Bridging the “Data Wisdom” Gap
Wisdom. That is what we are striving for. Wisdom is good judgement based on knowledge and experience. This leads to wise decisions.
Data. If we have good data we can make better decisions as it removes the guess-work and provides us with facts. But data alone is useless unless we turn it into relevant information and use it to improve our understanding. Even once we reach a point of understanding, there is still another leap before we reach the point of wisdom.
When you think of someone who is wise, you will probably conjure up in your mind images of a wisened, old person. The point being, that to have wisdom you not only need information, understanding and insight but also the gift of time and experience to have perspective, see long-term trends, understand the bigger-picture and maybe even have a “feel” about the future!
How do you bridge this gap from data to the Holy Grail of wisdom?
Wisdom in Asset Management
Take a critical infrastructure asset – like a bridge – that you want to stay operational to keep people and vital services moving, whilst balancing maintenance to keep it structurally sound so people using it stay safe. In such instances, making wise decisions is not only desired, but essential in avoiding disasters like the recent Morandi Bridge collapse that occurred in Genoa.
This is the key to good Asset Management. Wise decisions will allow you to unlock more value from your assets, optimise the balance of cost, risk and performance, reduce uncertainty in your decision-making, and above all, keep people safe.
Here are 6 steps to get you from data to wisdom:
1. Data – Start with the end in mind
In today’s world, we have lots of data. Infrastructure is getting more sophisticated. However, you need to understand why you are collecting the data – what decisions are you trying to make and work backwards to what your data requirements are. This will ensure you are collecting relevant data about the things you are most interested in. Remote condition monitoring using IOT sensors is becoming more feasible for many assets, but this alone does not make a “smart asset” – you need to use the data in an effective way to make smart decisions.
2. The asset as a part of a system
It is important to remember that assets do not generally operate in isolation; they will be part of a system. Therefore, you need to consider both the asset and the system around it to set an appropriate system boundary. The data collected from the asset can be combined with data from the rest of the system to understand the holistic picture.
3. Building Understanding
Advancements in cloud-based computing enable integration and analysis of big data sets quickly and efficiently. This gives you the power to visualise and analyse data from various sources in real time to investigate correlations and therefore understand relationships and dependencies. Capitalising on this capability to capture, integrate, visualise and analyse data will build your understanding of asset health and performance.
4. Gaining insight
Insight comes from using this analysis to build a greater understanding of asset behaviour combined with expert engineering knowledge and judgement. Overlaying information about other activities you know occur on the asset such as maintenance and inspection results will give you more powerful insight.
5. Getting perspective
Evaluating patterns and trends in historic data over time gives you perspective. This is not something you have to wait years to gain, as you may find the data you’ve been collecting already is sufficient to give you this historic view. You may also be able to overlay experience of real faults or failures with data from the asset at that time in the past to identify the root cause. This historic view is very powerful in developing a rich knowledge of the asset and its wider system.
6. Reaching the point of wisdom
The last step towards wisdom is developing a “feel” about the future. You can use machine learning techniques to predict future asset behaviours. Resulting predictions of asset behaviour are refined over time by collating more data to confirm and enhance the decision process. This cycle of prediction and feedback is a continuous improvement loop that will build enhanced wisdom and enable better decisions.
How does Amey do this now?
“Mercury” is Amey’s IOT Advanced Analytics solution. It has been deployed on the Forth Road Bridge (FRB) to support improved asset management decision-making and reduce uncertainties. Harnessing the power of cloud-based big-data analytics and machine learning, it combines data streams from numerous IOT sensors on FRB to monitor the condition of the bridge, provide alerts, and predict future asset behaviours.
For example, data collected from monitoring sensors installed on the FRB Suspended Side Span end rocker connection to the Side Tower was processed through Mercury, and the resulting end rocker response plots determined that this part of the bridge was articulating as expected. This allowed engineers to revise the risk of failure of these components and eliminate unnecessary work on the end rockers.
The benefits of an asset management system which incorporates structural health monitoring (SHM), accurate asset information data capture and processing were clearly demonstrated during the 2015 truss end link failure on FRB enabling engineers to evaluate the risk of other link failures and monitor asset condition after the remedial works. This gave both Transport Scotland and the Scottish Ministers the confidence required to reopen the bridge.
Amey operates and maintains the Forth Road Bridge and Queensferry Crossing on behalf of Transport Scotland. Ewan Angus, Amey’s Major Bridges Director, is presenting at the IAM Asset Management conference on November 28th. Ewan will be presenting and speaking about “Intelligent Infrastructure – Digitally Enabled Asset Management on the Forth Road Bridges”.