STATISTICAL PROCESS CONTROL IMPLEMENTATION AS EARLY WARNING SIGNAL FOR SAFETY INTERVENTION IMPROVEMENT AT MINING OPERATION

Abstract

As the frequency, severity, and costs of safety risks continue to become a challenge for mining industry, the company understood that the existing safety analytic does not provide adequate information, as it has been relying predominantly on collecting and evaluating aggregated data of lagging indicators about past accidents. This method has been negatively driving the organization to carry out repetitive cycle of accident analysis and problem solving, and therefore, undertaking reactive responses. This paper investigated how statistical process control, in particular control charts, can be applied to hazards data, as the leading indicator of accidents, to detect statistically trends in safety process and safety behavior, aiming to control the safety process in real-time manner before the occurrence of accidents. The result showed that the latest iteration of control limits development in Phase 3 is suitable as the control chart for safety process in one of case study mine operation site. Furthermore, the implementation of control charts to hazards data not only it helps the organization to transition its safety analytic to leading indicator analysis, it enables the organization to control safety process in real-time practice and to carry out timely safety intervention long before the potential occurrence of severe accidents, in which within this case, the first early warning signal was triggered 49 days before the occurrence of the fatality accident.