How Mt. Fuji by Haber Is Reinventing Process Automation in Paper Mills
The pulp and paper industry is undergoing a quiet revolution. Increasing customer-good-state demand for consistent product quality, intelligent use of resources, and little to no downtime are pushing manufacturers toward smarter solutions. The acquisition and implementation of smart technologies, along with advanced process automation, is evolving corporate standards in process control for modern, connected mills, as a standard emerges for AI in paper.
From Manual to Autonomous: The Shift in Paper Mill Operations
Traditional paper production systems rely heavily on operator experience and fixed control logic. While these systems can produce results, they seldom enable the dynamic adaptability possible with machine learning-driven approaches, adaptability being a defining element of artificial intelligence.
Introducing intelligence to various areas of the production line will allow mills to go from reactive firefighting to proactive optimization. Smart Systems constantly reads from the mill's sensory system, adjusts control variables, and provides a consistent production run, leaving the human operator to supervise rather than alter. We are entering a new phase of process control.
The Value of Real-Time Process Feedback
In a fast-paced production environment, even a few seconds of delay can result in defects or expensive rework. Advanced analytics-enabled systems can provide tighter control of processes by tracking real-time variables such as temperature, pressure, flow rates, and material consistency. The result is fewer variations, smoother transitions, and dramatically decreased batch variation.
This also allows mills to achieve standardized quality targets commonly referred to as the "golden batch," where every run produces within the parameters of the best runs established by historical data. Achieving the consistency by hand is not typically possible; AI turns it into a routine."
Supporting Smart Efficiency Along the Line:
In the case of paper manufacturing, artificial intelligence does not offer just basic automation and sensor provision; it unifies the automation systems with PLC, SCADA, and DCS systems into one intelligent platform. This consolidation gives managers and engineers the combination of visibility, monitoring, early detection of issues, and coordinated activities that span machines.
Consider an example:
Smart manufacturing systems can:
- Automatically set machine parameters based on the properties of the raw materials
- Optimize operations to maximize energy efficiency
- Predict and pre-emptively prevent faults from occurring to avoid unplanned downtime
- Optimize process loop synchronization to reduce trim waste
Visibility That Drives Results
What makes AI irreplaceable is not just automation but actionable visibility. When AI is implemented, mill managers don't have to guess where the issue is. Instead, the system surfaces the issues, recommends corrections, and can adapt processes in real time. This can be for a new shift crew, new furnishings, or any possible change, with AI ensuring a similar quality and speed in production.
Conclusion: AI Is the New Standard for Paper Mills
In all paper mills, process automation is no longer just an aspiration but a competitive imperative. By leveraging AI in the paper operations and improving the process control, mills can decrease costs, reduce downtime, and achieve consistency in production quality, shift after shift.
Frequently Asked Questions (FAQs)
Q1: What is the biggest benefit of using artificial intelligence at mills?
AI achieves control over steady-state conditions and can replicate production results in real time, regardless of other imposed input variabilities.
Q2: In what ways can AI be unrelated to or superior to traditional automation?
AI learns from data rather than logic. AI adapts to changing conditions and continuously learns in order to achieve better results over time.
Q3: Is artificial intelligence viable in older plants with legacy systems?
Yes. Mt. Fuji can connect with modern and legacy infrastructures, enabling the transformation into artificial intelligence without replacing existing systems.
