Get the tools you need to take your production to the next level
QualityLine’s AI algorithms will analyze your manufacturing data to deliver:
- AI Manufacturing Analytics dashboard
- Prediction of failures
- Manufacturing KPIs
- Root Cause Analysis
- Boost first pass yield
- Cross correlations between processes
&nbp;
Get useful insights from QualityLine AI analytics
using demo data
Check your own Manufacturing Quality & Efficiency
and get valuable insights instantly using your real data
How does it work?
What is required from you?
Step 1
Select your data
You are welcome to select any type of historical testing data
(AOI, end of line, functional testing and so on..).
Data Security
QualityLine is certified for ISO-27001 for data security. 
- Your data will be encrypted and will never be shared with anyone.
- You will set a user name and a password for secured access and data upload.
- If NDA is required, please send your NDA form for us to review and sign to:
info@quality-line.com
Step 2
Testing data and Repair / Rework data
- If the testing data is saved as test log files then please save all to zip.
- If the testing data is saved in database format then please send us a dump.
- Repair/Rework data (in any format) of units that failed during
the testing processes you upload and within the same period of time
(units that were found to be defective in testing).
Step 3
Tips for best analytics results
we recommend that your data will include:
Data for Testing Analytics
- Serial Number (SN) of each unit
- Product Part Number
- Testing station Name/number
- Operator Name (if exist)
- Timestamp (time/date)
- Status of the testing unit (PASS/FAIL)
- Process Name (if exist)
- Parameter name (the names of each tested parameter within each test session)
- Lower Limit of each test
- Higher Limit of each test
- Result of each test
- Test Status – the result of each test – pass/fail (if exist)
- Test Duration (if exist)
- Measuring Units (if exist)
Data for Repairs Analytics
- Serial Number (SN) of each unit
- Product Part Number
- Technician name or number (if exist)
- Failed parameter of symptom found in the testing
- The faulty component or material found defective during repair (component number and also reference designator)
- The failure code that was found by the technician (broken component, cold soldering…)
- Text description of the problem found (if exists)
Unlock the value of your data
Global end-to-end control
Automated and fast integration of any manufacturing data source
QualityLine experts have experience with more than 1500 production lines around the world and more than 30 years in the manufacturing industry.
We want to use our knowledge and experience to help you improve your manufacturing efficiency and product quality.
Our machine learning and artificial intelligence technology will make this possible.
Tips for best analytics results
we recommend that your data will include:
Data for Testing Analytics
- Serial Number (SN) of each unit
- Product Part Number
- Testing station Name/number
- Operator Name (if exist)
- Timestamp (time/date)
- Status of the testing unit (PASS/FAIL)
- Process Name (if exist)
- Parameter name (the names of each tested parameter within each test session)
- Lower Limit of each test
- Higher Limit of each test
- Result of each test
- Test Status – the result of each test – pass/fail (if exist)
- Test Duration (if exist)
- Measuring Units (if exist)
Data for Repairs Analytics
- Serial Number (SN) of each unit
- Product Part Number
- Technician name or number (if exist)
- Failed parameter of symptom found in the testing
- The faulty component or material found defective during repair (component number and also reference designator)
- The failure code that was found by the technician (broken component, cold soldering…)
- Text description of the problem found (if exists)
