Optimization Of Tribological Properties Of Aluminium Honeycomb Reinforced

Page 1

Mechanics, Materials Science & Engineering, May 2016

ISSN 2412-5954

Optimization Of Tribological Properties Of Aluminium Honeycomb Reinforced Polymeric Composites Using Grey Based Fuzzy Algorithm K.Panneerselvam1, K.Lokesh1, Chandresh D.1,T.N.S.Ramakrishna1 1

Department of Production Engineering, National Institute of Technology, Tiruchirappalli-620015, India DOI 10.13140/RG.2.1.4683.1762

Keywords: fuzzy logic, grey relational analysis (GRA), nylon 6, optimization, polypropylene (PP), tribology.

ABSTRACT. In this research two composite materials were fabricated by using two matrix materials and one common reinforcement material. The two matrix materials were Polypropylene and Nylon 6. Reinforcement material was Aluminium honeycomb core. Compression moulding machine was used for the fabrication of these composite materials. Two body abrasive wear experiments were conducted by using a pin-on-disc Tribotester under dry sliding condition and at room temperature. The design process parameters for two-body abrasive wear test were normal load, sliding velocity, sliding distance and abrasive paper grit size. The output responses were Coefficient Of Friction (COF) and Specific Wear Rate (SWR). The design of experiments is based on L 9Taguchi orthogonal array. Grey fuzzy logic algorithm was used for the optimization of input process parameters. For polypropylene composite material the highest Grey Fuzzy Reasoning Grade (GFRG) is obtained at 30 N normal load, 0.523 m/s sliding velocity, 450 m sliding distance, 320 grit size of abrasive paper and these are the optimum level of process parameters. For nylon composite material highest GFRG is obtained at 30 N normal load, 1.046 m/s sliding velocity, 150 m sliding distance, 400 grit size of abrasive paper and these are the optimum level of process parameters. The optimum level of process parameters were also validated with conformation experiments.

Introduction. Literatures revels that there are different approaches to handle prediction and multiobjective optimization problems. The common approaches includes Response Surface Methodology (RSM), [1,2], Artificial Neural Network (ANN), Genetic Algorithm (GA), [3], Fuzzy regression, [4] and Desirability Function (DF) approach, [5,6]. From last few years, polymeric composite materials have been widely used in many industries. Some of polymer materials, mainly thermoplastics are polypropylene (PP), Nylon etc., have shown grater improvement in their tribological and mechanical properties. The major advantage of polymer composite from a tribological point of view is their low wear rate [7]. Incorporation of inorganic particles into the polymers is best and an effective way to fabricate polymer composite materials with improved tribological properties. The degree of the reinforcement of the filler is depends up on the many factors like composition of the filler material, size of the filler, shape of the filler, matrix and filler bonding etc. [8]. The incorporation of the fillers can improve the tribological application depends on the type of application i.e., friction coefficient and wear resistance were not the properties of the base material. In particular brake pads and clutches require high coefficient of friction and low wear resistance whereas gears and bearings require low coefficient of friction and wear rate [9]. The major advantage of the polymer composites are of their self-lubricating property in tribological point of view. The present research work analysis based on fuzzy-logic finds applications in uncertain environment conditions. From last few years, fuzzy-logic-based multi-criteria optimizatin methods were mostly using in optimization of tribological parameters. It is also shoew that application of fuzzy logic technique improves the multi objective responses. Grey Relational Analysis (GRA) has strong potential to improve the capability of fuzzy-logic in multi-objective optimization problems. In grey fuzzy logic technique the optimization of multiple responses can be effectively changed into single Grey Fuzzy Reasoning Grade (GFRG).

MMSE Journal. Open Access www.mmse.xyz

15


Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.