CHEMMAT 759 : Industry 4.0 for Chemical Engineering

Engineering

2023 Semester Two (1235) (15 POINTS)

Course Prescription

In-depth coverage of digitalisation and Industry 4.0 in the context of modern biological, chemical, food and materials processing industries. Topics include model building, digital models and digital twins using process simulators, scripting, open source software and data-driven analysis using machine learning concepts, and the application of these to modelling a virtual plant.

Course Overview

Lectures 
Part I Introduction (2-3 lectures) 
• Industry 4.0 in general 
• Industry 4.0 (Internet of Things) IOT general introduction 
 
Part II: Digital models and Digital Twins (industrial process simulation) 
• Introduction to process models 
• Industrial process simulation 
• Developing digital models on industrial process simulators 
• Validating digital models on industrial process simulators 
• Introduction to dynamic models   
• Application of dynamic models and validation 
 
Part III:  Digital models and Digital Twins (including scripting and open source software) 
• Introduction to Python and MATLAB 
• Model building 
• Model application to unit operations  
 
Part IV: Data Driven analysis 
• introduction to data analytics 
• Statistical process control 
• Unsupervised machine learning 
• Supervised machine learning 
 
Workshops 
A digital model of a chemical engineering process will be provided for students to collect data from. Students can use the data to validate their own models for digital twin projects. Students also can apply data driven analysis on the data generated from the provided model.  Students will submit their reports including their digital twins and data analysis results at the end of semester. 

Course Requirements

Prerequisite: ENGSCI 311

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity

Learning Outcomes

By the end of this course, students will be able to:
  1. Explain the role of Industry 4.0 in process industries (including materials manufacturing) (Capability 1 and 4)
  2. Create digital models of unit operations (Capability 1, 2, 3, 4 and 5)
  3. Analyse multi-variate process data using machine learning concepts (Capability 1, 2, 3, 4 and 5)
  4. Apply digital twin technologies to a virtual plant (Capability 1, 2, 3, 4 and 5)

Assessments

Assessment Type Percentage Classification
Presentation 10% Individual Coursework
Project 40% Individual Coursework
Test 10% Individual Test
Final Exam 40% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4
Presentation
Project
Test
Final Exam

Students must sit the exam to pass the course. Otherwise, a DNS (did not sit) result will be returned.

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect approximately 20 hours of lectures, 20 hours tutorial/workshops, 30 hours of reading and thinking about the content and 80 hours of work on assignments and/or test/exam preparation.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities including labs/tutorials/studios/clinics to complete/receive credit for components of the course. 

Lectures will be available as recordings. Other learning activities including seminars/tutorials/labs/studios will not be available as recordings. 

The course may include live online events including group discussions/tutorials and these will be recorded. 

The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Health & Safety

The mode of delivery will be lectures and computer-based workshops.  Students will be advised in advance of any additional health and safety requirements. Further, students are expected to adhere to the guidelines outlined in the Health and Safety section of the Engineering Undergraduate Handbook.

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

  • Feedback from students SET reviews will be used for continuous improvements to the course in coming years. 

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 03/11/2022 09:54 a.m.