Founded in 1981, Indian Infosys provides business consulting, information technology, software engineering and outsourcing services.
The company has also embraced the IoT spirit sweeping the world, and more recently entered a joint partnership with GE to develop industrial IoT solutions.
CBR’s Joao Lima sat down with Gordon Muehl, VP industrial internet at Infosys, to talk IoT assets, virtual reality in the industrial space and the UK’s place in this scene.
CBR: How would you define an IoT asset?
GM: An IoT asset is a piece of machinery, or asset, which is enabled by a vendor to connect to the internet to drive efficiency.
If you look at the wider industrial market, there is a lot of investment in every kind of assets across complex machinery, from factory floors to aeroplanes.
CBR: How important is asset efficiency?
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GM: Any asset running in industry consumes a lot of energy and resources. Billions of pounds are spent every year on physically operating sites like power stations and refineries. Faced with those costs, there is a natural pressure to look for efficiencies.
An efficiency improvement of only 5% to 10% can equate to savings of millions of pounds. Through more efficient use of different assets throughout the organisation, real savings can be made.
CBR: How mature are asset efficiency strategies in industrial manufacturing?
GM: We are just in the beginning when considering the age of Industry 4.0 and the IoT. Industrial manufacturing has been working with data at a local, traditional level for some time.
The industry is familiar with analysing data within an organisation throughout a particular production plant, but now we are only beginning to extract real value out of new technologies.
In a recent study we commissioned, we looked at the varying levels of maturity in Industry 4.0 across China, France, Germany, the UK, and the US.
No country can claim to be the global early adopter in implementing Industry 4.0 in the context of asset efficiency; nevertheless, significantly more companies in China (57%) claim to be early adopters.
There are a number of factors driving this including focused initiatives, governmental investments and the Chinese manufacturing sector being quick to implement new technologies. Germany (21%), the UK (26%) and the US (32%) have similar maturity footprints, with France behind with 14%.
CBR: What is your view on the UK in the IoT/M2M asset management space?
GM: If you compare the UK with France and Germany, we see in Germany that IoT and asset management is a priority for the government and boardrooms throughout the country.
To keep up with burgeoning technologies, there needs to be top down change involving everyone from governments to industry bodies and trade unions.
The UK needs to make IoT and M2M asset management a higher priority if it wants to keep pace with industrial manufacturing.
Organisations need to pull in the same direction, as the UK is in danger of falling behind other European countries, let alone the success being seen in Chinese markets.
CBR: Could you explain your Asset Efficiency Testbed launched recently?
GM: The Asset Efficiency Testbed solution analyses real-time and historical data across key health parameters and predicts the serviceable life of assets in order to decrease downtime and increase asset utilisation.
The main goal is to collect asset information more efficiently and accurately, in real-time. Also, to enable usage of analytics to help companies, and engineering teams make the right decisions.
CBR: What are the benefits of implementing IoT-driven strategies in the industrial space?
GM: Today, people share playlists via the internet with anyone who is interested. This is similar to engineers sharing maintenance or repair instructions with colleagues in the industry. One machine tells another if it is not feeling good, and like a playlist, shares this with another machine.
An IoT strategy is a bit like two users, following each other on a streaming service over the internet. With connected machines, you can not only share playlists, but learn more.
For example, you can gain information about the performance of the machine and where it is from, allowing greater insight due to the machines being connected.
