SESW-09 Mining: your advantage with Ampla Gary Samata
Realize your resource-to-market potential Costly decisions due to unreliable data (Inventory, Grade) Maintenance & Production conflicts cause delays Excess energy & water consumption Poor Asset Performance (OEE) Lack of dynamic and optimized extraction sequencing Poor Process Performance (Quality, Recovery) Non conformance to load out plans High cost of poor utilization Mineral resources and commodity prices are externally determined Only HOW the resource-to-market chain is managed is controllable Goal is to deliver to the market at the right quantity, right time, right grade, right quality and right cost Make the most of your Resources by Planning and scheduling to optimise the Resource-to-Market chain (local plans are driven by the global plan, not vice versa) Making production, asset and process performance more RELIABLE and more capable Making better decisions through reliable and timely infomation Reducing cost and improving environmental performance by reducing excess energy and water usage
Integrated Planning and Optimization Solution for Mining Stock Management Mine Planning Concentrator & Smelter Planning Metal Balancing Supply Chain Operation APS Cathode Production Plant Operation Ampla Logistics Planning Rail, Road & Port
Ampla Introduction
Ampla in mining, metals and minerals Used by Top 6 Global Mining Companies In 100+ Mining & Metals installations Fastest payback in 6 hours Globally #1 in Downtime for Mining & Metals
Ampla architecture ERP
Built for mining, metals and minerals Material Tracking Asset Utilization Energy Management
User friendly interface Toolbar Filter Criteria Data Grid Plant Hierarchy Favorites Charting Pane Module Selection
Asset Management
Asset management / utilization Benefits Provides management visibility to manufacturing performance Helps maximize production capabilities Brings benefit through low cost capacity increases Process stability leading to quality and safety improvements Ampla Provides A cost effective and efficient process that captures all production losses in context Analytical tools on that information to identify and eliminate future problems
Ampla Downtime Ideal for Debottlenecking Processes Real-time Asset Performance Data Capture for FMECA Eliminating Manual Recording Raising Work Notifications Tracking Corrective Actions
Capturing the cause Consistency Relationship Matrix Cause Location Cause Classification 5 x Why? Effect Mappings Event Table Context Notes Crew
Analysis You don t know what you don t know and tomorrow s problem will not be the same as today s problem Group Sort Filter Summarize A picture speaks a thousand words Gantt Chart Pareto Chart Pie Chart
Metrics Ampla Metrics aggregates data from other Ampla modules to calculate Key Performance Indicator (KPI) results in real-time, color coded against target thresholds Real-time summary of current production KPI s can be presented through a customizable digital dashboard The following metrics charts are available: Line Chart Box Plot Chart XBar Chart RBar Chart
Daily Report: SSRS with Ops Log Operator Log Entry Here
Ampla Asset Management benefits Analyze production loss causes in near real-time Perform detailed root cause analysis to prioritize maintenance, new equipment and operating procedures Identify production bottlenecks and inefficiencies and develop ways to resolve them Empower effective decision making Benchmarking and gauging the effect of improvement initiatives or operational changes over time
Process Energy Optimization
The challenge for mining > Reduce energy consumption at the same time as increasing production > Engage operations teams to take ownership of energy management > Adopt best practices and reduce energy waste > Load shift to off-peak times as much as possible (depending on energy supply conditions) 19
Height Understanding energy in context Energy Information no context Energy Efficiency 15L per 100 km Energy Efficiency 15L per 100 km Energy Information with context Energy Efficiency 15L per 100 km Energy Efficiency 15L per 100 km profile of track Travel direction Distance Travel direction Distance
Production Automatically logs all inputs and outputs e.g. materials, consumables, energy, waste, emissions and product output A powerful feature of the Ampla Production summary chart is the ability to drill into reports/charts to see the underlying data. The drill-in functionality automatically applies a filter to your data
Energy Identify periods of excess energy consumption Measure and quantify the exact impact (kwh, $$$) Reduce power costs Baseline power for different phases of batch operations (eg furnace heatup, cooking, ramp down) Identify energy used during idle time Identify wasteful startup and shutdown sequences (eg motor stress) Cost engineering projects and power initiatives to establish measurable project scopes Increase accountability of operations teams Model Golden batch behavior for energy consumption Can be applied to Water, Air, Gas, Energy and Steam (WAGES) to baseline consumptions against the production outcomes the resources achieved. Reduce Costs on all your primary inputs.
Consumption with context
Average kwh per Tonne by Crew 39.10 39.59 33.05 34.09 20% variation best to worst
Average kwh per Tonne by Feed Type 34.15 54.15 35.33 34.59 59% variation in energy use from best to worst feed material
Energy Metrics Dashboard of same information
Ampla PEO Benefits Automatically capture energy events Automate the routine collection of production and consumption data Perform root cause analysis of over-consumption Stabilize your existing energy usage and improve operating procedures Understand the true cost of your WAGES energy sources Drive energy efficiency initiatives throughout your organization
Inventory Accounting
What is Inventory Accounting? Time and Location Accounting for Materials (Saleable, WIP, Waste ) Quantity (Amount & Type) Quality (Attributes) MT&IA is used for Operational Decision Making Detailed production and logistics scheduling Comply with ERP requirements Government Regulatory Requirements
Why do we need Inventory Accounting? Conformance to Plan Conformance to Stock Market Guidance In house compliance: ERP systems highlight production inconsistencies Challenging Commodity Prices and Costs Increasing granular information is now essential Mines need to have fine control of production, inventory and costs Increasing regulatory compliance from governments Huge penalties for out of spec products Accounting Systems vs Spreadsheets
Inventory with genealogy Stockpile Composition by Lot ID and Quality Profile ISA-95 Work Centre/ Material Concepts Quality Sample Data linked to Inventory Lots Obtains Metal Tons or calculated inventory Allows adjustments to calculated inventory Enters manual movements Define accuracies (% error) in data Consolidated view of Inventory with Quality Filter & view calculated & adjusted inventory Metrics drill down to Inventory data Track Genealogy from Blast Block to Port Validation workflow linked to user security
Material definition Materials are the things that Ampla tracks the balances of in Work Centres. The ISA-95 standard defines Materials as a definition of the properties and characteristics for a substance Synonyms Product Examples High Grade Product Waste WIP - Lockup 33
Work Centers Work Centers are locations within the Equipment Model that Ampla tracks the balance of Materials and the transactions that affect the balance (i.e. inputs and outputs) Synonyms Stocking Point Examples Product Stock PAD Process Plant Crusher 34
Movements Material Movements represent the business rules of what and when Material should be moved through the process. Automatic capture and manual entry Synonyms Material Transfer/Conversion Examples Pit to Crusher Plant to Stockpile (Stacking) Port to Ship (Ship load) 35
Lots Lot (from ISA-95) is an allotment of material, and it has a unique Lot Identifier. How the allotment is defined is based upon the industry and location within the supply chain. Synonyms Batch of material with the same attributes Examples 1 hour of production (LIMS) Bag of Product 36
Material Quality Analyze, report, and manage quality throughout the process. Captures key process-related data that impacts quality into a single repository to measure and compare against set targets and specifications. Flexible charting makes for easy analysis. Target Thresholds X-Bar Chart Out-of-Spec Count Chart LIMS System, Assay version Tracking Online Analyzers, Manual. Any number of Quality Parameters. Linked to Inventory lots for Calculated Inventory. 37 Frequency Distribution Chart Multi-field Chart
Lot Behaviors FIFO Lot Behaviour (FIFO, LIFO, Mixed, or Selective, and soon WAM) Defines how Lot processing will be handled. Lot Group Dynamic grouping of lots for dynamic stockpiles. Also has associated functionality such as WAG and Survey results. LIFO Relationships between lots is retained and is the biases of genealogy. 38
Material Tracking (Genealogy) Overview Relationship between particular lots. Genealogy. Tracking based on captured Movements Summarized Two directions Upstream / Forward Downstream / Backward Visualise and Analyse Material movements and tracking routes An example
Edits and Reprocessing Full support for Edits and Reprocessing of all movements so to match the actual state and preserve genealogy information. It cleans the slate in terms of balances and possible lot assignments and replay as if it had the correct data in the beginning Before Reprocessing During Reprocessing After Reprocessing 40
Material Balances
Stockpile Balances
Balance Over Time
Material Flows
Genealogy Tracking
Inventory Accounting Metallurgical balance per AMIRA P754 includes: Data Management & Reporting Measuring Saleable Product (stock-takes, lockup & errors) Metal Balancing (monitoring performance & reconciliation) Process errors are estimated using a proven mathematical reconciliation system Snapshot engine adjusts balances until provisional data has been closed off Measures metal balances across entire process with full Audit Trail of Changes
Inventory Accounting Process
Inventory Accounting Process Text
Inventory Accounting Process Balances for mass & metals Overall error % of balance Opening balance, adjustments, inputs, outputs and closing balance per work centre
Ampla Inventory Accounting benefits Realize unsurpassed visibility of inventory levels across your entire value chain Understand your work-in-progress and visualize your stock levels in terms of quantity and quality Manage and track your inventory and material movements Incorporate survey results and drive conformance to plan View genealogy of shipped product from resource to market, and across time Streamline and audit Inventory reporting and reconciliation activities
Ampla users include: Ampla: benefits realization in mining Mining/Crushing BHP Iron Ore (Pit) BHP OD (U/G) Illawarra Coal (U/G) RTCA Kestrel (U/G) RTCA Clermont (IPCC) BMA Crinum (U/G) Concentrators BHP Olympic Dam BHP Cannington BHP Nickel West (All) MMG (3 sites) Rio Tinto ERA Kennecott Copper Refine/Logistics BHP OD Refinery BHP Nickel West KNR BHP Iron Ore Rail Xstrata NCA Pit-to-Port RTCA Hail Creek Rail RT Alcan Gove Ship RTCA Hail Creek Operations Train Loadout (TLO) 2 Coal Handling Preparation Plants (CHPP) 44% Reduction in duration of delays within CHPP 48% Decrease in delay occurrences in CHPP 25 % Increase achieving Train Freight Incentive Scheme Coal Operations 8 wash plants and 1 port Targeted production rate loss 5% production improvement $200M increased revenues Cement Plant 2 Cement Kilns 50% reduction in stoppages 12% production improvement $1.6M increased revenues Manganese Mine Primary crusher to final product Targeted production rate loss 20% production improvement 600Ktpa increased production Olympic Dam Mine De-bottlenecking underground rail Increased availability by 3 hrs/day 18.7% production improvement 1.7Mtpa increased production Zinc & Lead Filter Plant 5 filter presses (4 Zn, 1 Pb/Zn) Increased utilization 78% to 94% 20.5% production improvement 100Ktpa increased production Alumina Refinery Ship (Bauxite) unloading Increased by 1 ship a year 0.45% production improvement $6.6M increased revenues Disclaimer: Names of some operations were withheld as the information was supplied to Schneider Electric only and not available in the public domain Numbers provided for unnamed case studies were rounded (approximated) based on best guess commodity prices and annual production levels
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