Initial Situation:

How many people are necessary to operate a paper machine optimally? Due to the high degree of automation, actual operation is possible with a very small production team. Over the last 10 years, some paper manufacturers have increased the production volume per employee by a factor of 10! At the same time, paper production is and remains a complex dynamic process with many possible settings and influencing options in a complex production plant. Due to the high and still increasing number of sensors, a fully manual monitoring of the production process by only a few persons is impossible in practice. As a result, problems in the system or operating settings are often not detected. The consequences are unplanned downtimes and quality deterioration in the end product. In many cases, only time-consuming ex-post analyses are possible. Even though process control systems are offering alarming functionality, the checks made are rule-based using static limits without taking operating mode, grades or changes in settings into account. As a result, end users are flooded with alarms, which is why these alarming functions are usually only used to a very limited extent.

Smart Data Approach:

Fully automated and dynamic monitoring of thousands of process signals and alarms in case of unusual patterns in sensor data allow early identification of problems in production. With this new insight derived from data, downtimes can be prevented and product quality is improved. In the Smart Data alarming system, the normal behaviour of the machine is continuously dynamically derived from historical data, taking into account grades and operating modes. Dependent alarms are summarized and prioritized according to importance. In addition to sensor data, monitoring can also be flexibly applied to other data such as quality parameters or calculated indicators such as raw material consumption etc. Resulting alarms are presented in a user-friendly interface where they can be investigated and processed further by end-users with extended analysis functions.


  • Increase of OEE – potentially saving several hundred thousands of euro per year
  • Prevention of Downtimes
  • Improved quality of the final product
  • Predictive maintenance


  • Real-time Monitoring
  • Dynamic calculation of threshold values
  • Consideration of grades and production modes
  • Prioritization of alarms
  • Automated monitoring of raw material and energy consumption

Production Monitoring 4.0 in the Paper Industry – Reduced downtime, improved quality, predictive maintenance

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Date: January 2020
Author: Leon Müller
© 2020 avato consulting ag
All Rights Reserved.

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