Automotive Manufacturer's Next-Generation QA & Safety Analytics Solution

Realizing new Vehicle QA (Quality Assurance) using Microsoft Analytics, Power BI and AI solutions. 

Automotive Manufacturer's Next-Generation QA & Safety Analytics Solution

Client Profile

Client name Automotive Truck Manufacturer
Industry Automotive, Manufacturing
Scale of Sales (Global base) $1.1 Billion
No. of Employees (Global base) 33,000 Employees

Project Outlines

Client Challenges

  • Manual handling of data and limited alerts caused latency in safety and compliance alert response time.
  • Difficulties with data quality and accessibility.
  • Limited technology infrastructure for data analytics.

Solutions

  • Built data pipelines to ingest, transform, and load gigabytes of data using Azure Data Factory, and stream and batch processing from multiple data sources using Azure Data Lake and Azure SQL Database
  • Built cognitive search to generate high-risk alerts using Azure Search and text analytics models using Cognitive services.
  • Pushed data via APIs to interactive Power BI reports.

Result

  • Reduced issue detection time by 97 percent.
  • Cycle time to generate essential reports was reduced by 90 percent.
  • Increased reporting of trending issues by more than 25 percent.

Featured Points

Difficulties with client challenges

Consolidate many data sources that were siloed without any central quality assurance data platform and data warehouse.

A growing US truck manufacturer faced several challenges in monitoring and assessing vehicle safety, quality, and compliance. One specific challenge was the manual handling of raw and unformatted data to identify high-risk problems. There was also a limited ability to proactively generate alerts on and understand trends of high-risk issues. These deficiencies caused latency in responding to safety and compliance issues identified in the field. Additionally, there were issues with data quality and data availability arising from large data volumes with an extensive variation. These issues and a lack of technology infrastructure hindered the business from achieving agile data analytics. 

 

Critical success factors of the project

Small start approach by using phased approach

Due to the data complexity with many different sources of information,  ABeam proposed a phased approach to ingest the data, build the database and create the Power BI reporting and visualization. 

ABeam designed and built a robust data analytics platform leveraging 100% managed services provided by Microsoft Azure, eliminating hardware leasing and software licensing renewal and decreasing delivery time and IT overhead.ABeam employed a package of Microsoft solutions, including data pipelines using Azure Data Factory to ingest, transform and load gigabytes of data via stream processing and batch processing from multiple data sources to Azure Data Lake and Azure SQL Database. Additionally, a cognitive search was built using Azure Search and text analytics models using Cognitive services, to generate high-risk dictionary catalog and alerts. Also, data was pushed via APIs to the Power BI reports that provide interactive and contextual vehicle insights that were actionable.

 

ABeam's contribution

Increased accuracy, insights, and reporting leads to simplify data analytics

ABeam established a better and more efficient quality assurance and compliance platform combined with an analytics solution. The benefits include faster access to data, allowing the client's field quality team to analyze real-time and aggregated data in hours rather than several months, which is a 97 percent increase in their time for analysis. Additionally, the simplified data analysis has reduced the time spent managing data, enabling the client's Field Quality Engineers to focus on analytics and insight, improving productivity.

Moreover, the cycle time to generate essential reports has been reduced by 90 percent. The client data analysis could institute the Kaizen analysis and reporting by refining, validating, and rectifying every facet of reportable data with complex rules, data mapping, and management. ABeam helped our client streamline their quality assurance and compliance processes while also enabling them to gain better insights and make more informed decisions based on the data they collect. 

With the ability to receive high-risk issue alerts and generate metrics related to safety and compliance, the engineers have increased the reporting of trending issues by more than 25 percent. This is a significant improvement, as it allows the client to identify and address potential issues before they become major problems.

Additionally, by using Microsoft Azure's fully managed services approach, the client is no longer dependent on IT to deploy systems and applications or manage and monitor data movement. This frees up the business team to focus on other essential tasks without worrying about the solution's technical details. The solution's feature-rich, reusable, and flexible nature also means that the client can scale their quality, safety, and compliance solutions as needed, creating a solid, proactive sensing solution that can adapt to their changing needs over time. The ABeam solution has helped the client to streamline their processes, increase efficiency, and improve safety and compliance reporting.

Related Solutions

page top