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Causal inference: An introduction on how to separate causal effects from spurious correlations in data

What is causal inference in statistics data science? While „correlation does not imply causation“, it is possible to identify causal effects even in data that does not come from randomized controlled trials. Our AI expert, Dr. Julien Siebert, just published…

What are Complex Systems? – Understanding and Assessing Complex Phenomena

Taking into account the complexity of the systems around us is the first step towards understanding them. In this post, our expert Dr. Julien Siebert (Fraunhofer IESE) describes the most important characteristics of a complex system from his point of…

Time Series Analysis: Outlier Detection

Time Traveling with Data Science: Outlier Detection (Part 3)

In our blog series on „Time Traveling with Data Science“, we previously introduced different tasks in time series analysis. In this blog post, we now present the task of Outlier Detection. Outliers are data so different from others that one…

Artificial Intelligence for Control Centers and Situation Rooms (Künstliche Intelligenz für Leitstellen

Artificial Intelligence for Control Centers and Situation Rooms – the Project SPELL (Part 1)

On 1 June 2021, the BMWi-funded project SPELL was launched (BMWi=German Federal Ministry of Economic Affairs). The project acronym stands for “Semantic Platform for Intelligent Decision-Making and Mission Support in Control Centers and Situation Rooms” (in German: “Semantische Plattform zur…

Virtual Continuous Testing – New Horizons for Modern Software-based Systems Development

Over the course of time, the indispensability of information and communications technology as an integral part of modern software-based systems has also given rise to the demand for more sophisticated development approaches. Among those, the established V-Model and its novel…

Continuous Engineering (Continuous Planning and Continuous Budgeting)

Continuous Engineering for Industrie 4.0 (Part 2)

Future-proof decision making can be enabled by Continuous Planning and Continuous Budgeting with Continuous Integration of Digital Twins: Today we continue the series Continuous Engineering for Industrie 4.0, where we are exploring how continuous engineering practices should be instantiated to the automation domain to support Industrie 4.0 principles.

Continuous Engineering for Industrie 4.0

Continuous Engineering for Industrie 4.0 (Part 1)

Rolling out changes in complex systems is always a challenge. Regardless of whether a software component needs to be modified or whether a change in the communication network needs to be made, any change may lead to unexpected behavior. Continuous…

Building the Industry 4.0 IT Infrastructure for Digital Twins

Industry 4.0 and Digital Twins promise many benefits, such as an efficient lot size 1 or various optimizations. However, successfully implementing these concepts requires a sophisticated IT infrastructure. What are the requirements on this infrastructure and how can it be…

CEP-CANdle tool: how to efficiently improve CAN bus design

Controller Area Network bus or CAN bus analysis is crucial for detecting the loss of important messages. In vehicle systems and many sophisticated embedded applications, preventing failures in the early development phase is an important demand of the market nowadays….

Fraunhofer IESE - Teil 5 Werkzeuge / Tools für Anforderungsdokumentation

Requirements Specification (5/5): What kind of tool do I need for Requirements Documentation?

This is the final article in a series of five blog posts on requirements documentation. Where documenting requirements is considered a de facto standard in classical projects, Agile contexts tend to avoid it, as it is seen purely as unreasonable…