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High Temperature Material Processes: An International Quarterly of High-Technology Plasma Processes
ESCI SJR: 0.176 SNIP: 0.48 CiteScore™: 1.3

ISSN 印刷: 1093-3611
ISSN オンライン: 1940-4360

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

DOI: 10.1615/HighTempMatProc.2017019985
pages 333-354

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

Mohammed Yunus
Department of Mechanical Engineering, College of Engineering and Islamic Architecture, Umm Al-Qura University, Makkah, Al-Abdiah, 24231, Kingdom of Saudi Arabia
Mohammad S. Alsoufi
Department of Mechanical Engineering, College of Engineering and Islamic Architecture, Umm Al-Qura University, Makkah, Al-Abdiah, 24231, Kingdom of Saudi Arabia

要約

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.


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