Human factor analysis for railway coach and bogie maintenance using principal component analysis and factor analysis

Abstract

One of the major challenges of railway transportation is to maintain the coach and bogie system for ensuring safety of passengers and goods, and maintain punctuality. In this context, there is a need to study the maintenance activities as well as humans involved in it. The present work aims to identify and analyse human factors responsible for coach and bogie maintenance of railway system. Thirty six human factors were identified. Principal component analysis (PCA) and factor analysis (FA) are used here. Three principal components were identified which represents 99% of the variance in the whole dataset. Factor analysis is performed on these three principal components to find most important factors based on individual factor loadings. Human machine interface, working environment, shift patterns, safety cultures, leadership, time pressure, situational awareness, perception, interpretation and training procedure were found to be few very important human factors.