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High Temperature Material Processes: An International Quarterly of High-Technology Plasma Processes

Publication de 4  numéros par an

ISSN Imprimer: 1093-3611

ISSN En ligne: 1940-4360

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 0.4 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.1 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00005 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.07 SJR: 0.198 SNIP: 0.48 CiteScore™:: 1.1 H-Index: 20

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EXPERIMENTAL INVESTIGATIONS ON PRECISION MACHINING OF THERMAL BARRIER COATINGS AND APPLICATION OF THE GREY RELATION APPROACH TO DETERMINE THE OPTIMUM PROCESS PARAMETERS

Volume 20, Numéro 4, 2016, pp. 333-354
DOI: 10.1615/HighTempMatProc.2017019985
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RÉSUMÉ

The metallic component of thermally sprayed industrial ceramic oxide coatings, i.e., thermal barrier coatings (TBC) exhibit both metal and ceramics features such as toughness, increased hardness, thermal and chemical degradation, and wear resistance. Despite their outstanding performance characteristics, TBCs are not widely used due to the high machining cost, difficulty to machine, and the inadequate machining information. The thickness (100 to 300 μm) of TBCs demand precision machining carried out by surface grinding and lapping using special tools. The performance characteristics of precision machining of TBCs are studied experimentally at various cutting parameters by measuring the cutting forces Ft and Fn and surface roughness Ra. Optimum machining conditions for better performance are discussed. Further work shows a productive approach to the optimization of the multiple output characteristics based on the grey relation analysis to minimize Ft, Fn, and Ra using trials conducted according to the orthogonal array of Taguchi's method. The table and graphs for each level of the precision machining factors (type of coating, grinding wheel type, spray jet power, and standoff distance) are obtained. Using the ANOVA, the significant influence of the type of a grinding wheel has been revealed. An optimal combination of the input parameters was verified through a series of confirmation tests. It is proved that the above output quality characteristics would improve the efficiency through this approach.

CITÉ PAR
  1. Yunus Mohammed, Alsoufi Mohammad S., Mathematical Modelling of a Friction Stir Welding Process to Predict the Joint Strength of Two Dissimilar Aluminium Alloys Using Experimental Data and Genetic Programming, Modelling and Simulation in Engineering, 2018, 2018. Crossref

  2. Asadullah Mohammed, Bhagyashekar M. S., Yunus Mohammed, RSM multi-properties optimization of various input factors of thermal barrier composites, Multiscale and Multidisciplinary Modeling, Experiments and Design, 5, 1, 2022. Crossref

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