Managing risk using the internet of things and artificial intelligence
Emerging technology is a door-opener to new possibilities and novel opportunities, but it also entails new forms of risk or shifts in existing risk. This can have negative economic impacts, making it important to innovate – not only with technology, but also in risk management, tapping into those new forms of technology. Experts at the Ferdinand Steinbeis Institute have been investigating the best way to do this, also testing ideas they have developed directly in practice – in keeping with the Ferdinand Steinbeis Institutes’ own philosophy that science should deliver sustainable benefit to the economy and society.
It’s not uncommon for sawmills and agricultural operations to fall victim to catastrophic fires, often caused by the increased use of technical equipment, electric motors, and highly automated machines used to perform important tasks without direct human input. This increased use of technology is extending the scope of technological risk, and the probability of things going wrong is rising sharply in many sectors of the economy.
On the one hand, this is raising the level of required investment in technical solutions, such as fire detection systems and extinguishing equipment. On the other hand, companies in such risky areas of industry are finding it increasingly difficult, if not impossible, to insure against risk without negatively impacting the bottom line. Aside from tangible damage that can result from technical risk, the indirect consequences of damage are becoming increasingly important. When technical equipment is damaged, this often results in interruptions to operations and in the longer term, this impacts a company’s ability to deliver. The economic consequences of such indirect impacts can be much more serious than the immediate damage. Given bottlenecks in the supply of spare parts and the long delivery times currently affecting replacement parts and machines, there has been a sharp rise in the importance given to downtime factors and corresponding disruptions in supply chains due to technical damage. As a result, there is growing concern in business and society in general that the increasing use of new technology will go hand in hand with a rise in technical risk, sometimes with dire economic consequences.
Technology is not only driving risk, it’s opening up entirely new ways to manage risk. There are several promising ways to detect emerging risks even earlier (for example, by using better fire detection sensors) and these offer the potential to minimize direct damage (for example, by introducing technological innovations to extinguishing systems) and insure against commercial impacts.
Business and economic benefits
Innovative risk management is not only helpful for individual companies, it also offers significant benefit to the economy: Value chains become more reliable, negative impacts on value creation can be avoided, and the rate at which new (automation) technologies are introduced can be accelerated. The only question is, how to make things happen.
To dig deeper into this issue, the Ferdinand Steinbeis Institute has initiated a Micro Testbed with partners from industry and the public sector looking at several potential solutions, which are currently being tested as part of a pilot study. The essential “ingredient list” for coming up with effective game-changers: a collaborative mindset, digital twins, and artificial intelligence to create transparency.
A cooperative mindset – laying a foundation for success
In many cases, technical risks have several causes. These emerge both from the nature of products and how they are used. To identify and assess technical risks, different capabilities are required, although these are often not available to individual companies. To manage risk effectively, a key prerequisite is therefore a business ecosystem comprising different elements; i.e. an ecosystem should be initiated by involving a variety of companies offering different capabilities.
Aside from the ability of business partners to make decisions of a commercial nature, an indispensable basis for collaboration is the willingness of those partners to openly explore new realms – as partners of equal standing participating in a “forum of trust.”
In the timber industry, for example, equipment manufacturers possess the process know-how and design capabilities to gauge technical risk relating to the current condition of equipment. Users – for example, the providers of industrial services or production companies – can assess the condition of equipment based on current use. Thanks to claims settled in the past, stakeholders in the insurance industry, who have a solid understanding of risk, have a comprehensive overview of the overall structure of risk. A good rule of thumb: The broader the skill sets within an ecosystem, the more effective it will be in avoiding risk. Therefore it is important for different partners involved in such arrangements to agree on the common goal of managing risk. They will also need to come up with a joint agreement regarding roles and responsibilities, even if this may have disruptive implications for existing business models, as in the example of the timber industry and the insurance industry.
Accordingly, in the future the competencies required to participate in ecosystems will be extremely important for companies. An essential element of such competencies is the courage and willingness to share information so that it can be used by others and deliver benefit.
Creating transparency with digital twins and artificial intelligence
To gain transparency, it’s important that parameters required to assess risk for a given object of interest are available in equal measure to all stakeholders, and that they are up to date and of the required quality. Experience shows that a suitable architecture for this can be created by using digital twins. These draw on internet technology in the cloud to reproduce actual objects in a virtual environment.
A Micro Testbed set up in the timber industry uses parameters captured continuously by automation systems, such as leakage current, residual current, load peaks, vibration noise, etc. These are then made available virtually in digital twins. This provides complete transparency regarding the current status of equipment in a virtual environment, and enables monitoring from a variety of angles using (AI) algorithms. Understanding how to use digital twins, the application of AI technology, and in particular how to interpret results is thus a key competence. Experience with the testbed approach shows that with the right skill sets and a collaborative approach to using data on the technical status of equipment, technical risks become manageable.
Dealing with risk: outlook
Using emerging technology for digitalization and automation purposes fuels technical risk that can result in significant commercial risk, especially in combination with conventional approaches to claim settlement. Methods of AIoT-based risk management thus offer a number of promising options for the future, not only providing opportunities of a commercial nature: There is also the potential to achieve overarching sustainability goals affecting society as a whole. However, to leverage this potential, there are still a considerable number of missing items on the “ingredients list.” SMEs in particular would be well advised to move forward more quickly in rethinking their approach to sharing data, and they will need to acquire new skills when it comes to the AIoT.
Micro Testbeds allow companies to collaborate across different sectors of industry – in partnership and pragmatically – in order to introduce shared value creation processes, which they can experiment with together within a real business environment based on methods not used before.
The focus thus lies in trying out small-scale application scenarios. In doing so, existing technologies are used to allow new products and services to emerge through interdisciplinary collaboration against the backdrop of digital solutions and networking. The results gained from Micro Testbeds deliver benefit to all parties in unanticipated ways.
Sebastian Renken (author)
Ferdinand Steinbeis Institute Stuttgart (Stuttgart)
Lena Noller (author)
Ferdinand Steinbeis Institute Heilbronn (Heilbronn)
Prof. Dr. habil. Heiner Lasi (author)
Ferdinand-Steinbeis-Gesellschaft für transferorientierte Forschung gGmbH of the Steinbeis Foundation (FSG) (Stuttgart)