In short
- From beam image to insight. Every beam-profiler test holds many measurements. The value is in connecting them across reports, stations, batches and time.
- Pass/fail is not enough. A beam can pass today while its margin to the limit shrinks. Analytics shows the trend before units fail.
- What the service includes: a measurement database, multi-parameter analytics, an image viewer, report drill-down, IZAK Insight Chat and scheduled email reports.
- For production and R&D. Monitor yield and drift on the line, or compare prototypes and experiments as one dataset.
From beam image to production and R&D insight.
A beam-profiler test produces far more than one number. Each report contains beam widths, area, ellipticity, centre of mass, azimuth angle, peak position, limits and metadata. The real value comes from connecting these measurements across many reports.
That is why we now offer AI Analytics for the IZAK Laser Beam Profiler: a new service for production lines and R&D teams.
Why static beam-profiler reports are not enough
A static report shows the result of one measurement. It does not show what happens across:
- many reports over time;
- more than one measurement simultaneously;
- behaviour across stations, batches or product families;
- trends before failure occurs;
- recurring relationships between process changes and beam performance.
A beam can pass today while its margin to the specification limit is shrinking. For an upper beam-width limit, the margin is:
M = Wmax − W
where Wmax is the upper beam-width limit and W is the measured beam width. A pass/fail result shows only the sign of M at one moment. Analytics shows how M changes over time, by batch and by station.
How long until a drifting beam width fails?
Enter the upper limit, today’s mean beam width, the unit-to-unit spread (σ) and the drift you see in the trend. The tool shows the margin, the process capability against the upper limit (Cpu) and how many weeks remain before the 3σ tail, and then the mean, reach the limit.
M = Wmax − W; Cpu = M / 3σ; weeks until the 3σ tail fails = (M − 3σ) / drift; weeks until the mean fails = M / drift. Assumes a linear drift and a stable spread.
From single-parameter review to multi-measurement analytics
The system analyses multiple measurements together to derive statistics, trends, correlations and engineering conclusions. Each report i is represented as a measurement vector:
xi = [Wmajor, Wminor, A, e, XCM, YCM, Xpeak, Ypeak, θ, …]
For each parameter, and for the set as a whole, the analysis covers:
- mean and spread;
- drift over time;
- specification margin;
- pass/fail contribution;
- comparison by station, batch, product type or date range;
- relationships between measurements rather than isolated values.
Beam problems often appear first as a subtle change in one parameter, and only later affect other parameters or the yield. Looking at all of them together is how you catch the change early.
| Measurement | A trend often points to |
|---|---|
| Beam width (major / minor) | Focus position, optics condition, a lens or collimator change |
| Ellipticity, azimuth | Astigmatism, tilt or misalignment in the optical path |
| Centre of mass, peak position | Pointing drift, mechanical shift, thermal effects |
| Area | Combined size changes; check with both widths |
What the AI Analytics workflow includes
Beam image viewer with overlays and profiles
The viewer shows the beam image with overlays, cursors and intensity profiles, so the image always stays linked to the numbers behind it.
Data exploration, filtering and graph-based analytics
Reports become a searchable analytics layer, filterable by date, station, laser type, batch, serial number and other fields. Teams use it to:
- monitor statistics across many runs;
- compare behaviour across VIS, MWIR and LWIR systems;
- observe trends in beam width and other measurements;
- identify recurring contributors to failure;
- investigate changes before they become yield problems.
Instead of reviewing reports one by one, users move directly to charts, trends and grouped statistics.
Multi-parameter analysis covers:
- beam width, major and minor
- ellipticity
- area
- centre of mass
- peak position
- azimuth angle
- pass/fail outcomes
- custom test metrics
For example, an engineer can check whether a change in beam width appears alone, or together with a centre-of-mass drift or a change in ellipticity, which points to a very different cause.
Report detail and engineering traceability
A detailed report view lets users open the exact report behind any point on a chart, review the values against the criteria, and see which parameter failed and in which direction.
IZAK Insight Chat
IZAK Insight Chat is a natural-language interface to the measurement database. Example questions:
- “Which measurement contributes most to failures?”
- “Which station should be investigated first?”
- “Show the latest failed report with major beam width above the limit.”
- “Compare beam-width behaviour before and after a batch change.”
- “Summarise weekly trends across multiple measurements.”
The goal is to help engineers reach the evidence faster, not to replace their engineering judgement.
Scheduled custom reports delivered by email
Custom reports can be generated daily, weekly or monthly and delivered by email, with the measurements, filters, graphs and summary tables you choose. Setting them up is straightforward.
Built for both production lines and R&D work
Monitor stability, yield and drift across units. Compare stations, batches, shifts and components, so drift becomes visible quickly.
Analyse performance across repeated experiments, prototypes, alignment changes, optics and operating conditions, turning scattered files into one comparable dataset.
Example: tracing a beam-width trend to a new lens batch
On one manufacturing line, the major beam width increased gradually over time. Analysing the data by time, station and batch linked the trend to a new batch of laser lenses.
Instead of seeing only that some units failed, the team could understand why the process changed and where to investigate first.
Watch: AI analytics for laser beam profiling
More than a demo: this is now a service offering
This is not only a demonstration video. It is a service we now offer to customers who want to extend their beam-profiling workflow with AI-driven analytics. The service can include:
- structuring historical measurement reports into a database
- multi-measurement analytics and trend dashboards
- report drill-down and traceability workflows
- beam image viewer integration
- IZAK Insight Chat for natural-language data inquiry
- scheduled daily, weekly or monthly email reports
- adaptation for production monitoring or R&D performance analysis
- customisation for specific laser families, test stations and measurement criteria
A practical foundation for future AI capabilities
Once the data is structured, further functions can be added, such as:
- anomaly detection
- early drift warnings
- near-limit alerts
- root-cause guidance
- predictive quality scoring
- automated engineering summaries
The first step is analytics that engineers can trust, connected to the beam image, the report and the measurement data.
Related reading: the essentials of laser beam profiling for QA, verifying top-hat beams and FPGA in electro-optics set-ups. Building a test station? See electro-optics system design and development.
Let’s discuss your application
If you work in laser manufacturing, beam characterisation, optical testing or photonics R&D, we would be glad to discuss the service with you. Book a demo meeting with IZAK Scientific, or contact us through our website. Contact us today.
Frequently asked questions
QCan AI Analytics use our existing beam-profiler reports?
QDoes Insight Chat replace the engineer?
QIs it only for production lines?
Tzachi Sabati
CEO, IZAK Scientific
Physicist specializing in photonics and quantum technologies, with deep expertise in quantum sensors and advanced optical systems. Leads the Advanced Quantum Lab course at the Technion, bridging academic excellence with industry innovation. At IZAK Scientific, provides cutting-edge photonics-based solutions, developing customized inspection and sensing systems for R&D and production. Passionate about advancing quantum sensing applications and integrating novel technologies to meet industry needs.
