Skanska is working with partners, including Volvo, to develop artificial intelligence for construction equipment to achieve less emissions, faster production and lower costs.
Construction sites can involve hundreds of multi-ton excavators, loaders, haulers and other heavy equipment. For the best performance, these machines should all work together seamlessly in a complicated ballet of sorts, with each machine doing its part at the prescribed time. But across the construction industry, such close coordination is difficult to achieve due to the ever-changing nature of sites. As a result, construction equipment can sit idle up to 40 percent of the time waiting on other equipment, increasing costs and carbon emissions.
To help solve this problem, Skanska is developing solutions to enable heavy equipment – such as multi-ton excavators, loaders and haulers – to work more efficiently. This involves exploring such methods as machine learning, route optimisation and artificial intelligence through a consortium of Skanska Norway, Volvo Construction Equipment, research organization SINTEF and construction software company Ditio.
This Norwegian project – half funded by the Norwegian government - will leverage equipment operating data to create a solution for the automatic real-time management of machinery on construction sites. With construction equipment accounting for a significant amount of the industry’s carbon emissions, this work is key to Skanska and society achieving climate emissions targets. Skanska is working to become climate neutral by 2045.
“This research aims to bring about significant reductions in time, emissions and construction costs, and the goal is to make the solution commercially available to everyone,” commented Jo Mortensen, Executive Vice President of Technology & Operational Efficiency at Skanska Norway. “If our industry is to achieve its sustainability goals, we need to work together.”
Algorithms that optimise performance
Skanska’s vision is having construction projects where every single construction machine knows at any given time where the other machines are, what they are doing and the most optimal way to organise the work.
Through this research project, we will be part of developing algorithms that can learn to recognise inefficient route choices and driving patterns, see which machines are needed where and coordinate machinery to avoid needless waiting, idling and work. Software company Ditio, part-owned by Skanska, has developed the software that we already use in Norway to log data about construction equipment operations, including where and when the machines operate.
Scientists from SINTEF Digital will use this huge amount of data to develop machine optimisation algorithms. This will be done in close collaboration with a Skanska highway project in Norway, which will become a living research laboratory. This research begins in early 2020 and is expected to continue until the end of 2022.
Currently, the machines on a construction site are coordinated by experienced supervisors with walkie talkies. Skanska and SINTEF will incorporate their practices into the algorithms that will ensure the optimal utilisation of the machines.
“The number of simultaneous operations in a large civil engineering project is very comprehensive and complex, so this project will give the construction managers solid real-time decision support,” said Lars Horn, Project Leader with Skanska Norway. “Once the algorithms can handle the simple tasks, supervisors will have more time available to use their skills to solve the most demanding bottlenecks.”
Furthermore, while this research focuses on existing machines, the final product is a key component to achieving a semi- or fully autonomous construction site.
Less emissions and less cost
To help this AI solution benefit the entire construction industry, the finished solution will be made available to the market.
Other benefits will include reduced climate impacts and other benefits to society. For instance, Norway spends NOK 100 billion a year on road construction, and about 70 percent of that cost is related to fuel, personnel and the operation of machinery.
“We will cut emissions, but we will also build roads faster and cheaper. If this goes as planned you will be able to see the impact on the state budget,” explained Randi Lekanger, Head of Environment at Skanska Norway.
DHL and the other logistics companies are already using artificial intelligence to find the most efficient parcel distribution routes. But Skanska has completely different challenges, says SINTEF researcher Signe Riemer-Sørensen.
“The big difference is that DHL only delivers, while Skanska is present across all the links in the value chain. At the construction site, they are both the sender and receiver of the masses to be moved. Therefore, Skanska has several considerations to take into account - and even more to gain when it comes optimisation for the benefit of the customer.”
Across our markets, Skanska is part of a variety of research and development activities with heavy equipment to lower emissions and costs and improve safety. These include Electric Site, a demonstration project in Sweden with Volvo Construction Equipment to develop new types of quarry equipment powered by electricity and new ways of working; devising plans to pilot autonomous excavators on a US highway construction project; and using semi-autonomous controls to aid operators in operating heavy construction equipment in several markets.