Modeling and Analysis of Surface Roughness Parameters in Drilling GFRP Composites Using Fuzzy Logic

Latha, B.; Senthilkumar, V.

doi:10.1080/10426910903447261

Cited by 79 publications

(42 citation statements)

References 22 publications

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“…3). This finding is also consistent with previous findings of drilling analysis of GFRP [8,14]. Wet grinding in emulsion coolant tends to produce better surface finish, if not the best, when the feed was low.…”

Section: Surface Roughnesssupporting

confidence: 94%

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Effects of Grinding Process Parameters and Coolants on the Grindability of GFRP Laminates

Chockalingam

Kok

Vijayaram

2013

Materials and Manufacturing Processes

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Grinding is one of the mandatory methods for fabrication of precise glass fibre reinforced plastic (GFRP) parts. In this work, grinding studies were carried out on GFRP using a CBN wheel. The grinding process was performed at different cutting speeds, feed rates and depth of cuts. Grinding performance was evaluated by measuring forces and surface roughness of the ground GFRP composite laminate material. The effects of coolants in grinding the composite laminate material were investigated. Test results showed that in most cases, dry grinding achieved the greatest material removal rate and the lowest surface area roughness (Sa). Higher speed tends to produce better surface finish in dry grinding. Surface area roughness produced in wet grinding shows random and drastic variations. Surfaces ground in synthetic coolant show clean, hard and smooth matrix, and are in general better quality than those ground with emulsion coolant. Optical and electron microscopy was used to evaluate the grinding mechanism of GFRP laminate material. Surface profile waviness is the predominating factor contributing to surface area roughness over surface peaks and valleys.

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Section: Surface Roughnesssupporting

confidence: 94%

“…He found that CBN yielded better performance and higher tool life than other cutting tools. Latha et al [8] reported that maintaining proper surface roughness is important and that machining process is to be controlled. Palanikumar et al [9] reported that machining performance of composite can be improved by optimal conditions.…”

Section: Introductionmentioning

confidence: 99%

Effects of Grinding Process Parameters and Coolants on the Grindability of GFRP Laminates

Chockalingam

Kok

Vijayaram

2013

Materials and Manufacturing Processes

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“…It has been observed in the published literature that number of researchers have applied Design of Experiment (DOE) techniques to analyze the influence of various process parameters [14][15][16][17]. Among the available techniques, RSM is a powerful tool which formulates the mathematical model of a given multi-variable problem and also uses statistical techniques for the analysis of the same problem.…”

Section: Methodsmentioning

confidence: 99%

Modeling and Optimization of Machining Nimonic C-263 Superalloy using Multicut Strategy in WEDM

Mandal

Dixit

Das

et al. 2015

Materials and Manufacturing Processes

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In recent years, Wire-Electrical Discharge Machining (WEDM) has gained popularity in industry due to its capability to generate complicated shapes in exotic materials, irrespective of their hardness. Conventional machining of Nimonic C-263 super alloy is an extremely difficult and costly process due to its high hardness and tool wear rate. The present research work investigates the influence of the WEDM process parameters on different performance measures during machining of Nimonic C-263 super alloy.Mathematical model for all four important performance measures, namely, cutting rate, surface roughness, spark gap and wire wear ratio, was developed and the responses were used for studying the inter-relationship between performance measures and process parameters. The optimal settings of operating conditions were predicted using desirability function. The effectiveness of multi-cut strategy was also investigated in the paper.

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“…9 utilized fuzzy logic for optimizing multiple performance characteristics. 13 Chen and Savage developed a fuzzy net-based multilevel in-process surface recognition system for milling operations, 14,15 while Arup Kumar and Dilip Kumar designed a genetic-fuzzy system to predict surface finish and the power requirement in grinding.…”

mentioning

confidence: 99%

Surface hardness prediction of CrN thin film coating on AL7075-T6 alloy using fuzzy logic system

Zalnezhad

Sarhan

Hamdi

2013

Int. J. Precis. Eng. Manuf.

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In recent years, CrN coating has been identified as one of the most promising protective layers on surfaces of tools and dies due to its excellent mechanical properties, corrosion resistance, and surface hardness. This study presents the predicting of chromium nitride (CrN) coating surface hardness on AL7075-T6 using fuzzy logic technique. First, Al7075-T6 was coated with CrN at different parameter conditions, after which the surfaces hardness of the CrN-coated specimens was measured using a micro hardness machine. Next, a fuzzy logic model was established to predict the surface hardness of CrN coating on AL7075-T6 with respect to changes in input process parameters, DC power, temperature, and nitrogen flow rate based on the trained data obtained from the micro hardness test. Three membership functions were allocated in connection with each model input. Finally, five new experimental tests were carried out to verify the predicted results achieved via the fuzzy logic model. The results indicate an agreement between the fuzzy model and experimental results with 94.664% accuracy.

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Modeling and Analysis of Surface Roughness Parameters in Drilling GFRP Composites Using Fuzzy Logic

Cited by 79 publications

References 22 publications

Effects of Grinding Process Parameters and Coolants on the Grindability of GFRP Laminates

Effects of Grinding Process Parameters and Coolants on the Grindability of GFRP Laminates

Modeling and Optimization of Machining Nimonic C-263 Superalloy using Multicut Strategy in WEDM

Surface hardness prediction of CrN thin film coating on AL7075-T6 alloy using fuzzy logic system

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