Last Updated on April 16, 2021 by Admin
In recent times, the Big Data model has received exceptional attention for nailing 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 an evident revolution as a result of a 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 importance of Big Data technologies to process extensive data, current Civil Engineering information systems are still lacking in the successful implementation of them.
The construction industry is responsible for undertaking some of the significant and most expensive projects on Earth. Huge amounts of resources and work go into major construction projects and of course, this means that huge volumes of data are generated.
Number crunching has always been a big part of construction – a commonly heard phrase is that construction companies are accounting companies that 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 have 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 Goto meeting 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 modeling. 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 backward and forward communications between architects, engineers, and owners, insights into the effects of changes are now visible almost instantaneously.
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 modeling) 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 is 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 a 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 expenses. 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 into account. “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 hemorrhaging 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 that 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 trialed at the moment but will undoubtedly soon be tied to systems 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, the completion time of the project was shortened by 12 weeks.