• Title/Summary/Keyword: TATA Motors

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Case Study On Knowledge Management Practices In Indian Manufacturing Organizations - Tata Motors, BHEL And Mahindra And Mahindra

  • Rangnekar, Santosh
    • Journal of Digital Convergence
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    • v.8 no.1
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    • pp.27-40
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    • 2010
  • This case study covers the Knowledge Management research paper that explores the clear idea about the knowledge practicesthat are used in the corporate sector to achieve the strategic advantage over the competitors. The quoted example of the three manufacturing firms TATA MOTORS, BHEL, and M&M have tried to compare the Knowledge practices in these firms, which explores the concept clearer that the competitors can use the same or the different type of knowledge practices to achieve the competitor advantages. In order to help knowledge management goals, an integrated knowledge management system consisting of the knowledge management techniques and technologies are used. The knowledge Management is supported by different techniques and practices whichare knowledge content, people skills, technology and strategy based. The technology and techniques supports these factors of knowledge management. The paper discuss different techniques and processes adapted by three Indian organizations and a comparison is made to suggest the guidelines of KM practices to manufacturing Industries.

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Optimization of Process Parameters for Dry Film Thickness to Achieve Superior Water-based Coating in Automotive Industries

  • Prasad, Pranay Kant;Singh, Abhinav Kr;Singh, Sandeep;Prasad, Shailesh Kumar;Pati, Sudhanshu Shekher
    • Corrosion Science and Technology
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    • v.21 no.2
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    • pp.121-129
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    • 2022
  • A study on water-based epoxy coated on mild steel using the electroplating method was conducted to optimize the process parameters for dry film thickness to achieve superior paint quality at optimal cost in an automotive plant. The regression model was used to adjust various parameters such as electrode voltage, bath temperature, processing time, non-volatile matter, and surface area to optimize the dry film thickness. The average dry film thickness computed using the model was in the range of 15 - 35 ㎛. The error in the computed dry film thickness with reference to the experimentally measured dry film thickness value was - 0.5809%, which was well within the acceptable limits of all paint shop standards. Our study showed that the dry film thickness on mild steel was more sensitive to electrode voltage and bath temperature than processing time. Further, the presence of non-volatile matter was found to have the maximum impact on dry film thickness.