For thousands of other reports visit RSC's Mineral Intellingence Map

AVZ Minerals Ltd.

opaxe

Summary

Project:

Manono

Deposit:Manono
Location:Democratic Republic Of The Congo
Commodities:Lithium-Tin
Date:4/21/2020
Report Code:JORC
Report Type:Feasibility Study
Project Stage:Pursuing Resource Increase/Upgrade
Report details:21-4-2020: AVZ Minerals Ltd. announces a Feasibility Study report for its Manono deposit at the Manono project. DFS results incl. post-tax NPV (10%) of US$1,028M and IRR of 33%. AVZ Minerals Limited (ASX:AVZ, “the Company”) announces completion of its Def
Resources:(Reserves, Total): 93Mt @ 1.58% Li2O, 988g/t Sn
CP/QP:[Overall Report]: Daniel Grosso, Karl van Olden (CSA Global Pty Ltd.)
ABSTRACT:AVZ Minerals Limited (ASX:AVZ, “the Company”) announces completion of its Definitive Feasibility Study (“DFS”) for the Manono Lithium and Tin Project (“Manono Project”) located in the Democratic Republic of Congo. The DFS results confirm outstanding project metrics and provide a higher level of confidence4 with respect to engineering design, construction requirements, logistics, project finance and risk assessments. The DFS indicates the project to be robust and viable with a product mix of Spodumene Concentrate (SC6) for 700,000 t/a and Primary Lithium Sulphate (PLS) for 46,000 t/a. PLS will be produced using 153,000 t/a of the SC6 product as feedstock. The processing flow sheet also allows for the recovery of tin and tantalum from hard rock ore as well as smaller amounts of alluvial tin and tantalum secured from local artisanal miners. The most cost-effective transport routes have been defined, thoroughly investigated and priced to meet the export requirements of the project. The thorough investigation has provided two suitable alternatives for transport of the products to port for export.

Full Report

opaxe is a smart software platform that reconfigures and redistributes information and produces business insights to help mining professionals and investors make better decisions. We utilise technology and machine learning for data collection and human intelligence for the value-added services.

Full Report