Grenacher: I anticipate that the sensor network in industrial plants and logistics on the whole will become extremely consolidated. At the same time, these sensors will become more efficient and affordable. In the future, all company systems, and also all replacement parts, tools, containers, and products will be represented by their “digital twins”—a complete factory on your computer. The multitude of data that can be collected, in combination with analysis by AI applications, will provide completely new insights into the interplay between business processes. This will lead to fully-automated smart factories, which will basically be self-operating without human intervention thanks to AI and digital twins.
Q: What new business models do you expect in the service sector as a result of the increasing digitalization of factories?
Grenacher: Industry 4.0 cannot function without a digital service concept because service is an essential part of digitalization. Service is already a distinguishing factor in competition. It’s no longer just about the product since it is often similar, even interchangeable. That is why customers primarily choose a partner that offers more and quicker services. And that is why every company’s goal should be to better understand its customers, to create better touchpoints, and to improve service. Here’s where new concepts like “machine-as-a-service“ come into play. This makes it possible for companies to just purchase machine performance from the manufacturer instead of the machine itself – including maintenance to guarantee consistent performance. Service Lifecycle Management plays a key role in this concept. In the future, entire ecosystems consisting of new service providers will arise around these concepts.
Q: Predictive maintenance is an important issue in the service sector. Are there emerging technologies that may soon become similarly important?
Grenacher: Augmented reality will soon allow experienced personnel to perform skilled jobs without detailed knowledge of each machine and with the appropriate on-site digital support. The technician will be supplied with missing details via data glasses, for example. This makes it possible to integrate qualified workers, who are not part of the service company’s workforce, into maintenance and skills management without the need for company-specific training. The full potential of machine learning will also unfold in the years to come: The use of artificial intelligence, for example, facilitates the assessment of a machine’s untapped potential and the extent to which its use in a specific application area or scenario might be beneficial.
Q: What new business models do you expect in the service sector as a result of the increasing digitalization of factories?
Grenacher: Industry 4.0 cannot function without a digital service concept because service is an essential part of digitalization. Service is already a distinguishing factor in competition. It’s no longer just about the product since it is often similar, even interchangeable. That is why customers primarily choose a partner that offers more and quicker services. And that is why every company’s goal should be to better understand its customers, to create better touchpoints, and to improve service. Here’s where new concepts like “machine-as-a-service“ come into play. This makes it possible for companies to just purchase machine performance from the manufacturer instead of the machine itself – including maintenance to guarantee consistent performance. Service Lifecycle Management plays a key role in this concept. In the future, entire ecosystems consisting of new service providers will arise around these concepts.
Q: Predictive maintenance is an important issue in the service sector. Are there emerging technologies that may soon become similarly important?
Grenacher: Augmented reality will soon allow experienced personnel to perform skilled jobs without detailed knowledge of each machine and with the appropriate on-site digital support. The technician will be supplied with missing details via data glasses, for example. This makes it possible to integrate qualified workers, who are not part of the service company’s workforce, into maintenance and skills management without the need for company-specific training. The full potential of machine learning will also unfold in the years to come: The use of artificial intelligence, for example, facilitates the assessment of a machine’s untapped potential and the extent to which its use in a specific application area or scenario might be beneficial.
Guys, I created a channel about Augmented Reality.
Are you interest for you?
Can I share a link of AR channel?
Are you interest for you?
Can I share a link of AR channel?
Head of the IfM's Distributed Information and Automation Laboratory (DIAL), Professor Duncan McFarlane, is a pioneer of the internet of things (IoT) and was part of the research team that coined the term "internet of things" 20 years ago. Today he and his research team are working with multinational companies to help transform their processes and supply chains by extending IoT technologies to the industrial IoT (IIoT). In this webinar Professor McFarlane provides an introduction to the IoT and the IIoT and the opportunities and challenges facing industry.
YouTube
Introduction to the Industrial Internet of Things (IIoT)
Head of the IfM's Distributed Information and Automation Laboratory (DIAL), Professor Duncan McFarlane, is a pioneer of the internet of things (IoT) and was part of the research team that coined the term "internet of things" 20 years ago. Today he and his…
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My company Aremi Studio gives a discount (30%) on development landing page.🚀
We use website builder ( it's built on React JS)
Free prototype in gift!
Mail: [email protected]
Website: https://aremi.studio/
DM: @vasylzelinskiy