Mine-to-mill reconciliation is a crucial function to understanding value and performance within a mine operation. By comparing actual results against estimates and assumptions, you can calibrate a mine plan and continuously improve it by delivering higher value through risk mitigation and embedding optimization opportunities. Optimized reconciliation programs unlock value in operations unseen by long-range planning or assumed to be too challenging to pursue. Additionally, reconciliation is a critical tool that enables leaders to make essential business decisions by providing confidence and understanding in a mine’s expected performance.
Mine-to-mill reconciliation relationships can be challenging to analyze, interpret, and communicate (Figure 1). As a result, many operations/companies fail to extract the full benefit of mine-to-mill reconciliation. As such, the focus is on easy-to-understand high-level outputs such as budget performance and the evaluation of tonnes, grades and recoveries against the assumptions made in resources and reserves.
Figure 1: Mine-to-mill reconciliation relationships across the integrated mine value chain
Source: Adapted from C. Morley (2003)
The failure to extract full benefit from reconciliation is often challenging due to the difficulty in determining “why” a metric is over or underperforming; instead, at best, areas of focus are determined. Subsequently, many risks are likely not identified or mitigated, and optimization opportunities can go unrecognized. Additionally, excessive time is likely to be spent trying to determine the cause.
Good to Great
To have the highest likelihood of determining “why” a reconciliation metric is performing, a reconciliation program needs to be supported by the following principles across an operation and organization. Essentially, this makes the difference between a good reconciliation program and a great one.
The first key to a great reconciliation program is having multiple types of and excellent quality data at each measurement point. Datasets need to range from capturing critical first principal data to high-level consolidated data within each measurement point. It is essential to have multiple data types at each measurement point to compare, validate, and isolate critical drivers to performance. For instance, examples of comparative datasets and quality data include:
- Combining excavation surveys and grade control geological models will allow you to calculate overall dilution and modelled ore grade. However, face maps, channel samples, and direction mark-up details (in an underground cut and fill mine) will allow you to reconcile over and underbreak performance as components to dilution performance compared to the reserve model and highlight potential optimization opportunities.
- The key to quality for many data types is proper maintenance and calibration of measurement tools, such as the weightometers or belt samplers in a processing plant. Additionally, supporting sample data, such as moisture samples, must be taken regularly to provide the sustenance required for the integrity of some data types, including weightometer data. Together maintenance, calibration, and support data can ensure no bias in many data types.
Secondly, to be successful, the reconciliation specialist must have an excellent understanding of the entire integrated mine value chain and what each data source represents. Additionally, key competencies include being highly numerate and analytical. Armed with these skills allows one to dive deeper into the possible source of variance on a critical metric.
From here, it is vital to analyze the many reconciliation relationships with different light, from analysis on a time horizon to study on a bench scale or vertical scale, such as tonnes per vertical meter. Furthermore, each deposit and mine are different as no two ore bodies are identical in a geological sense and a mine planning and execution sense.
Additionally, it is crucial to understand the noise and variance in each data set when reviewing different reconciliation relationships. As such, the key is to focus on trends that account for the noise and variance and not singular data points. For instance, looking at a twelve-month rolling average is likely to mask issues and potential optimization opportunities. Likewise, looking at monthly data is typically too narrow to identify the problems due to the noise and variance in even the most accurate data. However, reviewing a three-month weighted rolling average trend will highlight fundamental changes in the ore body or execution promptly with confidence (Figure 2).
Figure 2: Actual grade performance to reserves
Keep in mind, with a trend highlighting a potential issue or opportunity, it will likely be a combination of multiple short, medium, and long-term trends, reviewed in tandem, that will enable the identification of the “why.” Thus, allowing you to identify risks and opportunities with confidence.
A trigger action response plan (‘TARP’) is required to facilitate when a reconciliation trend warrants a deeper dive and reaction. The TARP is also necessary due to the hasty nature of teams when reading reconciliation trends to create a mitigating action when negative performance occurs, or embed upside in a mine plan. For instance, suppose there is not a framework in place to indicate when to initiate further research. In that case, time is likely wasted, and there is a high likelihood of generating phantom issues due to not enough data collected to narrow sufficiently in on a root cause. Combined with action on these phantom issues, there is potential to mask the critical problem or opportunity, thus increasing risk or not capturing potential value.
One potential method to analyzing trends and developing a TARP is through the use of control charts 1. These charts are beneficial as they allow the user to conclude whether the variance seen in the data is consistent or unpredictable; thus, helping management to determine when to act and the type of action needed.
Another key to a great reconciliation program is to have buy-in and understanding of reconciliation metrics at all levels in an organization. Thus, allowing the entire organization to leverage the knowledge in their decision-making (Figure 3). The most efficient way to facilitate buy-in and understanding is through a company communication and reporting plan, driven from the organization’s top.
Essential to effective communication is to know what each level needs to focus on:
- Site technical disciplines and site management: Focus on the analysis and improvement of building blocks. As a result, ensuring assumptions in resources, reserves, and the mine plan are validated and the operation is fully optimized
- Site management and business unit leadership: Understanding key performance indicators to the budget and ensuring an understanding of the risks and opportunities available
- Business unit and executive leadership: Are informed of issues within each site’s integrated mine value chain and are aware of opportunities for improved value extraction and the investment required
Figure 3: Communication and reporting plan through all levels in the organisation
Lastly, to embed the identified value and mitigate the identified risks, a continuous improvement program must be closely integrated with a reconciliation program. With each initiative implemented, the team will utilize reconciliation to determine the impact on performance, which in turn allows for optimization/correction of mining practices and re-calibration of the estimates and models for embedding into the mine plan. At which point, trends can be reanalyzed to identify new opportunities and risks, thus creating a circle of optimization.
While challenging to achieve, a great mine-to-mill reconciliation program has many value-adding benefits, including:
- Discovery of inefficiencies and the ability to determine the effectiveness of optimization in resource and reserve modelling, mine planning, and mine and plant operations
- Increased confidence across the entire mine value chain and in the team’s ability to deliver
- Management being better informed, allowing better decision making
- Maximizing value extraction from the resource
- Ability to be pro-active rather than reactive, thus reducing execution risk
- Support new investment with a confident understanding of the impact of benefits.
Typically, all mines have good reconciliation programs that can report on the key performance indicators that are in focus for management. However, for a mine to transition from good to a great reconciliation program and garner the benefits listed above, it is vital to have:
- Established workflows, audited, and quality assured data of many types, representing first principal and high-level data at each measurement point
- A reconciliation specialist who understands the mine integrated value chain from drill hole data to resource to reserve, to mine plans, to mine and plant operations, to recovery
- A reconciliation specialist who is highly numerate and analytical. Essential skills required to interpret the why for over or underperformance of each relationship
- Understanding and focus on appropriate trends in the reconciliation data
- Have a unique trigger action response plan for each deposit that, based on appropriate thresholds, identifies the key next steps
- Buy-in and confidence in the reconciliation output at all levels of an organization
- A communication plan that is unique and appropriate for each level of an organization
- Continuous improvement program to implement optimization opportunities
- Understanding of key performance indicators for each continuous improvement opportunity targeted for implementation.
Mine-to-mill reconciliation at Appian
Essential to Appian is integrating a comprehensive mine-to-mill reconciliation program at each of our operations to ensure that relevant risks are identified and mitigated and opportunities are explored and implemented to ensure maximum return from each investment made. This is a core principle within our operational excellence model at Appian.
1. A useful resource on control charts is https://asq.org/quality-resources/control-chart