A modified principal component analysis-based utility theory approach for optimization of correlated responses of EDM process

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

doi:10.4314/ijest.v4i2.3

Cited by 8 publications

(3 citation statements)

References 40 publications

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“…In this study, we compared the effects of using different time-scale compositions derived from original 10-day GF-1 NDVI data on mapping tree species, and the results showed that the accuracy of tree species' identification significantly increased from 30-day to 10-day time-series (p < 0.05). The accuracy of results was bettered when based on the PCA-transformed 10-day NDVI time series, by approximately 3%, because the PCA analysis can effectively remove redundant information from the time-series data and only retains a few independent spatiotemporal patterns that benefit forest identification [87,88].…”

Section: Discussionmentioning

confidence: 99%

Tree Species (Genera) Identification with GF-1 Time-Series in A Forested Landscape, Northeast China

Tian

Zhang

et al. 2020

Remote Sensing

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Forests are the most important component of terrestrial ecosystem; the accurate mapping of tree species is helpful for the management of forestry resources. Moderate- and high-resolution multispectral images have been commonly utilized to identify regional tree species in forest ecosystem, but the accuracy of recognition is still unsatisfactory. To enhance the forest mapping accuracy, this study integrated the land surface phenological metrics and text features of forest canopy on tree species identification based on Gaofen-1 (GF-1) wide field of view (WFV) and time-series images (36 10-day NDVI data), conducted at a forested landscape in Harqin Banner, Northeast China in 2017. The dominant tree species include Pinus tabulaeformis, Larix gmelinii, Populus davidiana, Betula platyphylla, and Quercus mongolica in the study region. The result of forest mapping derived from a 10-day dataset was also compared with the outcome based upon a commonly utilized 30-day dataset in tree species identification. The results indicate that tree species identification accuracy is significantly (p < 0.05) improved with higher temporal resolution (10-day, 79.4%) of images than commonly used monthly data (30-day, 76.14%), and the accuracy can be further increased to 85.13% with a combination of the information derived from principal component analysis (PCA) transformation, phenological metrics (standing for the information of growing season) and texture features. The integration of higher dimensional NDVI data, vegetation growth dynamics and feature of canopy simultaneously will be beneficial to map tree species at the landscape scale.

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Section: Discussionmentioning

confidence: 99%

Tree Species (Genera) Identification with GF-1 Time-Series in A Forested Landscape, Northeast China

Tian

Zhang

et al. 2020

Remote Sensing

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“…This creates confusion for the researchers to adopt which machining level for the better response. This gave rise to the introduction of one of the multi criteria decision making (MCDM) model called Utility concept approach, which gives one particular optimal level for multiple responses [30][31][32][33].…”

Section: Multi Criteria Decision Making (Mcdm)mentioning

confidence: 99%

Machinability Investigations on Aerospace Custom 450 Alloy Using TiAlN/TiCN, TiCN/TiAlN Coated and Uncoated Carbide Tools

Kumar¹,

Margabandu²,

Radhakrishnan³

et al. 2021

JESA

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In this present research, the machinability studies of TiAlN/TiCN, TiCN/TiAlN coated and uncoated inserts were investigated on machining custom 450 alloy. The machining input parameters such as feed rate (f), cutting speed (V) and depth of cut (d) are set using orthogonal array. The machining output parameters such as surface roughness, tool wear and cutting forces were studied for its parametric contribution and it was analyzed using Analysis of Variance (ANOVA). Further, the tool wear obtained was studied using scanning electron microscopic images and energy dispersive spectroscopy analysis was conducted to check the addition of work material elements to the coated tool surface. The results show that, the feed rate is the most contributing factor in deciding resultant forces, surface roughness and tool wear respectively. TiAlN/TiCN coated carbide tool has obtained improved machinability, when compared to TiCN/TiAlN coated carbide and uncoated carbide inserts. To obtain one optimal level for all three responses of three types of tools, multi criteria decision making approach, named utility concept approach is selected. Based on the MCDM analysis, it is found that trial number 4 gives better experimental output of improved surface integrity, lower resultant force and less tool wear for all types of tools.

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“…The evaluation of optimum machining parameters for obtaining good surface quality using Taguchi concept coupled with PCA (Datta and Mahapatra, 2010). Electric discharge machining parameters were optimized using modified PCA (Chakravorty et al, 2011). PCA has been used to assign weight criteria of each objective (Siddiquee et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization in end milling of GFRP composites using Taguchi techniques with principal component analysis

Jenarthanan

Gokulakrishnan

Jagannaath

et al. 2017

MMMS

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Purpose The purpose of this paper is to find out the optimum machining parameters using Taguchi technique with principal component analysis (PCA) during end milling of GFRP composites. Design/methodology/approach In multi-objective optimization, weight criteria of each objective are important for producing better and accurate solutions. This method has been employed for simultaneous minimization of surface roughness, cutting force and delamination factor. Experiments were planned using Taguchi’s orthogonal array with the machining parameters, namely, helix angle of the end mill cutter, spindle speed, feed rate and depth of cut were optimized with considerations of multiple response characteristics, including machining force, surface roughness and delamination as the responses. PCA is adopted to find the weight factors involved for all objectives. Finally analysis of variance concept is employed on multi-SN ratio to find out the relative significance of machining parameter in terms of their percentage contribution. Findings The multi-SN ratio is achieved by the product of weight factor and SN ratio to the performance characteristics in the utility concept. The results show that a combination of machining parameters for the optimized results has helix angle of 35°, machining speed of 4,000 m/min, feed rate of 750 mm/rev and depth of cut of 2.0 mm. Originality/value Effect of milling of GFRP composites on delamination factor, surface roughness and machining force with various helix angle solid carbide end mill has not been analysed yet using PCA techniques.

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A modified principal component analysis-based utility theory approach for optimization of correlated responses of EDM process

Cited by 8 publications

References 40 publications

Tree Species (Genera) Identification with GF-1 Time-Series in A Forested Landscape, Northeast China

Tree Species (Genera) Identification with GF-1 Time-Series in A Forested Landscape, Northeast China

Machinability Investigations on Aerospace Custom 450 Alloy Using TiAlN/TiCN, TiCN/TiAlN Coated and Uncoated Carbide Tools

Multi-objective optimization in end milling of GFRP composites using Taguchi techniques with principal component analysis

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