Enabling ambitious battery production at scale. By Puneet Sinha 

The battery industry is forecast to grow tenfold by the end of the decade. This growth is driven by increasing demand for lithium-ion cell batteries, predominantly for electrified transportation and energy storage. The high market demand and increasingly supportive governmental policies from many countries make for fierce competition between start-ups, joint ventures, and incumbents to determine the market leaders. New entrants and established suppliers face many of the same challenges of how to shrink scale-up time, reduce scrap rates, and maximize throughput while still meeting cost, quality, and sustainability targets. Traditional manufacturing practices cannot deliver on these ambitions.
Rather, businesses seeking to scale up their battery production cost-effectively, and take a leading market position, need a digital enterprise framework for manufacturing where the digital twin of production is connected to real factory operations through automation technologies and industrial IoT (IIoT) enabled devices. This enables virtual design and optimization of production line and validation of production processes before implementation on the factory floor, thereby de-risking investment and shortening the time to scale. Connecting the digital framework with automation hardware and software, and Industrial IoT facilitates an end-to-end integration of production. This delivers executional insights to large scale production and a data-driven framework to continuously improve production throughput while balancing process sustainability and profitability in the long-term.
Scaling faster with virtual development

Puneet Sinha
Examples from the last few years have shown that it can take seven years or more for companies to go from gigafactory announcements to achieving stable production at scale. This long time to scale up production is a big challenge in this rapidly changing battery market. The goal of virtual development of manufacturing is to accelerate the design, construction, and layout of your plant with connected, multi-disciplinary engineering. From there businesses can create a reliable virtual version of their processes, lines, and plants to commission production processes iteratively without the cost and risk of doing so in the real world. Additionally, leveraging simulations, cell engineering and optimization can be accelerated tremendously. With Siemens simulations, engineers can accurately evaluate impact of various chemistries on cell performance, cell safety and aging as well as can optimize cell design to maximize energy density and fast charging. They can virtually validate cell designs and behaviors against pack requirements and end system requirements leveraging Siemens digital twins. This unshackles companies from a costly and time-consuming testing only approach. We are seeing two-to-three times acceleration in battery design and engineering, as companies are adopting our digital twin framework. With a robust PLM backbone, the digital twins of product, production and factory remain connected, thus allowing companies to account for interdependencies and effects of change across the full lifecycle.
A digital twin of battery product and production is becoming a key need for the battery industry given the rapid evolution of material chemistries, cell design as well as manufacturing techniques. Capturing a leadership position in a shifting industry necessitates agility and those changes need to be verified rapidly to retain optimal energy and raw material usage.
One of our customers is leveraging the Siemens digital twin framework to accelerate cell engineering and optimization and virtually commission production lines for full scale manufacturing scaling from laboratory production processes. Adopting this framework has allowed them to shorten the time it takes for battery cells to go from laboratory to production at scale while also meeting sustainability goals and their own unique requirements.
Large scale production problems require integrated solutions
One of the biggest challenges for large scale production is very high scrap rate. We have seen scrap rate being 40 percent or higher at start of cell production while in most cases staying just below ten percent when the full-speed production capacity is achieved a few years after start of production. These levels are key bottlenecks in getting production cost reduced. To reduce scrap rate while meeting quality targets for Li-ion cell manufacturing, you need executional insights on the factory floor. Integrated hardware and software for end-to-end production process is key to improve cell production. It enables digital continuity from virtually validated process plans to paperless production execution. Manufacturing execution software connected with automation hardware through a SCADA layer allows manufacturing teams to easily orchestrate large scale production and enforce desired production practices. This is possible through integration of IT and OT which enables tracing, tracking, and machine integration to rapidly identify and mitigate issues.
The ease of data sharing within a plant and the supplier network also enables efficient scheduling at a much greater scale than possible before. Businesses can create more effective intra-plant logistics and secure supply chains to ensure the provenance of materials or the associated environmental impacts of each stage in manufacturing. A more connected manufacturing process reduces complexity while increasing the flexibility by standardizing vertically and horizontally. This has been invaluable to another one of our customers with the ambition to become a European leader of EV battery cells and modules.
Intelligent production excellence for maximizing throughput and sustainable manufacturing
Li-ion cell production consists of various manufacturing steps, each one of them having a varying degree of associated time, energy and capital attached to them. Some of these steps, for instance cell formation and aging, can take ten or more days, creating significant bottlenecks, affecting production throughput. Manufacturing steps such as electrode drying, or ink mixing needs to be optimized to reduce energy consumption without affecting quality. Additionally, cell production is a very energy intensive process that can consume up to 40 units of energy to produce one unit of battery energy. This puts pressure on companies to optimize the energy consumption of their plants to minimize their carbon footprint. To address such issues, battery manufacturers can improve usage of data from machines and factories, which in traditional battery production setup isn’t utilized well, to bring needed intelligence to battery production and factory operation.
Connection of Industrial IoT and automation technologies with manufacturing execution systems and digital twins of production holds the key to data-driven manufacturing. Li-ion cell manufacturing is a highly complex process that involves approximately. 600 process characteristics such as various machine parameters. Given the amount of data and the complicated interdependence of various manufacturing steps in a typical cell production process, AI is needed to understand the intercorrelation between the different steps and to learn from the product/process partners. Typical use cases involve, but are not limited to, inline quality control, computer vision to measure the slurry viscosity, coating defects and also prediction of the cell behavior during the aging process. Data platforms with standardized data models are critical to bringing IT and OT together and enabling seamless data harvesting from machines and factories.
Additionally, Industrial IoT and data-driven operation allow companies to track energy consumption and optimize factory operation to reduce their carbon footprint. Downtime during factory operation can also be reduced through predictive maintenance of the machinery, hence improve overall production throughput.
Winning the race
Finding the market leading positions in a rapidly scaling battery industry means embracing smart manufacturing practices. It means shifting left to simulate and validate before operations begin, reducing the time to propagate engineering changes, and enabling a resilient supply chain. With integrated hardware and software solutions bringing executional insights for end-to-end production enables reduction in scrap rate and improvement in quality. Manufacturing cost amounts to approximately 25 percent of cell cost, achieving faster scrap rate reduction, and improving quality and production throughput are central for the battery industry’s ambition to scale production capacity ten times more cost-effectively in the coming years. Doing all of this sustainably and profitably in the long-term requires businesses to minimize energy consumption, limit the holistic carbon footprint, maintain visibility across all of production, and predict problems before they happen.
Digitalization can be a daunting endeavor, but Siemens’ expertise in manufacturing along with our rapidly growing investment in batteries is available to any customer looking to leap into the future of production. We bring competency across both hardware and software, and many of the associated technologies our customers rely on every day. ■
Puneet Sinha
Puneet Sinha is Senior Director of the Battery Industry for Siemens Digital Industries Software. In this role, he heads company strategy and cross-functional growth focus for batteries. Sinha has 15 years of industrial experience in battery and electric vehicles’ go-to market strategy and product development, alongside taking pre-venue start-ups to successful exit.