relation: https://khub.utp.edu.my/scholars/12949/
title: Statistical optimization by the response surface methodology of direct recycled aluminum-alumina metal matrix composite (MMC-AlR) employing the metal forming process
creator: Ahmad, A.
creator: Lajis, M.A.
creator: Yusuf, N.K.
creator: Ab Rahim, S.N.
description: In this study, the response surface methodology (RSM) and desirability function (DF) were utilized to optimize the recycling conditions of aluminum (AA6061) chips, in the presence of particulate alumina (Al2O3), to obtain a metal matrix composite of recycled aluminum (MMC-AlR) using hot press forging processes. The effects of temperature (430-530 °C) and holding time (60-120 min) were investigated. The introduction of 2.0 wt.  of Al2O3 to the aluminum matrix was based on preliminary research and some pilot tests. This study employed the 2k factorial design of experiments that should satisfy the operating temperatures (T) of 430 ffiC and 530 ffiC with holding times (t) of 60 min and 120 min. The central composite design (CCD) was utilized for RSM with the axial and center point to evaluate the responses to the ultimate tensile strength (UTS), elongation to failure (ETF), and microhardness (MH). Based on RSM, with the desirability of 97.6, the significant parameters T = 530 °C and t = 120 min were suggested to yield an optimized composite performance with UTS = 317.99 MPa, ETF = 20.45, and MH = 86.656 HV. Three confirmation runs were performed based on the suggested optimum parameters, and the error revealed was less than 25. The mathematical models suggested by RSM could adequately describe the MMC-AlR responses of the factors being investigated. © 2020 by the authors.
publisher: MDPI AG
date: 2020
type: Article
type: PeerReviewed
identifier:   Ahmad, A. and Lajis, M.A. and Yusuf, N.K. and Ab Rahim, S.N.  (2020) Statistical optimization by the response surface methodology of direct recycled aluminum-alumina metal matrix composite (MMC-AlR) employing the metal forming process.  Processes, 8 (7).   ISSN 22279717     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088514182&doi=10.3390%2fpr8070805&partnerID=40&md5=e3d2105eeb6663789fa50c3e0773e348
relation: 10.3390/pr8070805
identifier: 10.3390/pr8070805