How Big Data Will Transform the Construction Industry
In
recent times, Big Data model has received
remarkable attention for tackling complex engineering problems. Amongst
the engineering fields, Big Data analytics is remarkably
impacting the Civil Engineering domain. The operation and maintenance of Civil
Engineering systems are now undergoing evident revolution
as a result of huge amount of information provided by emerging testing and
monitoring systems. The key role of Big Data in this revolution
is
well-understood. Despite the significance of the Big Data technologies to
process extensive
data, current Civil Engineering information systems are still lacking in
successful implementation of them.
Number crunching has always been a big
part of construction – a commonly heard phrase is that construction companies
are accounting companies which happen to erect buildings.
It’s an industry where 45% of costs are accounted for by
material waste and remedial work. So counting the cost of every screw could be
the difference between delivering on budget and bankrupting an organization financing
a build.
The construction firms has
started
to move into areas such as real-time, cloud-powered
analytics of large and unstructured datasets. Such methods have the potential
to redefine the conventionally burdened associations between the interested
parties. Architects – who want to unleash their creative energy – engineers –
who have to try and make it all fit together and not fall down again – and
owners, worried to keep costs from increase out of control.
John Jacobs, CIO for JE DUNN, responsible
for some of the largest construction projects in the US, told that this has
been achieved through building partnerships with tech firms in order to develop
industry specific tools.
Jacobs told “Here’s the primary issue – we have a complex
process that we go through to build a building. We need access to 2D and 3D
data, financial data, corporate data, documents, schedule elements, weather –
all this has to be linked and it’s a complex web.
“The world has Dropbox and Gotomeeting
to collaborate – we don’t have anything like that specifically for
construction. So we had to set out to build our own. And that means we’ve
created a tech foundation that we’re really finding to be transformational.”
JE DUNN partnered with Autodesk ADSK +4.20% to
build systems allowing real-time, data driven predictive modelling. They tied
Autodesk’s large model viewing functionality with their own estimating system
to develop custom visualization technology known as LENS.
“Now you have a picture,” says Jacobs. “The
owner can see that concept model from our design partner and see the dollars
tied to it. You can say ‘Show me what it would be like if we added another
floor’ or ‘what if we made this part bigger?’ Every element in the design is
tied to our cost estimate. It is completely integrated so the solution changes
visually, on the fly.
“This changes everything – the owner
can see that we understand what they want, and see that our numbers are right.
That level of reliability is really changing the industry and effectiveness of
our early pricing”
This massively speeds up the design
process and already, even at this early stage, contributes to waste saving.
Whereas before, minor changes to the design could mean several weeks or months
of backwards and forward communications between architects, engineers and
owners, insights into the effects of changes are now visible almost
instantaneously.
Hanspal Although it’s too early to
have much in the way of concrete results, Jacobs tells me that their new Big
Data driven BIM (building information modelling) system is estimated to have
reduced costs of one $60 million civic center construction project by $11
million, and cut the projected completion time by 12 weeks by drastically
shortening the pre-construction phase.
As with other industries, an obstacle
in construction is that much of the data which has been collected until now is
effectively siloed – held in isolation by the business department or division
which collected it, where it is useful for their own analytics but can’t
contribute to the big picture, birds’-eye view needed for real Big Data
analytics.
The move to cloud based storage
systems, which Dunn are now undergoing, puts all of this data at the fingertips
of anyone who needs it. Distributed storage systems mean the data can be added
to almost infinitely, as fast as it can be collected, at minimal cost.
Project managers can quickly gain an
overview of QA, safety, workforce and equipment data, simplifying the task of
identifying risk and evaluating performance. Problems can be identified before
they emerge, leading to large time and expense savings on remedial work.
External data plays a large part too,
for example meteorological reports. Weather conditions can delay building
projects which inevitably leads to mounting expense. But by recording the
actual effects of real world weather and using this data to model the likely
implications on current projects, more accurate assessments are possible.
As the larger projects can take several years to complete, economic and
political activity is likely to affect labor and material costs – so this must
also be taken account of.
“Data is the new dollar,” says
Autodesk’s SVP for products, Amar Hanspal. “Material waste accounts for
approximately 25% of a project’s cost, and rework adds an estimated 10%.
“This is inexcusable given the fact
that today’s digital tools are readily available to stop this haemorrhaging of
money, materials and time. This inefficiency costs big money to customers”
The way Hanspal sees it, collaborations
such as the one between his company and JE Dunn are disrupting an industry
which has for too long resisted change.
“The fundamental challenge of the
industry has been to manage the many parties – architects, engineers,
construction managers, sub-contractors, specialty tradesmen, and owners – that
are involved in the building process.
“Collecting, sharing understanding and
using the data generated across these groups helps break down silos across the
entire project team – it gets everyone on the same page and helps reduce risk.
“Ultimately data paired with advanced
technology, specifically those that embrace collaboration in the cloud, offers
an efficiency that reduces project delivery time and risk of errors, resulting
in increased profit margins.”
An exciting development in the field of
visualization is the emergence of AR (augmented reality) tools. While virtual
reality tours of buildings before they are complete have been around for a
while, AR takes things a step further. It means the user (e.g. a customer) can
stand at the site at the commencement of the build, and through a headset see
the entire finished project as it will look when it is completed, as a 3D
virtual model overlaid against a real skyline. This tech is being trialled at
the moment but will undoubtedly soon be tied to system’s such as Dunn’s BIM
platform. Small variables such as the placement of windows could be altered
with the user immediately being shown a visual representation of how this will
affect light in a room.
By 2030, the worldwide market for
construction services is expected to grow by 85% to $15.5 trillion. This will
present huge challenges, both in ensuring a sufficient supply of skilled labor,
and adopting new technologies to drive efficiency and innovation. Buildings are
becoming bigger and more complex and a growing focus is being put on
sustainability.
Big Data has the potential to provide
solutions to all of these issues, if the trend towards ongoing collaboration
between the industry and tech development continues.
Over the next five years Big Data and analytics will radically transform both the process of construction and the business of construction contracting. The future seems very bright for those companies which are able to embrace data analytics and new technology to innovate how we construct things.
As per Jacobs, the big data-driven building
information modeling system has already helped to drastically cut costs of a
$60 million civic center venture by as much as $11 million. In addition, completion time of the project was shortened by 12
weeks.
How Big Data Will Transform the Construction Industry
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