Quality Management and 'Sample DNA', supporting a proactive and integrated reconciliation
Keywords: Quality Management, Reconciliation, Sampling, Quality Quantification, Mine Integration.
Abstract
Currently, F-Series Reconciliation is used in the mining industry to monitor the ability of the supply chain to transform geological resources/reserves into saleable products required for the market. The inputs currently used in reconciliation include the information/data from the tonnes (involving different types of weightometers) and grades (involving different sampling points in the value chain).
This current metric faces several challenges including: 1) calculations are performed under the assumption that the input data (tonnes and quality) is representative of the different stages of the production process (from ore to product); 2) actions in response to reconciliation outcomes could be considered “reactive”, because, given they are generally calculated once a month or quarter; any issues identified have already impacted the financial outcomes to the organization for the period.
From the perspective of sampling/data representivity, Quality Management programs (as the evolution of Quality Assurance and Quality Control – QAQC - programs) are expected to be implemented across the value chain. This involves assessments to be undertaken to determine/quantify the “quality” of their inputs and processes, depending on the requirements established in the processing chain (e.g. geoscience, production, processing, port, and marketing).
The challenge of the current stage is that the quality of the inputs supporting the productive process are assessed in isolation and sometimes at different levels of maturity on sampling & QAQC concepts understanding, which can impact business capacity to optimise production decisions due to “false sense of data confidence”.
This paper elaborates on how the quality of the production inputs (tonnes and quality) could be managed in integration across the value chain, by the implementation of a centralised Quality Management to monitor, standardise, and manage the representivity of the information from “ore in the ground” to a “saleable product”. In addition, this paper highlights and opens the discussion on how the “sample DNA” (grade per particle size distribution) can be monitored and reconciled across the value chain to establish pro-active warnings if gaps are determined between Grade Control Model vs Grade Feed (same “ore DNA”), or Processing Plant versus Port (same “product DNA”), for example. Also, this work discusses on how today’s sampling practices can impact the “sample DNA” and the assessment of future technological applications related.