In recent years, the globalization of automotive manufacturers and suppliers has steadily increased. This also has an impact on the test facilities. A lack in transparency of the availability of test resources frequently leads to time-consuming, cost-intensive allocation conflicts and poor capacity utilization. This is where the Peak Resource Planner takes effect. Continue reading “Test Planning: Utilization, productivity and efficiency of test facilities”
Big Data in the field of automotive testing is mainly about the analysis of huge amounts of data that result from a wide range of test benches and driving tests. The aim is to identify new patterns and correlations in these test data in order to describe a complex system of different components and to predict the future behavior of this system. In this way, e.g. it is possible to gain important insights for the development of new simulation models and to achieve considerable savings in the execution of cost-intensive tests. Among other things, the basis for this are tools for Data Mining, Predictive Analytics or Machine Learning, which are nowadays available in a large number on the market – in some cases even free of charge.
However, the use of these tools requires well-documented test data. Continue reading “Big Data in the field of automotive testing requires Test Data Governance”