Search Results - "Kumaraguru, Senthilkumaran"

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  1. 1

    A view similarity-based shape complexity metric to guide part selection for additive manufacturing by Jayapal, Jayakrishnan, Kumaraguru, Senthilkumaran, Varadarajan, Sudhir

    Published in Rapid prototyping journal (02-03-2023)
    “…Purpose This paper aims to propose a view similarity-based shape complexity metric to guide part selection for additive manufacturing (AM) and advance the…”
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    Journal Article
  2. 2

    Faceted classification of manufacturing processes for sustainability performance evaluation by Kumaraguru, Senthilkumaran, Rachuri, Sudarsan, Lechevalier, David

    “…Sustainability characterization of manufacturing processes is key to the inventory data development for life cycle analysis of products and processes in…”
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    Journal Article
  3. 3

    Novel process planning approach for support-free additive manufacturing using multi-axis deposition systems by Manoharan, Madhanagopal, Kumaraguru, Senthilkumaran

    “…Direct Energy Deposition (DED) is one of the Metal Additive Manufacturing processes, which can be used to print near-net shapes and repair volumes using…”
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    Journal Article
  4. 4

    Evaluation of computationally optimized design variants for additive manufacturing using a fuzzy multi-criterion decision-making approach by Jayapal, Jayakrishnan, Kumaraguru, Senthilkumaran, Varadarajan, Sudhir

    “…The additive manufacturing industry requires effective and standardized methods for selecting design variants generated through computational tools. To address…”
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    Journal Article
  5. 5

    Developing a virtual machining model to generate MTConnect machine-monitoring data from STEP-NC by Shin, Seung-Jun, Woo, Jungyub, Kim, Duck Bong, Kumaraguru, Senthilkumaran, Rachuri, Sudarsan

    “…The ability to predict performance of manufacturing equipment during early stages of process planning is vital for improving efficiency of manufacturing…”
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    Journal Article
  6. 6

    Faster temperature prediction in the powder bed fusion process through the development of a surrogate model by Anandan Kumar, Hemnath, Kumaraguru, Senthilkumaran, Paul, CP, Bindra, KS

    Published in Optics and laser technology (01-09-2021)
    “…•Simulation and modelling of Powder Bed Fusion of nickel alloy IN625 single tracks.•Development of surrogate model to predict the thermal behaviour in reduced…”
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    Journal Article
  7. 7

    Methods and Tools for Performance Assurance of Smart Manufacturing Systems by Kibira, Deogratias, Morris, K C, Kumaraguru, Senthilkumaran

    “…The emerging concept of smart manufacturing systems is defined in part by the introduction of new technologies that are promoting rapid and widespread…”
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    Journal Article
  8. 8

    Energy metrics for product assembly equipment and processes by Feng, Shaw C., Senthilkumaran, Kumaraguru, Brown, Christopher U., Kulvatunyou, Boonserm

    Published in Journal of cleaner production (15-02-2014)
    “…A key factor deciding the capacity to increase the sustainability of final products is the energy efficiency. The energy embodied in a product is an…”
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    Journal Article
  9. 9

    Path Planning for Direct Energy Deposition with Collaborative Robots: A Review by Manoharan, Madhanagopal, Kumaraguru, Senthilkumaran

    “…This paper discusses the issues and opportunities in using stand-alone and collaborative robots in Additive Manufacturing (AM) processes. Recently, the…”
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    Conference Proceeding
  10. 10

    Collaborative motion synchronization for affordable open-source cobots by Manoharan, Madhanagopal, Thilak, Karanam Sreedhar Sai, Kumaraguru, Senthilkumaran

    “…Collaborative robots are increasingly used in several industries because of their safety and easy deployment for increased productivity. This paper presents…”
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    Conference Proceeding
  11. 11

    A Novel Volume Decomposition Methodology for Multi-Robots Collaborative Additive Manufacturing by Manoharan, Madhanagopal, Shridhar, Aditya Navghare, Vinod, Vivek Yadav, Kumaraguru, Senthilkumaran

    “…This work presents a methodology to decompose part volume into sub-volumes for work allocation to multiple robots considering the effect of bonding. The use of…”
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    Conference Proceeding