In an exclusive interview with Paper Mart, Dr. Ashok Kumar, Executive Director, Pudumjee Paper Products Limited, highlights the shift from conventional automation to intelligent process control systems to attain greater process stability and product consistency. He emphasises the role of Advanced Process Control (APC), Model Predictive Control (MPC), Artificial Intelligence (AI), and Machine Learning (ML) and other emerging technologies in predicting and controlling process variability, improving operational efficiency and enhancing paper quality. He also shares insights from a recent project involving replacing a conventional hydraulic headbox with a modern dilution control headbox integrated with the approach flow system, which substantially reduced variability and improved quality consistency.
Paper Mart: Where does process variability remain most persistent in paper manufacturing today, and how does it affect quality and operating performance? Please tell us the process stages or parameters where tighter stability can deliver the greatest measurable gains.
Ashok Kumar: In all sections of the paper manufacturing process, process variations happen continuously because several process parameters and operating conditions keep changing. These variations depend on the specific section of the manufacturing operation. At times, even small variations in one section can significantly affect the subsequent sections of the paper machine, as all the processes are integrated. On a paper machine, such variations can lead to quality problems, runnability issues resulting in sheet breaks, higher energy consumption, reduced production efficiency and increased overall losses.
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PM: How has the approach to controlling process variability changed in recent years? In other words, how are mills moving beyond conventional automation and feedback control to achieve greater process stability? Please explain with examples.
AK: Earlier, control systems were primarily used to control one process variable at a time. Today, modern control systems can monitor a large number of process variables simultaneously and understand how they influence one another. Suppliers are integrating Advanced Process Control (APC), Model Predictive Control (MPC), Artificial Intelligence (AI), and Machine Learning (ML), along with other emerging technologies, to predict and control process variations before they become major problems affecting overall operational efficiency and product quality.
PM: How are Advanced Process Control and Model Predictive Control being applied to reduce process variability? Where have they delivered measurable gains?
AK: Advanced control systems can distinguish whether a problem originates from the process or the control system and respond accordingly. This helps maintain process stability while reducing product variation and process disturbances. By utilising the experience from many installations, suppliers of these systems have developed control models that can recognise unusual process behaviour and help correct the problem before it affects production.
PM: What practical role are AI and machine learning playing in predicting and correcting process deviations before they affect production or quality?
AK: Advanced technologies, such as AI and Machine Learning (ML), can detect unusual process behaviour before it affects paper quality or equipment problems. They can also estimate important process values that cannot be measured continuously. By analysing data from previous production runs, the system learns which settings give the best results and recommends or automatically applies those settings when the same grade is produced again.
These settings, for example, may include parameters such as headbox dilution valve positions, vacuum controls, steam pressure settings, sectional drive draw and many other important process parameters.
PM: How are online measurement, smart instrumentation, machine vision, and QCS improving real-time detection and control of process variation? Where do significant measurement or data gaps still remain?
AK: Modern paper machines use various online measuring systems. These include Quality Control Systems (QCS), sheet formation index measurement, fibre orientation measurement, vibration monitoring, control valve diagnostics, flow measurement devices, machine vision cameras, infrared sensors, felt and wire tensions, colour and gloss sensors that continuously monitor both the process and paper quality. These systems detect process variations in real time, enabling immediate corrective actions. Advanced control systems automatically tune control loops, optimise performance, and detect operational limitations. Today’s paper machines are highly automated, as it is not possible to manufacture such a thin sheet of paper consistently without having advanced process measurement and control.
PM: Drives and motion control directly influence speed, tension, synchronisation, and machine stability. How are newer drive and control technologies helping mills reduce variability across the paper machine and associated processes?
AK: Drive and motion control systems have improved significantly over the years. Modern digital AC and DC drives provide better speed regulation, torque control, and web tension control, thereby improving machine stability. The use of regenerative drives also improves energy efficiency. Improved drive performance helps reduce sheet breaks and ensures the production of more consistent paper quality. However, digital drives pose a threat of power quality problems, which makes it essential to take necessary measures to mitigate power quality disturbances and maintain optimal drive performance.
Integrated automation and process data have transformed paper production from a process that primarily reacts to problems into one that can predict and prevent them.
PM: How are automation, advanced control, and integrated process data helping mills achieve more consistent paper quality? Which quality parameters have benefited most?
AK: Integrated automation enables different sections of the paper machine to communicate with each other. Process data is shared across the machine, allowing corrective actions to be taken before defects develop. If systems are not integrated, many opportunities for optimisation are lost.
Integrated automation and process data have transformed paper production from a process that primarily reacts to problems into one that can predict and prevent them. Among the various quality parameters, basis weight, moisture profile, ash and calliper have improved the most because they can be measured continuously and controlled automatically through closed-loop systems. This helps maintain consistent paper quality and makes the production process more stable and efficient.
PM: As control systems become more intelligent, how is the operator’s role in process control and decision-making changing?
AK: As automation becomes more advanced, the operator’s role is also changing. Instead of making frequent manual adjustments, operators now supervise automatic control systems, monitor process performance and system alarms & instructions, handle abnormal situations, and make decisions based on real-time process information and system recommendations.
To realise the full benefits of advanced automation, mills also need trained personnel who understand process analysis, advanced process control, data interpretation, AI-based tools, and digital troubleshooting. In many cases, operator training is as important as investing in new technology.
PM: What typically prevents a mill from achieving the full benefits of advanced automation and intelligent control? Please tell us more about issues such as legacy systems, data quality, system integration, instrumentation, workforce capabilities, etc.
AK: Many mills still face challenges when implementing advanced automation. Older control systems, disconnected equipment, incompatible communication protocols, limited instrumentation, poor-quality process data, cybersecurity requirements, and a shortage of skilled personnel all reduce the effectiveness of implementing advanced control systems. Reliable measurements and comprehensive process data are essential for successful implementation of advanced automation applications. A clear understanding and transparency between the system supplier and the mill personnel involved in the implementation is crucial for the successful and timely project execution.
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PM: Can you share a recent implementation that measurably reduced variability or improved quality consistency? What results were achieved, and where should mills prioritise investment next?
AK: One of our recent projects involved replacing a conventional hydraulic headbox with a modern dilution control headbox integrated with the approach flow system. The primary objective was to improve cross-direction (CD) basis weight control by reducing profile variations across the machine width. The dilution control headbox adjusts stock consistency across the machine width more accurately than the conventional system. This produces a more uniform basis weight profile, improves paper formation and fibre orientation, and thus improves overall process stability.
After commissioning the new system, we achieved better sheet formation, a significant reduction in CD basis weight variation, and a clear improvement in the 2-sigma profile. The machine now operates under more stable and repeatable conditions, resulting in more consistent product quality, reduced process fluctuations, and improved machine performance. This project clearly demonstrated the advantages of dilution control headbox technology in improving paper machine efficiency and product consistency.
Overall, modern automation has helped paper mills to reduce their process variability, resulting in improvement of paper quality and consistent production of high-quality products. This has led to cost savings by reducing fibre consumption, chemical and energy usage, improving machine uptime, and reducing waste.
In future, further improvements will come from better integration of automation systems, wider use of advanced process control systems, intelligent sensors, data analysis, and upgradation of older control systems with modern technology. The Indian paper industry has made significant progress in improving the level of automation across its operations. Today, most paper mills are implementing this strategy in their own way to achieve consistency of automation in operational processes to deliver quality products with the desired quality attributes.
Further improvements will come from better integration of automation systems, wider use of advanced process control systems, intelligent sensors, data analysis, and upgradation of older control systems with modern technology.
