What is the RRB Conformation Method?
The RRB Conformation Method is an integral component of our Stockpile and Inventory Optimization application. Its primary purpose is to fine-tune stockpile block models, ensuring they closely match real-world topography data obtained from scan surveys. By doing so, it minimizes deviations between the topology of your model and the actual site conditions.
Key Steps to understand the RRB Conformation Method
The RRB Conformation Method proceeds through several essential steps, each contributing to its effectiveness:
Calculate Differences: Measure the height differences between the scan data and the model to identify where adjusments are needed.
Clean the Data: Remove insignificant model data to ensure that only the relevant materials are considered.
Adjust the Base: Adjust the base height in certain areas to match the scan's height information to accurately reflect real-world conditions.
Remove Material Gaps: Eliminate materials in the model that aren't covered by the scan data, aligning the model with the scan's boundaries.
Redistribute Material:Balance material heights to match the scan's topography, which may involve moving material from some areas to others. During this step, materials with similar characteristics are intelligently regrouped to maintain a consistent material mix. This meticulous process ensures that the model faithfully represents the real-world distribution and characteristics of materials within the stockpile.
When to Use the RRB Conformation Method?
Site Scenarios: Consider using the RRB method when precise alignment with real-world topography is crucial for your site. It is particularly valuable when dealing with high-quality input data, including accurate GPS tracking locations for dumps/reclaims and reliable material properties. The effectiveness of the RRB method heavily depends on the quality of this input data.
Data Quality Considerations: The effectiveness of the RRB method heavily depends on the quality of input data, including accurate GPS locations and reliable material properties.
Benefits of the RRB Conformation Method
Accurate Alignment: The RRB method ensures precise alignment between the stockpile model and real-world topography, reducing discrepancies for improved accuracy.
Material Mix Preservation: It intelligently maintains the right mix of materials during redistribution, preserving material properties and characteristics.
Discrepancy Reduction: By addressing height differences and redistributing materials, the method minimizes discrepancies between the model and scan data, resulting in a more reliable representation of the stockpile.
How to Implement the RRB Conformation Method
Please reach out IntelliSense.io support team to configure the conformation method of your choice.
Other Model Conformation Methods
In addition to the RRB Conformation Method, the Stockpile and Inventory Application offers various other conformation methods such as the Subregions Redistribution of Batches (SRB), Local Density Adjustment (LDA) and the Hybrid GPS-Scan Driven approach. These conformation methods are designed to cater to different site requirements and scenarios, allowing you to choose the most suitable approach.
Note: Each conformation method can be configured to align with your stockpile modeling needs. Whether you prioritize topography precise alignment, material mix preservation, or other factors, our application allows you to tailor the conformation method accordingly.
Conclusion
The RRB Conformation Method is a valuable tool for achieving precise stockpile modeling alignment. Understanding its key steps, benefits and considerations is essential for leveraging its power in your site. Additionally, our application offers a range of other conformation methods, each configurable to meet your specific stockpile modeling requirements.