Artificial Intelligence in the TIC industry

Artificial Intelligence has been on the rise over the past decade. It’s already everywhere around us. Your phone pointing you to the best restaurants nearby. Beating humans in chess. Cars that drive themselves. The AI we know and use in our daily lives is Artificial Narrow Intelligence (ANI)[1]. ANI is very good at doing one specific thing and improving upon that. All applications mentioned above are examples of ANI.

The Testing, Inspection and Certification (TIC) industry is dependant on skilled inspectors to perform audits. These inspectors need a keen pair of eyes, vast knowledge of regulations and procedures, and specialised knowledge of machines.

That’s a lot of expertise you need to perform quality inspections. ANI can assist in getting inspections done safer, faster and more accurate. We’ll take you through a few ways in which ANI can help inspection companies create a more safe, secure world for everyone.

 


 

1. Computer Vision & AI Computer vision has been around for decades. It focuses on capturing and analysing pictures. Since the price of optical lenses has dropped significantly in recent years, computer vision technology is now a lot more affordable than it used to be. As you might imagine, ANI and computer vision go hand in hand. Image and pattern recognition are a big focus for those studying artificial intelligence. Consequentially, most AI improvements are made in the area of visual detection.

There are several benefits to combining AI and computer vision. First of all, artificial intelligence improves upon its own detection capabilities. It becomes more and more accurate in recognizing dangers and defects. Second, computers and lenses don’t get tired! Everyone has an off-day every now and again. A foggy brain, eye strain, distractions; they happen to the best of us. Machines don’t suffer such conditions (assuming they are kept in good shape).

Anything detected by a digital camera is likely to be more accurate than what the human eye sees. You can apply the concept of computer vision and ANI in many different ways. Many factories already use it to automate the quality control of their manufacturing process, for example. We call this specific application of computer vision and AI in industrial processes ‘Machine Vision’.

The big benefit for the TIC industry seems to be in the application of computer vision in drones. Think about it: instead clambering into a dangerous space, you send in the drone to take pictures. And you analyse them in real-time on your mobile device. You’ll stay safe while you have all the information you need during your inspection. The AI can give you precise measurements and analysis to help you determine the next steps.

 


 

2. Planning & Scheduling

Planning and scheduling can be a very complex business. The more people, materials and actions you need to take into account, the more daunting it gets. Artificial intelligence has the potential to make this a lot easier. As I’ve stated earlier, pattern recognition is something that AI is exceptional at[2]. Considering this, it makes sense to apply ANI to work planning. It could recognize and calculate an inspector’s most optimal route for the day and plan the right equipment along with it. Combined with report data, AI could even schedule the required follow-up actions.

Applying ANI to planning has the potential to save planners a lot of headaches. Additionally, it ensures a fair, balanced planning. After all, a machine that plans off of pure, factual data won’t play favourites! They plan and schedule in the most optimal way. Period. All an AI needs is a little input. Give it some information, such as what work to plan and which people/expertises are available. The AI will take care of the rest.

On top of schedule planning, an AI can automate inventory and purchasing. If set up right, ANI can assist in keeping track of stock levels of materials and tools. You can automate ordering repairs and replenishments of stock. Even better: if you combine this with the capabilities for workforce scheduling, you’ll never have trouble planning a job or project ever again!

I know, I know… It almost sounds too good to be true, doesn’t it?

 


 

3. Analytics

Nowadays, we’re drowning in data. We have acces to far more than a single person could ever meaningfully use to perform their work. AI is a powerful tool in compiling relevant data. It can filter, arrange and present data in a clear, visual interface. In short: AI can give you the exact data you need to make informed decisions.

As said, computers are far better and identifying patterns and trends than humans are. Imagine I gave you a 1000 page document of inspection statistics and told you to ‘make a ranking of the most common deficiencies over the past 10 years. I imagine I probably would not get invited to your next party. Artificial Intelligence has no trouble going through all that, seeing the patterns and organizing the data. It could even, based on previous calculations, give advice on what to do with the information.

You could even go a step beyond. If you allow an AI to make autonomous decisions, it could prioritise and plan all the work for you. This is especially useful in the management and planning departments.

These are some simple examples of applying artificial intelligence to (historical) datasets. The point is: no matter what you want to know, an AI is capable of giving you all the relevant data you need, when you need it. The only limits are the questions you ask it!

As the technology matures faster and faster, we’re working to apply the capabilities of Artificial Intelligence to our own products. If you want to know more, you can download the brochure here.

 


[1] Artificial General Intelligence (AGI) is the next step in the development of artificial intelligence. AGI refers to an AI attaining a level of understanding the same as the human brain. When AGI becomes real, it will likely cause a societal shift unlike anything we have seen so far. If you have some time and you’re interested to learn more, I highly recommend this article by Tim Urban. It’s a long read and couple of years old, but its main points are as relevant today as when the article first appeared in 2015.

[2] A lot better than us humans, who often think we are very good at this. More often than not, our pattern recognition and subsequent decision-making is based in biases. Computers have no such problems, providing they are not designed with inherent biases.

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