Improving the mathematical model of change in the body state of an employee
DOI:
https://doi.org/10.15587/1729-4061.2020.195755Keywords:
labor safety, production factor, employee’s body condition, Hammerstein model, functional moduleAbstract
Current models of labor safety management at enterprises have several drawbacks. The main drawback of such models consists in their focus on the analysis of the accidents that have already occurred at the enterprise. In addition, the existing models poorly take into account the mutual influence of several production factors on each other during their combined effect on the employee’s body.
To eliminate these shortcomings, the task of improving the mathematical model of change in the employee body state was set. The Hammerstein model was considered as the initial model of change in the employee’s body state. In the course of this model improvement, an individual component of the model that describes the employee’s state immediately before the start of the work shift was chosen for situations of impossibility or severe limitation of applying technologies for monitoring the employee’s body state. To assess the mutual impact of various production factors, instead of a vector function that describes the cumulative effect of factors on the employee’s body, a set of multiple regression equations that describe the mutual impact of factors on individual employee’s body state parameters was introduced into the model.
The improved model was tested at an industrial enterprise using the example of a team of welders (5 persons). To assess their body state, systolic and diastolic blood pressure, heart rate and reaction time to a light stimulus were used. The results presented in the article make it possible to draw a general conclusion about the adequacy of the proposed model to the observed results of the impact of production factors on employee organisms. It was pointed out that the results of modeling slightly exceeded the results of direct measurements in most casesReferences
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Copyright (c) 2020 Maksym Ievlanov, Nataliia Serdiuk, Andrew Feshchenko, Tetiana Duiunova, Mykola Kiriienko, Ihor Cherepnov, Liudmyla Pivnenko, Vasilij Dyakonov
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