As the pulp and paper industry looks forward to Paperex 2025, many topics of discussion are turning on automation, precision measurement, and the operationalization of data. In this regard, Paper Mart spoke to Mr. Stephen Ashton, Consultant at Haber, and Dr. Claudy D’Costa, Head of the Sensor R&D Division at Haber, who have been a crucial part of the advancements of sensors for essential components of papermaking. We discussed how optical sensing, computer vision, and machine learning are evolving domains for better visibility of fiber, sheet, and the process, while also getting to know how some of Haber’s systems, like the Freeness Tester, Fiber Morphology Analyzer, and Web Inspection System, are already defining the future of measurement and control in Indian mills.
Paper Mart: We’re seeing a heavy emphasis on automation and sensing at this year’s Paperex. From the perspective of R&D, what changes can you foresee in how mills view process measurement?
Stephen Ashton: Based on the current trends and our focus on it, I believe that the mindset is changing. In current times, I believe, continuous measurement is no longer an option but a necessity. Decisions based on periodic lab results and operator judgment, depending solely on it, shall be a thing of the past. The volatile nature of raw material quality, faster production speeds, and tighter quality tolerances are pushing mills to take a greater technological view of their processes.
Claudy D’Costa: Sensors, particularly optical and imaging sensors, provide that granularity. They observe the process in real-time but do not get in its way, fueling most of the change we see.
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PM: Haber seems to be tremendously focused on this area. Could you elaborate on how those initiatives got started?
CD: The answer is in these four words: Gaps In Mill Data. Parameters like freeness or fiber morphology influence almost everything downstream, yet the measurement methods are often inconsistent or too slow for real-time decision-making.
We began exploring how optical systems, combined with ML models, could capture fiber and sheet behavior more quickly. Our goal is to bring clarity to areas measured either occasionally or with a lot of variation, to spearhead the industry in transitioning the existing processes to the next stage.
PM: Could you give us some examples of some of the systems that Haber has produced based on this thinking?
CD: Freeness, being a deceptively simple metric, when measured manually, does not provide reliable data, hence the need for an automated system. That’s where Haber’s Freeness Tester (HRAFT) comes in, automating the test to produce more repeatable results, about ±1 °SR across shifts and improving grade-change efficiency.
On the wet end, with Haber’s Fiber Morphology Analyzer (FMA), we strongly believe our sensing technologies will make a meaningful impact in fiber characterization. Instead of treating fibers as just “long” or “short,” FMA, by capturing shape, surface development, fines content, among other parameters, helps evaluate how the sheets form and behave. And when it comes to the dry end, computer vision takes quality evaluation to the next level. Haber’s Web Inspection System (WIS) uses ultra-high definition imaging to detect formation issues, coating-related defects, amongst others, to ensure that now, the quality analyst doesn’t miss out on even minor irregularities, even at high machine speeds.
Each of these systems grew from the same principle – Capture what’s really happening, objectively and continuously.
PM: You brought up computer vision. It’s something people use every day without knowing, especially for digital identity authentication, at toll booths, and even for supermarket logistics. How are you planning to tap into its potential when it comes to paper manufacturing?
SA: The beauty of computer vision is that the underlying idea remains the same, whether it’s verifying someone’s identity or tracking crowds at an airport. The system helps us “see” patterns in a way we couldn’t before.
In paper manufacturing, we use that capability to observe fibers or the moving web. Fiber behavior (curl, coarseness, and fibrillation) shifts subtly as pulping or refining changes. When computer vision captures those micro-level signals, machine learning models can interpret them and highlight what operators need to act on.
On the sheet side, vision helps us catch early-stage defects before they grow into quality losses. It’s essentially putting a highly disciplined observer next to the process.
PM: It seems that Haber is introducing multiple solutions to transform mill operations. How can these products come together to create value for mills?
SA: We know that each of these products can strengthen a different layer of decision-making inside a mill. FMA helps mills understand fibre behaviour in depth, WIS gives continuous clarity on sheet quality, and HRAFT ensures consistency in refining. But what is truly impactful is how they can now slot naturally into the larger ecosystem we’ve already built with eLIXA, Kaiznn, and Mt. Fuji.
Those platforms strengthen a mill’s planning and mill-wide optimization, while the sensors reinforce that intelligence with real-time, ground-level data, creating an ecosystem that helps mills operate with a level of clarity and control like never before.
In the long term, our focus is on building tools that help mills make better decisions automatically and reduce variability while also working towards the next frontier: Giving mills the ability to operate with foresight.
PM: With this growing portfolio, can we expect to see Haber exhibiting at Paperex 2025?
SA: Yes, we’ll be present at Paperex, and this edition is particularly exciting for us. It’s the first time we’ll be showcasing all these products side by side, giving visitors a clear sense of how they integrate into one cohesive intelligence layer for the mill. Looking forward to some fruitful conversations at our stall there!
Haber’s FMA helps mills understand fibre behaviour in depth, WIS gives continuous clarity on sheet quality, and HRAFT ensures consistency in refining. But what is truly impactful is how they can now slot naturally into the larger ecosystem we’ve already built with eLIXA, Kaiznn, and Mt. Fuji.
