Gigafactory of the future: Efficient innovation fueled by the digital core
Gigafactories give battery manufacturers the opportunity to transform how they operate, with a focus on efficiency, sustainability, and rapid growth. According to Capgemini research, 54 percent of automotive, battery, and energy executives in the US and Europe say their organization is currently building a gigafactory, or are planning to build one over the next five years. Government incentives are also making it easier for companies to continue to capitalize on the benefits of sustainable operations that gigafactories can provide.
Scalable gigafactory innovation focuses on connecting physical operations with data-driven insights and digital technologies to automate processes, provide 360-degree site awareness and boost efficiency – while lowering costs and reducing waste. A robust digital core can help companies build this factory of the future.
The digital core links sensors, machinery, engineering design, and operational platforms like enterprise resource planning (ERP), manufacturing execution systems (MES), manufacturing operations management (MOM), product lifecycle management (PLM), and advanced analytics to provide the foundation for efficient gigafactory operations. With a centralized system, companies can identify quality issues quickly, scale strategically, and further sustainability goals with better traceability.
Here's how organizations can integrate digital core into their gigafactory strategy, and what leaders need to consider when building the factory of the future.
Boost your gigafactory ramp-up with Siemens and Capgemini; Courtesy of Siemens
A well-designed digital core can help a gigafactory get up and running quickly, with real-time monitoring, automation, and data-driven decision making, once in operation. A robust digital core delivers the following benefits.
Seamless integration. Enabling well-integrated connections across and within the digital architecture and systems makes core a key value driver. That means a product can be designed digitally and then tested virtually in the exact gigafactory setup. Any problems can be identified, and then the design can simply be transferred into the manufacturing facility’s IT and OT systems.
Data-driven decision making across the value chain. The digital core supports analyzing high volumes of data from heterogenous systems to detect even small product and process deviations, to alert theorganization about issues. These insights can help companies quickly address potential problems and provide insight to design solutions. It can also mitigate supply risks by tracking supply availability, quality and origin, matching procurement to demand, and navigating supply fluctuations – while also ensuring compliance.
A digital thread. Data-driven decision making can only exist when digital continuity or a thread exists. All the collected real-time data from design, machine, and quality control can create a chain of causality that traces problems back to their origin and simulates alternative approaches. For example, if a battery fails the final quality check, it is possible to detect the specific problem – a worn out machine, an oversight in an early-stage material inspection, a slowing fan causing the temperature to rise – and quickly address it.
A foundation for digital twins and GenAI. Digital continuity and connected data threads provide the basis for digital twins, which can use this connected picture to simulate the entire battery lifecycle and enable sophisticated design and performance optimization, at lower costs. Custom GenAI applications, like digital assistants, can reduce the number of on-site technical experts and speed up response times.
A replicable and scalable setup. All these digital core features offer a blueprint that allows the efficient implementation of new technology. This blueprint can also transpose to other factories – streamlining future expansion.
Organizations can maximize the power of the digital core in two key ways: establishing a semantic integration layer and investing in hybrid architecture.
Semantic integration layer
A semantic integration layer is a centralized hub that standardizes and contextualizes data from the disparate systems around the gigafactory, allowing systems to exchange consistent data from a unique source of truth (the semantic layer). This layer provides users a 360-degree view of the gigafactory and a path to analytics and AI. This allows the organization to quickly find the information they need, build business intelligence tools, and generate insights. This integration layer is really two parts – a top layer that sets organization-wide standards and a bottom layer designed around the specific needs and use cases of that factory.
The key to building a semantic integration layer is setting up ontologies. Ontologies describe the relationships between objects, rather than just mapping the data itself. This allows different data sources to be meaningfully combined. Ontologies encode different data “languages” into a standardized set of rules, so they can be searched and understood by a variety of users. This process supports the understanding of the gigafactory, high-value simulation and automation, and more reliable decision making.
Hybrid architecture
Hybrid architecture integrates on-premises and cloud for storage and processing. Cloud appears as the clear preferred choice; in fact, on-premises (or edge) is considered a new domain by the cloud in a continuum of architecture, data, and security. Combining them is the best way to optimize performance and scalability.
Cloud is the place to build and host software programs, reusable applications that will be deployed or shared between multiple sites, or systems that will need to scale over time. The major cloud suites all come with powerful analytics tools that can optimize gigafactory operations. However, cloud can sometimes be slow and expensive, particularly when sending off high volumes of data for analysis.
On-premises processing is better for applications like fault detection, which need real-time responses for data security, or for when scalability is not the major challenge.
It is never as simple as choosing one or the other. This must be a carefully planned approach to understand and take advantage of disruptive business opportunities in the short-term, with the ability to scale for growth over time.
A key part of the digital core is the management software. Engineers use Product Lifecycle Management (PLM) software to design and specify products. These designs are then handed over to the gigafactory, which uses Manufacturing Execution System (MES) software to ensure it is produced to specification. Operational data are also sent back to engineering for scenario optimization and product or process optimization.
Think of it like a chef developing a new recipe.
Engineers want to come up with a unique take on a battery design that is best suited to the cost and efficiency needs of their customers, and the available materials.
Once a mechanical or chemical optimization is ready, they codify the “recipe” for producing that battery into the PLM – listing the ingredients (such as electrode and electrolyte material), precise quantities, the order in which they should be combined, and the conditions (pressure, temperature, etc).
Of course, producing a battery at scale has more constraints than making it on the lab bench. But, thanks to a joined up digital core which has a digital map of the factory and its machinery, the PLM can simulate how that recipe would play out using the actual data and conditions of the gigafactory shop floor. This what-if analysis can optimize the design, or propose efficiency changes to the factory layout, material flow, quality checks, etc.
Once the recipe is codified, it is transferred through the digital core and to the MES. The MES will then translate that list of instructions into the physical outputs that make the battery, whether that’s controlling machines or providing instructions to humans.
And, when manufacturing starts, data from the process and the product are collected via the semantic layer and analyzed in real-time. When errors occur, the MES pushes back the contextualized information to the PLM through the digital continuity layer for product/process optimization.
The digital core is the gigafactory’s most important lever for optimizing end-to-end business process efficiency, and therefore time, cost, and throughput. Setting it up correctly is, thus, the prerequisite for both short and long-term success. Today, digital core is the foundation that distinguishes the new generation of gigafactories from past battery producers.
Adopt an iterative approach to the design of your semantic integration layer, hybrid architecture, and ontology. For example, don’t spend years building the perfect ontology, but rather pick a few transformational use cases in a priority domain (e.g. quality control). Build ontologies around that domain, and then gradually work outwards to deliver real value.
Leverage quick wins – based on the problems users describe – in order to get user buy-in. Remember, users involved in day-to-day operations often struggle to see the bigger picture, so keep focused on long-term transformation and don’t become obsessed with troubleshooting.
Prioritize paradigm shifts to seize and apply digital core’s full potential, as digital applications will change an established business process to deliver a major benefit. For example, batteries must undergo three weeks of aging after production before they can be certified; if we can spot which ones will fail at the start of this process, we can dispose of them early, saving a lot of time and space in the short term, and giving us data to help improve failure rates in the long term.
Establishing a digital core is challenging because it requires substantial effort to ensure that subsystems can talk to each other, and to the semantic layer. That means modeling standard business objects to facilitate systems integration from OT to IT, and across domains.
Having the right people – those with hard-won expertise of setting up similar systems, and well-versed in the intricacies and dependencies of data management, usage, and drawing inferences – can help bring this vision of the gigafactory of the future to life.
Capgemini presented a variety of topics on battery manufacturing at Hannover Messe 2024, please see links below to these insightful sessions:
Capgemini recently published a study with leading academia and industry experts to explore accelerating battery cell development and engineering. To learn more, click here.
