The filigree silhouette and the nippiness of e-scooters bring with them a certain level of risk, especially when they travel in parallel to the nearside of trucks and the latter have to turn off in that direction. In such cases, the Sideguard Assist from Mercedes-Benz, as can be found in the latest Actros, can help defuse such critical situations.
The system has the ability to detect moving or stationary objects in the monitoring zone along the nearside of the truck. Those objects may include pedestrians, cyclists, road signs or even e-scooters. In such a case, the driver will initially be informed of their presence using visual means. To this end, the MirrorCam display on the co-driver's side will show a yellow triangular warning symbol. If there is a risk of collision, the display then flashes red repeatedly and after two seconds, it lights up red permanently. In addition to this, a warning tone sounds on the co-driver's side at the same time.
Sideguard Assist from Mercedes-Benz Trucks is the only assistance system of this kind available on the truck market to be fully integrated into the vehicle architecture and is available ex factory for numerous model variants of the Actros and Arocs. It works for both rigid vehicles and entire vehicle combinations up to 18.75 m in length.
Proof that a system such as Sideguard Assist from Mercedes-Benz Trucks can reduce the number of serious accidents involving personal injury during nearside manoeuvres can be seen in an analysis of accidents between trucks and cyclists carried out by accident researchers from the "Gesamtverband der Deutschen Versicherungswirtschaft e. V." insurers' institute. The insurers suppose that such a system could prevent around half of all accidents involving trucks and cyclists. The number of related fatalities can be ideally reduced by nearly a third, and the number of serious injuries by more than 40%.
These innovations will help deliver a new generation of electrified and intelligent automobiles that embody the company’s Nissan Intelligent Mobility vision, while also making production operations more flexible, efficient and sustainable. Following an initial investment of about JPY33 billion ($300.3 million) at the company’s Tochigi Plant in Japan, with work to finish in 2020, the technologies will be rolled out across factories globally.
Since 1933, Nissan has honed its ability to mass-produce vehicles to the highest possible standards. Over the same period, the company’s takumi master technicians have perfected a range of complex or delicate processes requiring a high degree of craftsmanship.
This latest investment represents a necessary rethinking of conventional carmaking and tackles the structural and technical challenges of producing vehicles that will lead the industry in a new era of electrification and intelligence.
“We’re facing an unprecedented evolution in the capabilities of our vehicles,” said Hideyuki Sakamoto, Nissan’s executive vice president for manufacturing and supply chain management. “Our job is to make this evolution a reality by rethinking how we build cars. This will also mean shifting the efforts of our expert technicians from techniques they’ve already mastered to new, unexplored areas.”
Nissan’s next generation of cars will be electrified, intelligent and connected. This adds new complexity to design and construction, requiring major advancements in production engineering. One such advancement is the “universal powertrain mounting system” developed by Nissan’s Production Engineering Research and Development Centre.
Mounting powertrains in cars is a lengthy process and strenuous work for assembly line staff, who must install multiple components in sequence. Nissan’s new system uses an automated pallet to mount the entire powertrain at once. The system measures the car’s dimensions in real time during mounting, and the pallet makes micro-adjustments accordingly. This ensures that powertrains are installed to within a small fraction of a millimeter’s accuracy.
The new system is also highly adaptable. The same pallet can mount three types of powertrains (internal combustion engine, e-POWER and pure electric), and can assemble and mount 27 different powertrain module combinations.
Nissan has developed certain specialist skills and processes that, until now, could only be performed by trained craftspeople. Through an intensive collaborative process, Nissan’s craftspeople and engineers have digitised parts of these delicate processes and “trained” robots to perform them around the clock. This will allow the craftspeople to focus on new, unexplored areas of expertise.
One example of a task that can now be automated is sealing – applying a paste-like material to seams around the vehicle body to prevent water intrusion.
Sealing is generally done by experts, as the necessary dexterity and speed can be acquired through training but isn’t easy to replicate. In addition to automating the process of applying sealant, Nissan’s engineers analysed the precise movements and gestures of trained workers when smoothing and finishing sealant, and calculated the pressure applied at each stage. Next, they converted this information to instructions for robots and made further refinements through extensive trial and error.
As a result, robots can now apply and finish sealant quickly and precisely along even the most complex of seams.
Robots can now perform certain strenuous tasks efficiently, freeing workers to perform more valuable jobs elsewhere on the line. This also improves ergonomics, making factories easier places to work. One example is the installation of a headliner, the overhead layer of material on the inside of a car’s roof.
Workers must enter each vehicle’s cabin to perform this physically demanding job. The task has become even harder as cars come with more connected features, adding to the number of devices in and around the headliners.
Nissan’s solution is to use robots to insert the headliner through the front of the vehicle and then fasten it. Sensors monitor changes in pressure and use a proprietary logic system to determine when the clips have snapped securely into place.
Nissan is also working to reduce the environmental impact of building cars. Changes in the painting process are especially noticeable. Car bodies must usually be painted at high temperatures, because the viscosity of paint is hard to control at lower temperatures. By contrast, bumpers are made of plastic, so they need to be painted at low temperatures. This requires two separate painting processes for one vehicle.
Nissan has developed a water-based paint that maintains the right viscosity at low temperatures, so that bodies and bumpers can be painted together. This will cut carbon dioxide emissions from the process by 25%. Nissan will also use a water-free painting booth that makes it possible to collect all waste paint and reuse it in other production processes.
“These new technologies and innovations are at the heart of the company’s competitiveness,” said Sakamoto. “They will be rolled out globally in the coming years, underpinning the future of Nissan Intelligent Mobility and reinforcing our status as a leader in technology.”
The data collected through “Tyre Leap AI Analysis” will support engineers to create longer lasting tyres with more consistent performance over time and is a key element of SRI’s “SMART TYRE CONCEPT”.
Tyres are typically produced from a range of materials, such as rubber (both natural and synthetic), reinforcing filling substances (e.g. silica and soot), as well as various chemicals and additives. Its properties are derived from the complex interaction between these materials. As these properties evolves with mechanical load, understanding the effects between the elements on tyre life was until now, extremely difficult.
In a bid to gain a better understanding, Tyre Leap AI Analysis, using artificial intelligence, was developed by SRI in collaboration with Prof Kimi Haseyama from Hokkaido University in Sapporo. Real-world data along with advanced image processing, such as electron microscopy, are used to analyse the internal structure.
By comparing images of old and new tyres, Tyre Leap AI Analysis can with high levels of accuracy, predict how changes to materials and structure will change performance. The new technology thus has the huge potential for forecasting tyre properties through its lifespan and far exceeds human capabilities to predict the changes and guide the development of future products.
According to SRI’s engineers, creating a tyre that delivers a more consistent level of performance over its lifespan would not only offer a safety benefit but could extend the tyre’s service life.
Teneo will be used by a central team within Scania to create highly intelligent conversational interfaces throughout the entire organisation. Strong collaboration features within Teneo that support enterprise wide development will allow Scania's developers and business users alike to build advanced chatbot applications in multiple languages for a wide range of internal and external uses.
"Conversational AI is changing how people interact with technology by making it faster, easier and more efficient to complete even the most complex of tasks," said Jacob Pantzerhielm, Manager New Technology at Scania. "We chose to work with Artificial Solutions because of the humanlike conversational experience Teneo delivers, alongside excellent scaling and integration abilities."
Part of the Traton Group, a wholly owned subsidiary of the Volkswagen Group, Scania is a world-leading provider of transport solutions, including trucks and buses for heavy transport applications combined with an extensive product-related service offering.
Teneo is Artificial Solutions award-wining conversational AI application development platform. It enables enterprises to build highly conversational applications in more than 35 languages running over any device, service or operating system. Real-time data analytics allows organisations to increase personalisation, automatically maintain the conversational system, and deliver actionable insight back to the business, while enabling compliance with privacy regulations such as GDPR.
"We welcome the opportunity to work with Scania and are excited about the projects they have planned," says Stuart Glyde, Sales Director Nordics at Artificial Solutions. "As conversational AI expands its role within enterprises so the need for integration into a wide spectrum of other technology such as robotic process automation increases. This in turn places more emphasis on being able to re-use conversational AI resources in order to maximise value, something Teneo enables with ease."
Qualcomm Technologies is providing the 5G test network and 5G industrial test devices that run on its foundational 5G technologies, and Siemens is supplying industrial end-devices like automated guided vehicles (AGV).
The 5G private standalone network proof-of-concept at the Siemens Automotive Test Center enables Siemens and Qualcomm Technologies to test technologies, solve problems, and come up with solutions for the future of private wireless applications in industrial settings. Qualcomm Technologies set up 5G industrial test devices along with a 5G standalone test network that includes a 5G core network and 5G base station with remote radio head. Siemens provided the actual industrial setup including Simatic control systems and IO devices.
“We are excited to announce our 5G private network proof-of-concept collaboration project with Siemens. This project will provide invaluable real-world learnings that both companies can apply to future deployments and marks an important key milestone as 5G moves into industrial automation,” said Enrico Salvatori, Senior Vice President, Qualcomm Europe, Inc. & President, Qualcomm Europe/MEA. “Combining our 5G connectivity capabilities with Siemens’ deep industry know-how will help us deploy technologies, refine solutions, and work to make the smart industrial future a reality.”
“Industrial 5G is the gateway to an all-encompassing, wireless network for production, maintenance, and logistics. High data rates, ultra-reliable transmission, and extremely low latencies will allow significant increases in efficiency and flexibility in industrial added value,” said Eckard Eberle, CEO of Process Automation at Siemens. “We are therefore extremely pleased to have this collaboration with Qualcomm Technologies so that we can drive forward the development and technical implementation of private 5G networks in the industrial sector. Our decades of experience in industrial communication and our industry expertise combined with Qualcomm Technologies’ know-how are paving the way for wireless networks in the factory of the future.”
In the course of this joint research effort at the Siemens Automotive Test Center, currently available industrial technologies such as OPC UA and Profinet will be tested and evaluated - technologies that require a 5G private network in order to work. In Germany, private networks can use the local broadband spectrum from 3.7-3.8 GHz, which has been reserved for industrial usage in local deployments.
These private networks allow industrial sites to control and manage their own networks as they see fit, allowing for high reliability, low latency, and the ability to reconfigure the network to suit changing needs while at the same time keeping data onsite for added security.
Qualcomm Technologies and Siemens have a longstanding technical collaboration focused on cooperation in wireless technologies. This has resulted in over 15 years of success and the development of Siemens’ unique Scalance portfolio of industrial wireless products.
With Qualcomm Technologies’ leading expertise in 5G technologies, this collaboration continues to evolve —leading into the first 5G private standalone network in an industrial environment using the 3.7-3.8GHz band. This allows solutions to be tested and developed which the industry will be able to use with the upcoming Release 16 of the 5G standard.