Decision Support System for Mining Machinery Risk Mitigation Driven by Ergonomics and Contextual Theory

Abstract

Despite being very old, the mining industry continues to be one of the major sources of pollution, with more people killed or injured than in all other industries. Prevention of incidents/accidents on machinery in mining pits and the issues of operator safety on mining machinery largely depend on the ergonomic adaptation of the workplace, compliance with safety procedures and policies, and organizational and other influential factors. Evidently, scarce consideration of those factors in the available literature has not given satisfactory results till now. The aim of this paper is to first set up a comprehensive model based on ergonomic factors and contextual theory, which takes into account all the influencing factors on the occurrence of incidents/accidents and represents a complex system of interdependence of influential variables of diverse, mostly stochastic nature, and then design a software solution on the given basis. In this research, based on the extensive data collected, a model was generated using the structural equations modelling methodology, which was then used to design the reasoning logic in the expert system for mitigating the risks of the operation of mining machines. An innovative solution incorporating a mathematical model of the interdependence of influential variables into the stored knowledge base offers a decision support system that provides recommendations for the maintenance of a particular mining machine, depending on the assessment of model factors in a specific decision-making situation at the higher organizational level and ergonomic suitability for the operator at the lower organizational level, and, in that manner, enables the mitigating of risky/unwanted events.