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Exploring Causes of Crane Accidents from Incident Reports Using Decision Tree

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Information and Communication Technology for Intelligent Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 106))

Abstract

Electrical Overhead Traveling (EOT) cranes in manufacturing industries serve the purpose of material handling in complex working environment. Complexity involved in human machine interaction at the workplace make it hazard and incident prone. In current study, emerging data mining technique like Decision tree (DT) is adopted to explore the underlying causes involved in incidents happened in the studied plant from the year 2014–2016. Interesting results are obtained from the analysis like number of incidents happened during construction and maintenance activities and in weekend (Saturday, Sunday) are more. Managerial implications are suggested for betterment of safety management system of the studied plant.

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Authors and Affiliations

  1. Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Krantiraditya Dhalmahapatra, Kritika Singh, Yash Jain & J. Maiti

Authors
  1. Krantiraditya Dhalmahapatra
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  2. Kritika Singh
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  3. Yash Jain
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  4. J. Maiti
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Corresponding author

Correspondence to Krantiraditya Dhalmahapatra .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, India

    Suresh Chandra Satapathy

  2. Sabar Institute of Technology, Gujarat Technological University, Ahmedabad, Gujarat, India

    Amit Joshi

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© 2019 Springer Nature Singapore Pte Ltd.

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Dhalmahapatra, K., Singh, K., Jain, Y., Maiti, J. (2019). Exploring Causes of Crane Accidents from Incident Reports Using Decision Tree. In: Satapathy, S., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems . Smart Innovation, Systems and Technologies, vol 106. Springer, Singapore. https://doi.org/10.1007/978-981-13-1742-2_18

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