{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T20:39:23Z","timestamp":1772311163841,"version":"3.50.1"},"reference-count":34,"publisher":"Emerald","issue":"3","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["GS"],"published-print":{"date-parts":[[2019,7,1]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to examine the performance parameters of WEDM to improve the productivity and material removal rate (MRR) with a high surface finish of high chromium-high carbon dies steel.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>The experiments were performed on AGIE CUT 220 CNC WEDM. High chromium-high carbon dies steel (D3) was used in the form of a rectangular plate. The workpiece and the brass wire having diameter \u0278 0.25\u2009mm had linked up with +ve and \u2013ve polarity in the DC power source, respectively. De-ionized water having a conductivity level of 0.6\u2009<jats:italic>\u00b5<\/jats:italic>s\/cm was used as the dielectric medium. The dielectric fluid was flushed from the top and bottom nozzles and material was submerged in the dielectric.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The WEDM process parameters for D3 die steel had optimized by using Grey relational analysis method couples with Taguchi method. The optimum solution has been calculated for MRR, cutting speed (Cs), machining time and surface roughness (SR) (Ra value). A fuzzy logic model using Matlab was developed for the prediction of performance parameters, namely MRR, cutting speed (Cs), machining time (M\/c time) and SR with respect to changes in input parameters.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>The fuzzy model shows the 96.19 percent accuracy between the experimental values and the predicted values.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>The optimized parameters by multi-parametric optimization method showed considerable improvement in the process and will facilitate the WEDM, tool and die industries, defense and aerospace industries to improve the productivity with the higher surface finish.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This manuscript represents valid work and the authors have no conflict of interests. The attained optimum outcomes had also been examined through a real experiment and established to be satisfactory.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/gs-01-2019-0004","type":"journal-article","created":{"date-parts":[[2019,6,17]],"date-time":"2019-06-17T04:00:57Z","timestamp":1560744057000},"page":"336-355","source":"Crossref","is-referenced-by-count":5,"title":["Selection of WEDM parameters to measure the performance and productivity of die steel grade D3 using GRA and fuzzy logic system"],"prefix":"10.1108","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8505-036X","authenticated-orcid":false,"given":"Sandeep","family":"Kumar","sequence":"first","affiliation":[]},{"given":"Dhanabalan","family":"S.","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020092220515554800_ref001","doi-asserted-by":"crossref","unstructured":"Abraham (2005), \u201cAdaptation of fuzzy inference system using neural learning\u201d, in Nedjah, N. and Mourelle, L.-de-M. 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