Azure IoT Central and Power BI on Image Defect Analysis
About Lam Research
Lam Research is a $9.65 billion+ American corporation that engages in design, manufacture, marketing, and service of semiconductor processing equipment used in the fabrication of integrated circuits. with over 11,000+ employees.
Customer Need / Business Driver
- Need to cut down on costs and increase agility moving away from SAP Hana and consolidating to the Azure Cloud
- Provide near Real-time reporting to stakeholders using Power BI
- Provide an Agile approach to Cross Functional Analytics. A departure from their siloed solutions
Lam Research selected KPI over multiple vendors through a rigorous RFP process. KPI’s expertise in Azure, AWS, GCP, EBS and Power BI was the key differentiator for Lam Research in addition to KPI’s blended shore model to minimize cost and risk for Lam Research.
What KPI Delivered
- Design and Implement Azure Solution and recommended the IoT Central solution for real time data ingestion
- Implemented Data warehouse to ingest structured, semi structured and unstructured data from different sources
- Migrated reports from Qlik Sense, MS Dynamics 365 to Power BI
KPI delivered an automated data standardization and Power BI data sources that could hook into other systems/files to allow users to analyze defects on Images and take necessary action.
- Optimized the process for Image Defect Analysis reporting
- Accomplished data standardization Automated the manual reporting process
- Closed data gaps between customers and Lam Research’s data
- Repeatable processes with restart ability and recoverability
- User can view and analyze the data generated from the inspection of parts by automated visual inspection
- Users now can update standard dictionary tables from Power BI using Power apps which will uplift the analysis on Images to gauge the effectiveness of Defects
- Along with Image and Defect analysis users can also view the image of the inspected disc in the power bi which will leverage the analysis on defects