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Anish Sachdeva
Researcher at Dr. B. R. Ambedkar National Institute of Technology Jalandhar
Publications - 109
Citations - 1938
Anish Sachdeva is an academic researcher from Dr. B. R. Ambedkar National Institute of Technology Jalandhar. The author has contributed to research in topics: Supply chain & Quality (business). The author has an hindex of 20, co-authored 94 publications receiving 1464 citations. Previous affiliations of Anish Sachdeva include Indian Institute of Technology Roorkee.
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Review of research work in sinking EDM and WEDM on metal matrix composite materials
TL;DR: A review of EDM process and year wise research work done in EDM on metal matrix composites is presented in this article, which also discusses the future trend of research work in the same area.
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Tool wear, chip formation and workpiece surface issues in CBN hard turning: A review
TL;DR: A survey of the recent research progress in hard turning with CBN tools in regard of tool wear, surface issues and chip formation is presented in this paper, where a significant pool of CBN turning studies has been surveyed in an attempt to achieve better understanding of tool wears, chip formation, surface finish, white layer formation, micro-hardness variation and residual stress on the basis of varying CBN content, binder, tool edge geometry, cooling methods and cutting parameters.
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Investigation of the stability of MgO nanofluid and its effect on the thermal performance of flat plate solar collector
TL;DR: In this paper, the thermal performance of flat plate solar collector (FPSC) was investigated at different particle concentrations (0.08% − 0.4%) as a function of time.
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Investigating surface roughness of parts produced by SLS process
TL;DR: In this article, the surface roughness (SR) of parts produced by the SLS process has been investigated and the empirical models have been purposed to predict the feasibility of different process parameters viz., laser power, scan spacing, bed temperature, hatch length, and scan count.
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Risk analysis of cutting system under intuitionistic fuzzy environment
TL;DR: An integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes is proposed.