Quantitative Data Assessment To Support Risk Based Decision-Making In The Minerals Industry

The Coal Mine Safety Regime Model (CMSR) developed by Professor Jim Joy as part of ACARP C15011 Stage 1 represents a holistic and leading-practice risk management process designed to support the Australian coal mining industry. CMSR encompasses four layers of risk management, i.e. from strategic to operational.

The model is an important part of the Global Minerals Industry Risk Management education and training programme derived by the University of Queensland and applied across the global operations of Anglo American. The model is also the basis for their operational risk management procedures. In Anglo American, as well as other major mining companies, the basis of acceptable risk is evolving from qualitative risk re-ranking to risk-control effectiveness estimation. The risk opportunity decision-making model (RODMMODEL) and in particular the risk-cost-benefit (RCB) decision support tools, i.e. RCB generator (RCBGEN) and the generic and incremental qualitative, semi-qualitative, qualitative risk-control evaluation assessments method (SQ3RCEAMETHOD), support the objectives of the top two layers of the above CMSR model.

The aims of this project were to:

· Analyse mine site data sources which are applicable for quantitative analysis;

· Define quantitative data capture methodologies in data poor areas;

· Apply these data sets to risk-control effectiveness models to enable fully quantitative risk control effectiveness; and

· Demonstrate robust QRA in two significant risk areas.

This project advanced the initial overarching framework as depicted in the RODMMODEL, with a particular focus on the application of the generic and incremental SQ3RCEAMETHOD, that is part of the overall quantitative risk-control effectiveness assessment process (QRCEAPROCESS). The RODMMODEL is a generic and robust way to demonstrate meeting legal obligations for managing hazards and the associated risks.

In this project, the risk analysis process takes decision makers beyond the use of matrices to prioritise major hazards and the associated MUEs and risk-cause-consequence pairs.

The SQ3RCEAMETHOD can also be applied independently to rank effectiveness of risk management strategies using its techniques ranging from qualitative to quantitative to suit the risk management activity, resources and skill sets available.

The two case studies comprised of:

· Heavy vehicle interaction with people in underground mines (site-based); and

· Unplanned movement of longwall (LW) equipment (site-based).

The project case study-related outputs were synthesised to highlight important findings specific to the major hazards analysed. Each case study identified useful existing data and highlighted gaps where data could be collected to support risk-based decision-making processes. A generic model has been developed that is applicable to the analysis of other major hazards in mining and other industries.

The Risk-Control Effectiveness Process and Methodology Summary

The development of the QRCEAPROCESS has introduced three distinct steps and as such has been renamed to overcome potential confusion with the nomenclature for one of the newly-introduced step, i.e. step 3. In summary, the QRCEAPROCESS has three new steps as follows:

· Generically define the risk-control scope/criteria and identify risk-controls;

· Generically describe the risk-control system functionality and define the system set-up requirements; and

· Apply the SQ3RCEAMETHOD, semi-quantitative/quantitative/qualitative risk-control effectiveness methodology.