## 3 Results
### Decision Support System for Mining Machinery Risk Mitigation  
On the basis of the structural equation model that describes the contextual dependence of the risk of the operation of mining machines, the designed decision support system (DSS) is programmed in the C# language with a dual function. The first module of the designed DSS refers to the rule base mechanism that observes each factor individually in the operator-mining machine system and gives a recommendation for risk mitigation in the event that one of the observed values exceeds the permitted threshold level (Supplementary Materials--Knowledge Base S1: Knowledge base). The second module of the designed DSS refers to the implementation of mathematical Equations (1)-(8) in the inference mechanism, which, based on the numerical values of the entered observed variables, obtains the values of the constructs whose value is assessed from the aspect of risk for the occurrence of unwanted events in the human-mining machine system. Formula (1) describes the general form of mathematical structural equations, while Formula (2) describes the relations of ergonomic features of the operator system and workplace (EO) with four constructs (AC, ES, EC, EE). These four constructs represent the influence of the anthropometric characteristics of the operator, ergonomic adjustments of seats, control organs, and working conditions. Formula (5) gives the mathematical relation between EO and AC, ES, EC, and EE constructs for the final extraction of the EO segment. Formula (2) represents safety and health at work, also using four constructs (SAC, SC, RP, SP). These four constructs take into account the mining operators' attitudes in light of safety awareness, competencies, safety communications, and compliance with safety rules, procedures, and policies. Formula (4) describes the calculation of SHW--safety and health at work--on the basis of four complementary constructs (SAC, SC, RP, SP). Formula (6) represents the mining machine causes of downtime: the impact factor of downtimes originating from inadequate management (misuse) of the mining machine (IF), the influence factor of electrical downtime on the mining machine (EF), the impact factor of the technical downtime on the mining machine (TF), and the impact factor of organizational downtime on the mining machine (OF). These four constructs use the collected data for each workplace and its impact is calculated as the risk of mining machine downtimes. The risk of occurrence of the mining machine-specific downtime is calculated as the product of the duration of the observed downtime, its level of danger, and the frequency of occurrence. Formula (7) describes the relation between the first group of the mining machine causes of downtime and safety and health at work. We have found that only the first group of causes of downtime was interrelated with the SHW construct. That is the reason why we divided the causes of the mining machine downtime break in two groups. Formula (8) describes the relation between the mining machine causes of downtime (divided into two groups--RM1 and RM2) and ergonomic characteristics of the operator system and workplace (EO). This equation provides a view on the indirect link between the anthropometric characteristics of the operator, ergonomic adjustments of seats, control organs, and working conditions and mining machine causes of downtime, where, in some of the causes, the human factor is dominant (abuse of machine, organizational factor, inadequate maintenance, etc.) The contextual, ergonomic, adaptive decision support system is designed as a web-based tool, which the user accesses online.