Test Results
Just a Click away
Just a Click away
Capture, Aggregate, Normalize and Analyze Test Data in Real-Time From Any Format
Rapid Test Engineering Workflows
- Web-access to all tester records and analytics
- UUT History/Event Report
- Raw data support, including waveforms
- Complete Serial Number History Report
- Characterize and Correlate
- Statistical Process Control (SPC)
- Failure Paretos
- Station Performance and optimization
- Test Process Performance
- First-Pass, Last-Pass, Throughput Yield
- Retest/Rework
- Drilldown from Yield or SPC to unit performance
- Web-based graphs and charts
- Traceability
Building the Digital Thread for Electronics Manufacturer requires the ability to seamlessly incorporate new and upcoming sources of manufacturing data, enterprise attributes, and other silo’d data sources.
- What to consider when implementing a new test format
- Extensibility
- Compatibility
- Future Proof
- Raw Data support
- Customized Formats
- Binary, text, images, PDF, other
- (PDF Download): Application of ATML Test Results and IntraStage to facilitate Intelligent Data Analysis
- (PDF download) How To Use Test Data to Better Manage ATEs
Success with a Manufacturing Intelligence platform requires a firm understanding of a company’s current manufacturing environment, digital readiness, and roadmap to the factory of the future.
- Customization and Integration use case
- Integration of manufacturing parametrics with existing PLM, ERP, and MES
- ETL process for new datasets
- Features of a complex electronics data warehouse
- (PDF Download): Digitize Your Paper-Based Test Data to Generate New Insights
- What Does SPC Mean To You and Your Organization?
- Achieving Success With a Phased Approach
Advanced Test Engineering Topics
Manufacturing Intelligence means having the off-the-shelf analytics and documentation to deploy and support advanced test engineering features.
- Gage RnR on-demand
- Realtime SPC and WECO
- Hidden Factory
- Other DB integration
- Enterprise integration
- Emerging standard and best practices
- Workflows
- Spec phase/requirements
- Subscriptions
- The Power of Attributes and Metadata
- Applying Machine Learning and A.I.
- Strategy for Very Large Datasets
Yield and Pareto drilldowns
Learn how General Atomics digitized multiple data silos to ID issues that affected product quality
Real-time visibility
Converting ATE data and digitizing paper forms to identify and resolve manufacturing problems quickly
Read the Case Study
Turning Data Into Action
Learn how Medtronic integrated BlackBelt to gain a full picture of their KPIs
Lower Costs, Faster Production time
Analyzing data from across the product lifecycle
WiP and Cycle Times
Intelligence from supplier subcomonents, CM Lower-Level Assemblies, and Higher-Level Assemblies
Learn More