Improved Fragmentation Through Data Integration - Introduction

- Organization:
- Society for Mining, Metallurgy & Exploration
- Pages:
- 3
- File Size:
- 64 KB
- Publication Date:
- Jan 1, 2011
Abstract
An overwhelming amount of data can be collected around the blasting process. This information can include blasting product, pattern design, blast results, and routing. It is only when these data sources are combined in a concise and accurate form that they are of real use in determining the safety and economic implications of each parameter. Two key technological aspects of blasting are drill fleet management (DFM) and size fraction analysis (SFA). As these technologies are integrated as near-real-time measurement and QA/QC tools, the resolution and realization of blasting parameters is significantly increased. The Freeport-McMoRan Morenci Mine has integrated these technologies along with other existing database structures to create a responsive and sustainable tool for reconciliation, forecasting and parameter matching. This ability allows Morenci to customize blast patterns to meet the criteria most critical to each shot, whether the impact is influenced by routing and recovery, equipment maintenance or safety concerns. DRILL FLEET MANAGEMENT The current DFM was stabilized in its current form in mid 2009 after database and hardware maintenance met stability requirements. Currently the system is running on 12 production drills. The system receives pattern layout and is capable of semi-autonomous drilling over the entire district. The fleet is capable of drilling in highly altered intrusive units and hard granites through the range of sedimentary and volcanic units that comprise the Morenci District. The system brings a level of accuracy not achievable with earlier paint-marked patterns. Depth control is also increased along with more consistent wear and maintenance patterns due to semi-autonomous drilling.
Citation
APA:
(2011) Improved Fragmentation Through Data Integration - IntroductionMLA: Improved Fragmentation Through Data Integration - Introduction. Society for Mining, Metallurgy & Exploration, 2011.