What happens in the "digital factory"? Key trends from the Hannover Messe 2018
At the world's leading trade show for industrial technology, state-of-the-art production technologies and solutions for industrial automation were once again on display this year. In view of the trend towards a digital transformation in the manufacturing industry, we took a look around the trade fair to see which technologies are currently being offered to implement a "digital factory". And, interestingly, the motto of this year's Hannover Messe was "Integrated Industry – Connect & Collaborate", which indicates that the fair is more than a stage to put new products related to production technologies and industrial automation on display. So, what were the key trends we saw at the Hannover Messe this year?
Industrial IoT platforms
Industry-specific IoT platforms designed to support collaboration in dedicated manufacturing ecosystems are gaining traction. For instance, at the fair we saw a virtual marketplace for the paper industry ("merQbiz"), initiated by paper machine manufacturer Voith, as well as a platform for the wood industry (“tapio”), initiated by Homag. Such industry-specific platforms make it possible for all relevant partners to connect with one another, and it is mainly industry-specific software applications that run on these platforms to map B2B processes, such as the assignment of maintenance contracts to service providers or of transport orders to logistics service providers when ordering raw materials. Apart from supporting such industry-specific B2B processes, further common examples are, of course, apps that allow for remote monitoring of connected devices and predictive maintenance service offerings.
One of the buzzwords at the fair was clearly the "digital twin", with hardly any exhibitor not mentioning it. But what exactly does this term refer to? A digital twin describes the virtual model of a real object (e.g. a product, machine or manufacturing plant), and the idea is to have a virtual model that contains all the relevant data of a product. This can start with data from the area of product development and range to e.g. CAD data, engineering documentations or service instructions. It can also be enriched with production data to gain insights on how a product has been produced, with maintenance data or data from real-life operations to monitor the product's performance on the shop floor. Once all data of a physical product (e.g. from the areas of design, engineering, production, operations or maintenance) have been fully captured by the digital twin, it can function as THE basis for further product and process optimization, but – more importantly – for product and service innovations.
In contrast to the traditional subtractive manufacturing process, in an additive process, i.e. 3D printing, objects can be produced in such a way that both material usage and consumption can be minimized, as well as new geometries and functionalities (such as conformal cooling) implemented, which would not be possible with conventional construction and assembly methods. For example, new geometries and materials make it possible to produce parts that are more lightweight, which is particularly important in aircraft construction. In addition, 3D printing processes also enable decentralized production, which simultaneously also raises the question of security when exchanging 3D print files, however: How, for example, do you ensure that only the licensed number of 3D print files is printed on-site? Digital rights management (DRM) concepts will play an important role here, but also distributed ledger technologies (DLTs) such as blockchain. Use cases of how blockchain can be used in an additive manufacturing scenario were for example shown at the booth of the SAMPL initiative: It is coordinated by PLM provider ProStep and offers a solution that is based on a private Ethereum blockchain and can be used to enable transparent license management.
As 3D printing becomes increasingly important, the need for software solutions that support a design optimized for 3D printing will increase with it. With the so-called generative approach, products and components can be modeled to optimize products in terms of achieving minimum masses and integrating new functionalities (such as cooling channels close to the mold contour) into the design.
Artificial intelligence (AI)
The use of artificial intelligence in manufacturing is still a very young topic. The areas of application, however, are manifold. According to a recent PAC survey, manufacturing companies see AI's greatest benefit in the implementation of predictive maintenance concepts for their production facilities, followed by increased flexibility and automation support in manufacturing. For example, usage scenarios in which AI is used to perform production quality checks using visual camera systems as well as image recognition and analysis techniques were on show at the trade fair.
Something that was striking about the robots in action at the trade fair is that demonstrations behind metal grids are becoming increasingly rare. The reason for this is that robotic solutions today are increasingly collaborative and geared toward collaboration with people. Sensors are used to give robots this intelligence. These include sensors that respond to touch or force. "Smart" robots are also increasingly able to process visual information using camera systems and execute processes automatically. In order for robots to continue evolving into intelligent machines and be able to make decisions autonomously about the next process steps, however, solutions that enable sensor data to be evaluated directly at the site of operation are required. This is where so-called edge analytics solutions become important: using these, people no longer have to analyze the operating and machine data and trigger the next steps, rather this is done by IT systems with appropriate AI tools, IT infrastructures and data exchange standards, which enable real-time communication between the various machines and robots. The keywords here are time-sensitive networks (TSN) and OPC UA.
Augmented reality (AR) and virtual reality (VR)
Using technologies for the so-called augmented reality, the gap between the digital and real world can be closed. For example, warehouse employees or service personnel can view operating instructions and relevant product, job or maintenance data on mobile devices (e.g. tablets), which, as an additional layer of information over the real object, enhances workflow efficiency and increases quality. However, virtual reality technologies can also be used to provide training for future service assignments or test products and production environments virtually.
These trends are just a short excerpt of what I consider my personal highlights of the fair. There were, of course, many more, and you can rest assured that we will keep an eye on all the important trends. So, stay tuned for more reports to come – for a detailed analysis of the top trends in the manufacturing industry.
To read on, please have a look at our Expert Views on the Hannover Messe 2018 (subscription-based):
- Expert View: Hannover Messe 2018: What happens in the digital factory?
- Expert View: Hannover Messe 2018: What is behind this year's motto "Connect & Collaborate"?
- Expert View: What are the key trends around IoT platforms and IoT applications at the Hannover Messe 2018?