Industry services

The I²C² team has an active research group of around ten PhDs across two universities with strong external and industrial links. Leveraging off our in house expertise we can assist implementation, tuning and maintenance of Advanced Process Control at your facility.

Process simulation / modelling

Process simulation

Process simulation is a model-based representation of chemical, physical, biological, and other technical processes and unit operations in software. Basic prerequisites are a thorough knowledge of chemical and physical properties of pure components and mixtures, of reactions, and of mathematical models which, in combination, allow the calculation of a process in computers.

Process simulation software describes processes in flow diagrams where unit operations are positioned and connected by product streams. The software has to solve the mass and energy balance to find a stable operating point. The goal of a process simulation is to find optimal conditions for an examined process.


Process optimisation is the discipline of adjusting a process so as to optimise some specified set of parameters without violating some constraint. The Industrial Information Control Centre, (I2C2) has recently completed a significant steam utility optimisation project for a major international oil and gas client. The project involved building and adapting process models for steam generators, boilers, gas turbines, condensers and interfaced these models with the client’s in-house process simulation software.

Advanced Process Control (APC)

The Industrial Information and Control Centre (I2C2) is a strong proponent of Advanced Process Control (APC) in general, and in particular a very powerful controller known as Model Predictive Control or MPC and optimisation techniques.

Model Predictive Control (MPC)

Model Predictive Control has widely been recognised as the most valuable advanced controller available to date. However the implantation and maintenance of such a controller requires significant resources and expertise.

The team are investigating the creation of support software to assess in real-time which models are suitable for MPC, what architecture one should use, and continually monitor the controller's performance for a major dairy client in New Zealand.


Process monitoring

Through analysis from statistical methods, process monitoring is a tool to ensure that processes are operated at its full potential to produce conforming product. Fault detection and diagnosis are two main parts of process monitoring.

Fault detection

Fault detection is recognising that a problem has occurred, even if you don't yet know the root cause. Faults may be detected by a variety of quantitative or qualitative means. This includes many of the multivariable, model-based approaches. It also includes simple, traditional techniques for single variables, such as

  • Alarms based on high, low, or deviation limits for process variables or rates of change.
  • Statistical process control (SPC) measures.
  • Summary alarms generated by package subsystems.

Fault diagnosis

Fault diagnosis is pinpointing one or more root causes of problems, to the point where corrective action can be taken. This is also referred to as “fault isolation”, especially when emphasising the distinction from fault detection. In common, casual usage, "fault diagnosis" often includes fault detection, so “fault isolation” emphasises the distinction.


  • Statistical Process Control (SPC)
  • Principle Component Analysis (PCA)
  • Partial Least Square (PLS)
  • Linear Discriminant Analysis (LDA)

Control Performance Assessment (CPA)

Control loop performance directly affects the operability and profitability of industrial plants. Considering the importance of control loops, one would expect that they always perform at their peak, but this is not the case. In fact, many studies have shown that roughly one third of industrial control loops perform poorly.

Poorly performing control loops can make a plant difficult to operate and have several costly side effects, including:

  • Reduced production rate.
  • Lower efficiency.
  • Poor product quality.
  • More off-spec product or rework.
  • Increased emissions.
  • Plant trips following process upsets.
  • Slower startup and transition times.
  • Premature equipment wear.

For these reasons, control loop performance should always be kept at the highest possible level. Control Performance Assessment (CPA) is a recently developed tool to evaluate the control loop performance. CPA includes the use of statistical and signal processing techniques to help judge performance and effectiveness of control schemes for purposes of:

  • Determination of performance benchmarks.
  • Diagnosis of underlying causes of poor performance.
  • Detection of poor performing loops.
  • Suggested improvement areas.

At present most CPA techniques are restricted to linear systems, but most industrial processes are nonlinear to some degree. As a result many important phenomena such as a control valve stiction cannot be linearised, and hence adequately approximated by analysis based on linear systems. Capitalising on the expertise of postdoctoral fellow Dr Wei Yu, the centre’s directors have developed new techniques to extend CPA into the general nonlinear systems including cases of valve stiction.

The I2C2 team has a very strong academic and applied industrial track record in control performance assessment both in developing GUI software and developing new algorithms to detect and quantify valve stiction.


Software design

JSteam Excel Add-in (Steam utility modelling software)

JSteam is an Excel 2007 add-in to allow process and energy engineers to be able to model a range of industrial steam utility systems within the familiar Excel environment. JSteam utilises the latest code optimisation features to enable high speed thermodynamics for near instantaneous model convergence.

Utility models are built around a graphical Process Flow Diagram (PFD) using standard PFD symbols inserted similarly to standard Excel shapes. Unit operation results and thermodynamic properties are calculated in user defined cell locations, and are linked using standard cell reference techniques.

Automatically inserted and formatted tables speed up the model building process which results in an easy to use and learn modelling system. Utilising Excel enables the model to be expanded across multiple Excel sheets to best suit the plant, model, and engineers preference.

JSteam is written using the latest code libraries from Microsoft to enable enhanced functionality including an intuitive Excel ribbon interface and function wizard.

Controller auto-tuning

The tuning of PID loops is tedious, error prone and fraught with complications. However I2C2 has developed auto-tuning software based on relays. This provides a quick and robust way for operators to re-tune poor performing control loops.

jMPC Toolbox

Developed by an I2C2 research engineer, the jMPC Toolbox is a mature MATLAB® Toolbox which enables research and development of MPC controllers within the powerful MATLAB® environment.

The jMPC Toolbox includes advanced features such as:

  • Full Simulink® integration for control of real processes via an external A/D & D/A interface.
  • Performance tuned Quadratic Programming (QP) solver.
  • Nonlinear simulations using Ordinary Differential Equation (ODE) models with automatic linearisation.
  • Advanced MPC features such as control move blocking, soft constraints and measured disturbance control.
  • Classroom focused Graphical User Interface (GUI) for teaching MPC.


Technical support

The Industrial Information and Control (I2C2) which was established in 2008 is a joint collaboration between Auckland University of Technology and The University of Auckland.

Our team is a multidisciplinary group of chemical, mechanical and electrical engineers with backgrounds in pulp & paper, oil & gas, diary, aluminium, manufacturing and bio-technology processes.

Contact us for further information or to discuss your requirements.


Flyers providing an overview of services and the methods we offer for solutions in industry based organisations.

Advanced Process Control (APC) solutions
Model predictive control & controller tuning (303.7 kB, PDF)
Process Simulation & Optimisation
Computer aided process modelling & optimisation (272.1 kB, PDF)
JSteam Excel Add-In
Steam utility modelling software (343.4 kB, PDF)