The quality control system (QCS) is critical to modern papermaking. Digital tools and automation enable a continuous and proactive approach to collecting and analyzing real-time data from a QCS to improve preventive maintenance, speed up intervention, minimize downtime and optimize maintenance scheduling.

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_{Jacob Groth, ABB Pulp and Paper, Columbus, Ohio, United States, jacob.groth@us.abb.com

Donald Stanley, ABB Pulp and Paper, Columbus, Ohio, United States, donald.stanley@us.abb.com

Kevin Starr, ABB Pulp and Paper, Columbus, Ohio, United States, kevin.starr@us.abb.com

Tom Foster, ABB Pulp and Paper, Columbus, Ohio, United States, tom.foster@us.abb.com

Bob Haag, ABB Pulp and Paper, Columbus, Ohio, United States, bob.haag@us.abb.com

Robert Retlich, ABB Pulp and Paper, Columbus, Ohio, United States, robert.retlich@us.abb.com}

Every paper machine of any significant size has an online QCS that measures various properties of the produced paper. Without a QCS, papermakers would be producing paper blindly and would only discover defective product after the fact. Once a QCS is installed, maintenance and service are crucial for preserving and enhancing the quality, productivity and efficiency of the papermaking process. Here, QCS field service technicians play a pivotal role.

As QCS technology evolves, hardware, software and data management changes necessitate an expansion of the technicians’ responsibilities. Principally, it has become vital for them always to be connected to the QCS equipment in real time. The ability to also distribute data remotely to experts who can help solve problems brings resolution time down significantly. There will still be challenges – such as having the capacity for large data transfer or ensuring secure data encryption – when implementing this digital future within QCS service. However, these are problems that can be solved with a strong IT security team.

With this improvement in problem-solving based on digital tools, automation and skilled service personnel, mills can migrate their maintenance programs from reactive to proactive and beyond. This is all possible as a part of a digital revolution in QCS service.

Existing style of service

Currently, much of QCS service relies heavily on manual processes performed by on-site technicians whose tasks include scheduled preventive maintenance activities such as visual inspections, equipment functionality checks, cleaning, operator training, measurement correlation, key performance indicator (KPI) recording and control system security »01. These routine tasks demand precision and consistency to ensure optimal system performance.

However, this “clipboard” approach has limitations. Technicians can only perform a finite number of rounds daily and some equipment may be difficult to access or require downtime for maintenance. Additionally, this methodology provides only a snapshot of the system’s state, potentially missing gradual or intermittent issues. Data recording and sharing practices are also often not uniform, varying from paper trails to digital records.

Industry expectations and requirements

In today’s competitive manufacturing environment, customer requirements have never been higher. Companies are expected to deliver on-target, quality products as cost-effectively as possible. Optimization may not always mean improving the characteristics of the final product but rather decreasing costs and increasing production while maintaining the quality target. Such expectations make continuous improvement imperative.

Another pressure is the “changing of the guard,” where knowledgeable veteran employees leave the industry, taking their years of experience. Newer facility members need time to absorb the existing collective wisdom and become as proficient as their mentors. Digital data collection can make it easier to store, translate and relay that knowledge.

As a result of these circumstances, reliance on control systems has reached an all-time high and mills require ever more knowledge and expertise to keep up with today’s industry standards. To help mills reach their full potential, service providers such as ABB must look to the future to determine how best to serve their customers’ needs.

A modern digital approach to QCS service

The future of QCS service lies in enhancing the productivity of the field service team through digital tools and automation »02 – 03. Digital data collection and analysis can streamline routine maintenance, allowing technicians to focus on more complex and value-added tasks. This approach enables remote troubleshooting and near real-time data sharing with experts, reducing resolution times [1]. Moreover, trending and tracking data reveals patterns a few snapshots a week may not see, leading to fewer downtimes, a better understanding of equipment health and more incisive root-cause failure analyses.

These improvements are not limited to preventative maintenance rounds. The vast amount of data and remote connectivity to onsite equipment also allow corrective work to be completed. For example, an alert is reported to an off-site support engineer, informing them that a loop needs to be tuned or a setting needs updating. This engineer can then “remote in” from anywhere to perform that corrective action. They can then see the results of that action as quickly as the feedback can become available digitally. This saves them a trip onsite, speeds up corrective intervention and keeps the mill running with minimal interruption from service.

The mechanisms for sharing this data vary: email, text, online portal, or delivery directly onto a control room screen. Customizing these digital notification channels improves the service’s efficacy and prioritizing the highest-value outputs keeps reports lean and service teams engaged.

Safety is always paramount to a facility’s success. Streamlining the troubleshooting process with these improved tools lessens the chance of an unsafe scenario emerging. For example, after a shutdown, there is often a rush to restart, and operatives can be fatigued by the intensity of many tasks involved. Reducing the time required to solve issues and repair equipment mitigates risks here.

Another key improvement is the documentation of issues and their solutions – ie, the creation of an ever-growing knowledge base to share challenges, root-cause analyses and successes. Multi-site sharing of such a knowledge base can help a company solve an issue at one facility that was previously experienced and documented at a different facility. The knowledge base also facilitates a move to prescriptive maintenance.

Future digital services may include features like a “playbook” for responding to alerts and direct communication with support lines for immediate diagnostics. Some of these playbook pages may be standard operating procedures (SOPs), giving details on how to respond to the alerts to eliminate guesswork about the proper path forward.

The implications of machine learning (ML) and artificial intelligence (AI)

The introduction of ML is profoundly impacting process analysis by reducing bias and the time needed for detailed data analysis. Types of ML include supervised learning, unsupervised learning and reinforcement learning. Each type requires different granularities of training and testing data to build models that predict outcomes based on process variables. Model accuracy is verified against actual process data, making access to a wide range of such data, covering a multitude of conditions and situations, desirable.

ML will play a crucial role in evolving from predictive to prescriptive maintenance, offering faster and more accurate predictions than a team of human analysts.

ML is a subset of AI. Despite the current feeling that AI will be an immense improvement and should be adopted quickly, the integration of AI requires meticulous oversight to ensure the validity of its predictions. Human expertise remains essential to guide and validate AI outputs, preventing false correlations and ensuring reliable system adjustments. In any case, it will always be critical to have onsite service personnel as physical changes to hardware must be done on-site, in person, and many maintenance tasks cannot be digitized or otherwise automated.

Challenges and solutions in digital service delivery

Despite all the improvements that digital services can offer, there are still barriers to receiving all the potential benefits:

Data security:

Increasing digital threats require robust IT security measures.
Strong user account controls, permissions and data encryption are essential.

Customer readiness:

Some customers may be hesitant to adopt digital solutions.
Programs must be adaptable to match customers’ digital readiness and scalability.

Alarm rationalization:

Creating valuable, time-sensitive alerts without overwhelming users with data noise.
Involvement of experienced employees to set appropriate alert levels and reduce false positives.

A rapidly changing service world

The evolution of QCS service from manual to digitally enhanced methods promises significant improvements in maintenance efficiency and system reliability. By embracing digital tools and ML, QCS field service teams can transition from reactive to proactive maintenance strategies, achieving better performance and reducing downtime in paper mills. Data security, customer readiness and alarm rationalization challenges can be addressed through thoughtful implementation and continuous improvement, ensuring a successful digital transformation.

References
[1] Stanley, D. et al., “Advanced Data Strategies for Papermaking Optimization,” TAPPICon 2021, Atlanta, GA, 2021.
[2] Starr, K., “Automation Service Solutions for the 21st Century,” International Society of Automation, ISA 2016. Available: https://isa.ie/wp-content/uploads/2016/06/2016_ISA_Automation_Services_for_the_21st_Century-Kevin_Star.pdf. [Accessed June 7, 2024.]

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