Environmental and Operational Benefits
through Implementing a Fleet Management
System in Mining Industry
Walter Schmidt Felsch Junior1*, Carlos Enrique Arroyo Ortiz2, Adilson Curi2, Douglas Ramos Gonçalves3 and Alexandro Afonso Pinto4
1 Mining Engineer, PhD Student at the Universidade Federal de Ouro Preto, Brazil
2 Mining Engineer, Professor at the Universidade Federal de Ouro Preto, Brazil
3 Mining Engineer, Universidade Federal de Ouro Preto, Brazil
4 Mining Engineer, Mine Planning Manager at VALE, Brazil
Submission: April 24, 2020; Published: May 08, 2020
*Corresponding author: Walter Schmidt Felsch Junior, Mining Engineer, PhD Student at the Universidade Federal de Ouro Preto, Brazil
How to cite this article: Felsch Jr. W S, Arroyo C E O, Curi A, Gonçalves D R, Pinto A A. Environmental and Operational Benefits through Implementing a
Fleet Management System in Mining Industry. Int J Environ Sci Nat Res. 2020; 24(3): 556140. DOI: 10.19080/IJESNR.2020.24.556140
Mining fleet management is fundamental to the transportation infrastructure in a mining nowadays. Several factors influence the success of a new system adoption, such as changes in the project design, operational maturity, direct leadership engagement, and senior management participation. To start with, the main objective of this study is to present the results obtained with the implementation of the Fleet Management System in a mining company located in the Southeast region of Brazil. In this study, the chronology of the implementation of the technology was presented, comparing the operational factors and environmental impacts to the operation results. As a result, there was a 23% increase in the transportation fleet performance, which led to a monthly potential reduction in the emission of 136 tons of greenhouse gases in the atmosphere because of the reduction of the transportation fleet required for ore movement. Furthermore, these gains may be enhanced over the years, expanding its possibilities with the use of new techniques and research.
A mine is similar to a manufacturing facility where raw materials are acquired and processed to a finished product that is shipped to customers. In the mining production cycle this process begins with the drilling, sampling and blasting of the raw material. After that, haul trucks that transport blasted material from a loading location to stockpiles or the crusher are closely tracked by a fleet management system. For instance, the demand for increasing competitiveness, associated to the adoption of new knowledge and technologies is present in every company and organizations of all segments. In the specific case of mining, productivity gains and cost reduction need specific solutions, usually developed for harsh conditioned environments that are not found in another kind of business. Moreover, applications in the world involving the use of GPS technology in fleet control has existed in mining since the decade of 1970, but each implementation shows its adaptation challenges to operating conditions.
Firstly, mining companies are conditioned to constantly reinvent themselves to survive, as they must always strive to be more efficient and sustainable [1,2]. Also, automation has played a key role in the production process and has improved operational performance in mining companies by increasing the presence of technology in the work routine of technical teams. Thus, the aim of this paper is to present a case study on the implementation of a fleet management system, also known as an electronic order in a mine, located in the Southeast region of Brazil, it analyzed data from operational KPIs obtained from the use of an automated fleet allocation compared to a manual control production. Before that, a survey of historical data for the period prior to the implementation of the fleet control system was made to compare it to the information generated in the post-implementation period. Manual control for production systems portrays a practice of truck dispatching in which a technician responsible for the equipment direction control is located in a strategic mine point and makes
decisions based on the situation analyzed on his field of vision.
Also, it is based on his experience, and by sending instructions to
the operators of load and transport equipment.
Secondly, drivers use pen and paper for taking notes of the
trips (loading and transportation), and this information is then
stored in manual control spreadsheets. Therefore, manual information
has a great potential for errors at various stages of the
process which leads to a low data reliability. In the case of mining,
recording mass moved and operational stops made by the equipment
operators by using paper and pen may contain incorrect information.
Also, a later typing of the information in a spreadsheet
might contain errors and be manipulated. Other important operational
processes are related to the low assimilation to the manual
system, such as driving the equipment for supply, meals, and shift
changes, among others. Also, various methods have been developed
to implement transport equipment allocations, and these methods
can be grouped into three basic types of fleet management
systems: Manual systems; Semi-automatic Systems (static allocations);
and Automatic Systems (dynamic allocations) .
After the implementation of the fleet control system, the same
KPIs were analyzed using the information contained in the database
that integrates the system to compare the information which
was manually raised at the beginning of the program operation.
By the moment this data was processed, it was noticed a significant
gain in the productive performance of the equipment in the
first few months after the system deployment. Consequently, these
gains have risen gradually over the years showing the assimilation
of the software within the production process.
For instance, automated dispatch systems were introduced
in the market at the end of the ‘70s. By definition, these systems
have the ability to directly allocate the truck to a task, overcoming
limitations imposed by manual operation. One example of this limitation
is when dealing with a large volume of information in a
short time because it is difficult to analyze the current situation
and take effective allocation decisions . In recent years, researchers
have investigated a variety of approaches to improving mine
equipment performance using embedded technologies to reduce
diesel consumption greenhouse gases emissions into the atmosphere
As a matter of fact, the main benefits provided by the fleet
management systems are: the automatic control of the mass moved
according to the origin of the loading and its tipping location;
Identification of the main reasons for fleet stoppage, generating
the opportunity to reduce and eliminate manageable operational
occurrences; Implementation of quality control of the ore, with
the insertion of the planned mass for each mining front, inserted
by the mine planning area; Control of operational performance
of operational teams, equipment operators and working day periods.
A well planned and implemented fleet control system can generate
good savings for the mining companies. That is why there
is efficiency for having a computerized order maximizing the time
at the mine, minimizing the number of trucks needed for transport,
increasing the production of load equipment by reducing
idleness and meeting the quality standards of the plant process
. An inadequate decision may compromise the quality of the
ore produced, or decrease the productivity of the various equipment,
incurring productivity loss .
This study uses current data production notes that were taken
manually by the operators and data generated through the database
of the fleet management system of loading and transport
equipment of this mine under study.
In the project, the following assumptions were taken:
a) Provide the mine operation, planning, accounting and
maintenance departments with tools for analysis of comprehensible
and reliable information.
b) Provide high-level supervision staff with tools for quality
c) Eliminate duplication of work connected to updating
maps, plans and diagrams in paper and electronic forms.
Also, the methodology and data analysis will be presented,
comparing the pointing manual information to the fleet management
The trucks are directed to be loaded by a manual way, using
the communication radio. The fleet controller cannot track the
location of the equipment to seek a better allocation, and it can
generate several losses in the mining production process, mainly
due to the lack of management associated to the control of the
Employees who operate the equipment use pen and paper to
write down equipment activities and their shutdowns. Moreover,
the cycles are informed, containing the loading and dump ones as
well as the number of trips made. Thus, if any downtime is required,
these should also be noted for its reasons. Finally, these notes,
called the “daily part”, are sent to a control room where they are
manually scanned, and control reports are generated.
The main objective of fleet management systems is to maximize
production time at the mine, minimize the number of trucks
needed for transportation, enhance the production of loading equipment by reducing its idle capacity, and meet the quality standards
of the beneficiation plant. On the other hand, the challenges
identified by industrial stakeholders include fleet cost-reduction,
fuel price volatility, increased fleet safety, reduced accident rates,
environmental performance of mining fleet, and increased productivity
of both human and machinery capital.
The database of the fleet management system was used to store
the data. This information is handled through Structured Query
Language (SQL) queries in the DBMS (Database Management System)
and displayed through the Report Service which reports a
platform integrated with SQL tools and components. After this
treatment, some information is collected, and the most relevant
for this work is: Haulage mass (t); Average load (t); Number of
cycles; Average distance transport (km); Time of equipment operation
(hours); Equipment used for transportation, among others.
Performance evaluation is critical because there is a gap between
the performance expectations set by the organization and
its actual performance. Thus, the need for increasing effective performance
management has driven companies to develop ways to
monitor and evaluate their performance .
Furthermore, the performance assessment tool should provide
subsidies for comparing different database information and
should reflect the real picture of the situation, making it possible
to identify the pros of the management, as well as the cons, which
require greater attention .
In addition, the performance management aims to diagnosing
and analyzing the performance of the operating teams, generating
insightful actions in identifying low-income and good operating
practices. Also, it provides the administration of human resources
information for decision-making on salaries, merit, bonuses,
promotions, layoffs, training, and career planning, offering growth
and development to the evaluated employee. For example, from
November 2014, early in the third period, it was introduced a performance
management of traffic control teams, and KPI’s were
created with specific goals as it follows:
In order to verify the variations in production KPIs, data was
collected relating to three distinct periods of operation, as illustrated
in Figure 1:
a) First Period: (FEBRUARY/2009 to JULY/2012): Absence
of the fleet control system (Pointing Manual).
b) Second Period (AUGUST/2012 to SEPTEMBER/2014):
Fleet control system implementation period (period of adaptation
and system development).
c) Third Period (OCTOBER/2014 a DECEMBER/2016): Effective
use of the fleet control system (Performance Management
Following this study, data for the first period of analysis was
taken from tables created in EXCEL format and filled in manually
by technicians responsible for mine production. At the second and
third periods, the data was taken from reports created through
consults from the order system database. The KPIs analyzed were:
Considering a real situation in the mining process, it is possible
to list the variable “productivity” as the most important indicator
to measure the production process. Also, the productivity rate
has a strong correlation ship with the average distance of the trucks
transport (ADT). As productivity varies as a function of time
and its own behavior associated to the variation of other variables
inside the mining process, it is possible to say that this random
variable has a behavior similar to a continuous stochastic process.
Thus, it is possible to build a function (equation) where the productivity
of a process, or part of it, may be the study of a variable.
In order to have a better comparison criterion between the mentioned
periods, it was created an analytical KPI of the transport
fleet called “Productive Performance”. This KPI is obtained by the
ratio between the productivity rates of the fleet with their respective
average distance of transport.
As a result, when using the information relating to the years
2012 and 2016, it was identified a correlation of 86.02%, in which
validates the KPI as a criterion of control. Moreover, the equations
obtained above 75% correlations were classified as satisfactory
Comparing the historical average of the year before using the
fleet management system to the implementation of it, it is seen
a gain of 13.68% in the Productive Performance of the transport
equipment within the first six months using the software inside
Consequently, this gain in Productive Performance remained
constantly growing in the following months, with an increasing
experience and system assimilation. Then, it showed a gain of
21.4% in the second period compared to the first, and 23.1% in
the second period compared to the third, as it seen in Figure 2.
Table 1 illustrates the results of the average performance for
each reporting period.
When analyzing the KPIs chosen for the control of the transport
fleet, the indicator of queues time stood out. Thus, this indicator
showed great potential for reduction and demonstrated an
indication of oversizing of the transport fleet.
Figure 3 shows the evolution of the KPI: Queue time (loading
and dumping) during the process.
Improved equipment fleet performance can benefit the mining
companies’ finances, for instance, one of the great benefits is
the improvement of fleet sizing with the reduction of the number
of equipment needed to fulfill the company premises.
Furthermore, a simulation was developed using the Minesight
® software, inserting the new operational performance data
of the mining equipment, calculated from the improvement observed
with the implementation of the fleet management system. As
a result, using average monthly handling of 300,000 t of ore and
waste, the number of trucks needed to transport this volume of
material was reduced as shown in Table 2.
The best results of productive efficiency, associated to smaller
queue times of equipment and reducing the number of necessary
equipment for production, resulted in the reduction of emissions
of greenhouse gases.
Table 3 shows the values of carbon dioxide emission from a
wide range of refined products. Also, the fuel used in transport
equipment is diesel oil, therefore the value used for the calculation
of emission values will be 0.00268 t per liter of diesel fuel
The trucks used in the mine have an average consumption of
17 liters of diesel oil per hour of operation. Moreover, each truck
works for approximately 271 hours per month. Finally, a reduction
of 11 trucks could impact savings of 50,676 liters of diesel oil
The improvement of the operational performance of the fleet
made it possible to reduce the number of necessary equipment for
compliance with the production of the mine. All of it, generating
an annual emission reduction of 1,630 t of GHG in the atmosphere.
Table 4 illustrates the values of diesel oil that were saved and
the values of reduction in the emission of greenhouse gases.
Significant improvements in information technology have led
to the mining industry to develop many decision-making models
in order to assist in the better allocation of transport equipment
in surface mines.
Firstly, the assimilation of the fleet management system, which
alters operational culture is simpler than the factors initially
considered, and it provides greater gains than those established
for its viability. Consequently, this result is consistent with other
developed studies related to the same theme [5-7,9]
Secondly, the main function of a fleet management system is
to maximize the productive time related to mine equipment, minimize
the number of trucks needed for transport, maximize the
production of load equipment by reducing idleness and queues
at loading area, and meet the quality standards of the processing
Thus, the core idea of this study was to quantify the gains
through the KPI Productive Performance, comparing it to the manual
operating system (daily notes using pen), and the automated
electronic dispatch, which showed excellent results. Also, the
KPI is formed by the relationship between the effective transport
productivity and the average transport distance, reaching a correlation
of 86.02% data, which demonstrates the adherence to the
data obtained during the work.
In addition, the fleet control system can reduce the operating
costs by reducing the required transport fleet to meet production
goals. All of it, by increasing the use of the fleet and reducing empty
truck trips events.
And last but not least, the success of any technological application
is dependent on the continuous improvement, performance
culture and drive for excellence.
Analysis of the Productive Performance between the period
before and after the implementation of the electronic dispatch
system shows that there was a significant gain in the performance
of the transport fleet, of over 13% just in the first six months of
use. Also, along the time and the increased operational maturity,
these gains have been growing. The greater assimilation of the
system within the larger process generates the possibility of gains
and cost savings, enhancing the company’s competitiveness in the
Furthermore, this improvement in the performance made
it possible to reduce the number of the equipment necessary in
compliance with the production of the mine, generating an annual
greenhouse gases emission reduction of 1.630t in the atmosphere.
Moreover, it has been proven that new fleet management technologies
which result in an increased fleet performance can reduce
greenhouse gas emissions by reducing the number of equipment
needed to operate the mining venture.
Also, with the use of a fleet management system, it was possible
to eliminate the use of paper. Thus, it changed the need for
filling manually pointing chips or the daily part of the electronic
note, so the electronically stored data could generate real-time reports
production. Consequently, this allows decisions to be made
during the shift.
In conclusion, maximizing the effective transport fleet
productivity results in less equipment necessary for transporting
ore and waste in mining operations.
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