An Integrated Reporting System for Mining Operations

An Integrated Reporting System for Mining Operations

N o v 2 0 1 2

An Integrated Reporting System for Mining Operations | Nov 2012

© 2012, HCL Technologies, Ltd. Reproduction prohibited. This document is protected under copyright by the author. All rights reserved.

TABLE OF CONTENTS

Abstract ............................................................................................. 3

Abbreviations .................................................................................... 4

Market Trends/Challenges ................................................................ 5

Mining Operations ......................................................................... 5

Data Sources .................................................................................... 6

Problem Statement ........................................................................... 7

Solution – An Integrated Reporting System ...................................... 7

Reporting Using Maqplex ................................................................ 10

Customized Data Analytics on Maqplex ......................................... 11

a. Truck-Shovel Optimization .................................................. 11 b. Fleet Management Solutions .............................................. 11 c. Energy Balance .................................................................. 11

Application on the Cloud ................................................................. 12

A Typical Use Case ......................................................................... 13

Conclusion....................................................................................... 14

References ...................................................................................... 15

Author Info ....................................................................................... 15



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Abstract

Metals and mineral mining operations are comprised of many unit

operations – blasting at the ore site, picking of ore by shovels, and

transporting of ore by huge trucks to crushing and grinding units.

The crushed ore is filtered, washed and dispatched from the mine to

the metal processing plants.

There are many systems monitoring and controlling each unit

operation, but there are not many system applications that can be

used for total integrated monitoring of mining operations.

This paper discusses the actual realities and how integrated

reporting can benefit mine operators.

There are many systems

monitoring and controlling

each of the unit operations, but

there are not many system

applications that can be used

for total integrated monitoring

of mining operations.



4

Abbreviations

Sl. No. Acronym Full Form

1 GSM

/GPRS

Global System for Mobile /General Packet

Radio Service

2 KPI Key Performance Indicators

3 LIMS Laboratory Information Management

System

4 M2M Machine to Machine - communication

between any 2 machines

5 PLC Programmable Logic Controller

6 OPC Ole for Process Control – a

communication protocol used in process

industry

7 ODBC Open Data base connectivity – an adapter

to connect to databases

8 TCP /IP Transmission communication protocol

/Internet Protocol



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Market Trends/Challenges

Mining Operations

The metals and minerals process starts with blasting an identified site with explosives. The blast produces heaps of ore that need to be transported. The transportation of ores from the source (after blasting) to the dispatch center is done by huge trucks. These trucks can carry 300 tons of ore and cost $3M each. The trucks are loaded by a shovel. The shovels are bigger than the trucks, and costlier too. The snapshot below shows the shovel on the left with the truck on the right.

Ref : http://www.geo.msu.edu/geogmich/tilden.html

Here is pictorial representation of a mining operation

o Usually a medium-sized mine will have 20-30 trucks of varying sizes (size is based on the amount of ore they can transport) and it takes 4-5 shovel dumps to fill a truck. A mine will have 3-4 shovels in operation at any point in time.

o Mines will have a separate bay for fueling the trucks, and the fueling operation is controlled by a fuel management system.

Usually a medium-sized mine

will have 20-30 trucks of

varying sizes (size is based on

the amount of ore they can

transport), and it takes 4-5

shovel dumps to fill a truck -- a

mine would have 3-4 shovels.



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o In many mines, the ore has to be crushed to a certain size by crushers (ball mills) and washed to remove impurities. The purity and size of the ore is checked before dispatch by doing lab analyses of samples.

o A blending operation may be required if the ore does not meet the required customer specifications before it is finally dispatched out of the mine.

Data Sources

The central mine operation control room needs to access data from many sources to monitor the entire mining operation.

Central Mine

Operation

system

Crushers -PLC

Shovels

Fuel

Management

System

Operator Shift

Information

Lab Data

Mine Static

Data (from db)

Truck Data

The various data sources are:

o The data comes from onboard computers installed in the trucks. The onboard computer monitors the health of trucks – tire pressure, engine temperature, remaining fuel, etc. This data is transmitted to the central server.

o The fuel management system controls the fueling of the trucks. Truck drivers swipe a card to be allowed access to fueling, and are directed toward a designated bay. Once in place, the trucks are filled with a pre-defined quantity of fuel. The driver swipes the card while exiting. The fuel management system also sends their data to the central server

o The shovels also transmit data to the central system: the time taken for each dump and the number of dumps made in a day are some of the data transmitted by the shovel.

o Ore crushers are operated by the PLC. The PLC data is also transmitted to a central control room.

There are varied Data Sources

to collect data in a mine.



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o The shift log details the list of drivers operating the trucks, details of the trucks, and a list of standby trucks/shovels.

o Laboratory data – Many mines have their own laboratory that tests the quality of the ore (% purity) before being dispatched. The lab periodically conducts tests, and these are recorded in the lab management system. A central control room needs to access the lab data, too.

o Manually-entered data or static data like a mine survey that needs to be accessed from the existing database.

Problem Statement

Currently, mine operators have to monitor individual systems to check the respective unit operations – the PLC console to monitor the crushing/grinding, the fuel management system console for fuel vending operations, the truck dispatch system, etc. There are obvious disadvantages in these, such as:

o It becomes difficult for operators to collate information from all these different sources

o Operators lose track of productivity improvement measures and efficiency monitoring

o Key performance indicators across the mine are cumbersome to calculate, and many times are done manually

o Archival and playback of past data cannot be done for complete mining, and moreover, not all individual systems support archival and playback features.

Solution – An Integrated Reporting System

A common reporting framework that would interface to all data sources in the mine, collect and archive data with the facility to perform advanced data analytics, and an easy interface to smartphones is the ideal solution. The framework should be a cloud-based web application so it offers the highest scalability for the future at the most optimal cost. HCL’s MaqPlex M2M framework is best suited for this application. MaqPlex is a feature-rich cloud middleware platform for M2M services:

o Communicate reliably and in real-time with any remote equipment

o Comprised of a comprehensive set of features for remote device and software management.

o Facilitates easy and quick onboarding of devices and services, and is based on open standards and hardware agnostic

o Field analytics to understand the remote equipment status in the field, provide proactive maintenance services, and observe which features are most popular and what problems typically arise

MaqPlex is a feature-rich cloud

middleware platform for M2M

using the cloud.



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o Platform to build/integrate value-added services that can be offered to generate monthly revenues

Here is a MaqPlex architecture diagram for this application:



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Operator Shift Data

* Lubricant Temp* Truck Load Time* Empty Run Time* Idle Time

* Fuel Sump levels, * Temperature, * Density ; * Trucks fuelled /day ,* Time to fuel/ truck

*material moved by each bucket*Load Time*Swing Time*Total cycle Time

*Qty. of ore crushed /day , * power consumed , * Vibration & Bearing temp * Reduction ratio of ore crushed

* Ore composition * Purity , size, density

*Driver schedule for week/month , *Truck trip schedule *Truck trip & idle time , *breakdown report, * Truck mileage;

* Mine lease boundary;* Area of mine development;* access roads ;* conveyors and stockpile areas, * accident & emergency plan

Database # 1Database # 2

ODBC ODBCGSM /GPRS Interface OPC Interface HttpsTCP /IP

Message Queue

Detection

Categorization

Prioritization

Description

Response

Alerts & Event Engine

Alerts & Event Meta data Management

Alerts & Event Mnmgt. Web service

Energy Balance

Truck Fleet Management

Data Analytics

KPI Analytics

Data Retreival

Query

Reporting Services

Diagnostics Data

Event Data

Process Data

HTTP SOAP HTTPSREST

Customer Mngmt.

Subscription Mngmt.

Metering & Billing

Campaigns & PromotionsNotification

Mngmt.

Cloud Service Mngmt.

DATA

DATAPROTOC

OL

MAQPLEX

FRAMEWORK

USERS

DATASOURCE

Truck /Shovel Optimzation



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The originating data sources are varied and are the most challenging parts of this solution.

o Truck/Shovel data – Trucks send data in real-time to a central server. It sends the truck health parameters like lubricant temperature, engine performance data, truck load time (time it was loaded), empty run time (plying with no load), idle time (wait time). Truck/shovel data is sent via wireless mode using GSM/GPRS. Maqplex has GSM/GPRS adapters to collect this data.

o Fuel Management system – Fuel sump levels, temperature, density ; trucks fueled each day, time taken to fuel each truck, and frequency of fueling each truck. Fuel management controllers are connected to a server and Maqplex has TCP/IP adapters to pick up the data.

o Crushing – The quantity of ore crushed/day, power consumed, bearing temperature of crushers, vibration analysis, and reduction ratio of ore crushed. Crushers and grinders are connected by PLC. As most PLC support OPC, OPC adapters in Maqplex connect to PLC to retrieve the data

o Lab Management system – Report date, time, ore composition with respect to purity, size and density. A web service interface to collect the data is used.

o Shift Operation Data – Shift timings, driver schedule for the week/month, truck trip schedule, truck trip report, truck idle time, breakdown report, truck mileage, and road quality.

o Static data, such as mine surveys, is stored in the database, and MaqPlex requests that data using ODBC connectors.

Reporting Using Maqplex

Data collected from different sources is time stamped and stored in a central database. The MaqPlex dashboard uses the data to present reports, plots and predictions. Some of typical dashboard presentations include:

o Real-time and archived graphical data plotting o Truck/Shovel KPI indicators – the number of shovels

operating, the variability in truck loading, hauling and return times, overall shovel utilization, overall truck utilizations and truck fuel consumption.

o Grinding KPI – Size reduction ratio, power consumption, closed side setting (CSS)

o LIMS KPI – Ore composition, density, o Energy flow across equipment, thereby presenting the

energy balance calculations

MaqPlex provides a dashboard

to view complete mining

operations

Analytics is a standard feature

in MaqPlex, with an easy plug-

in provided for external

modules



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Customized Data Analytics on Maqplex

a. Truck-Shovel Optimization

Truck/Shovel operations need to be optimized during the mining operation. The trucks/shovels should in operation for the maximum amount of time. Ideally, they should either be getting filled, be on the move, be dumping material at the dispatch center, or moving toward the shovel. Any wait time in these operations reduces mine productivity. Similarly, shovels should be in operation all the time –either picking up materials or dumping into the trucks. If shovels are waiting for trucks to arrive, that is idle time, so software applications are used to optimize the truck/shovel productivity.

GPS installed on trucks is used to track the truck location. Optimization analytics can be performed using the Maqplex engine on the central server. All trucks have an onboard, tablet-interactive computer, which will display the designated shovel after each truck unloads ore at the dispatch center, and when it’s ready to move to the next. Maqplex data analytics will also provide the shortest path to reach the shovel, as mines extend few square kilometers and paths may be blocked due to truck breakdown or non-availability of a path due to blasting in the vicinity.

A UI interface on the MaqPlex dashboard will show the movement of trucks in the mine and the allocation of trucks to each shovel. The optimization program runs in the background, allocating trucks to shovel. The optimization package is an adaptive, self-learning application that will fine-tune based on weather conditions, as it takes more time for trucks to cover distances on wet roads (note that mines have only paved areas for trucks to ply, and do not have concrete roads).

b. Fleet Management Solutions

Fleet management extends beyond truck/shovel optimization. Fleet management tracks the status of all trucks/shovels at the mine. The status of trucks and shovels that are not available, and the time needed for them to be put back to operation are monitored. Repair progress updates, schedules for periodic maintenance, and a history of maintenance are done for each truck/shovel, and a spare parts inventory is maintained.

c. Energy Balance

Energy balance is an accounting of the materials and energy

entering and leaving equipment or a unit operation (like grinding,

crushing, etc.) and its processes. Energy balances provide

significant energy and cost savings by calculating:

o How much energy is being used, wasted or lost, and where this occurs

By taking the application to the

cloud, end users pay only for

what they use and at the best

possible price



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o Whether the systems and equipment are operating according to design and work schedules

o The efficiency of energy‑using processes, unit operations

o If possible, to reuse spent energy

Application on the Cloud

MaqPlex is an M2M framework that uses the cloud infrastructure for hosting the application, computing and for the database. The cloud is the ideal backbone for this application, offering many benefits such as:

o The application can be split into many services – data monitoring services, analytics services, optimization services, etc., and can be offered to customers

o End users pay only for the services used, and only for time used

o Scalable to cater to any number of end users with performance and response time guaranteed

o Analytics can be expanded in the future to include more proven optimization applications for mines

o Option of remote monitoring by experts in another part of world.

o All the above at the least possible cost

MaqPlex is an M2M framework

that uses the cloud

infrastructure for hosting the

application, computing and for

the database



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A Typical Use Case

An iron ore mine with an annual capacity of 10 million tons operating

with fleet of 12 trucks and four shovels. Washeries were 3 kms

away from the source of the ore. The lab for measuring the

composition of ore was in central building. Dispatch of ore, using a

wagon, was from the washeries.

Though the trucks and shovels had an embedded computer that

directed the trucks to shovel, the washeries controller by PLC and

lab reports available on dedicated servers, there were operation

issues that included:

o Managers could not get productivity metrics on each unit’s

operation or complete mining operations on an hourly/daily

basis without cumbersome calculations

o It was difficult to instantly assess truck availability without

doing a manual audit of trucks in use

o Data validation and reconciliation could not be done all the

time to check the correctness of incoming data

o Fuel expenses were not uniform throughout the month, and

there was more consumption on low productive days.

o Due to the economic downturn, there is inadequate budget

for IT expenditures

MaqPlex is an ideal application to solve these mining operation

issues.

o With MaqPlex dashboards, all unit operations and

equipment performance are available in easy visual formats

o A user-friendly query engine can compare present data with

past data as graphs or tabular formats. Any abnormal

increase in fuel or power can easily be identified and root

causes determined.

o Powerful analytics on fleet management ensures that trucks

are available for the maximum time, and downtime for

trucks is considerably reduced.

o Energy balances ensure there is no waste or energy

leakage, thereby reducing the carbon footprint and making

a greener mine.

o MaqPlex is a cloud-based application that requires nominal

IT infrastructure cost by end users. A subscription to

services can be on a monthly basis, and more importantly,

users pay only for what is used.

MaqPlex can be scaled and

deployed for any mine,

however small or big it may be



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Conclusion

As mining operations extend from crude blasting to lab analysis for

ore blending, mine operations are quite challenging and need a

skilled operational force to manage them. So obviously, the staff

needs to be equipped with software and hardware that make their

job easier. A comprehensive integrated reporting system that can

receive input from any data source in the mine and present it as

relevant KPI is certainly a must-have tool for mining operations.

Analytics modules like truck/shovel optimization and energy balance

improve the efficiency of plant operations. Moreover, by taking the

applications to the cloud, the entire IT cost can be reduced

substantially.

HCL’s MaqPlex is tailored specifically for the mining industry, with

adapters to receive data from trucks/shovels to the wagon dispatch

system. Its strong analytics framework is an ideal platform to

execute optimization applications like fleet management and energy

balance applications, and above all, Maqplex is cloud-enabled so it

can deliver all the features at reduced cost with easy integration to

smartphones and to tablet computers.

HCL’s MaqPlex is tailored

specifically for the mining

industry, with adapters to take

receive from trucks/shovels to

the wagon dispatch system



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References

1. HCL’s Maqplex M2M framework

2. Energy Mass Balance in Mining -

http://www.ret.gov.au/energy/Documents/energyefficiencyo

pps/EMB%20Mining.pdf

Author Info

Mahesh Subrmaniam is with the ERS

Industrial Practice of HCL Technologies. He

has more than 20 years of experience in

Industrial Automation and IT services. His

current area of interest is condition monitoring

and automation solutions for the process

industry.

http://www.ret.gov.au/energy/Documents/energyefficiencyopps/EMB%20Mining.pdf

http://www.ret.gov.au/energy/Documents/energyefficiencyopps/EMB%20Mining.pdf

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An Integrated Reporting System for Mining Operations

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