Optimizing the ultrasonic inserting parameters to achieve maximum pull – Out strength using response surface methodology and genetic algorithm integration technique

Anand, K.; Elangovan, S.

doi:10.1016/j.measurement.2016.12.025

Cited by 20 publications

(4 citation statements)

References 11 publications

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“…Usually, a low-order polynomial approximation is used within a certain range of design variables. In general, a second-order polynomial approximation model is [27] 0 11…”

Section: Methods Of Positioning Error Compensationmentioning

confidence: 99%

Positioning Error Compensation of a Flexible Track Hybrid Robot for Aircraft Assembly Based on Response Surface Methodology and Experimental Study

Tian

Wang

et al. 2021

Preprint

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With the development of aviation industry, more stringent demands are put forward for the performance and manufacturing level of aircraft. Moreover, the automation and precision of aircraft assembly determine the efficiency and quality of aircraft production. In order to improve the positioning precision of the flexible track hybrid robots which are applied to the flexible automatic assembly of aircraft, a precision compensation method based on response surface methodology was proposed in this paper. Firstly, the global positioning error model, optimized by characteristics of error data, was constructed to predict the positioning errors of the flexible track hybrid robot. Secondly, the predicted errors are utilized to realize the compensation of the target points at drilling workspace on nose and front fuselage assembly areas. Finally, a series of experiments of the flexible track hybrid robot with no-load and drilling scenarios are implemented to validate the proposed precision compensation method. The experiment of a hybrid robot for aircraft assembly shows that the mean value of the absolute positioning precision of the end-effector was promoted from 0.081 mm to 0.025 mm, maximum error reduced from 0.143 mm to 0.039 mm., respectively, which means that the position accuracy of the robot is increased by 69.1% and 72.7% for two experimental conditions.

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“…Usually, a low-order polynomial approximation is used within a certain range of design variables. In general, a second-order polynomial approximation model is [27] 0 11…”

Section: Methods Of Positioning Error Compensationmentioning

confidence: 99%

Positioning Error Compensation of a Flexible Track Hybrid Robot for Aircraft Assembly Based on Response Surface Methodology and Experimental Study

Tian

Wang

et al. 2021

Preprint

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“…Tayal et al 15 investigated the impact strength of A356/MG BmC by optimising the process parameters. Similarly, Anand and Elangovan, 16 reported that RSM coupled with GA may be used to optimise the process parameters.…”

Section: Introductionmentioning

confidence: 99%

Investigation on the effect of Zn interlayer and process parameters optimisation in the production of Al-SS bimetallic castings

Raja

Kavitha

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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The effect of Zn interlayer on the stainless steel insert in the fabrication of Aluminium-Stainless Steel (Al-SS) Bimetallic casting (BmC) is reported. The design of Experiments was conducted with pouring temperature (680°C–730°C), insert preheat temperature (100°C–400°C) and insert thickness (1–3 mm) as influencing process parameters to produce Al-SS BmC. The maximum bond strength of 25.33 MPa was achieved when the experimental conditions were 705°C pouring temperature, 250°C insert temperature and 2 mm insert thickness. Using Response Surface Methodology (RSM), the interaction between the process parameters has been studied and a second-order polynomial equation was derived for maximising the bond strength. The predicted maximum bond strength using RSM for the above experimental conditions is 26.75 MPa. The output of RSM was given to the Genetic Algorithm (GA) to identify the maximum bond strength at forbidden parametric values. The maximum bond strength predicted using GA by interpolation is 26.87 MPa. However, the three process parametric conditions are 707°C, 277°C, and 1.86 mm respectively for achieving the maximum bond strength in the given Al-SS BmC’s. Experimental validation of the above conditions was conducted and the results obtained confirmed the predicted bond strength value using the GA technique. Spiral morphology due to the formation of Zn10Fe3 intermetallics was observed at the Zn-SS interface when the pouring temperature increased to 730°C and this might have led to the reduced bond strength of BmC than the bond strength achieved at 705°C and 707°C. The formation of the Al-rich and Fe-rich solid solutions as reaction layer between Al and SS without the micro gap around 705°C may contribute to the significant increase in bond strength of produced BmC with different insert temperatures and insert thickness.

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“…Anand et al [3] have used RSM-GA integration technique for optimizing the ultrasonic insertion process to maximize pullout strength. The authors revealed that RSM-GA integration technique yields better results than RSM.…”

Section: Introductionmentioning

confidence: 99%

Modelling and multi-objective optimization of ultrasonic inserting parameters through fuzzy logic and genetic algorithm

Anand

Elangovan

2019

J Braz. Soc. Mech. Sci. Eng.

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As the usage of plastic components has increased in various industries, the methods for fastening have increased rapidly. When the plastic components are fastened by self-tapping screws or bolts, failure occurs because of stripped threads or plastic creep. In these circumstances, threaded metal inserts provide improved joint performance and ability to assemble and disassemble the components without degrading them. Even though many techniques such as insert moulding, thermal insertion and cold insertion are available for joining thermoplastic material with metal insert, ultrasonic insertion is one of the most preferred processes because of the shorter cycle time usually less than a second, possibility of simultaneous installation of the multiple inserts and large-scale automation possibilities for higher production operations. The technical problems faced by the industries in ultrasonic insertion process are poor insertion quality which affects the function of the product. These problems arise because of the improper selection of insertion parameters. The objective of this paper is to optimize the ultrasonic insertion parameters for improving the quality of joint through non-traditional optimization techniques. Response surface methodology (RSM) is used to design the experiments, and then pullout strength and stripping torque are measured. Data obtained from the measurement are utilized to develop a nonlinear equation between the responses and predictors, and optimal combinations of insertion parameters are found out by fuzzy logic and genetic algorithm (GA) approach. From the confirmatory test, it was observed that the fuzzy logic yields better output results than GA.

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Optimizing the ultrasonic inserting parameters to achieve maximum pull – Out strength using response surface methodology and genetic algorithm integration technique

Cited by 20 publications

References 11 publications

Positioning Error Compensation of a Flexible Track Hybrid Robot for Aircraft Assembly Based on Response Surface Methodology and Experimental Study

Positioning Error Compensation of a Flexible Track Hybrid Robot for Aircraft Assembly Based on Response Surface Methodology and Experimental Study

Investigation on the effect of Zn interlayer and process parameters optimisation in the production of Al-SS bimetallic castings

Modelling and multi-objective optimization of ultrasonic inserting parameters through fuzzy logic and genetic algorithm

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