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Finding the market leading positions in a rapidly scaling battery industry means embracing smart manufacturing practices
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 datadriven 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
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