Capgemini
Canvas Category Consultancy : Company : Information Technology
Capgemini partners with companies to transform and manage their business by unlocking the value of technology. As a leading strategic partner to companies around the world, we have leveraged technology to enable business transformation for more than 50 years. We address the entire breadth of business needs, from strategy and design to managing operations. To do this, we draw on deep industry expertise and a command of the fast-evolving fields of cloud, data artificial intelligence, connectivity, software, digital engineering, and platforms.
Assembly Line
Mixed-Model Lines Enable Multiple Power Train Configurations
Mixed-model automotive assembly plants must have the workstations, tools and components necessary to efficiently build hybrids in the same facility as electric and internal combustion engine (ICE) vehicles. However, assembling cars with different power trains is much harder than making multiple types of pens, syringes or toothbrushes on the same assembly line. Mixed-model assembly lines typically also need to be laid out differently than lines that only produce one type of vehicle.
“Mixed-model assembly is used regularly across industries, most notably the discrete electronics industry where products such as smart phones with multiple form factors and internal configurations are manufactured,” notes Khalid Sebti, executive vice president and managing director of Capgemini Engineering. “Use in the auto industry is different, but not necessarily more complex, due to designs shifting to multi-use platforms to accommodate different power train options.
One complex problem that Porsche had to solve involved fastening. The marriage of a gas or hybrid vehicle requires the underbody and chassis to be screwed together in 20 places. However, in the all-electric variant, there are 50 joints that need to be tightened. Porsche engineers developed an automatic screw loading system that, depending on the product line and fittings, can handle any screw size and shape, torque and angle at high speeds. A measuring device regularly passes along the assembly line to check the screw spindles during ongoing production operations. As a result, there are virtually no idle times or delays.
ABB co-launches interoperability initiative to unlock Industrial IoT insights for more efficient and sustainable industry
At the Hannover Messe on April 23, 2024, founding members ABB (including B&R), Capgemini, Microsoft, Rockwell Automation, Schneider Electric (including AVEVA) and Siemens announced collaboration on a new initiative to deliver interoperability for Industrial IoT ecosystems.
Hosted by the Linux Foundation and open to further interested parties, the Margo initiative draws its name from the Latin word for ‘edge’ and will define mechanisms for interoperability between applications, devices and orchestration software at the edge1 of industrial ecosystems. In particular, Margo will make it easy to run and combine applications from any ecosystem member on top of the hardware and runtime system of any other member. Margo aims to deliver on its interoperability promise through a modern and agile open-source approach, which will bring industrial companies increased flexibility, simplicity and scalability as they undergo digital transition in complex, multi-vendor environments.
The Connected Ecosystem in Life Sciences
Why Manufacturing Facilities need Software Defined Networks
Software Defined Networking, or SDN, involves digitizing all moving parts of the network, so the entire thing can be joined up and controlled through a single user interface. Changes and updates can be made consistently across the network, at the push of a button. With SDN, the entire factory and its IIoT (Industrial IoT) network can be dynamically managed and configured using a single SDN controller, handling all the elements that make a network work and adapting without users even noticing: network monitoring, packet forwarding, networking devices status checks, load balancing, queue management, scheduling and quality of experience (QoE) awareness. SDNs also have far fewer problems than networks made of physical switches and gateways, reducing time spent on troubleshooting and reconfiguring. That creates a network that is flexible, scalable, efficient, secure, and resilient.
Capgemini to acquire Unity’s Digital Twin Professional Services arm to accelerate enterprises’ digital transformation through real-time 3D technology
Capgemini and Unity (NYSE: U), the world’s leading platform for creating and growing real-time 3D (RT3D) content, announced an expansion of their strategic alliance that will see Capgemini take on Unity’s Digital Twin Professional Services arm. Per the agreement, Unity’s Digital Twin Professional Services team will join and embed within Capgemini, forming one of the largest pools of Unity enterprise developers in the world. The transaction will accelerate the iteration and implementation of the market leading real-time 3D (RT3D) visualization software for the industrial application of digital twins. It will allow end users to envision, understand, and interact with physical systems – a key enabler for intelligent industry. The deal is expected to close in the second quarter of 2024.
Gigafactories: Accelerate the battery manufacturing industry with Siemens and Capgemini
🏭 Dark factories, bright future?
An automatic (or ‘dark’) factory can be defined as ‘a place where raw materials enter, and finished products leave with little or no human intervention’. One of the earliest descriptions of the automatic factory in fiction was Philip K. Dick’s 1955 short story ’Autofac’, a dystopian and darkly comic scenario in which entirely automated factories threaten to use up the planet’s resources, by continuing to produce things that people don’t need.
Dark factories are a part of the global digital transformation and move to the Industrial Internet of Things (IIoT), which is being driven by increasingly capable robotics and automation, AI and 5G connectivity. In this article, we’ll discuss the benefits, challenges, and how companies can move forward with this concept.
It’s also important to consider that fully automated factories have been tried previously, with varying degrees of success. There are a few cautionary tales; IBM tried its own in the 1980s, but closed it because it wasn’t able to respond to changing market needs. Apple also built such a plant in the 1980s, but closed it in the early 90s – likely because the plant was unable to deal with increasingly smaller components. More recently, Tesla walked back some of the automation at its Fremont CA facility, when machines failed to meet its ambitious manufacturing targets. This shows us the importance of flexibility and forward planning.
Transforming industrial crane system automation at Schneider Electric with 5G
Boehringer Ingelheim: Healthy data creates a better world
On the way to the industrial Metaverse
A recent Capgemini Research Institute report explored this potential in more depth; Total Immersion; How immersive experiences and the metaverse benefit customer experience and operations, found that 77% of consumers expect immersive experiences to impact how they interact with people, brands and services, but also that organizations recognize the broad opportunities it presents to drive value across the business, specifically in their internal operations.
As opposed to the static spaces of the consumer metaverse, the dynamic spaces of the industrial metaverse are complex and layered. This ever-evolving reality involves interactions on a deeper, more collaborative level. We suggest the dynamic experiences of the industrial metaverse are best exemplified by the next generation of digital twin technology.
Capgemini and Microsoft collaborate to offer Digital Twin Solutions
Capgemini today announced that it is collaborating with Microsoft to deliver a first-of-its kind, cloud-native, serverless Azure-based digital twin platform, called ReflectIoD. This secure, highly scalable platform will leverage best-in-class architecture and technological components from the Azure suite to help transform an organization’s operations and maintenance efficiency, enabling intelligent industry and driving sustainable business value. It will also enable enterprises to meet the ever-growing needs of standardized brownfields management[1] throughout their life cycle and across ecosystems.
The Growing Need for Private 5G Networks in Manufacturing Plants
Traditionally, data generated from wired & Wi-Fi-based instrumentation devices installed in manufacturing plants are processed either on the local premises or in the public cloud to control the behavior of these devices. Typically, these devices require highly reliable connectivity for quick communications, a latency of less than 1ms, secure data management and data storage, proper traffic isolation between different critical applications running in the factory, and guaranteed QoS for day-to-day operations managed over the private network.
With potentially hundreds of thousands of critical sensors and control systems used in larger factory environments, 5G private network implementations are increasingly finding a way. 5G networks will be powered by massive, distributed computing, located closer to sensors and machines, and capable of applying artificial intelligence and machine/deep learning algorithms to handle huge amounts of industrial and critical data within the factory environment. A 5G factory has a private network design with its own 5G network built in, where 5G devices, RAN, and core are integrated into a complete ecosystem from end-to-end. A private 5G network does not interface with or leverage resources and functionalities from the public 5G MNO network. However, a private 5G frequency is used when a factory creates its own private 5G network, whereas an MNO’s publicly licensed frequency can be used if the MNO builds a private 5G network for a factory. MNOs’ public 5G networks can be used as backup to an existing private 5G network, enabling it to connect all the manufacturing equipment and devices installed in a factory environment to a public 5G network if the private 5G network fails for any reason.