Meet Siemens Digital Industries Software’s senior Battery Industry director.
PLM and automation solutions play a decisive role in one of the world’s hottest areas right now: battery development and manufacturing. This industry is seeing such strong momentum that it isn’t expected to slow down any time this decade. Most important forecasts from analysts indicate that battery development and manufacturing is expected to grow eight to ten times by the end of the decade in 2030. This will take the industry from a currently predicted capacity in the mid-hundreds to low thousands of gigawatt-hours to up to 10,000 GWh or more. Out of this, the German Frauenhofer Institute calculates that by 2030, facilities in Europe will account for over 1,700 GWh.
A so-called gigafactory, which is often talked about in the context of battery manufacturing, costs big bucks to build. For example, the Northvolt One facility in Skellefteå, Sweden, will have a production capacity of 60 GWh when finished, and some estimates say the company raised billions of dollars to produce one facility. The commercial power required to build these factories is enormous, especially when investments around PLM and automation are needed to support product development.
Therefore, this is a particularly attractive PLM and automation market, where the big three of Siemens, Dassault Systèmes and PTC have developed various types of support.
It’s not surprising that Siemens Digital Industries Software—with one of the market’s most advanced seamless integration between PLM and automation solutions—has invested significant development money into this area, and reached a position as a market leader. But how did they get there? What does it take to build and scale up state-of-the-art battery production? How much does Siemens’ ability to offer seamless system connections between PLM and automation tools matter?
In today’s article, we discuss this with Puneet Sinha, senior director of Battery Industry at Siemens Digital Industries Software.
“It can take five to seven years or more for companies to go from announcing a gigafactory to stable production at scale,” says Sinha. “This long scale-up time is a major challenge in this rapidly changing market. With virtual development, digital twins and manufacturing, the conditions change dramatically in everything from speeding up design and construction to creating the layout of the facility with connected, multidisciplinary engineering, where above all the simulation pieces have a key role.”
A Brief Look at the Market Reveals Costly Adventures
However costly, the total PLM and automation investments in these projects are still a relatively limited share. The exact size of these investments are a trade secret, but an educated guess—based on list prices and expected customer discounts—is that the PLM and automation investments in Siemens Digital Industries’ PLM and Closed-Loop Manufacturing concepts in a gigafactory the size of Northvolt One’s (40 GWh) are in the range of $22 to $25 million.
Of this, the PLM parts are valued at $1 .9 million to $2.3 million, depending on the size and specific details of the layout. The automation pieces are normally valued at a factor of 10 relative to the PLM investments, which lands the automation investments in the range of $20 to $25 million dollars.
Ultimately, the production of lithium-ion batteries, which are primarily used in the automotive industry, involves a lot of money. This in turns underscores the necessity of establishing effective tools for scaling-up the battery production with digital, seamlessly connected tools that cover the entire value chain, according to Siemens’ Sinha.
This means that the benefits of creating reliable virtual versions of products, processes, production lines and facilities, with iterative deployments of production processes, are very large, argues Sinha. Furthermore, these ventures can be made without the costs and risks normally associated with producing equivalent facilities in the real world.
“Precisely,” he says. “Through simulation in the Siemens environments, and within the framework of the Siemens Xcelerator portfolio, engineers can easily account for multiple domains spanning chemistry, mechanical, electrical and software to accurately evaluate the impact of different chemistries on cell performance, cell safety and aging. They can also optimize the cell design to maximize energy density and fast charging. By leveraging Siemens digital twins, they can also virtually validate cell designs and behaviors against package and end-system requirements. This frees companies from costly and time-consuming testing methods.”
Strong Connections Between Product Development and Manufacturing Tools
That said, it’s important to note that the industry’s growth is driven by increasing demand for lithium-ion batteries, primarily for electrified transportation and energy storage. The high demand in the market and the trend of government support for these ventures in many countries create fierce competition between start-ups, joint ventures and established companies.
It takes a lot to win prominent market positions in this industry. Both new entrants and established suppliers face many of the same challenges in terms of how to reduce scale-up time, reduce the amount of scrap and maximize throughput while meeting the increasing objectives for cost, quality and sustainability. In short, traditional manufacturing methods cannot fulfill these ambitions, claims Sinha.
He believes that Siemens has a strong advantage when it comes to the connections between the product development and automation tools.
“Companies that want to scale up production cost-effectively and take a leading market position need is a digital framework for product development and manufacturing, where production’s digital twin is connected to real factory operations through automation technology and where industrial IoT (IIoT) is enabled,” he says. “This, in turn, enables digital design and optimization of the production line, and validation of production processes prior to implementation on the factory floor, reducing investment risk and shortening time to scale. Connecting the digital framework with automation hardware and software, as well as industrial IoT facilitates an overall integration of production.”
According to Sinha, this provides executable insights to improve production quality and enforces manufacturing best practices for scrap rate reduction and maximizing production throughput, while balancing process sustainability and profitability in the long term.
Simulation is of Primary Importance
Undoubtedly, the design and simulation areas are of primary importance. A connected workflow of Simcenter Battery Design Studio, Simcenter Amesim and STAR-CCM+ is a good example. The solution supports engineers in digital validation of Li-ion cell and pack designs thanks to detailed cell geometric specifications, electrical and thermal behavior simulation. Comprehensive components of a battery cell are available, as well as a materials database to support model development. In addition, Simcenter portfolio has several levels of performance models: a physics-based macro-homogeneous model to gain insights into the cell’s electrochemical mechanisms, and an equivalent RCR circuit model, which is an empirical approach to modeling the cell’s behavior in a highly computationally efficient way.
“Utilization of simulations, cell technology and optimization accelerate the development time radically,” Sinha says. He also points out that this confirms the importance of using digital twins.
He adds, “With Siemens simulations, engineers can accurately evaluate the impact of different chemistries on cell performance, cell safety and aging and can optimize cell design to maximize energy density and fast charging. They can virtually validate cell designs and behaviors against package and end-system requirements by leveraging Siemens digital twins. This frees companies from costly and time-consuming testing methods. We see two to three times acceleration in battery design and construction as companies pick up our digital twin framework. With a robust PLM backbone, the digital twins of product, production and factory remain connected, enabling companies to consider the interdependencies and impacts of change throughout the lifecycle.”
The Digital Twin is a Key Component
According to Sinha, the digital twin is a key component, particularly related to the rapid development of material chemistry, cell design and manufacturing techniques. In this context, he points to a customer example where, by establishing Siemens’ digital twin framework, they have been able to shorten the time it takes for battery cells to go from laboratory to large-scale production, while meeting sustainability goals and their own unique requirements.
Linking industrial IoT and automation technologies with manufacturing execution systems and a digital twin of the production facility is of fundamental importance in data-driven manufacturing, he claims.
Manufacturing Li-ion cells is a very complex process that involves around 600 process characteristics, such as various machine parameters.
“Given the amount of data and the complex interdependencies between different manufacturing steps in a typical cell production process, AI is needed to understand the interplay between the different steps and learn from the product [or] process partners,” says Sinha. “Typical use cases involve, but are not limited to, quality control of the production line, computer vision to measure viscosity and coating defects, but also predict the cell behavior during the formation and aging process. Battery-specific IT (information technology such as MES, cloud etc.) and OT (operation technologies such as PLCs, drives etc.) integration, data collection from machines and gigafactory in the context of production process and analytics are critical enablers for improving production quality and throughput.”
He also stresses that industrial IoT and data-driven operations enable companies to track energy consumption and optimize factory operations to reduce their carbon footprint.
Another value is that various forms of downtime in the factory can be reduced through predictive maintenance of the machinery, which improves the overall production throughput.
The Secret to Becoming a Market Winner
How do you become a winner in the rapidly growing battery industry?
Puneet Sinha’s short answer is: “Embrace smart design and manufacturing practices.” And to succeed in this, above all, it is necessary to make full use of connected digital tools.
“Exactly,” he says, “I usually say that you should move to the left in the traditional development sequence. Simulate and validate digitally before operations begin. Also, ensure single source of truth for cell, pack, machines and factory definitions and development with robust PLM backbone. It reduces the time to propagate technological changes and enables a resilient supply chain. With integrated hardware and software solutions, providing executive insights for end-to-end production, enabling scrap rate reduction and improved quality.”
One of the biggest challenges for large-scale production is high levels of waste. Here too, Sinha believes, the digital twin framework connected with automation technology and IOT can play an important role.
The background is that battery cell manufacturing involves various steps such as ink mixing, electrode coating, calendaring to formation and aging before cells go through quality check. Even minute errors in the various steps can lead to poor quality of cells. The rejected electrode rolls and cells lead to increased manufacturing cost, and lowered production throughput. The majority of cell manufacturing practices are built on many years of experience from a few companies, which is extremely tough to replicate in new companies who are just starting production. Even in the seasoned companies, it can be tough to translate with changes in battery materials. Therefore, companies often rely on trial-and-error methods to tweak their production, which is costly and inefficient.
“We have seen levels that were 40 percent or higher at the start of cell production, while in most cases it is just under 10 percent when the production capacity has reached full speed a few years after the start of production. It is important to bring these levels down, for the production costs to fall,” Sinha notes.
“In order to reduce waste levels and at the same time meet the quality targets for the manufacture of Li-ion cells, insights are required about execution on the factory floor. I believe that integrated hardware and software for the end-to-end production process is the key to improving cell production. It enables digital continuity from validated process plans to paperless production execution. Manufacturing execution software connected to automation hardware through a SCADA layer enables manufacturing teams to easily orchestrate large-scale production and enforce desired production practices. This is possible through the integration of IT and OT which enables tracking and machine integration to quickly identify and fix problems.”
The ambition of the battery industry is to cost-effectively scale production capacity 10x in the years up to 2030. “Making all of this sustainable and profitable in the long term requires companies to minimize energy consumption, limit the holistic carbon footprint, maintain visibility across production and predict problems before they happen,” concludes Sinha.
