Process performance software solutions

Digital solutions maximizing the profitability of industrial processes - in a repeatable, time-efficient and systematic manner

Process performance with ABB:  Our offering  |  Expert insights |  Your journey  |  Analyst views  |  Testimonials  |  Downloads |  Cyber security  | Digital transformation

If you are looking to capture additional throughput, recovery/yield and consistent quality while reducing energy and consumables -  accelerating autonomous operations in process industries
  • Push your process closer to constraints with Advanced Process Control and related technologies
  • Benchmark your current process performance and then evaluate potential benefit improvements through ABB Plant Fingerprints
  • Identify process models from data, capturing the intricate relations between various parameters
  • Foster continuous improvement based on monitoring and fine tuning with collaborative operations
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Our offering

Make the next step towards autonomous optimization for your process

by solution type
by industry & application
Advanced Process Control

Stabilize operations and then push towards process constraints with Model Predictive Control, Fuzzy Logic and nested logic functions
Performance optimization for control loops

Monitoring and management of base level PID control
AlarmInsight®

AlarmInsight® supports alarm management activities throughout the full lifecycle of the plant from designing alarms to verification and optimization.
Mining

Underground mine ventilation on demand, ore tracking, blending, grinding, flotation, dewatering
Cement

Rotary cement kilns and mills, alternative fuel management, material blending
Metals

Dry grinding, pellet firing & drying; energy recovery from blast furnace gas; profile rolling, cold rolling
Pulp and paper

Fiberline, chemical recovery; wet end control, paper quality, sheet break performance, virtual measurement

Expert Insights

Blog by Gajanan Rothe
Streamlining Paper Manufacturing
Blog by Ramon Luiz Bueno
My journey from Automation to Optimization
Blog by Ashwini Ujja
My APC journey that fueled growth and innovation
Blog by Bruno Maldi
The Advanced Process Control Experience
Blog by Akshay Patil
A junior’s journey into Advanced Process Control
Blog by Manoj Rengasamy
Mastering Advanced Process Control: A Professional Journey
Boiler & steam turbine optimization
Superior management of steam network complexity in industrial plants
by J. Sikström, R. Brown, R. Koorts
Digital twin / simulation model with Advanced Process Control at Boliden mine
Q&Awith Sanjit Shewale
Can a ML algorithm ever truly understand the dynamic conditions inside a cement plant?
by Abhijit Badwe
3 critical success factors observed from over 100 APC applications in pulp & paper
Max Tschurtschenthaler, Gregor Schuetz
Building an intelligent cement plant and a revolution in HMI
Automation project execution optimization

New technologies and methodology for faster and more cost-efficient project execution
by Tarun Mathur
Bar mill and wire rod mill optimization: profile rolling process goes digital
by Jan Nyqvist
Underground mine ventilation: how to improve safety and half energy costs
By Hakan Osterholm
Online and virtual measurements enable new closed loop control strategies for pulp quality
A simple way to know if your alarm management system is doing its job well
by Andre Herzog
Optimizing stockyard ­operations
By Tarun Mathur
Increase productivity, reduce energy consumption in iron and steelmaking processes
Paper winding science got smarter, providing up to 8% more capacity
ARC Advisory Group, Frost & Sullivan, Control Global
New technologies and methodology for faster and more cost-efficient project execution
By F. Lenders, N. Li, D. Janka and A. Cohen
Improving cold rolling mill performance with advanced data analytics
by Kevin Starr
An intuitive, non-mathematical explanation for control terms and tuning
Pulp and paper process optimization opportunities with digital technologies
by Ryan Koorts
Cement plant on autopilot: a practical guide to success
ABB Review
APC and Analytics: new tools revolutionize data analysis, reduce modeling effort

Analyst and ABB views

International Society of Automation
ARC Advisory Group
McKinsey

Innovative business models can secure the sustainability of the achieved benefits

ISA
"APC technology continues to evolve for many in the industry. Improved design and modern user interface modeling platforms facilitate data analysis and greatly reduce modeling effort. This offers users a greater flexibility in evaluating and testing models that best fit process data. This approach enables accelerated commissioning and online monitoring of advanced controllers."

Towards autonomous operation by Advanced Process Control, online optimization and analytics

ARC Advisory Group
"With the availability of more tools and better methodologies, an increasing number of companies are now starting to apply APC to smaller units that were difficult in the past to justify on an ROI basis. In addition, more transition and startup sequencing technology is being integrated with control applications to provide safer and more profitable operations. Incorporating rigorous modeling technology into the controller will also extend its applicable range and accuracy."

Advanced control techniques are also finding many applications in batch and semi-batch operations. This often includes performing multi-variable model predictive control (MPC). For processes featuring strong interaction among different units, MPC offers substantial performance improvements compared with traditional single-input, single-output control strategies. A feature of MPC is the ability to effectively manage multiple operational constraints.

The convergence of software tools and increasing integration of AI

McKinsey
"Enabling APCs to operate more efficiently requires a combination of regular tunings and a compre­hensive approach that addresses sensors, devices, and control loops, as well as educating and training control-room operators on the latest techniques. With the recent advances in computing power (and lower computing costs) APCs can be tuned using machine-learning models"
Advanced analytics can produce responsive insights from large amounts of historical data, increasing the speed of the tuning process and reducing human bias or intervention.

Develop a vision for your operations

Increase
in throughput

~5%


Increase
in yield

~3%


Reduction
in energy consumption

~10%


Reduction
in variability

~50%


High
utilization factor

~95-100%


Let's talk

Testimonials

A PULP MILL

"The new digital solution is a good example of how we can leverage our resources even better to increase our productivity and our margins. Operators are able to simulate both their own and overall processes in advance, helping to reduce the risk of unplanned shutdowns."

Ingela Ekebro, Project director at SCA pulp mill

SCA Östrand to increase pulp mill efficiency with integrated, digitalized automation solution

Producing an even quality pulp at a consistently high production rate is a challenging task. The raw material quality, such as chip size and chip moisture, tends to change with the seasons, natural geographic factors, and the wood source.

This marks the first time in the pulp industry that an integrated automation solution will manage end-to-end production — from the woodyard to the baling line — from a single control room. ABB Ability™ Advanced Process Control stabilizes pulp production, reduces chemical usage and coordinates the numerous loops to incur optimum, on-specification, pulp quality at minimum variance. It allows operators to have full control over the system and provides insight to keep power supply and production processes at continuous high levels.

Operators can control the system against key ratios, such as reducing operating costs while keeping processes within emissions restrictions. They are able to simulate both their own and overall processes in advance, helping to reduce the risk of unplanned shutdowns.
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A PAPER MILL

“Savings of 10% in filler consumption, 20% in retention aid consumption, 15% in polymer consumption, 10% production increase, 10% in sheet break reduction, and a decrease in production cost of $2.50/ton were achieved by effective control of the paper properties. Additionally, optimising the usage of chemicals and utilities, significantly reduced downtime and hence production costs.”

Paper mill in Indonesia

Proactively control retention & reduce ash variability with Wet End Control

Forming of a paper roll involves a series of highly complex processes and a misstep in any of these areas will lead to a defect in the sheet forming or weakening of the paper web, eventually leading to a sheet break or rejection due to poor quality. forming of a paper roll involves a series of highly complex processes and a misstep in any of these areas will lead to a defect in the sheet forming or weakening of the paper web, eventually leading to a sheet break or rejection due to poor quality.

Unlike most industrial applications still limited to reactive control schemes that offer mainly single-input single-output control, an MPC (Model Predictive Control) strategy provides a wide scope for proactive control that improves process stability at a lower operational cost.

ABB's Wet End Control APC for paper mills solution improves wet end stability, helping to reduce product variability, chemical usage and sheet breaks while improving machine runnability. To achieve this, it uses dynamic models that automatically adjust to process changes and optimally coordinate chemical dosages in presence of destabilizing back-end process changes.

Available as a subscription-based service, mills can further benefit from continuous monitoring and further control tuning for sustainable results.



A PELLETIZING PLANT

“Acting as an ‘autopilot’, the solution drives the process towards more profitable operation via modeling and optimization techniques. It reduces the need for operators to continuously monitor and modify processes around the clock. Remote access support and KPI tracking by ABB expects ensure that the benefits are sustained over the life cycle of the plant.”

Indian steel plant

Enabling ironmakers to squeeze more value out of existing processes

Pellet plant dryers face a range of operating challenges, including intermittent disturbances in feed rates, long process delays, and variations in the calorific value of the blast furnace gas (which makes temperature control difficult). Temperature limits are, therefore, often not met, resulting in insufficient drying of the material, negatively impacting energy consumption and productivity.

Control of the drying kilns, indurating machine burners and grinding circuits with conventional PID controllers is unstable, mainly due to process delays.

APC for metals maintained the individual temperature profile, delivering a 15% reduction in standard deviation for the indurating machine temperature profile along the indurating machine burner zone, improving pellet quality and reducing burner fuel consumption by ensuring burn-out temperature is reached at the right location.

APC maintained the outlet temperature of the iron ore dryer at the desired setpoint despite intermittent disturbance in feed rate and process delays.

APC was installed on a grinding circuit that included a roller-press with static V-separator and single chamber ball mill, improving control performance with a 4% productivity increase, 3% energy savings and 60% reduction of returns standard deviation.

A CEMENT PLANT

 ABB dramatically improved SO2 emission control and helped to significantly reduce hydrate consumption by 11%. "Previously we found it difficult juggling all the hydrate injection points with other pressing plant distractions. Now it is all handled by Expert Optimizer.”

Wolfgang Schulz, Plant Operator at CEMEX

ABB Ability™ Expert Optimizer improved SO2 emission control at a CEMEX plant in Germany

The CEMEX plant located in Rüdersdorf, Germany, already utilizing ABB’s Expert Optimizer on their RMP, mills and kiln, approached ABB to improve their emissions control system. The ultimate challenge was to reduce deviation around the operating target for daily SO2 emission.
ABB utilized established advanced process control techniques to reduce emission variability. This allowed the plant to run closer to targets and constraints, ensuring zero emission violations while decreasing unnecessary hydrate overdosing and consumption. 

The controller reduced operator workload by automatically optimizing the short-term exhaust SO2 target based on the current daily average. There are two optimization modes that allow the operator to select either normal or aggressive optimization, based on whether to target the daily average below the limit at the end of the day or within the next 30 minutes. ABB Ability™ Expert Optimizer automatically adjusts the multiple feeder points of lime hydrate to ensure the SO2 and HCL targets are stringently met.
A MINING CONCENTRATOR

A study highlights the value of simulations and exciting development opportunities with the AI technology. "It is important to use accurate simulation models and well-defined goal functions. Because an algorithm is only able to solve the problems formulated for it, process know-how and experience are at least as important in this type of development as classic process control."

 Johannes Sikström, Project Manager at Boliden

A study was conducted at Boliden to see if technology is available today that could make concentrators self-learning.

"We directed our attention to the grinding process in Aitik, where we have a well-developed simulation model. We wanted to see if AI was able to do better than our existing control strategy. "

“At systems technology, we develop dynamic simulations of our processes. These simulations can be used in the same way as a game where we define what is a win and what is a loss. In the case of self-learning algorithms – so-called deep learning or reinforcement learning – the challenge is the great quantity of data necessary for the algorithm to learn enough about the system for it to make effective decisions. 

This is why games are such a major area within AI research. Games are well suited to enable algorithms to train themselves, and what constitutes a successful result – a win – is also well defined,”
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Cyber security and data ownership

Industrial cyber security guide
ABB's process performance digital solutions support all the deployment variants needed: on premise, on ABB managed or customer manages cloud, on customer private cloud / data center. You own your data. We ensure defence in depth cyber security, data protection, reliability, privacy, intellectual property.

The Cyber Security Reference Architecture is an ABB-developed design standard for industrial systems and associated security controls. ABB engineering teams use the architecture during system deployments, and ABB service units use it to update and modernize existing customer networks to bring them in line with current cyber security standards and best practices.

ABB Ability™ digital services have successfully improved the cyber security of industrial sites across the globe. Many customers have scheduled risk assessments as part of their ongoing annual service agreements, while others have implemented cyber security analytics dashboards to continuously monitor, diagnose and resolve security issues.

Compliance

ABB’s security measures in the Reference Architecture meet or exceed IEC 62443-3-3 security level 2 (SL2) as defined in foundational requirement section 5 (RE5). It also aligns with other common standards such as the NIST framework, ISO 27001 and NERC-CIP. Implementing the reference architecture does not guarantee passage of external certification audits; however, ABB can support compliance for specific security standards with additional recommendations.

Digital transformation partnership: you think big, we get practical.

For every industrial operation ambitious about Industry 4.0, ABB has built a framework to help drive and manage a complex change.
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