Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2022Novel Fuzzy Measurement Alternatives and Ranking according to the Compromise Solution-Based Green Machining Optimization11citations

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G. Shanmugasundar, G. Shanmugasundar
1 / 1 shared
Cep, Robert
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2022

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  • G. Shanmugasundar, G. Shanmugasundar
  • Cep, Robert
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article

Novel Fuzzy Measurement Alternatives and Ranking according to the Compromise Solution-Based Green Machining Optimization

  • G. Shanmugasundar, G. Shanmugasundar
  • Mahanta, Tapan K.
  • Cep, Robert
Abstract

<jats:p>Due to the increase in the impact of different manufacturing processes on the environment, green manufacturing processes are the prime focus of many current pieces of research. In the current article, a green machining process for stainless steel and SS304 and AISI1045 steel has been optimized using newly developed Fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (F-MARCOS) method in the form of two case studies. In the first case study, nose radius, cutting speed, depth of cut, and feed rate are selected as the process parameters whereas surface roughness, consumption of electrical energy, and power factor are the outputs. In the second case study width of cut, depth of cut, feed rate, and cutting speed were the process parameters and material removal rate (MRR), active energy consumption (ACE), and surface roughness (Ra) are the response variables. The MARCOS method ranks the alternatives based on the ideal and anti-ideal solutions for the different criteria. The inclusion of fuzzy logic adds worth to the model by using a linguistic scale to make the method more practical and flexible. Based on the detailed analysis, it ranked the best alternative in case study one which results in a power factor of 0.862, 26.68 kJ of electrical energy consumption, and surface roughness of 0.36 μm. In the second case study, the best alternative selected by this method gave an MRR of 2400 mm3/min and Ra of 2.29 μm and utilizes 53.988 kJ ACE.</jats:p>

Topics
  • surface
  • stainless steel
  • inclusion