 2023

FU Mech Eng

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“…Given the process's complexity and the large number of factors investigated, multi-objective optimization is a critical asset to exploit in order to achieve industrial criteria for cost, quality, and productivity [27]. Both approaches (DF and GRA) were employed in this research to achieve this objective.…”

Section: Multi-objective Optimization Of Cutting Parametersmentioning

confidence: 99%

Minimizing Tool Wear, Cutting Temperature and Surface Roughness in the Intermittent Turning of AISI D3 Steel Using the DF and GRA Method

Khelfaoui¹,

Yallese²,

Boucherit³

et al. 2023

Tribol. Ind.

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Intermittent turning (IT) is characterized by a different context than continuous turning (CT). The cutting tool is shocked each time it goes off-load and engages a new surface. This interruption causes severe cutting conditions, which fatally affect the performance parameters. The purpose of this study is to assess the effects of four cutting factors, tool nose radius (r), cutting speed (Vc), feed rate (f), and depth of cut (ap), on the following output performance parameters: surface roughness (Ra), cutting temperature (T°), and cutting tool wear (VB) during turning (IT) AISI D3 cold work tool steel. A triple CVD (AI2O3/TiC/TiCN)-coated carbide cutting tool was used. A Taguchi L9 (3^4) experimental design was adopted for carrying out the experiments in intermittent turning. To improve the performance parameters based on three (3) highly particular scenarios that fulfill industrial criteria, the desirability function (DF) and the grey relational analysis method (GRA) were used. Finally, the optimization findings of the two strategies were compared in order to evaluate the performance of each method.

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“…On the other hand, AISI D3 high-alloy steel has been the subject of several experimental studies that focus on machinability, MQ lubrication, tool wear, modeling, and optimization of cutting conditions [13][14][15][16][17][18][19][20]. Also, the desirability function approach is among the multi-objective optimization methods extensively used in many industrial sectors because of the advantages it presents [21][22][23][24][25][26][27][28]. Several researchers have adopted the GRA method as a multi-objective optimization method for cutting conditions due to its effectiveness in making the right decision for selecting the optimal parameters [29][30][31][32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Statistical analysis, modeling and multi-objective optimization of parameters intermittent turning process of AISI D3

Khelfaoui

Yallese

Ouelaa

et al. 2023

JMES

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Intermittent machining is characterized by its complex and irregular context. This intermittency causes machining to occur under difficult conditions that greatly influence the technological performance parameters. The aim of the present work is to evaluate the effects of input parameters, cutting speed, Vc, depth of cut, ap, tool nose radius, r and feed rate, f, on surface roughness, Ra, tangential cutting force, Fz, motor power consumption, Pm, cutting power, Pc and material removal rate (MRR), during intermittent turning (IT) of AISI D3 tool steel. Machining was performed with a triple CVD coated carbide tool (AI2O3/TiC/TiCN) by adopting a Taguchi L9 (3^4) experimental design. The ANOVA and RSM methods were used to analyze the effects of cutting factors on the outputs parameters resulting in statistical prediction models. In addition, a multi-objective optimization of the cutting conditions exploiting the desirability function (DF) was done according to four cases of relative importance corresponding to different industrial contexts. Furthermore, the grey relational analysis (GRA) method was applied and compared with the DF method. The results show that the optimal regime found by the DF method, (r =1.6mm, Vc= 240 m/min, f = 0.084 mm/rev and ap = 0.64 mm), favors Ra and MRR. On the other hand, for the GRA method, the combination of (r = 0.4 mm, Vc = 240 m/min f = 0.08 mm/rev and ap = 0.3 mm) favors the minimization of Fz, Pm and Pc. This work presents an originality because the results found are very useful in the field of optimization for a better control of the process IT.

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Desirability Function Analysis (DFA) in Multiple Responses Optimization of Abrasive Water Jet Cutting Process

Cited by 18 publications

References 7 publications

Process Optimization by Applying the Response Surface Methodology (Rsm) to the Abrasive Suspension Water Jet Cutting of Phenolic Composites

Process Optimization by Applying the Response Surface Methodology (Rsm) to the Abrasive Suspension Water Jet Cutting of Phenolic Composites

Minimizing Tool Wear, Cutting Temperature and Surface Roughness in the Intermittent Turning of AISI D3 Steel Using the DF and GRA Method

Statistical analysis, modeling and multi-objective optimization of parameters intermittent turning process of AISI D3

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