Optimization of Multiple Responses of Ultrasonic Machining (USM) Process: A Comparative Study

Chakravorty, Rina; Gauri, Susanta Kumar; Chakraborty, Shankar

doi:10.5267/j.ijiec.2012.012.001

Cited by 8 publications

(7 citation statements)

References 27 publications

(58 reference statements)

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“…Chakravorty et al [9] Multi-response optimization using weighted signal-to-noise (WSN) ratio method and utility theory (UT) method in USM process.…”

Section: Methodsmentioning

confidence: 99%

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Multi-response optimization and modeling of trim cut WEDM operation of commercially pure titanium (CPTi) considering multiple user's preferences

Chalisgaonkar¹,

Kumar

2015

Engineering Science and Technology, an International Journal

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a b s t r a c tIn this research work, development of a multi response optimization technique has been undertaken, using traditional utility method in conjunction with the weight assignment concept (for multiple customer's priorities) in trim cut wire electrical discharge machining (WEDM). Pure titanium has been selected as work material for experimentation. The effect of key process parameters such a wire type (zinc coated and uncoated brass wire), pulse on time (T ON ), pulse off time (T OFF ), peak current (IP), wire feed (WF), servo voltage (SV) and wire offset (W OFF ) were investigated on material removal rate (MRR), surface roughness and wire weight consumption (eroded weight of wire after machining) in finish cut WEDM operation. Two different types of wire electrodes were taken for experimental research (uncoated, zinc coated). Further, the variation of the MRR was modeled semi-empirically through dimensional analysis. The developed model is mechanistic, as it can be used by the machinists to predict the MRR over a wide range of input parameters. The optimization of multiple responses has been done for satisfying the priorities of multiple users, in contrast to the traditional multi-response techniques where the optimized process setting is realized without giving any attention to the priorities of different users.

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“…Chakravorty et al [9] Multi-response optimization using weighted signal-to-noise (WSN) ratio method and utility theory (UT) method in USM process.…”

Section: Methodsmentioning

confidence: 99%

“…Same weight-age was given to quality characteristics. 9 Nayak et al [10] AHP and TOPSIS method for WEDM for of D-2 tool steel MRR, surface finish and kerf width…”

Section: Methodsmentioning

confidence: 99%

Multi-response optimization and modeling of trim cut WEDM operation of commercially pure titanium (CPTi) considering multiple user's preferences

Chalisgaonkar¹,

Kumar

2015

Engineering Science and Technology, an International Journal

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“…Those models were then optimized using GA technique. Chakravorty et al [18] compared the performance of weighted signal-to-noise (WSN) ratio method, GRA method, multi-response signal-to-noise (MRSN) ratio method and utility theory (UT) approach for multi-response optimization of USM processes. It was shown that WSN ratio and UT methods would provide better overall optimization results.…”

Section: Literature Reviewmentioning

confidence: 99%

Parametric optimization of ultrasonic machining process using gravitational search and fireworks algorithms

Goswami

Chakraborty

2015

Ain Shams Engineering Journal

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Ultrasonic machining (USM) is a mechanical material removal process used to erode holes and cavities in hard or brittle workpieces by using shaped tools, high-frequency mechanical motion and an abrasive slurry. Unlike other non-traditional machining processes, such as laser beam and electrical discharge machining, USM process does not thermally damage the workpiece or introduce significant levels of residual stress, which is important for survival of materials in service. For having enhanced machining performance and better machined job characteristics, it is often required to determine the optimal control parameter settings of an USM process. The earlier mathematical approaches for parametric optimization of USM processes have mostly yielded near optimal or sub-optimal solutions. In this paper, two almost unexplored nonconventional optimization techniques, i.e. gravitational search algorithm (GSA) and fireworks algorithm (FWA) are applied for parametric optimization of USM processes. The optimization performance of these two algorithms is compared with that of other popular population-based algorithms, and the effects of their algorithm parameters on the derived optimal solutions and computational speed are also investigated. It is observed that FWA provides the best optimal results for the considered USM processes. Ó 2014 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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“…The desirability function approach has been used in multiple output optimisations [38,39] which are able to optimise for multiple responses. A comparative study conducted by Chakravorty et al [40] was done on the effectiveness of several multi-response optimisation techniques. It was concluded that the use of a desirability function was the strongest option for optimisation.…”

Section: Desirability Functionmentioning

confidence: 99%

Automated weighted outlier detection technique for multivariate data

Thennadil

Dewar

Herdsman

et al. 2018

Control Engineering Practice

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In the chemical and petrochemical industries, spectroscopy-based online analysers are becoming common for process monitoring and control applications. A significant challenge in using these analysers as part of process monitoring and control loops is the large amount of personnel time required for calibration and maintenance of models which involve decision inputs such as whether an observation is an outlier, the number of latent variables in a model, type of pre-processing and when a calibration model has to be updated. Since no one measure works well for all applications, supervision by the process data analyst is required which invariably involves some level of subjectivity. In this paper, we focus on the detection of multivariate outliers in a calibration set. We propose a method which combines multiple outlier detection techniques to identify a set of outlying observations without operator input. Apart from the overall methodology, this work introduces several novelties. The system uses partial least squares (PLS) instead of principal component analysis (PCA) which is normally used for detecting multivariate outliers. A simple modification to the Mahalanobis distance was also proposed which appears to be more sensitive to outliers than the conventional Mahalanobis distance. The methodology also introduces the concept of a desirability function to enable automatic decision making based on multiple statistical measures for outlier detection. The methodology is demonstrated using Raman spectroscopy data collected from an industrial distillation process

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Optimization of Multiple Responses of Ultrasonic Machining (USM) Process: A Comparative Study

Cited by 8 publications

References 27 publications

Multi-response optimization and modeling of trim cut WEDM operation of commercially pure titanium (CPTi) considering multiple user's preferences

Multi-response optimization and modeling of trim cut WEDM operation of commercially pure titanium (CPTi) considering multiple user's preferences

Parametric optimization of ultrasonic machining process using gravitational search and fireworks algorithms

Automated weighted outlier detection technique for multivariate data

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