On The Line Ep. 5: AI and Machine Learning for Quality Control in F&B Manufacturing
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How ML and AI Powered Technologies Support Quality Teams in Food and Beverage Manufacturing
Welcome to On the Line with Laminar, our series where we go inside the world of process manufacturing to hear what's really driving change on the production floor.
In this episode, Sanjay Rajan, Head of Go-to-Market at Laminar, sits down with Mahde Alchab, Forward Deployed Engineer at Laminar and former QC microbiology technician. They cover the full arc of what it means to bring AI and machine learning into a quality-first manufacturing environment — from why QA teams need to be in the room from day one, to how ML is finally cracking chronic process failures like emulsification that facilities have been living with for decades.
Catch the video or check out the transcript below!
Role of Quality Assurance Teams in Introducing New Technologies
Sanjay: You started your career as a QC microbiology tech — environmental monitoring, swabbing, sterilization protocols. What's quality's role when new technology gets introduced into a facility?
Mahde: Quality finds themselves in a very interesting position in any manufacturing plant. They are the shot callers — especially when it comes to introducing new technology or making real process parameter changes. Anytime operations or engineering decides a change needs to happen, quality is always the final sign-off.
Importance of Quality Team Involvement in New Technology Deployments
Mahde: When I'm introducing this technology into a new plant, the first thing I do is ask to speak to quality — not just management, but the people on the floor doing the testing and writing the reports. This tool is meant to improve not just their process or their quality standards, but their day-to-day life as a quality technician.
I loop them in earlier than most people think is necessary. Understanding how the technology works and what it takes to integrate it into a facility is paramount to having a quality team that not only trusts our product, but relies on it. This isn't just a quality tool — to quality, it is the tool.
Sanjay: How important is it for quality to understand technology that's going to become their assist?
Mahde: Super important. They need to be interested and engaged early. In the context of PLC tags — a quality tech doesn't do PLC programming, and they'll tell you that. But when they hear the specific tags we're monitoring, like flow rate or conductivity, alarm bells go off. They're thinking: I check the flow meter every shift. I check conductivity too. It builds understanding — and understanding is the only real foundation for trust.
How Quality Teams Shape Better AI Models
Mahde: When you hear us talk about the same exact metrics that quality is already measuring, that should give assurance to quality assurance that we're doing the right thing. And it gives them the opportunity to say, hey, you talked about all of these tags, but we also have a pH probe. Why aren't you gathering that?
I love when they ask questions like that. When a quality member is asking me questions, it means they understand what we're building well enough to improve it.
What Causes Emulsification Failures in Food Manufacturing — and Can They Be Predicted?
Sanjay: Every food and beverage customer we talk to says there are chronic issues underlying their process just waiting to be squeezed out — not just for profitability, but for efficiency and sustainability. One of those is emulsification. Why is it that our technology can take a cut at a problem that facilities producing mayo and ketchup for decades haven't fully solved?
Mahde: I'll stick with mayonnaise here. The process is a very delicate balance of so many variables. You have your egg, you have your oil, you have to control the flow rate at which the oil is added into the egg, hold a very specific temperature and pressure — and if you break any of that, you will not be making mayonnaise. When you have that many factors coming together to make one product and something goes wrong, who knows what happened. That's the problem.
If we had a means to predict it — if we had a measure of something that told us something bad is happening, we are going to have a split event — that would be phenomenal
How Laminar’s Self-Optimizing Technology Detects Food Manufacturing Quality Failures Before They Happen
Sanjay: If you can predict an event before it happens, it's downtime prevention, it's product loss prevention. Input costs are going up right now, so making sure raw materials are efficiently used matters more than ever. Three split events a month can become zero because the system is self-correcting.
Mahde: Each facility is going to be very different in how they operate and what process parameters are leading to failures. But the approach largely remains the same — analyzing the patterns that lead to breakdowns and training off of that. When we're able to look at all of this data with our telemetry and apply it to a trained model that knows exactly at what point things happen, it is very scalable.
How Does ML-Driven Quality Control Scale Across Products and Facilities?
Sanjay: If we see enough of these across enough lines and potentially different factories, we could come up with a reference model for emulsification for a particular product that can be deployed very quickly — and then tuned to be bespoke for specific factory conditions. Is that where you see this going?
Mahde: Yeah, we can certainly have a base layer — almost like a template — where we have our set expected values and then you apply it and see what doesn't fit. From there it's simple: you put the puzzle piece on and see where it fits. That's the beautiful thing.
Sanjay: Taking hard problems that have been optimized to the maximum possible with existing technology and squeezing out that last mile of value — whether it's sustainability, profitability, or efficiency. Because these operations are at scale, even a little improvement goes a long way. Cutting breakdowns by 90% — customers absolutely love it.
What's Next?
That wraps up Episode 5 of On The Line with Laminar.
To see how Laminar's ML platform gives food and beverage quality teams real-time process intelligence — from CIP validation to predictive failure detection — explore our customer stories or talk to the team.
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