Vehicles with a potential defect should be identified in advance, before the failure actually occurs, in order to reduce or avoid warranty costs.
By combining measured value data, master data of the vehicle and diagnostic data, a prognosis model can be created that can reliably predict the occurrence of faults (predictive car maintenance).
With the help of the specialist department and other specialists, errors can be detected and identified in advance.
The forecasting model identifies 75% of the affected vehicles in advance. Testing costs and any extensive recall campaigns can be avoided. Warranty costs are reduced by over 50%. Customer satisfaction will be increased.
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