S
S. K. Mukherjee
Researcher at Birla Institute of Technology, Mesra
Publications - 47
Citations - 654
S. K. Mukherjee is an academic researcher from Birla Institute of Technology, Mesra. The author has contributed to research in topics: Thermoelectric effect & Chemistry. The author has an hindex of 10, co-authored 28 publications receiving 504 citations. Previous affiliations of S. K. Mukherjee include University of Duisburg-Essen & Birla Institute of Technology and Science.
Papers
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Integrating AHP with QFD for robot selection under requirement perspective
TL;DR: In this paper, an integrated model combining AHP and QFD has been delineated for the industrial robot selection problem, where seven technical requirement factors have been considered for the case study.
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Distance-based consensus method for ABC analysis
TL;DR: This article demonstrates a way of classifying inventory items using the TOPSIS (‘Technique for Order Preference by Similarity to Ideal Solution’) model, which has been applied in a pharmaceutical company located in the heart of Kolkata, India.
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Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF
TL;DR: The key objective of this paper is to guide decision makers in finding out the best candidate-alternative with higher degree of satisfaction with lesser degree of vagueness under tripartite fuzzy environment.
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Effect of deposition process parameters on resistivity of metal and alloy films deposited using anodic vacuum arc technique
TL;DR: In this paper, electrical resistivity and average grain size of deposited thin films have been measured and their dependence on the deposition process parameters has been investigated and compared with numerically generated results using Fuchs-Sondheimer theory and Mayadas-Shatzkes theory which has been found to be in good agreement for film thickness greater than 80nm.
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A fully fuzzified, intelligent theory-of-constraints product-mix decision
TL;DR: In this article, a fuzzified approach using fuzzy linear programming (FLP) using a suitably designed smooth logistic membership function (MF) for finding fuzziness patterns at disparate levels of satisfaction for theory of constraints-based (TOC) product-mix decision problems is presented.