FLEET MANAGEMENT
Rewind and fast-forward functions allow users to
scrub through the timeline until they reach a
moment of critical interest. Then, dispatchers can
pause the activity to examine it in greater detail.
This function gives mines a whole new depth of
understanding and insight over the system’s
previous playback capabilities.”
A new Dispatch Configuration screen makes it
easier for dispatchers to take advantage of
automated dispatching, which has been proven
to give active users 11% gains in mine output.
System 6 also makes it easier for mines to take
full advantage of automated, algorithmic
dispatching. An updated Dispatch Configuration
interface allows dispatchers to simply drag
trucks from one group to another, checking
dynamic sidebars to see reporting details like
Loading Unit Projections and Dump Targets. As
with other views in Fleet Control, Dispatch
Configuration now appears as another tabbed
window. Mines never need to take their eyes off
production to adjust dispatching parameters – all
monitoring and control happens together as an
intuitive, unified activity.
“Our research team has always known that
mines get optimal production results from using
automated, algorithmic dispatching. Yet, many
mines have struggled to make full use of this
technology — especially when software made
counterintuitive but effective dispatching
decisions. This upgraded Dispatch Configuration
makes it obvious to dispatchers how to configure
the system for optimal value, while also showing
dispatch details that prove any unexpected
results. Ultimately, this additional information is
giving mines increased confidence in the system
and helping them get higher production output.”
System 6 also sets data interoperability front
and centre with the new Wenco Data Warehouse.
This online analytical processing (OLAP)
database serves as a central bank of data from
sources throughout your entire mining enterprise.
It merges records from fleet management
systems, condition-based maintenance solutions,
ERP systems, mine planning systems, and any
other data solution used in operating your mine.
“With all this data connected in one central
location, mine managers and data analysts can
explore information across multiple systems like
never before.”
The Wenco Data Warehouse relies on a design
known as a star schema to keep data rapidly
accessible. Star schemas process data and handle
queries much faster than other database
architectures. Data populates the Wenco Data
Warehouse through an extract-transform-load
process. First, the system copies all data from each
of your available data sources — fleet management
databases, maintenance records, ERP systems, and
so on. As it extracts data, the system performs an
initial validation and quality check to ensure only
38 International Mining | MAY 2019
viable information gets imported.
Data from disparate mining systems populates
the Wenco Data Warehouse — fleet
management, maintenance, ERP, and more. After
the data has been extracted, the system converts
it into a standard format. “Different data sources
often use different database systems, units of
measure, character sets, or terminology to record
essential details of your mine. This
transformation stage keeps all data in the Wenco
Data Warehouse functioning in a consistent way.
With the data standardised, the system then
loads it into the Wenco Data Warehouse for use
in reporting and intelligence. Individual systems
still maintain the operational databases they
need to function, but reporting personnel can
finally manipulate mining data and run queries
across multiple datasets to uncover insights –
without affecting real-time operation.”
While the Wenco Data Warehouse is necessary
for strong analytics and business intelligence, it
also sets the foundation for future automation.
To create workflows and processes that occur
without heavy human interaction, data from
multiple systems needs to work interoperably.
The Wenco Data Warehouse prepares all of the
discrete data systems used in mining for sharing
information among each other in a coherent way.
Users of the Wenco Mine Performance Suite
can already take advantage of this data
interoperability with Avoca, the suite’s business
intelligence (BI) application. Dashboards and
dynamic visualisations are ready to connect the
dots and unearth valuable data correlations
throughout the entire operation. “But, forward-
thinking mines need to consider where the industry
is headed. How will they be able to use their data to
extract unrealised value in coming years? What can
they do now to take advantage of emerging
technologies when they become available?” BI
involves systems and methods for analysing data to
support smart business decisions. Unlike standard
reporting, BI includes a broad set of functions to
help users understand business conditions —
dynamic reports, data mining, predictive and
prescriptive analytics, and more. Using these
technologies, organisations can explore their data
and identify opportunities for improvement, then
implement fact-based strategies that advance them
toward their performance goals.
“Sectors like retail and finance have prized BI
for a generation, but mining has only adopted it
in recent years. Still, adoption is poised to
increase. As digital transformation takes hold in
the industry, mines say they are eager to find
solutions that help them understand cyclical
trends, project accurate forecasts, and improve
the effects of their decisions.”
Avoca starts by validating and importing all
mining data into the Wenco Data Warehouse.
This data comes from fleet management
databases, maintenance records, ERP systems,
or any other data system used throughout the
operation. Once the data is ready, mines can
quickly and easily explore rich visualisations that
show links between equipment units, operational
statuses, geography, machine condition, supply
chain data, material processing, and other
factors on site. Wenco organises this data across
a series of preconfigured dashboards that
relate to common mine departments –
Operations, Equipment and Maintenance,
Administration, and so on. “Simply looking at
these dashboards provides useful information
about operational behaviour and progress
toward goals. But, the system comes alive when
mine personnel use it to manipulate and interact
with their data.”
Clicking and dragging on any visualisation
selects a series of data points, focusing on areas
of interest and filtering out remaining data. At
the same time, other visualisations on the
dashboard change to match the data selection.
Users can opt to include or exclude certain
points, then watch as related visualisations
update in real time. In this way, users can easily
explore how certain data points behave in relation
to each other, accessing new depths of knowledge
about their mining operations in the process.
One Wenco customer recently reported how it
uses Avoca to extract more value from its
employees’ work hours. To make better use of its
human resources, this site pays a lot of attention
to Avoca’s Haul Cycle Variability dashboard.
Blending information from several data systems,
this dashboard shows variations in the amount of
time it takes operators to complete cycles of a
known haul route. By clicking and filtering the
data shown in the dashboard, managers can
easily sort and rank the active operator roster
based on performance. Operators on the left of
the chart frequently complete their circuits faster
than average, while operators on the right take
longer than average more often. Ideally,
operators want to complete each haul cycle as
close to the average as possible.
Site managers already know the majority of
slow-driving operators are trainees. They are
more interested in knowing which veteran
operators continue to take longer than average
to complete their haul cycles. Clicking and
filtering the same data once again, they can
easily exclude any operators who have joined the
company in recent months. With the dashboard
showing only long-time employees, managers can
easily see which operators are underperforming.
Then, they can show this chart to those operators
to prove they require additional training.
Before doing this analysis in Avoca, a site
engineer would spend days collating this data in
Microsoft Excel, cleansing it of errors, analysing
it, and preparing a report to senior management.