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Unit outline_

CHNG3806: Risk Management for Chemical Engineering

Semester 2, 2022 [Normal day] - Remote

This unit of study aims to develop an appreciation of project and risk management practice of process systems for chemical and process engineering. It employs a holistic approach to management covering vital concepts in project management, technical risk assessment and decision making, economic evaluation and financial risk assessment, and project design optimization. It provides students with the experience and working knowledge to solve real world engineering problems in process-led and product-driven industries. By the end of this unit of study a student should be competent in: preparing a resume for use in employment applications; developing project work plans in conjunction with project management schedules; performing economic evaluations of projects, plans and processes; performing qualitative and quantitative risk assessments of projects, plans and processes; exploring optimization of complex processes under risk and uncertainty, covering unit operations, business units, enterprises and value chains.

Unit details and rules

Academic unit Chemical and Biomolecular Engineering
Credit points 6
Prerequisites
? 
CHNG2801 and CHNG2802 and CHNG2803 and CHNG2804 and CHNG2806
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Enrolment in this unit of study assumes that all core 2000 level chemical engineering units have been successfully completed

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator David Wang, david.wang1@sydney.edu.au
Lecturer(s) David Wang, david.wang1@sydney.edu.au
Gustavo Fimbres Weihs, gustavo.fimbresweihs@sydney.edu.au
Type Description Weight Due Length
Assignment hurdle task group assignment Rapid ranking
Rapid ranking group work.
15% Week 04
Due date: 28 Aug 2022 at 23:59
10 pages
Outcomes assessed: LO1 LO2
Assignment hurdle task group assignment Syndicate exercise in HAZOP and review report
HAZOP group work (15%) Safety review report (10%)
25% Week 06
Due date: 11 Sep 2022 at 23:59
15 pages
Outcomes assessed: LO1 LO3
Assignment hurdle task Quantitative risk assessment
Take home quiz.
5% Week 07
Due date: 18 Sep 2022 at 23:59
5 pages
Outcomes assessed: LO4
Assignment hurdle task group assignment Equipment and production cost
Estimate cost of equipment.
20% Week 09
Due date: 09 Oct 2022 at 23:59
10 pages
Outcomes assessed: LO6 LO8
Tutorial quiz hurdle task Class quiz on depreciations, time value of money
Open book quiz.
10% Week 09
Due date: 07 Oct 2022 at 14:00
3 hours
Outcomes assessed: LO6
Tutorial quiz hurdle task Multi-Objective Optimisation Quiz
In-class quiz.
5% Week 13
Due date: 04 Nov 2022 at 14:00
3 hours
Outcomes assessed: LO7
Assignment hurdle task Economic evaluation and optimisation
Take home assignment.
20% Week 13
Due date: 06 Nov 2022 at 23:59
10 pages
Outcomes assessed: LO5 LO6 LO7 LO8
hurdle task = hurdle task ?
group assignment = group assignment ?
Group assignment with individually assessed component = group assignment with individually assessed component ?

Assessment summary

Assignments and Quizzes in this course are hurdle assessments which the passing mark is 60/100.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

 

Distinction

75 - 84

 

Credit

65 - 74

 

Pass

50 - 64

 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

Unless prior approval is granted by the course coordinator/lecturers, late submission will attract 5% penalty of the full mark per day.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to course and risk management Lecture and tutorial (5 hr) LO1
Week 02 Major incidents and hazard identification Lecture and tutorial (5 hr) LO1
Week 03 Risk management and rapid ranking Lecture and tutorial (5 hr) LO1 LO2 LO3
Week 04 HAZOP Lecture and tutorial (5 hr) LO1 LO2
Week 05 Week in industry Placement (5 hr) LO1 LO3
Week 06 Industry Safety Practices and Safety Review Lecture and tutorial (5 hr) LO1 LO3
Week 07 Quantitative risk assessment Lecture and tutorial (5 hr) LO4
Week 08 Engineering equipment costing Lecture and tutorial (5 hr) LO5
Week 09 Cashflows and time value of money Lecture and tutorial (5 hr) LO5 LO8
Week 10 Forecasting, depreciation, tax Lecture and tutorial (5 hr) LO6
Week 11 Economic evaluation of projects Lecture and tutorial (5 hr) LO7
Week 12 MultiObjective optimisations Lecture and tutorial (5 hr) LO6 LO7 LO8
Week 13 Water quality and impact assessment Lecture (2 hr) LO1

Attendance and class requirements

Students are expected to spend about 5 hours/week of independent/group study outside the specified contact periods.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed on the Library eReserve link available on Canvas.

  • Tweeddale, Mark. Managing Risk and Reliability of Process Plants. Boston, Mass: Gulf Professional Pub., 2007. 
  • Plant Design and Economics for Chemical Engineers. Peters, Timmerhaus and West. 0-07-239266-5. Fifth edition. McGraw Hill. 2003.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. describe and appreciate the implications of major hazard facility
  • LO2. perform qualitative risk assessment of projects using rapid ranking
  • LO3. perform detailed review of process design using Hazop technique.
  • LO4. perform a quantitative risk assessment of projects
  • LO5. estimate project costs from the flowsheet design
  • LO6. understand the implications of depreciation and tax in project costing
  • LO7. perform basic economic evaluation of projects and optimise design
  • LO8. understand the economies of scale in projects

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

Previous student evaluations identified an online approach to offer individual and group feedback on assignments via CANVAS and created more interactive tutorials to better contextualise industrial/contemporary relevance.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.