Stone Junction Ltd

Black box insurance model offers real time premiums for manufacturer’s machinery

28 November 2019

Inrobin has partnered with The University of Strathclyde’s Advanced Forming Research Centre (AFRC) to develop a new insurance model offering an Industry 4.0 approach aimed at achieving better pricing for manufacturers.

Based on the Industrial Internet of Things (IIoT), the new model analyses real time data from industrial machinery. This allows insurance companies to offer competitive premium rates based on individual usage of equipment according to factors, such as frequency of machine maintenance and operational efficiency.   

Manufacturers are set to benefit from a combined offering of risk prevention and tailored insurance, with in depth data analysis also providing a deeper understanding of how to run machinery more efficiently.

This new model will also bring additional benefits, helping manufacturers improve maintenance schedules and prevent breakdowns, which can cause expensive downtime. 

Inrobin worked with the AFRC’s bid writing team to secure Innovate UK funding. The firm’s data science experts will now work with the research centre to trial the system on its industrial machinery. It will also exploit the centre’s expertise in IIoT and connectivity, while tapping into its extensive list of manufacturing contacts to gather further information to guide the project. 

Aiming to predict machinery life expectancy based on usage, the programme also helps ensure that equipment is properly serviced and maintained, while flagging up unforeseen issues potentially affecting production.

Insurance providers currently assume that two companies buying the same machine should pay the same premium based on the same life expectancy; however, the new model will offer a more tailored pricing approach – analysing each machine’s specific behaviour and machine maintenance in real time to adjust rates. 

Jose-Maria Guerra, chief executive officer at Inrobin, said: “Using IIoT we can track life expectancy and failure expectations within the machine in real time to offer manufacturers a premium that fits their needs, ensuring that they have the right type of coverage.

“Working with AFRC's cutting-edge equipment throughout the project allows us to build up an understanding of failure and test certain things that would not be possible within a manufacturing environment. 

“We’ve already been speaking to global insurance companies that have registered interest and we are set to work on a pilot project with a major European provider later this year.” 

Danny McMahon, metrology and digital manufacturing team lead at the AFRC, said: “According to current insurance models, a manufacturer who uses a machine to its full capacity every day without regular maintenance might be on the exact same insurance premium as a company that’s using it at 25% or 50% capacity, while also servicing their machinery each month. With the new model, insurance companies will offer a more competitive service while manufacturers will maintain their machinery more efficiently. 

“Inrobin’s new model will create a more transparent offering for industrial machinery similar to the use of ‘black box insurance' for cars. In the way that sensible drivers who are looking after their vehicles are rewarded with a cheaper premium, manufacturers sensibly using their equipment can take out insurance that reflects their use rather than an industry average.

“The AFRC will act as a transition to market for Inrobin. Following on from helping with the initial bid, we’ll use our state-of-the-art machinery to trial the system and offer machinery expertise to push exploitation forward helping the business to grow.” 


Print this page | E-mail this page


Optimal Drive Technology

This website uses cookies primarily for visitor analytics. Certain pages will ask you to fill in contact details to receive additional information. On these pages you have the option of having the site log your details for future visits. Indicating you want the site to remember your details will place a cookie on your device. To view our full cookie policy, please click here. You can also view it at any time by going to our Contact Us page.