At Paperex 2025, JMC Paper Tech Private Limited is unveiling MILLMIND, a next-generation AI-powered Mill Intelligence and Optimization Platform designed exclusively for the pulp and paper sector. Built on decades of engineering expertise and global mill experience, MILLMIND addresses the industry’s biggest challenges– from high energy consumption and unpredictable downtime to quality variability and limited real-time visibility. The platform integrates paper-industry-specific AI models, predictive maintenance, energy and chemical optimisation, digital dashboards, and future-ready automation capabilities. In an exclusive conversation with Paper Mart, Mr. Rajni Patel, Managing Director, JMC Paper Tech Private Limited, positions JMC not just as a machinery supplier, but as a technology partner driving India toward the era of Smart Paper Mills. With MILLMIND, JMC aims to empower mills of all sizes to operate smarter, safer, and more efficiently while strengthening the country’s digital manufacturing ecosystem under ‘Make in India’.
Paper Mart: Can you give us an overview of the AI-based product you have launched? What challenges does it cater to?
Rajni Patel: At Paperex, JMC Paper Tech is proud to launch MILLMIND, a next-generation AI-powered Mill Intelligence and Optimization Platform designed specifically for the pulp & paper manufacturing industry.
JMC Paper Tech has unveiled MILLMIND, a next-generation AI-powered Mill Intelligence and Optimization Platform, at Paperex. Designed specifically for the pulp and paper manufacturing industry, MILLMIND integrates advanced digital capabilities tailored to real mill environments.
The platform combines multiple features, including real-time machine data monitoring, predictive and prescriptive AI analytics, production optimization algorithms, and energy-saving as well as cost-reduction models. It also enables quality forecasting, defect prediction, and offers integrated dashboards to support faster and more informed decision-making for mill management.
The objective behind MILLMIND is clear: to transform traditional paper mills into smart, self-learning, future-ready factories. By improving productivity, reducing downtime, and lowering overall operational costs, the platform addresses long-standing limitations within the industry.
MILLMIND directly tackles key challenges such as high energy consumption, unpredictable breakdowns, lack of real-time visibility into machine parameters, quality fluctuations, manual dependency in troubleshooting, inefficient production planning, and rising labour, raw material, and utility costs. Its strength lies in AI models trained specifically on pulp and paper mill behaviour—offering a level of precision and relevance that generic industrial platforms cannot provide.
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PM: What inspired JMC to move into AI-Driven solutions for the Paper Industry?
RP: As a company that has supplied end-to-end paper machinery for decades, JMC has always focused on innovation and continuous improvement. The development of MILLMIND was driven by three major inspirations that emerged from years of engagement with mills across the world.
The first was JMC’s deep understanding of mill pain points. Through global projects in India, Africa, the Middle East, Mexico, and several other regions, the team observed the same challenges repeating across mills. Operators often worked with limited visibility into machine behaviour, decision-making was frequently delayed, quality fluctuated, and there was a noticeable absence of data-driven diagnosis. These experiences highlighted a clear realisation: automation in mills must evolve beyond hardware and move toward intelligent, insight-driven decision-making.
The second inspiration came from the global shift toward digital mills. With Industry 4.0 transforming manufacturing worldwide, large international mills have already adopted data-driven technologies, while medium-sized mills still rely heavily on manual judgement. JMC saw an opportunity and a responsibility to bridge this technological gap, enabling more mills to benefit from smart manufacturing tools.
The third driving factor was JMC’s vision to make mills more efficient, sustainable, and profitable. Rising operational costs and increasing global competition continue to pressure paper mills. AI-driven intelligence could play a transformative role in improving energy efficiency, optimising steam and power usage, enhancing fibre utilisation, refining chemical dosing, and ensuring consistent production quality.
These motivations collectively led to the creation of MILLMIND—an AI-driven platform designed to bring intelligent automation inside the mill and empower both owners and operators with advanced, future-ready tools.
The platform combines multiple features, including real-time machine data monitoring, predictive and prescriptive AI analytics, production optimization algorithms, and energy-saving as well as cost-reduction models.
PM: What unique features or innovations set this AI solution apart from existing technologies in the industry?
RP: MILLMIND is not just an automation dashboard; it functions as a complete digital brain for the paper mill. It introduces several key innovations designed specifically for the pulp and paper industry. One of the most significant advancements is its paper-industry-specific AI models. Unlike generic industrial systems, MILLMIND’s algorithms are developed using real paper machine behaviour, stock preparation dynamics, steam and condensate patterns, correlations between quality parameters, and extensive real-world mill case studies.
Another major feature is its ability for predictive failure detection and downtime prevention. The platform identifies early warning signs of issues such as bearing heating, pump cavitation, vacuum fluctuations, dryer load imbalance, headbox variation, and press nip problems—allowing mills to act before breakdowns occur. Preventing these failures can save mills millions in downtime losses.
MILLMIND also excels in real-time energy and chemical optimisation, offering AI-based recommendations for reducing steam consumption, electrical load, refining energy, and chemical dosage. In addition to process optimisation, the system provides quality prediction before production, accurately forecasting parameters such as GSM, BF, moisture, porosity, and strength before the reel is produced. This enables corrective action well in advance.
For management, the platform offers integrated decision dashboards that present real-time insights into production, consumption, machine efficiency, breakdown trends, fibre loss, water usage, and cost per MT—transforming raw operational data into actionable business intelligence.
Importantly, MILLMIND is designed to be compatible with all types of mills. It works with existing or new machines, supports any DCS/PLC, and is suitable for mills ranging from 50 to 500 TPD. Whether it is kraft, duplex, speciality, tissue, or writing and printing grades, MILLMIND is ready to integrate seamlessly across mill types and capacities.
PM: What market trends or shifts do you anticipate as mills increasingly adopt AI and digital automation technologies?
RP: In the coming years, as mills increasingly adopt MILLMIND-like AI technologies, the paper industry is set to undergo a significant transformation. One of the biggest shifts will be the movement from manual decision-making to autonomous, AI-driven operations, resulting in far greater consistency and stability across processes. Predictive control will help mills achieve higher quality output, while energy optimisation models can contribute to substantial cost savings, often in the range of 15–20%.
The adoption of digital twins will further enhance machine optimisation, allowing mills to simulate performance, prevent failures, and fine-tune operations without disrupting production. With this digital evolution, the industry will also see a growing need for skilled technicians and digital operators, as data-centric roles become central to mill operations.
Production planning will increasingly rely on real-time insights rather than assumptions, supported by cloud-based visibility for mills operating across multiple locations. Predictive maintenance will shift from being an innovation to becoming the new industry standard. As mills continue modernising, AI is poised to become as essential as steam, power, and raw material, shaping the core of future mill operations.
MILLMIND is designed to be compatible with all types of mills. It works with existing or new machines, supports any DCS/PLC, and is suitable for mills ranging from 50 to 500 TPD.
PM: How does this AI initiative align with the company’s long-term vision and strategy?
RP: MILLMIND aligns seamlessly with JMC’s long-term vision for the pulp and paper sector. The company aims to evolve from a traditional machinery supplier into a true technology partner, offering integrated solutions that combine engineering, automation, and AI. With this platform, JMC seeks to support mills in improving energy efficiency, strengthening sustainability practices, and enhancing overall productivity and profitability across global operations.
The initiative also reflects JMC’s commitment to lead India into the era of Smart Paper Mills, helping build a stronger digital manufacturing ecosystem in line with the “Make in India” mission. MILLMIND is designed not just to modernise mills but to empower them with intelligent, future-ready capabilities that redefine how the industry operates. For JMC, MILLMIND is more than a product — it is the future foundation of the company’s technological leadership, representing a significant step toward shaping the next generation of the pulp and paper industry.
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PM: How do you see AI shaping the future of paper machinery over the next 5–10 years?
RP: The next decade is set to bring a complete transformation to the paper industry, with AI playing a central role in reshaping how mills operate. One of the biggest shifts will be the emergence of autonomous paper machines, where deckle adjustments, steam load management, chemical dosing, and machine speed will all be controlled automatically by intelligent systems. Alongside this, unplanned downtime will drastically reduce, as predictive maintenance becomes the norm and breakdowns become rare events.
AI will also introduce the widespread use of digital twin simulations, allowing mills to test grade changes or GSM adjustments virtually before implementing them on the machine. This will dramatically improve operational predictability. Operator dependence will evolve as well—AI will guide less experienced operators through precise recommendations, reducing skill gaps across shifts and teams.
Energy optimisation will become another defining advancement. With AI-driven controls, mills can aim for 20–30% reductions in energy cost, taking a major step toward energy-neutral operations. At the same time, integrated supply chain intelligence will optimise everything from waste paper procurement to finished reel dispatch, making the entire value chain more efficient and responsive.
Ultimately, control rooms will transition from manual supervision to fully AI-assisted environments, where human expertise is strengthened—not replaced—by intelligent automation. AI will empower operators, engineers, and decision-makers to reach new levels of efficiency that were previously unattainable.
One of the biggest shifts will be the movement from manual decision-making to autonomous, AI-driven operations, resulting in far greater consistency and stability across processes. Predictive control will help mills achieve higher quality output, while energy optimisation models can contribute to substantial cost savings, often in the range of 15–20%.
