Exploring Causes of Crane Accidents from Incident Reports Using Decision Tree Krantiraditya Dhalmahapatra, Kritika Singh, Yash Jain and J. Maiti Abstract Electrical Overhead Traveling (EOT) cranes in manufacturing industries serve the purpose of material handling in complex working environment. Com- plexity 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. Keywords EOT crane ⋅ Decision tree ⋅ CART ⋅ Occupational safety 1 Introduction Occupational accident prevention is the key for effective safety management of any industry. Exploration of causes and sequential events that led to these accidents will effect in deployment of interventions to prevent the further occurrence. Manufac- turing industries have seen increase in occupational accidents owing to application of high end machineries with complex working procedures for better productivity. K. Dhalmahapatra ( ✉ ) ⋅ K. Singh ⋅ Y. Jain ⋅ J. Maiti Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India e-mail: kranti.dhalmahapatra@gmail.com K. Singh e-mail: kritika.swati@gmail.com Y. Jain e-mail: yashjainjain1704@gmail.com J. Maiti e-mail: jhareswar.maiti@gmail.com © Springer Nature Singapore Pte Ltd. 2019 S. C. Satapathy and A. Joshi (eds.), Information and Communication Technology for Intelligent Systems, Smart Innovation, Systems and Technologies 106, https://doi.org/10.1007/978-981-13-1742-2_18 175