# Development of a justification process for selecting alternative risk reduction measures

## TL;DR

This study creates a process to choose the best ways to reduce mining risks while keeping costs low.

## Contribution

The study introduces an eleven-step risk management process with feedback loops and efficiency-based decision algorithms.

## Key findings

- A methodology was developed to select risk reduction measures based on financial efficiency.
- Algorithms were created to solve decision-making problems involving combinations of preventive measures.
- An example calculation demonstrated the process for reducing pneumoconiosis risk in miners.

## Abstract

The aim of this study is to develop a process for determining a set of alternative preventive measures to reduce risk levels, using the example of reducing the incidence of occupational pneumoconiosis in miners under conditions of financial cost minimization.

This study was conducted using a system analysis to identify priority directions for risk reduction under limited financial resources based on the relationship between the measures and their risk reduction efficiency. A methodology was developed to justify the selection of risk reduction measures from a set of alternatives based on the calculation of an efficiency factor grounded in financial losses. An eleven-step risk management process was designed to determine alternative preventive measures, characterized by feedback loops that enable the selection of optimal risk reduction strategies.

This study presents algorithms for solving three types of decision-making problems regarding the selection of combinations of preventive measures from a defined set of alternatives. These algorithms consider the priority of the measures and allow for a comparison between the effectiveness of several measures and a single measure that can also reduce the risk to an acceptable level.

An example of calculating the efficiency of preventive measures to reduce the risk of pneumoconiosis among miners is also provided. A key feature of this study is the improvement in the risk management process by integrating the efficiency factor of risk reduction under financial constraints.