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Identification and Ranking of Supply Chain Risks Using Fuzzy TOPSIS: A Case Study of Indian Automotive Manufacturing

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Advances in Mechanical Engineering and Technology

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

To remain competitive and profit margin in the dynamic market scenario, automotive manufacturing industries are bound to render high-quality products at the optimum cost. However, complexities associated with various interlinked activities in the Automotive Supply Chain (SC) ultimately make the external and internal SC environment extremely uncertain. Firms surrounded by an uncertain environment are exposed to multiple risk factors at all SC echelons causing disruptions that leads to inferior operational performance. Indian automotive industry is a leading industrial sector and set to see immense growth, making a more extensive supply chain network and posing challenges due to increasing complexities. In addition, the level of collaboration and highly complex SC makes the automotive SC vulnerable to risks. The proper assessment of risk factors critical to the automotive SC is essential for policy-makers to build proactive risk mitigation strategies. This study investigates Critical Risk Factors (CRFs) existing in the manufacturing SC of Indian automotive industries. Ranking of identified CRFs is done using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) based on the severity of adverse impact on five criterion using survey data. The results indicate that among the identified 13 CRFs, ‘Delay risks’, ‘Risks related to management’ and ‘Risks related to raw materials’ are crucial to Indian automotive industries. This study's outcome is expected to assist forefront managers of the Indian automotive sector in framing proactive risk mitigation strategies and adopting a systematic approach for risk prioritization.

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Author information

Authors and Affiliations

  1. Research Scholar, Department of Mechanical Engineering, Rajiv Gandhi Institute of Technology, Mumbai, Maharashtra, India

    Vinod G. Surange

  2. Assistant Professor, Department of Mechanical Engineering, St. John College of Engineering and Management, Palghar, Maharashtra, India

    Vinod G. Surange

  3. Rajiv Gandhi Institute of Technology, Mumbai, Maharashtra, India

    Sanjay U. Bokade

Authors
  1. Vinod G. Surange
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  2. Sanjay U. Bokade
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Editor information

Editors and Affiliations

  1. Department of Design, Department of Mechanical Engineering, Delhi Technological University, New Delhi, India

    Ranganath M. Singari

  2. Department of Mechanical Engineering, Indian Institute of Technology Indore, Indore, Madhya Pradesh, India

    Pavan Kumar Kankar

  3. Physico-Mechanical Metrology, CSIR - National Physical Laboratory, New Delhi, India

    Girija Moona

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Surange, V.G., Bokade, S.U. (2022). Identification and Ranking of Supply Chain Risks Using Fuzzy TOPSIS: A Case Study of Indian Automotive Manufacturing. In: Singari, R.M., Kankar, P.K., Moona, G. (eds) Advances in Mechanical Engineering and Technology. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-9613-8_8

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  • DOI: https://doi.org/10.1007/978-981-16-9613-8_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-9612-1

  • Online ISBN: 978-981-16-9613-8

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