Course coordinator
Professor Anh Nguyen
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Chemical Engineering School
This course involves the application of optimization and advanced control to identify potential improvements of industrial processes. Fundamental principles of formulating and solving optimization problems are introduced, along with critical interpretation of results and practical considerations in implementation of optimization output. The principles of Advanced Process Control are introduced and applied to industrial applications. Emphasis is on applying advanced control structures (e.g., equation-based control, etc.) to optimise existing processes. Students will be able to model the benefits of proposed control structures to justify their use in complex unit operations. Part of the justification will involve consideration of hardware and cost factors in implementing various control structures.
The efficient use of natural resources and implementation of sustainability within the process industries relies on the application of optimization theory and practice. Many complex problems of different nature arise in meeting the challenge of efficient use of resources, be they time, money, energy, raw materials and people. This course gives a broad overview on optimization and the practice of model formulation and solution on industrially relevant problems. For advanced single and multi-variable control, optimization strategies are important. The course introduces the theory and practice behind model-based multivariable control and its implementation.
Course requirements
Assumed background
This course assumes completion of the UQ BE Chemical Engineering program and particularly the outcomes from courses in unit operations, flowsheeting, basic process control and mathematics. It also assumes basic programming skills and a working knowledge of Simulink.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
CHEE3007 and (CHEE4060 or CHEE2020)
Restrictions
Permission is required from the HoS to enrol, please contact studentenquiries@chemeng.uq.edu.au
Course contact
Course staff
Lecturer
Professor Anh Nguyen
Tutor
Mr Dave Somasundaram
Mr Braden Fritz
Timetable
The timetable for this course is available on the UQ Public Timetable.
Aims and outcomes
This course will address the issues of system-wide optimization of processes, and their subsequent control. It will look at the benefit of optimization and also improved control performance. A range of optimization approaches that can be used to address system-wide and sub-unit optimization will be investigated, taking into account the underlying nature of the process. This includes constrained linear and nonlinear behaviour, steady state and dynamic situations, as well as discrete decision variable cases. In achieving optimized operation, a range of advanced process control (APC) applications will be addressed. This aspect considers advanced control for single input, single output systems and also multivariable control which relies on the use of process models and optimization methods to compute control moves. Practical aspects of implementation are addressed.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Identify opportunities for optimization and advanced control to improve performance in process systems
LO2.
Identify and formulate a range of optimization approaches to address design, control, sustainability and scheduling problems in the process industries, taking into account the characteristics of the process
LO3.
Generate optimal solutions to complex industrial problems through the application of specialised optimization codes, and interpet what actions should (or should not) be taken based on your findings
LO4.
Synthesize, apply and evaluate advanced SISO methods for difficult-to-control systems
LO5.
Formulate appropriate models and apply them to generate MPC applications to industrial processes, assessing the performance benefits of advanced process control
LO6.
Apply critical thinking skills to analyze, synthesize and effectively communicate technical information
LO7.
Demonstrate professional conduct in engaging with industry, including an appreciation of sustainability
LO8.
Improve teamwork skills through practice, reflection, feedback and change
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Paper/ Report/ Annotation, Performance |
Individual exercises
|
20% Hurdle |
24/03/2025 3:00 pm 2/05/2025 3:00 pm |
| Paper/ Report/ Annotation, Performance, Presentation, Project |
Project Part A Presentation and Report
|
25% |
31/03/2025 4:00 pm 11/04/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113 |
| Paper/ Report/ Annotation, Participation/ Student contribution, Presentation |
Project Part B Presentation and Report
|
25% |
19/05/2025 4:00 pm 30/05/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113 |
| Examination |
Exam During Exam Period (School) - Individual Oral Defence
|
30% Hurdle |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
A hurdle is an assessment requirement that must be satisfied in order to receive a specific grade for the course. Check the assessment details for more information about hurdle requirements.
Assessment details
Individual exercises
- Hurdle
- Online
- Mode
- Written
- Category
- Paper/ Report/ Annotation, Performance
- Weight
- 20% Hurdle
- Due date
24/03/2025 3:00 pm
2/05/2025 3:00 pm
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
Individual exercise 1 Due 24 Mar 15:00 Weight: 10%
Performance on nominated individual case studies and set tasks, from Part A content.
Individual exercise 2 Due 2 May 15:00 Weight: 10%
Performance on nominated individual case studies and set tasks from Part B content.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
For an overall grade of 4 or higher in this course, students require an overall grade >=50 % AND an average grade across the individual assignments >=50 % AND grade >=50 % on individual oral defence.Submission guidelines
Submission through Blackboard: Turnitin.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 1 grade for each 24 hour period from time submission is due will apply for up to 7 days. After 7 days you will receive a mark of 0.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Project Part A Presentation and Report
- In-person
- Online
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation, Performance, Presentation, Project
- Weight
- 25%
- Due date
31/03/2025 4:00 pm
11/04/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113
- Learning outcomes
- L01, L02, L03, L06, L07, L08
Task description
Project presentation Part A Due Mar 31 Mar 16:00 Weight: 5%
Presentation to students, staff and industry personnel. A single, combined presentation will be completed for both the CHEE7111 and CHEE7113 components of the project. Students will be required to mark and respond to presentations by other groups, as well as present their own work.
Each group will upload a presentation to Blackboard prior to the scheduled presentation time, then either play a recording of their presentation or present live, and then respond live to questions and comments from teaching staff, classmates and industry partner.
Exact timing will depend on availability of industry clients, estimated due date is class time on this date.
Project report Part A Due 11 Apr 15:00 Weight: 20%
A team-based project focussed on a process system of complex nature. It will involve both written submission and team-based presentation to the client(s).
The single project report will cover Part A projects from both CHEE7111 and CHEE7113.
Submissions will be through Blackboard. A Turnitin link will be made available before the due date.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit presentation files via Blackboard. Presentations will be held during class time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 1 grade for each 24 hour period from time submission is due will apply for up to 7 days. After 7 days you will receive a mark of 0.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Project Part B Presentation and Report
- In-person
- Online
- Mode
- Oral, Written
- Category
- Paper/ Report/ Annotation, Participation/ Student contribution, Presentation
- Weight
- 25%
- Due date
19/05/2025 4:00 pm
30/05/2025 3:00 pm
Single combined submission for CHEE7111 and CHEE7113
- Learning outcomes
- L04, L05, L06, L07, L08
Task description
Project presentation Part B Due 19/05 16:00 Weight: 5%
Presentation to students, staff and industry personnel. A single, combined presentation will be completed for both the CHEE7111 and CHEE7113 components of the project. Students will be required to mark and respond to presentations by other groups, as well as present their own work.
Each group will upload a presentation to Blackboard prior to the scheduled presentation time, then either play a recording of their presentation or present live, and then respond live to questions and comments from teaching staff, classmates and industry partner.
Exact timing will depend on availability of industry clients, estimated due date is class time on this date.
Project report Part B Due 30/05 15:00 Weight: 20%
A second project dealing with course content and skills applied to a process design or operational issue. It will involve both written submission and team-based presentation to the client(s).
The single project report will cover Part B projects from both CHEE7111 and CHEE7113.
Submissions will be through Blackboard. A Turnitin link will be made available before the due date.
Artificial Intelligence (AI) and Machine Translation (MT) are emerging tools that may support students in completing this assessment task. Students may appropriately use AI and/or MT in completing this assessment task. Students must clearly reference any use of AI or MT in each instance. A failure to reference AI use may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submit presentation files via Blackboard. Presentations will be held during class time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 1 grade for each 24 hour period from time submission is due will apply for up to 7 days. After 7 days you will receive a mark of 0.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Exam During Exam Period (School) - Individual Oral Defence
- Hurdle
- Identity Verified
- In-person
- Mode
- Oral
- Category
- Examination
- Weight
- 30% Hurdle
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Learning outcomes
- L01, L02, L03, L04, L05, L06, L07
Task description
This is an oral assessment: you will speak on a topic of your choosing for 3 minutes, then defend your comments on that topic and respond to other questions related to the course.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI) or Machine Translation (MT). Students are advised that the use of AI or MT technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Hurdle requirements
For an overall grade of 4 or higher in this course, students require an overall grade >=50 % AND an average grade across the individual assignments >=50 % AND grade >=50 % on individual oral defence.Exam details
| Planning time | no planning time minutes |
|---|---|
| Duration | 30 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed Book examination - no written materials permitted |
| Exam platform | Other |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Assessments must be submitted on or before the due date. Late submissions of assessment items will only be accepted if approval for late submission has been obtained prior to the due date.
Penalties Apply for Late Submission
Refer PPL Assessment Procedure Section 3 Part C (48)
A Student Access Plan (SAP) can only be used for a first extension. Extensions based on an SAP may be granted for up to seven (7) days, or the maximum number of days specified in the Course Instance (CI), if it is less than seven (7) days. Any further extensions will require additional supporting documentation, such as a medical certificate.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Description |
|---|---|
| 1 (Low Fail) |
Absence of evidence of achievement of course learning outcomes. Course grade description: Typically <20 %. As for grade 2. |
| 2 (Fail) |
Minimal evidence of achievement of course learning outcomes. Course grade description: Typically 20-44 %. Demonstrates clear deficiencies in understanding and applying fundamental concepts; communicates information or ideas in ways that are frequently incomplete or confusing and give little attention to the conventions of the discipline. Grade scores below 3 indicate lack of professional competence in the course material and/or students have failed to complete sufficient assessment items for these requirements to be assessed. |
| 3 (Marginal Fail) |
Demonstrated evidence of developing achievement of course learning outcomes Course grade description: Falls short of satisfying basic requirements for a Pass, due to not demonstrating required competence in assessment and/or failure to complete sufficient assessment for competence to be reasonably assessed. Overall grade typically 45-49% AND/OR grade <50 % across the individual assignments AND/OR grade <50 % on individual oral defence. |
| 4 (Pass) |
Demonstrated evidence of functional achievement of course learning outcomes. Course grade description: For an overall grade of 4 or higher in this course, students require an overall grade >=50 % AND an average grade across the individual assignments >=50 % AND grade >=50 % on individual oral defence. |
| 5 (Credit) |
Demonstrated evidence of proficient achievement of course learning outcomes. Course grade description: For an overall grade of 5 in this course, students typically require an aggregate score of 65-74% AND overall grade >60 % across individual assessment items. |
| 6 (Distinction) |
Demonstrated evidence of advanced achievement of course learning outcomes. Course grade description: For an overall grade of 6 in this course, students typically require an aggregate score of 75-84% AND overall grade >70 % across individual assessment items. |
| 7 (High Distinction) |
Demonstrated evidence of exceptional achievement of course learning outcomes. Course grade description: For an overall grade of 6 in this course, students typically require an aggregate score of at least 85% AND overall grade >80 % across individual assessment items. |
Supplementary assessment
Supplementary assessment is available for this course.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Library resources are available on the UQ Library website.
Additional learning resources information
Edgar, T.F., Himmelblau, Lasdon, D.M. (2001), Optimization of Chemical Processes, 2nd Edition, McGraw-Hill, New York.
Biegler, L., Grossmann, I., Westerberg, A. (1997), Systematic methods of chemical process design, Prentice Hall.
Reklaitis, G.V., Ravindran, A., Ragsdell, K.M. (1983), Engineering Optimization: methods and applications, Wiley.
Marlin, T.E. (2000), Process control: Designing processes and control systems for dynamic performance, 2nd edition, McGraw-Hill, ISBN 0-07-039362-1.
AIMMS optimization system
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Multiple weeks |
Problem-based learning |
Part A: Process optimization Students will be introduced to key aspects of process optimization during workshop sessions, then apply these skills in tutorial and guided sessions to complete an individual assignment and industry-based group project. Topics covered include: Why, where, when of optimization: Best; Importance/GOP; Application areas: tank design(s), railcar allocation issue; Numerical solution fundamentals: Analytic, Numerical methods, Application areas; Modelling and solving linear problems (Linear programming, LP), introduction to GAMS: Modelling and solving non-linear and mixed problems and batch operations (Non-linear programming, NLP, Mixed Integer Programming, MILP). Guest lectures and engagement with industry partner will take place in parallel with the tutorials and workshop sessions. Learning outcomes: L01, L02, L03, L06, L08 |
Problem-based learning |
Part B: Process control Students will be introduced to key aspects of process control during workshop sessions, then apply these skills in tutorial and guided sessions to complete an individual assignment and industry-based group project. Topics covered include: multivariable control using model predictive control (MPC). Principal and basis for model predictive control, and internal model control (IMC); introduction to multivariable model predictive control: dynamic matrix control (DMC). Guest lectures and engagement with industry partner will take place in parallel with the tutorials and workshop sessions. Learning outcomes: L01, L04, L05, L06, L08 |
|
Problem-based learning |
Part A: Process optimization NOTE THAT ALL CHEE7111 AND CHEE7113 TIMETABLED CLASSES IN WEEK 1 WILL BE DEVOTED TO CHE7111 , AND IN WEEK 2 ALL CHEE7111 & 7113 CLASSES WILL BE DEVOTED TO CHEE7113. FROM WEEK 3 ONWARD, CHEE7111 AND CHEE7113 CLASSES WILL RUN EACH WEEK. Students will be introduced to key aspects of process optimization during workshop sessions, then apply these skills in tutorial and guided sessions to complete an individual assignment . Topics covered include: Why, where, when of optimization: Best; Importance/GOP; Application areas: tank design(s), railcar allocation issue; Numerical solution fundamentals: Analytic, Numerical methods, Application areas; Modelling and solving linear problems (Linear programming, LP), Modelling and solving non-linear and mixed problems and batch operations (Non-linear programming, NLP, Mixed Integer Programming, MILP). Learning outcomes: L01, L02, L03, L06, L08 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.
School guidelines
Your school has additional guidelines you'll need to follow for this course:
- Safety Induction for Practicals
Course guidelines
Anyone undertaking courses with a practical component must complete the UQ Undergraduate Student Laboratory Safety Induction and pass the associated assessment.
Specific instructions, usage guidelines and rules for each of the undergraduate laboratories will be delivered as part of each course.
In some cases, students may be required to attend a specific face-to-face laboratory induction/training session.