As the pulp and paper industry continues to seek ways to enhance operational efficiency and sustainability, advancements in technology are playing a crucial role. In an interview with Paper Mart, Dr. Claudy D’Costa, Head of the Sensor R&D Division at Haber, who previously presented on the impact of artificial intelligence on filtrate turbidity testing (FTT) at IPPTA, discusses how Haber is integrating sensor technology and machine learning to monitor fiber morphology, offering potential benefits to Indian pulp & paper industry.
Paper Mart: Could you start by explaining your role at Haber and what the company is focusing on in the pulp and paper industry?
Claudy D’ Costa: As the Head of the Sensor R&D Division, my role involves developing and implementing advanced sensor technologies tailored to the pulp and paper industry. As a team, we are focused on developing sensor solutions that go beyond mere monitoring; they must provide actionable insights. By combining deep industry knowledge with cutting-edge sensor technology, we’re building tools that will revolutionize how paper mills operate. We’re not just developing sensors; we’re solving problems. Imagine having real-time data on fiber characteristics, that directly correlate to paper strength or smoothness. That’s the kind of impact we’re aiming for. It’s about empowering paper mills to make data-driven decisions, reduce waste, and produce higher-quality products.
PM: What motivated Haber to concentrate on sensor technology and machine learning for the pulp and paper sector right now?
CC: Our focus on sensor technology and machine learning really comes from wanting to tackle some of the big challenges in the pulp and paper industry. Traditional methods often have trouble with things like raw material variability and process inconsistencies. By using advanced sensors and machine learning, we can provide real-time, precise data that helps mills make smarter decisions and fine-tune their operations. It’s not just about having better technology; it’s about offering solutions that address these core issues and drive real improvements. We’re committed to innovation and want to ensure that our solutions make a tangible difference in how the industry operates.
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PM: Can you go into more detail about how Haber is developing these sensor technologies?
CC: At Haber, we’re taking a hands-on approach, revolutionizing the way fiber morphology is looked at, by blending advanced optical sensors with machine learning. Here’s how it works: We place these high-precision sensors throughout the production line to keep a close watch on key fiber properties like length, diameter, and fibrillation. The sensors capture detailed, high-resolution images and data, which we then analyze in real-time using machine learning. This lets us spot trends and predict the best process settings on the go, so we can adjust things like refining intensity and chemical dosages as needed. It’s all about tackling those long-standing industry issues and boosting both the quality of the product and the efficiency of the process.
PM: That’s impressive. How does Haber use machine learning and computer vision?
CC: Machine learning and computer vision are game-changers. We start by using high-precision optical sensors to collect detailed data on fiber characteristics throughout the production process. It allows us to monitor fiber properties with incredible accuracy. We can even spot tiny changes in fiber characteristics. The data from these sensors is fed into machine learning models that analyze it in real-time, helping us identify patterns and make predictions. This lets us adjust process parameters on the fly, ensuring that we maintain consistent fiber quality and enhance paper properties. Overall, it means a more efficient production process, less waste, and a more sustainable approach to manufacturing.
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PM: It’s clear that technology is making a significant impact. How does computer vision contribute to improving the overall process?
CC: Computer vision really is transformative for our operations. It’s a technology many people encounter in their daily lives, like the facial recognition you use on your smartphones and the DigiYatra system at airports, or your Aadhaar-based identification systems. In the pulp and paper industry, it lets us monitor fiber characteristics with outstanding precision. This leads to more consistent paper quality and fewer defects. By providing detailed and accurate data, computer vision helps us make better use of resources, cut down on waste, and lower operational costs. This not only boosts economic efficiency but also supports our environmental goals. For paper mills, this translates to significant cost savings and a more sustainable production process, allowing them to operate more economically while meeting their sustainability objectives.
