Optimal laser welding process parameters and expected weld bead profile for P92 steel

Satyanarayana, G.; Narayana, K. L.; Rao, B. Nageswara

doi:10.1007/s42452-019-1333-3

Cited by 21 publications

(9 citation statements)

References 41 publications

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“…A systematic popular statistical approach, namely, the Taguchi method 20 considers an orthogonal array (OA) and recommends few tests for generating information on performance indicators (PIs) to all possible combinations of the levels of input variables or to the full factorial design of experiments (DOE). This approach minimizes the expenditure as well as time-consumption of trial test runs and obtains solutions for many engineering optimization problems, such as minimization on the introduction of damages in composites due to drilling, [21][22][23][24] rigid body dynamic separation process during the flights of space vehicles, [25][26][27] heat exchanger performance, 28 planetary gears design, 29,30 welding [31][32][33][34][35][36] and machining processes, [37][38][39][40][41][42][43][44][45] and fuel engine performance. [46][47][48][49] Kumar et al 50 performed experiments to investigate the performance of HP considering three input variables (such as heat input [A], inclination angle [B], and flow rate [C]) for the three PIs: efficiency η ( ), thermal resistance (THR), and overall heat transfer coefficient (OHTC).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multiobjective optimization for the optimal heat pipe working parameters based on Taguchi's design of experiments

2021

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A heat pipe (HP) is a device transferring large quantities of heat through a small area of the cross‐section with very small deviations in temperature. The thermal impedance of HP is lower while thermal conductance is higher. HPs are designed for controlling temperature, amplification of heat flux, and diminution. HPs are being used in the cooling of aircraft and electronics, solar energy, systems of heat recovery, and nuclear reactors. Complex mathematical formulation demands experimentation to acquire the physical phenomena. Performing experiments is a tedious task with increasing the working parameters and their assigned levels. In such situations, a systematic statistical approach (viz., the Taguchi method) has to be adopted to minimize the number of experiments and to provide the information for the full factorial design of experiments. This paper adopts the modified Taguchi method and applies a simple and reliable multiobjective optimization concept to determine the optimal HP working parameters (viz., heat input, inclination angle, and flow rate). In the optimization process, efficiency, thermal resistance, and overall heat transfer coefficient are the performance indicators (PIs). Empirical relations are developed and validated for the PIs in terms of the HP working parameters. The recommended Taguchi's orthogonal array to perform a few tests may not have the set of optimal working parameters. Additional tests are to be performed to confirm the estimates of the PIs for the optimal working parameters. Confirmation test results in the present study indicate close‐to/within the estimated range.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiobjective optimization for the optimal heat pipe working parameters based on Taguchi's design of experiments

2021

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“…Weld bead geometry features (WBGFs) can reflect the welding process parameters and are effective evidence to suggest how to optimize the latter. This is because the relationship between WBGFs and weld process parameters can be built with various models [ 9 , 10 , 11 ]. Thus, the real-time modeling of WBGFs is the really demanded technology for the effective control of weld formation especially and accurate metal deposition [ 12 , 13 ] during the multipass welding process.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Modeling of Weld Bead Geometry Features in Thick Plate GMAW Based on Machine Vision and Learning

Pan

et al. 2020

Sensors

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Weld bead geometry features (WBGFs) such as the bead width, height, area, and center of gravity are the common factors for weighing welding quality control. The effective modeling of these WBGFs contributes to implementing timely decision making of welding process parameters to improve welding quality and enhance automatic levels. In this work, a dynamic modeling method of WBGFs is presented based on machine vision and learning in multipass gas metal arc welding (GMAW) with typical joints. A laser vision sensing system is used to detect weld seam profiles (WSPs) during the GMAW process. A novel WSP extraction method is proposed using scale-invariant feature transform and machine learning. The feature points of the extracted WSP, namely the boundary points of the weld beads, are identified with slope mutation detection and number supervision. In order to stabilize the modeling process, a fault detection and diagnosis method is implemented with cubic exponential smoothing, and the diagnostic accuracy is within 1.50 pixels. A linear interpolation method is presented to implement sub pixel discrimination of the weld bead before modeling WBGFs. With the effective feature points and the extracted WSP, a scheme of modeling the area, center of gravity, and all-position width and height of the weld bead is presented. Experimental results show that the proposed method in this work adapts to the variable features of the weld beads in thick plate GMAW with T-joints and butt/lap joints. This work can provide more evidence to control the weld formation in a thick plate GMAW in real time.

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“…This paper examines the simplicity and the adequacy of Taguchi approach to trace optimal process parameters for achieving the maximum tensile load bearing capacity of the laser weld thin galvanized steel sheets. It follows the modified Taguchi method [32][33][34][35] in finding the expected range of the output responses and Taguchi's simple single-objective optimization technique.…”

Section: Introductionmentioning

confidence: 99%

Optimal Process Parameters to Achieve Maximum Tensile Load Bearing Capacity of Laser Weld Thin Galvanized Steel Sheets

Harish*¹,

Prasad*²,

Reddy³

et al. 2019

IJRTE

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Steels are protected against corrosion through hot-dip galvanization in which material surfaces are coated with molten zinc. Galvanized steel products are reliable in coating life and performance with lower maintenance and repair cost. Welding of such zinc coated steel sheets is of great economic importance in the automotive industries. Many researchers have utilized the S/N ratio transformation while obtaining the optimal solution of several manufacturing processes. However, the additive law in Taguchi technique estimates the deterministic output response from the mean values of the ANOVA table and unable to provide the expected range of the output response. This paper deals with optimal process parameters for achieving maximum tensile load bearing capacity of laser weld thin galvanized steel sheets utilizing the concepts of a modified Taguchi design of experiments. Excepted range of the tensile load bearing capacity is provided for the specified laser process parameters. Empirical relation is developed and validated for the tensile load bearing capacity in terms of the laser process parameters viz., laser power, welding speed and focal point position

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Optimal laser welding process parameters and expected weld bead profile for P92 steel

Cited by 21 publications

References 41 publications

Multiobjective optimization for the optimal heat pipe working parameters based on Taguchi's design of experiments

Multiobjective optimization for the optimal heat pipe working parameters based on Taguchi's design of experiments

Dynamic Modeling of Weld Bead Geometry Features in Thick Plate GMAW Based on Machine Vision and Learning

Optimal Process Parameters to Achieve Maximum Tensile Load Bearing Capacity of Laser Weld Thin Galvanized Steel Sheets

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