Stochastic models of risk management of worker fatigue emergence

Purpose: The purpose of the paper is to develop stochastic models for managing the risk of fatigue in an organisation, taking into account the intensity of the negative impact of fatigue factors on workers at the workplace and the intensity of their recovery from such an impact. Design/methodology/approach: It uses the method of analysis of scientific literature to actualise the purpose and define the research tasks; Markov process theory methods are used for mathematical description of random processes of worker fatigue development and their recovery from it during a work shift; methods of probability theory and queuing are used to find the limiting probability distribution of random Markov process’ states. Findings: The proposed stochastic models allow the organisation to carry out the process of managing the risk of fatigue emergence by changing the work-rest schedule’s duration, depending on the parameters’ characteristics of the negative impact intensity of fatigue factors on workers and the recovery of their corpora from such an impact. By changing the specified parameters’ characteristics, it is possible to determine the work schedule during which the period of worker’s fatigue will be as long as possible and the rest schedule during which the period of recovery from the fatigue state will be minimal. Practical implications: The application of the proposed models makes it possible to increase the level of labour productivity in the organisation by determining such durations of work and rest schedules, which provide the opportunity for workers to carry out labour activities during the maximum possible period of time of the work shift, without reaching a fatigued state. Originality/value: For the first time, an approach for managing the fatigue risk is proposed by establishing dependencies between the duration of work and rest schedule and the parameters’ characteristics of the negative impact intensity of the fatigue factors on the worker and their recovery from such an impact, based on the application of the Markov processes theory.