Big Data in the field of automotive testing requires Test Data Governance

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”

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Peak Solution at Automotive Testing Expo Stuttgart 2017

Cross-site utilization of test resources, integrated test request and order processes, global access to test data and big (test) data solutions: These are the topics that are the focus of Peak Solution at Automotive Testing Expo Europe 2017 in Stuttgart (20th to 22nd of June). Continue reading “Peak Solution at Automotive Testing Expo Stuttgart 2017”

Peak Solution and PSA Group collaborate for Big Data Solution

Peak Solution and PSA Groupe have agreed to collaborate on a ‘Big Data’ project. The aim is to develop a flexible and scalable solution to systematically manage and analyze the huge amount of data that results from car testing. The two partners will also incorporate into the project recommendations and results from the ASAM-BigODS Work Group.

Continue reading “Peak Solution and PSA Group collaborate for Big Data Solution”

ASAM ODS goes Big Data

The ASAM e.V. is currently working on a project that prepares the expansion of ASAM ODS to Big Data. Phase 1 of the project was finished successfully last year with a collection of use-cases, features and non-functional requirements of end users for processing large amounts of data throughout the automotive development process. Now, ASAM Technical Steering Committee (TSC) has approved phase 2 of the project.

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What do test engineers expect from Big Data?

Car manufacturers and suppliers facing the challenge to handle a growing amount of data coming from various sources such as test stands, test automation systems and field test equipment in an efficient manner. At the same time, they want to link development and test data with information on vehicle use. The goal is clear: Due to the increasing complexity of vehicles, the engineers must get a holistic, cross-domain understanding of the interaction and behavior of individual car components and performance parameters in the context of different environmental situations. In doing so, they want to make use of existing experience and knowledge in the company or even in the industry. Therefore, the companies want to collect, refine and systematically provide the entire development knowledge for different user groups.

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ToDo´s to extend ASAM ODS to Big Data

Driving tests produce an enormous amount of measured data for different development disciplines. Some companies have therefore begun to collect these data in a so-called “Data Lake”.

At the heart of such a “Data Lake” is usually the open source platform Hadoop. It provides a variety of frameworks that enable to process and analyze the incoming data volumes flexible in manifold ways.

Continue reading “ToDo´s to extend ASAM ODS to Big Data”

BigODS project examples

Automotive companies generate large amounts of test data from various sources such as test benches, simulations, driving and field tests. This data volume is growing exponentially day-by-day. Because traditional solutions reach their performance limits, the industry is dealing for some time with the question of how Big Data technologies can be beneficially used in the field of test data management and analysis. Frequently the companies desire to enhance established standards like ASAM ODS gradually.

The development of index-based search methods as well as new query and analysis techniques for ODS data are two concrete project examples.

Continue reading “BigODS project examples”