08/02/2022

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NorCom Information Technology GmbH & Co. KGaA has received two follow-up orders for an AI project at a German automobile manufacturer that has been running since the beginning of the year. NorCom supports the customer with the AI platform DaSense on the one hand in the implementation of current innovations in the industry, on the other hand with the extended root cause analysis in operational business. Within this framework, NorCom is developing several AI apps on various aspects of these topics. The projects started in July and should be completed by the end of the year.

AI apps support current challenges in the automotive industry

The automotive industry is characterized by rapidly advancing technological developments, but also by ever-increasing legal restrictions. In both areas, NorCom's AI apps are designed to help respond to current requirements in the best possible way.

A new app supports the implementation of the regulations from the new Euro 7 emissions standard, which is intended to further reduce pollutant emissions. The already existing cold start app, which analyzes the starting behavior of vehicles and classifies and visualizes starting processes, will be expanded to include use cases for the 48-volt vehicle electrical system. The new 48-volt electrical system was developed to cover the increasing demand for electrical power in cars, for example for assistance systems.

Extensive use of Root Cause Analysis

Root Cause Analysis determines how, why and when a problematic event occurs. The aim is to be able to systematically avoid a problem that occurs in the future by analyzing the causes, instead of solving it afterwards. The results of the root cause analysis also provide important information in order to determine the underlying causes of errors and to be able to rectify them in a cost-efficient and customer-friendly manner.

The already existing data science app should be used more efficiently, on a larger scale and in more diverse ways. In addition to optimization for a larger group of end users, the app is to be expanded to include tools for root cause analysis. Three new apps are being created here that provide information about dependencies between error codes that occur, monitor the success of repair measures and make predictions about the likely occurrence of certain error codes. The error codes are related to external circumstances such as driving frequency, location, weather conditions or driving speed. But also instruments and sensors inside the car, as well as their interactions, are included in the evaluation.

“The projects show how diverse artificial intelligence can be used to solve complex problems in everyday work. The AI platform DaSense offers an optimal basis for a variety of AI apps that enable a large group of users to efficiently analyze huge amounts of data," comments Dr. Tobias Abthoff the upcoming projects. "We look forward to implementing these extensive tasks in the coming months and realizing rapid success in the operational business."