Background & philosophy
The thinking behind HLC Analytics
Why one engineer is working on consulting, AI, traffic-load data and monitoring at the same time — and why they belong together.
Background
During the decades-long journey in bridge engineering, I have had the opportunity to work from many different perspectives—as a bridge designer, proof checker, project manager, client representative, authority engineer and standards developer. Those experiences have shown me where the biggest challenges lie throughout the life of a bridge.
Three years ago, just after leaving my previous role and being introduced to artificial intelligence, I started asking a simple question:
Where could these new tools genuinely improve bridge engineering?
Rather than focusing on individual tasks, I wanted to look at bridge engineering as a whole—from the first design assumptions to the end of a bridge's service life. After extensive experimentation, I realised that several important areas already produce large amounts of valuable engineering data, yet much of that information remains underutilised.
HLC Analytics is the result of that exploration.
The four areas below are independent initiatives, but they all share the same objective: reducing unnecessary friction in bridge engineering, making better use of engineering knowledge and data, and ultimately helping engineers make better decisions throughout the life of a bridge.
01 · Consulting
Solving today's problems, learning every day.
HLC Analytics provides consulting services to bridge owners, authorities, designers and educational institutions.
Focusing on the areas where the collected experience provides the greatest value, the objective is to help organisations solve today's engineering challenges while continuously learning something new every day. Every project also provides new knowledge that contributes to future work, creating a continuous cycle of learning and improvement.
02 · Alma
Less friction — and a memory that lasts.
Alma is a genuine attempt to reduce friction in bridge engineering.
It is not intended to replace standards, engineering judgement or experienced engineers. Instead, Alma supports engineers by making standards easier to understand, improving the consistency of their interpretation and helping engineers apply them correctly in practice.
At the same time, Alma is an attempt to preserve engineering knowledge. Important engineering decisions, interpretations and project experience should not disappear when projects end or experts retire. Instead, they should become part of a continuously growing engineering memory that benefits future projects and future generations of engineers.
03 · WIM-Cal
Traffic data anyone can understand.
WIM-Cal is an effort to make traffic load data more accessible and more useful.
Its purpose is not only to organise traffic measurements for engineering analysis, but also to make the information understandable to a much wider audience, including bridge owners, infrastructure managers and public authorities.
Transparency is one of the fundamental principles of WIM-Cal.
The assumptions behind every analysis are always visible. Some of the methods deliberately prioritise simplicity and comparability over fully calibrated reliability analyses, allowing engineers and non-specialists alike to understand the characteristics of measured traffic.
Using the same methodology for every dataset makes meaningful comparisons possible between different regions, measurement campaigns and time periods. While absolute calibration of reliability levels will always require competent engineering judgement, WIM-Cal provides a consistent foundation upon which more advanced analyses can be built.
As artificial intelligence continues to develop, structured traffic databases will also make it much easier to introduce new analysis methods in the future without changing the underlying data. Today's engineering insights may therefore become tomorrow's advanced reliability analyses using the very same datasets.
04 · Monitoring
From measurement data to engineering knowledge.
Bridges have been monitored for decades, yet the enormous amount of measurement data has often limited its practical value. Processing and interpreting the data requires considerable engineering effort, meaning that much of the available information remains underutilised.
Artificial intelligence changes this balance.
It allows domain experts to rapidly experiment with different methods of analysing and visualising data. Sometimes the greatest improvements come not from entirely new technologies, but simply from discovering better ways to present and interpret existing information.
HLC Analytics approaches monitoring from the ground up. The first objective is to create tools that bridge owners and clients can easily understand and use in everyday decision-making. More advanced analytical methods will gradually be added as the system evolves.
The ultimate objective is not to collect more monitoring data, but to transform that data into engineering knowledge that supports safer decisions, earlier detection of structural changes and longer, more sustainable service lives.
— Heikki Lilja, HLC Analytics