The
construction industry uses 13 billion cubic meters of ready-mix concrete every
year. The logistics and quality assurance of this concrete depend on legacy
technologies that are no longer sufficient for today’s needs. To address this, Caidio
is introducing AI-based solutions to help the supply chain deliver better
quality concrete more efficiently.
The Challenges of the
Concrete Supply Chain
The ready-mix
concrete supply chain process starts at the batch plant that produces the
concrete (typically a wet mix in Finland). Transit mixers then deliver the
concrete to the construction site. At the site, the concrete is poured or
pumped into molds and left to cure and dry. What happens at each stage has an
effect on the quality of the final product.
Many of the
measurement methods used in concrete quality assurance date back to the 1970s
or even earlier. Documentation is usually paper based, and phone calls remain
the main communication channel. Outdated practices make it hard to control the
quality of the product throughout the process.
This is
becoming increasingly apparent as demonstrated by some recent worrying examples
of concrete quality problems in Finland. For example, in Northern Finland, in
the city of Kemijärvi, a newly built bridge had to be dismantled because of
fragile concrete. In Turku, concrete strength deficiencies halted the
construction of a large hospital extension; indeed, the problems were so
serious that they added an extra year to the construction schedule.
Collaborating to Make the
Industry Better
A group of
construction industry forerunners decided to get together to attempt to solve
the quality problems. In late 2017, the newly established DigiConcrete working group arranged a workshop to identify the challenges in concrete
construction. The group believed that digitalization was the key to better
quality.
The next
spring, the group identified Artificial Intelligence (AI) and the Internet of
Things (IoT) as potential solutions to the problems. Unfortunately, DigiConcrete
could not find any companies offering AI solutions for the concrete value
chain. That discovery led to the establishment of Caidio, a concrete intelligence
startup.
“Pasi Karppinen,
whom I already knew and whose firm was a member of the group, suggested that we
should start up a company, one that would revolutionize the industry,” says Aku Wilenius, a former National
Instruments engineer, who joined the team and became the CEO of that startup.
Experimenting with AI
Working with members of the DigiConcrete group, Caidio started an experimentation project to study and test the possibilities of using AI for concrete construction. The DigiConcrete project received funding from the Finnish government’s KIRA-digi program.
One of
project partners was Congrid, a company offering a digital alternative to paper-based
quality reporting. In the experiments, Caidio used Congrid’s mobile concrete
log sheet to test how AI could be used to analyze it.
“Another
test involved an AI-based construction assistant. As we know, knowledge in the
industry is very much person-specific and we wondered how that knowledge could
be passed on to a less-experienced worker,” Wilenius explains.
The idea
was that the digital assistant could collect data across the entire concrete
construction process, including from design models and databases, to open data
sources, and IoT sensors. It could use weather and traffic data to determine
the behavior of ready-mix concrete during transport. It was intended that AI algorithms
would control the whole process and product quality, prompting users to make the
right decisions throughout the process.
One of the
experiments tested locational tags to track down concrete pumps on a
construction site. Surprisingly, it’s not always straightforward for a truck
driver to find the right pump on a large site.
The
KIRA-digi experiment also included tests on concrete quantity estimation, mold
heating during the winter, logistics optimization, raw material quality control,
and safety on the construction site. In addition, Aalto University is developing
new digital measurement methods and sensor technology for concrete quality
measurement in collaboration with the DigiConcrete project.
“In 2019,
we’re planning to pick the most feasible use cases from our experiments and to start
piloting them in real-life construction projects,” says Wilenius. “As a
company, we’ll focus on providing the underlying intelligence for all relevant processes.
We’re also always happy to collaborate with others who want to develop apps and
user interfaces that utilize our inference machine.”
You can
connect with Aku Wilenius on LinkedIn.
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