Off-line multiresponse optimization of electrochemical surface grinding by a multi-objective programming method

Ilhan, R.E.; Sathyanarayanan, G.; Storer, Robert H.; Liao, T. Warren

doi:10.1016/0890-6955(92)90013-7

Cited by 20 publications

(3 citation statements)

References 2 publications

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“…An effort has been made to predict surface roughness in end milling process by using ANN model based on design experiments Oktem et al (in press). Ilhan et al (1992) have used a [2 8 .3] factorial design with a total number of 718 experiments to establish the different objective functions corresponding to surface roughness of the electrochemical surface grinding process. Nabil and Ridha (2006) developed an approach combining the design of experiments (DOE) and the ANN methods to establish accurate models for ground surface roughness parameters prediction.…”

Section: Introductionmentioning

confidence: 99%

A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method

Çaydaş

Hasçalik

2008

Journal of Materials Processing Technology

215

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Section: Introductionmentioning

confidence: 99%

A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method

Çaydaş

Hasçalik

2008

Journal of Materials Processing Technology

215

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“…Traditionally, there are several methods available in the literature for solving and optimising multi-response optimisation problems (MROPs) like goal attainment (Xu et al 2004), goal programming (Clayton et al 1982), the weighting method (Ilhan et al 1992), the e-constraint method (Coello Coello 2000), and so on. But, none of these methods consider all the responses simultaneously, which is a basic requirement in most MROPs.…”

Section: Introductionmentioning

confidence: 99%

Synergy of ICA and MCDM for multi‐response optimisation problems

Fallah-Jamshidi

Amiri

2013

International Journal of Production Research

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Of late, attempts are being made to optimise production system problems by minimum cost. A good available device in this area is response surface methodology. This methodology combines experimental designs and statistical techniques for empirical model building and optimising. In most situations simulated models for real world problems are non-linear multi-response, while responses are conflicting. The simultaneous optimisation of several conflicting responses is computationally expensive. So this makes the problem solving extremely complex. Since few attempts have been made to scrutinise this domain, in this paper the nonlinear continuous multi-response problem is investigated. In order to tackle multi-response optimisation difficulties, we propose a new hybrid meta heuristic based on the imperialist competitive algorithm. It simulates a socioeconomical procedure, imperialistic competition. When there are some non-dominated solutions in searching space, a technique for order performance by similarity to ideal solution is used to identify which nondominated solutions are imperialists and which ones belong to colonial societies. A particle swarm-like mechanism is employed to model the influence of imperialists on colonies. The algorithm will continue until only one imperialist obtains all countries' possessions. In order to prevent carrying out extensive experiments to find optimum parameters of the algorithm, we apply the Taguchi approach. Since there is no standard benchmark in this field, we use three case studies from distinguished papers in the multi-response optimisation field. Comparing the results with some works mentioned in the literature reveals the superiority of the proposed algorithm.

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“…Electrochemical grinding (ECG), which utilizes both mechanical and electrochemical actions to remove material, is a promising way to reduce tool wear and improve grindability. During electrochemical action, electrolyte solution is pumped into the machining electrodes [6]. Abrasive grains serve as insulator to maintain the chemical individual reactions (anodic oxide) occurring in the machining gap between the tool and the workpiece to form an oxygen layer on the work-surface.…”

Section: Introductionmentioning

confidence: 99%

Fundamental Investigation of Ultrasonic Assisted Pulsed Electrochemical Grinding of Ti-6Al-4V

Nomura

2016

MSF

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Aiming at the development of a novel grinding technology for the highly efficient machining of difficult to machine materials such as Ti-6Al-4V, an ultrasonic assisted pulsed electrochemical grinding (UAECG) method was proposed. The current work is to reveal the fundamental grinding characteristics of the UAECG of Ti-6Al-4V by experimentally investigating the effect of vibration amplitude on grinding forces, actual material removal and work-surface roughness under different process parameters such as the input voltage and rotational speed. Summarizing the obtained results revealed that the grinding forces in UAECG are significantly smaller than those in conventional grinding (CG).

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Off-line multiresponse optimization of electrochemical surface grinding by a multi-objective programming method

Cited by 20 publications

References 2 publications

A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method

A study on surface roughness in abrasive waterjet machining process using artificial neural networks and regression analysis method

Synergy of ICA and MCDM for multi‐response optimisation problems

Fundamental Investigation of Ultrasonic Assisted Pulsed Electrochemical Grinding of Ti-6Al-4V

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