“The machine learning can spot anomalies that human operators might miss across millions of data points,” he added. “Manufacturers are using ML to anticipate shortages and how to handle those shortages in components more efficiently,” he added.Īdditionally, ML supports component quality inspections using data from camera inspections to check assembly processes and sequences in terms of complexity, speed and accuracy. The technology can also help manufacturers navigate current global component shortages. ![]() “ML not only handles the sheer scale, breadth and accuracy of the data, but also the timeliness.” “If you avoid unnecessary maintenance, you reduce costs, increase productivity, and do not have unplanned downtime,” he said. Automotive industry specialist Richard Felton explains that ML systems can help avoid unplanned maintenance by analysing data to improve predictive maintenance schedules. ![]() One area where ML is supporting car manufacturers is in reducing production line interruptions. Digital transformation is underpinning this as cloud-based technology such as artificial intelligence (AI) and machine learning (ML) play pivotal roles. ![]() Central to this is ensuring production processes remain as clean and efficient as possible while maintaining product quality and reducing wastage. Case Study: How Technology is Helping Automotive Manufacturers Achieve Sustainable GoalsĬar manufacturers face a range of challenges globally as they strive to move towards sustainable manufacturing. A digital transformation in car production is supporting manufacturers as they transit towards sustainable manufacturing.
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