A Markovian Analysis of Industrial Accident Data in a Nigerian Manufacturing Company

Despite the effort of manufacturing company owners in Nigeria to curtailindustrial accident occurrence, it still remains a daunting challenge. This study seeks topredict the drift of industrial accidents in manufacturing companies in Delta State,Nigeria in order to ensure the health and safety of staff in the workplace. Markov Chain(MC) model was used to analyse eleven year industrial accident data obtained from aprimary source: Health, Safety, and Environment (HSE) department of a manufacturingcompany in the Delta state of Nigeria. The data was summarised as integrated safetydata to give a better picture of the organisation safety culture. The data was analysedand found to have absorbing chain tendencies. It also possesses a note of stochasticregularity, which fits into an MC model. Accident data in the company were classifiedinto five states, namely fatality, loss time accident, medical aid accident, first aidincident, and near-miss. The result from the study reveals that fatality and loss timeaccidents were absorbing states, while medical aid accidents, first aid incidents, andnear-miss were found to be non-absorbing states. A worker who commits an error inthe form of near miss 1000 times stands a chance of fatality 77 times out of this totaltime of work error. This study will serve as a guide to manufacturing companystakeholders on the need to create safety awareness among the workforce.