As the world moves towards more sustainable energy solutions, the demand for batteries has skyrocketed. However, producing batteries is a cost-intensive endeavour, and meeting or even cutting the time-to-market plans are crucial for upcoming battery manufacturers. 

In this article and through a series of follow-up blog posts, we will examine the role that digitalisation plays in addressing and resolving challenges in the battery manufacturing industry, as well as promoting sustainable practices for the future.  

Leveraging Digitalisation in Battery Manufacturing 

Fortunately, digitalisation is an area where many new players can gain an advantage and it is an area where Elisa IndustrIQ has gathered lots of expertise in the past. Companies that have already applied digital solutions to their production processes know the advantages it brings – reduced costs and greater efficiency without compromising product quality. New players in the industry should look for partners who understand and have expertise in introducing digital tools from a technical and operational perspective. 

The battery market is highly competitive, and delays in product development can lead to missed opportunities and lost revenue. Therefore, it is crucial to adopt an efficient and agile approach to product development, leveraging the latest technologies and industry best practices.  

The Importance of Efficient Product Development for Battery Manufacturers 

The battery market is evolving rapidly, and manufacturers need to keep up with the latest trends and technologies to remain competitive. This requires an efficient product development process that can quickly transform innovative ideas into commercial products. However, manufacturers must also ensure that the product meets the highest standards for quality and safety, as batteries are critical components of many high-tech devices and systems. For companies entering the battery manufacturing industry, it is essential to focus on saving time and resources without compromising the product’s performance and quality.  

The ability to deliver high-quality batteries quickly and efficiently is critical to the success of battery manufacturers in the fast-paced and competitive battery market. By investing in research and development and leveraging advanced manufacturing software, battery manufacturers can streamline their product development process while ensuring that the final product meets or exceeds customer expectations.  

Our approach to streamlining product development and reducing time-to-market for batteries is to focus on minimising the number of unnecessary tests during the product development phase. This can be achieved by thoroughly documenting all engineering decisions and test results throughout the product development process. This results in a more and more powerful digital model of the production system that allows to simulate the system’s behaviour with regards to changes in parameters. Thus, development paths are identified where testing can be reduced or even eliminated, without compromising the quality or safety of the final product. Additionally, we can build a comprehensive model of the product and its performance characteristics, which can be used to simulate various operating conditions and identify potential issues before they occur.  

To support our approach of reducing unnecessary tests during product development, we have developed a software solution that provides an engineering-centric toolset. Our solution facilitates the documentation of the product development journey, from the initial concept stage to the final product testing and validation. It enables you to capture all engineering decisions and test results in a database, which can be easily accessed and shared among team members. 

By using our software, our customers can significantly reduce the number of experiments required during the product development process, thus helping to plan the time-to-market in a more resourceful way. This approach enables battery manufacturers to deliver high-quality products to market faster while costs and reducing the environmental impact of their activities. 

Furthermore, the platform allows for the generation of user-centric reports that can be customised according to the needs of the engineering team. These reports provide critical information about the product development process, including information about the testing and validation of the product, which can be used to optimise the process and ensure that the product meets or exceeds customer expectations.  

Ultimately, this enables battery manufacturers to bring innovative and sustainable battery solutions to market more quickly and efficiently, while maintaining a competitive edge in the industry. 

Capturing and Sharing Data in a Structured, Centralised Way

One of the key advantages of Xperidesk is that it allows battery manufacturing companies to capture and share data in a structured, centralised way. Unlike with typical spreadsheets, where data can be difficult to manage and analyse, Xperidesk provides a standardised framework for data collection and documentation. This ensures that data can easily be leveraged, not only by other users but also by other systems.  

By centralising data in this way, teams can build a powerful knowledge base that will have a tremendous impact on the learning and scaling journey of their organisation. 

The structured data captured by Xperidesk can be easily searched, filtered, and analysed using powerful data analytics and visualisation tools. This enables teams to quickly identify patterns, trends, and anomalies in their data, allowing them to make data-driven decisions and optimise their product development process. In addition, the platform provides a secure, auditable, and compliant data management environment, ensuring that data is traceable and can be used for regulatory compliance and quality assurance purposes. 

Streamlining Product Development to Reduce Time-to-Market  

Xperidesk enables battery manufacturing teams to build a thorough process understanding. The platform works closely with engineers to capture and document the detailed process knowledge that underpins battery manufacturing. By recording this knowledge in a structured way, teams can gain insights into the key drivers of process performance and identify areas where improvements can be made. 

One of the key benefits of this process understanding is that it can be used to initiate a virtual prototyping process. With virtual prototyping, teams can simulate and verify their processes digitally before applying them to a physical production system. This can be done using a variety of advanced modeling and simulation tools, which allow engineers to explore the impact of different process configurations and settings on product quality and performance. 

By using virtual prototyping, battery manufacturing engineering teams can identify potential process issues before they occur, reducing the risk of costly errors and rework. It also enables teams to optimise their processes for maximum efficiency and quality, resulting in higher yields, faster time-to-market, and lower costs. 

Design of Experiments: A Powerful Approach to Process Optimisation with Cornerstone 

Cornerstone is an advanced tool for modeling and optimising processes in battery manufacturing. It provides a comprehensive suite of tools for Design of Experiments (DOE), which is a powerful approach to process optimisation that enables teams to systematically explore and optimise their process variables. 

With Cornerstone, battery manufacturing engineering teams can define their process variables and their corresponding ranges, and then generate a set of experiments to explore the interactions between these variables. The results of these experiments are then used to build a mathematical model of the process, which can be used to optimise the process settings for maximum efficiency and quality. 

Using Cornerstone to Optimise Processes: A Data-Driven Approach 

The key advantage of Cornerstone is that it enables teams to optimise their processes using a data-driven approach. By systematically exploring the interactions between process variables, teams can identify the optimal process settings for maximum efficiency and quality. This approach can significantly reduce the time and cost involved in process optimisation, and can help to ensure that the resulting processes are highly efficient and effective. 

Cornerstone also provides a powerful statistical toolset that is tailored to the needs of engineers, enabling them to optimise their processes and improve product quality without being burdened with the details of statistics. Cornerstone provides a wide range of statistical tools and techniques, including Design of Experiments (DOE), Analysis of Variance (ANOVA), and Statistical Process Control (SPC), among others. These tools enable teams to collect, analyse, and interpret data from their manufacturing processes, and to make data-driven decisions that optimise their processes and improve product quality. 

Cornerstone’s Design of Experiments (DOE) functionality enables engineering teams to investigate process sensitivity and learn how noise in certain process variables will propagate to the responses of the same process. By running experiments in a controlled environment, engineers can identify the factors that have the greatest impact on process performance, and determine the optimal settings for those factors. 

Cornerstone uses a variety of statistical techniques, including factorial designs, response surface methodology, and optimisation algorithms, to help engineers identify the most important factors and optimise their processes. The software can handle both continuous and categorical variables, and can generate a variety of graphical outputs to help users understand the relationships between process variables and responses. 

Another benefit of using Cornerstone is that it can handle large amounts of data, making it suitable for working with Big Data infrastructures. The software is designed to easily and quickly detect correlations in the data, even when dealing with large datasets. This makes it an essential tool for engineering teams working in industries such as battery manufacturing, where data volume can be significant. 

Cornerstone’s ability to handle big data and identify correlations makes it an efficient and powerful tool for identifying process variables that affect product quality. By identifying these variables, engineers can optimise their processes and improve product quality, ultimately leading to higher customer satisfaction and increased profits. 

Furthermore, Cornerstone provides the flexibility to integrate with existing data sources and software tools, making it easy to incorporate into existing engineering workflows. This allows engineering teams to seamlessly integrate Cornerstone into their existing process design and optimisation activities, improving their overall efficiency and effectiveness. 

Ultimately, this enables battery manufacturers to bring innovative and sustainable battery solutions to market more quickly and efficiently, while maintaining a competitive edge in the industry. 

Reducing the Number of Experiments: Statistically Optimised Experiment Plans

Cornerstone helps in fast finding of a usable process model and root-cause analysis via exploratory and visual data analysis. This helps engineers identify which factors have the most significant impact on their process and quickly understand the relationship between input and output variables. By utilising various visualisations and graphs, engineers can see the effect of their changes in real-time and determine the optimal settings for their process.  

Additionally, Cornerstone helps in quickly identifying the root cause of any issues that may arise during the production process. By analysing the data collected, engineers can determine where the problem originated and take corrective actions to prevent it from happening in the future. This capability can significantly reduce downtime and production costs while improving product quality.  

By utilising Cornerstone’s statistically optimised experiment plans, engineers can reduce the number of experiments needed to achieve their desired results. This leads to a more efficient development process, as engineers can quickly identify the most critical process factors and focus their efforts on optimising them.  

Additionally, the software’s ability to perform quick and accurate root-cause analysis helps to prevent repeated experiments that may have been conducted due to incorrect assumptions. This reduction in the number of experiments needed to achieve the desired results significantly speeds up the overall development process, ultimately reducing time-to-market. Furthermore, Cornerstone’s ability to provide valuable insights into the data collected can help in the development of better and more reliable products.  

Learn to cut corners digitally  

Overall, the use of Cornerstone in the battery manufacturing industry can result in a more efficient, cost-effective, and optimised development process, ultimately leading to more sustainable operations. Our tools ensure that engineers spend their time efficiently, don’t repeat mistakes, and learn quickly and comprehensively. Once sufficient data is available it also allows to cut corners during the product development test, thus making the development process more efficient than any other software.