Mathematical Model for Prediction and Optimization of Weld Bead Geometry in All-Position Automatic Welding of Pipes

Liao, Baoyi; Shi, Yonghua; Cui, Yanxin; Cui, Shuwan; Jiang, Zexin; Yi, Yaoyong

doi:10.3390/met8100756

Cited by 8 publications

(2 citation statements)

References 17 publications

(18 reference statements)

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“…Table 4 , Table 5 , Table 6 , Table 7 and Table 8 represent the ANOVA analysis of the recorded machine torque, PZ temperature, surface roughness of the processed zone, hardness values, and UTS mathematical model. The values of “Prob > F” less than 0.0500 indicate mathematical model terms are significant, and a value greater than 0.1000 indicate the model terms are not significant [ 37 ]. Table 4 , Table 5 , Table 6 , Table 7 and Table 8 show the result of ANOVA for the recorded machine torque model, PZ temperature model, surface roughness in processing paths, hardness value, and the UTS models, respectively, and the F-values of the mathematical models are 29.82, 349.14, 93.55, 307.55, and 650.71.…”

Section: Resultsmentioning

confidence: 99%

Optimization of Bobbin Tool Friction Stir Processing Parameters of AA1050 Using Response Surface Methodology

et al. 2022

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The current research designed a statistical model for the bobbin tool friction stir processing (BT-FSP) of AA1050 aluminum alloy using the Response Surface Method (RSM). The analysis studied the influence of tool travel speeds of 100, 200, and 300 mm/min and different pin geometries (triangle, square, and cylindrical) at a constant tool rotation speed (RS) of 600 rpm on processing 8 mm thickness AA1050. The developed mathematical model optimizes the effect of the applied BT-FSP parameters on machine torque, processing zone (PZ) temperature, surface roughness, hardness values, and ultimate tensile strength (UTS). The experimental design is based on the Face Central Composite Design (FCCD), using linear and quadratic polynomial equations to develop the mathematical models. The results show that the proposed model adequately predicts the responses within the processing parameters, and the pin geometry is the most influential parameter during the BT-FSP of AA1050. The analysis of variance exhibit that the developed mathematical models can effectively predict the values of the machine torque, PZ temperature, surface roughness, hardness, and UTS with a confidence level of over 95% for the AA1050 BT-FSP. The optimization process shows that the optimum parameters to attain the highest mechanical properties in terms of hardness and tensile strength at the lowest surface roughness and machine torque are travel speed (TS) of 200 mm/min using cylindrical (Cy) pin geometry at the constant RS of 600 rpm. The PZ temperature of the processed specimens decreased with increasing TS at different pin geometries. Meanwhile, the surface roughness of the processed passes and machine torque increased with increasing the TS at different pin geometries. Increasing TS from 100 to 300 mm/min increases the hardness values of the processed materials using different pin geometries. The highest UTS of 79 MPa for the processed specimens was attained at the TS of 200 mm/min and RS of 600 rpm using the Cy pin geometry.

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Section: Resultsmentioning

confidence: 99%

Optimization of Bobbin Tool Friction Stir Processing Parameters of AA1050 Using Response Surface Methodology

et al. 2022

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“…RSM is a widely used modelling technique which is used to develop a mathematical relationship between the machining variables and output responses [40,41]. RSM consists of both modelling and statistic approaches.…”

Section: Design Matrix As Per the Response Surface Methodologymentioning

confidence: 99%

Optimization of Activated Tungsten Inert Gas Welding Process Parameters Using Heat Transfer Search Algorithm: With Experimental Validation Using Case Studies

Vora

Patel

Srinivasan

et al. 2021

Metals

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The Activated Tungsten Inert Gas welding (A-TIG) technique is characterized by its capability to impart enhanced penetration in single pass welding. Weld bead shape achieved by A-TIG welding has a major part in deciding the final quality of the weld. Various machining variables influence the weld bead shape and hence an optimum combination of machining variables is of utmost importance. The current study has reported the optimization of machining variables of A-TIG welding technique by integrating Response Surface Methodology (RSM) with an innovative Heat Transfer Search (HTS) optimization algorithm, particularly for attaining full penetration in 6 mm thick carbon steels. Welding current, length of the arc and torch travel speed were selected as input process parameters, whereas penetration depth, depth-to-width ratio, heat input and width of the heat-affected zone were considered as output variables for the investigations. Using the experimental data, statistical models were generated for the response characteristics. Four different case studies, simulating the real-time fabrication problem, were considered and the optimization was carried out using HTS. Validation tests were also carried out for these case studies and 3D surface plots were generated to confirm the effectiveness of the HTS algorithm. It was found that the HTS algorithm effectively optimized the process parameters and negligible errors were observed when predicted and experimental values compared. HTS algorithm is a parameter-less optimization technique and hence it is easy to implement with higher effectiveness.

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Model-Based Joining Process Design for the Body Shop Process Chain

Schwarz

Ackert

Falk

et al. 2022

2nd International Conference on Advanced Joining Processes (AJP 2021)

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Mathematical Model for Prediction and Optimization of Weld Bead Geometry in All-Position Automatic Welding of Pipes

Cited by 8 publications

References 17 publications

Optimization of Bobbin Tool Friction Stir Processing Parameters of AA1050 Using Response Surface Methodology

Optimization of Bobbin Tool Friction Stir Processing Parameters of AA1050 Using Response Surface Methodology

Optimization of Activated Tungsten Inert Gas Welding Process Parameters Using Heat Transfer Search Algorithm: With Experimental Validation Using Case Studies

Model-Based Joining Process Design for the Body Shop Process Chain

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