Predictive monitoring for the identification of faulty vehicle parts
Identification of potentially failure-prone parts along the production and logistics process up to the customer.
Identification of faulty supplier batches through a generic data model
Visualisation of the tracing of conspicuous supplier batches in QlikSense
Challenge
A car manufacturer wants to trace the identification of vehicle failures back to logistics. The whereabouts of potentially failure-prone parts from defective supplier batches are currently untraceable and pose a risk. To ensure quality, the affected parts are to be identified in logistics and at the customer.
Solution
A generic data model enables the linking of data sources along the production process. Traceability of the defective parts back to the supplier and visualisation of the process is made possible.
Result
With the QlikSense application, it is possible to locate the parts in logistics and at the customer. The generic data model enables the identification of different parts that have failed at the customer.
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Insurance Automative Logistics Energy Trade & E-Commerce
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