To achieve mass-market production of electric vehicles, production costs must be reduced. According to a study by Boston Consulting Group, roughly 35% of total vehicle costs relate to the battery pack. The battery cells themselves make up about 70% of the battery pack. But how can cell production costs be reduced? The same study provides an interesting answer: the application of next-generation digital technologies. Let’s have a look.
Tracking and tracing of processes
Digital technologies can help battery cell manufacturers improve their processes – and their bottom line – by achieving transparency in operational performance, for example, by providing deep insights into how processes are performing; why certain processes are not performing as desired; and how performance can be improved to achieve the necessary quality, efficiency, availability, and reliability targets. In this area, data analysis is a key instrument. The challenge in battery cell manufacturing (as in many other industries) is in bringing data analysis capabilities closer to the process in order to be able to obtain results in time – ideally, in real time – to correct deviations and prevent faults.
Bringing IT to the Industrial Edge
Conventional data processing on the field level is often costly and time-consuming, not very scalable, and not necessarily secure. In contrast, Siemens Industrial Edge brings typical IT standards such as central software management to the machine in a way that is industry compliant. With Industrial Edge, Siemens solutions are able to implement applications and solutions on the shopfloor that far exceed the functions of a traditional controller: Industrial Edge allows you to analyze all the data at the point of origin and preprocess them instantly. The optimized data points can then be transferred more quickly to the cloud, where, for example, you have access to more computing power and larger storage capacities. Among other things, this permits precise analysis of data over longer periods of time.
The solution at work
One application that benefits greatly from these data monitoring and control capabilities is predictive maintenance. Let me provide an example that can be applied to battery cell production. One critical process step is the cell stack formation, where the winding, coiling, and stacking processes rely on the precise control of web tension in the winder. Any deviations in drive performance – caused by interference, faults, or external factors – can result in quality defects in the battery cell. Every cell that is not expected to meet the final quality standards is rejected, resulting in loss of product, loss of (quite valuable) materials, and loss of production performance.
In a joint project with our Industrial Edge team, Siemens has developed a dedicated Industrial Edge App that can help detect and evaluate process anomalies and automatically locate the fault source in a production machine. To achieve this, Siemens uses signals and data readily available from the drive and automation systems that are related to the technological parameters of the production machine (e.g., web tension and synchronization accuracy). Specifically, we trace fast drive and process data in the SIMOTION motion control system, generate a frequency spectrum with fast Fourier transform analysis in the edge device (for example, an Edge-Enabled SIMATIC IPC), and then compare the actual data with archive data to identify deviations via advanced data analysis. This allows us to monitor the process condition without additional sensor hardware and not only identify the cause of a deviation but also assign quality characteristics to the product – predicting not only the process quality but also the product quality in one step.
A consistent case for consistency
With this technology, battery cell manufacturers can achieve improvements in two of the four factory-of-the-future use cases that the Boston Consulting Group cites as especially valuable for reducing costs. Predictive maintenance alone can reduce cell production costs by 7% to 10%, and smart inline quality control has an even larger impact: using big-data analytics to improve quality control during cell finishing can reduce cell production costs by up to 15%. With battery manufacturers all over the world ramping up their production capacities, production efficiency will prove vital in establishing market leadership – and digital solutions such as Industrial Edge computing can be a key factor in winning the race to the future of battery production.
Learn more about how to bring IT to the shopfloor: Industrial Edge