Drivetech - Blog #ReliabilityDrivetech - Blog #Reliabilityhttps://www.drivetech-ai.in/blogs/tag/reliabilityThu, 07 May 2026 16:04:59 +0530http://zoho.com/sites/<![CDATA[How StellarAi's Advanced 'Event-based Search' helped an OEM locate a crucial problem from their big data.]]>https://www.drivetech-ai.in/blogs/post/StellarAi-Event-based-SearchThe Problem   While working closely with one of our OEM customers, DriveTech was tasked diagnosing a critical issue they were facing with thei ]]>

The Problem 
While working closely with one of our OEM customers, DriveTech was tasked diagnosing a critical issue they were facing with their proto vehicle fleet. Essentially the requirement was to collect network data from affected vehicles, analyze it and come up with the correct diagnosis in a week.  

 

The Solution 

DriveTech installed data logger devices and recorded the CAN network data from the vehicles and their multiple networks. This data acquisition was done for a week in hope to catch a replication of the failure event on the CAN log. During this time the vehicles were routinely driven for 100 to 150 kms every day, generating large amounts of data. The devices captured multiple failure events, and now the data had to be analyzed.  This case was very critical and demanded urgent resolution as the failure was adversely affecting the test program. DriveTech was left with ~ 100+ GBs of data (500+ files) which had to be analyzed. Each file would take around 45 minutes for analysis and analyzing 500+ files would mean spending a month or more just isolating the events. 

The Turning Point 
     To specifically address this, we decided to leverage our in-house Data Analytics platform, StellarAi. This platform excels at handling vast amounts of data with minimal processing time. The standout feature that proved invaluable in this case was the Advanced ‘Event-based’ Search functionality. We were looking for specific events within this huge amount of CAN data, and the advanced event-based search needed only a 1-line query to locate the files containing failure events in less than a minute.      

We were able to quickly visualize the data from these files, which helped us pinpoint the precise instance when failure occurred. We were able to visualize multiple such files simultaneously which helped us narrow down the potential causes.                

Collective analysis of files from all the affected vehicles enabled us to precisely identify the cause of failure and come up with a diagnosis. We were also able to recreate the failure on a bench set up, validating our diagnosis. 

Conclusion  

After some more on-road testing & inspection, we were able to definitively conclude the reason for failure and notified the Automaker with potential insights. DriveTech was able to use StellarAi’s value added features and converge the analysis quickly. Without features such as event based Advanced Search it would have taken anyone a very long time to resolve the issue; while losing valuable time in getting new models into the market. 

]]>Sat, 04 Nov 2023 13:41:00 +0530<![CDATA[Maximizing The Value Of Automotive Test Data Through Effective Data Management ]]>https://www.drivetech-ai.in/blogs/post/Maximizing-The-Value-Of-Automotive-Test-Data-Through-Effective-Data-ManagementIntroduction Efficient data management is the linchpin to unlock the true potential of automotive test data. Without a system driven approach, centrali ]]>

Introduction

Efficient data management is the linchpin to unlock the true potential of automotive test data. Without a system driven approach, centralized management of automotive test data is heavily dependent on human intervention making it an uncertainity.

The Significance of Automotive Test Data Management

When data is scattered across multiple locations, its full potential remains untapped. OEMs invest significantly in collecting test data, and effective data management ensures this valuable resource is fully utilized. By centralizing data, OEMs gain easy access, traceability of historical data, and comprehensive analysis capabilities, enabling them to make informed decisions, optimize processes, and extract actionable insights for enhanced vehicle development.

Maximizing the Value with StellarAi

StellarAi by DriveTech focuses on Data Consolidation and Management as one of its core functions. With StellarAi, you can easily centralize project data in a secure data warehouse. The web platform also offers the ability to organize data into separate datasets and arrange files in the desired sequence. This system consolidated data can be shared exclusively with the relevant team members, eliminating the need to physically handle large amounts of data.

StellarAi also seamlessly integrates with your existing DAQ tools, allowing you to gather data from specified locations remotely. It also comes with a built-in feature for automated analysis based on this data. (Read more about it here).

Conclusion

Effective automotive test data management is crucial for leveraging the full value of data investments. StellarAi provides the tools and capabilities to systematically centralize and optimize data management, driving better outcomes in vehicle development.

]]>Wed, 11 Oct 2023 19:38:32 +0530<![CDATA[Automotive Test Data Analytics: Automate for Efficiency]]>https://www.drivetech-ai.in/blogs/post/Automotive-Test-Data-Analytics-Automate-for-EfficiencyIntroduction In the fast-paced automotive industry, the analysis of test data holds immense importance for efficient vehicle development. The need for ]]>
boosting-efficiency

Introduction


In the fast-paced automotive industry, the analysis of test data holds immense importance for efficient vehicle development. The need for automation in this domain has become increasingly critical, as manual methods struggle to handle the growing data volumes, leading to productivity challenges and hindered operational efficiency.


The Impact of Manual Methods on Productivity

Relying solely on manual analysis methods in automotive test data analytics can significantly hamper productivity. Data collection, organization, and processing become time-consuming and error-prone, resulting in delays and inefficiencies. Analysts spend substantial time on repetitive tasks, limiting their capacity for higher-value activities. This lack of automation not only slows down the analytics process but also inhibits data-driven decision-making, impeding the overall efficiency of the organization.

The Power of Automation in Test Data Analytics

Automation is the key to overcoming the limitations of manual methods in automotive test data analytics. By automating data collection and processing, OEMs can streamline workflows and free up valuable analyst time. Real-time monitoring capabilities enable prompt anomaly detection, enhancing safety and reliability. Automation improves productivity, reduces costs, and fosters standardized processes, ultimately bolstering OEMs' efficiency and competitiveness.


Introducing StellarAi: Revolutionizing Automotive Test Data Analytics


DriveTech's StellarAi web-platform steps up to address these challenges and more. It empowers users to automate their repetitive data analysis tasks effortlessly. StellarAi allows the replication of analysis preferences, expediting results generation across various file groups. Its 'Datasets' feature seamlessly links data sources with individual repositories, automatically updating analysis results upon receiving new files from the source. StellarAi comes with a host of other value added features that help the analyst reduce time spent on manual work, and converge the analysis quickly.


Conclusion

Automation has become a necessity in automotive test data analytics, as manual methods hinder productivity and efficiency. Solutions like StellarAi pave the way for streamlined processes, improved decision-making, and heightened OEM performance.

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