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Unit outline_

QBUS3340: Operations Management

Semester 2, 2022 [Normal day] - Remote

This unit covers the fundamentals of operations management, an exciting area that has a profound effect on the productivity of both manufacturing and services. The techniques of operations management apply throughout the world to virtually all productive enterprises (i.e. offices, hospitals, restaurants, department stores and factories) - the production of goods and services requires operations management. The efficient production of goods and services requires the effective application of the concepts, tools, and techniques introduced in this unit. These include quality management, capacity planning, location and layout strategies, supply chain management and inventory control.

Unit details and rules

Academic unit Business Analytics
Credit points 6
Prerequisites
? 
BUSS1020 or DATA1001 or ECMT1010 or ENVX1001 or ENVX1002 or STAT1021 or ((MATH1005 or MATH1015) and MATH1115) or 6 credit points of MATH units which must include MATH1905
Corequisites
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None
Prohibitions
? 
QBUS2330
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Simon Loria, simon.loria@sydney.edu.au
Type Description Weight Due Length
Small continuous assessment Bi-Weekly Quizzes
MCQ and numerical type questions completed using MyOMLab
20% - 1 hour
Outcomes assessed: LO1 LO4 LO3 LO2
Final exam (Take-home short release) Type D final exam Final exam
Take home written exam
50% Formal exam period 2.5 hours
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Individual Assignment 1
Written report using Cadmus
15% Week 07
Due date: 16 Sep 2022 at 23:59
1200 words
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Individual Assignment 2
Written Report using Cadmus
15% Week 13
Due date: 04 Nov 2022 at 23:59
1200 words
Outcomes assessed: LO1 LO2 LO3 LO4
Online task hurdle task Weekly Homework
MCQ and Short Answer using MyOMLab. Hurdle task for Bi-weekly Quizzes
0% Weekly No time limit
Outcomes assessed: LO1 LO4 LO3 LO2
hurdle task = hurdle task ?
Type D final exam = Type D final exam ?

Assessment summary

  • Weekly homework: Completed online using MyOMLab which is accessed through Canvas. While there is no marks for completing these tasks, a 65% passing grade is a pre-requisite for access to the bi-weekly quizzes.
  • Bi-weekly Quizzes:  Completed online using MyOMLab which is accessed through Canvas. There are 4 quizzes worth 5% each – 20% in total.  Quizzes are held in Week 3, 5, 9 and 11. Each quiz will cover content from the previous 2 or 3 weeks. You will not be able to commence each quiz unless you have satisfactorily completed the previous weekly homework tasks.   
  • Individual assignment 1: A written report of up to 1,200 words supported by numerical analysis with quesions drawn from the first 5 weeks of the course. The report is submitted using Cadmus and must be to a professional standard.
  • Individual assignment 2: A written report of up to 1,200 words supported by numerical analysis with quesions covering the weeks 6 – 10 of the course. The report is submitted using Cadmus and must be to a professional standard. 
  • Final exam: A Short release take home exam submitted using Cadmus, covering content from week 1 – 13. It may comprise short-answer, numerical and/or extended response type questions aimed a examining students’ depth of understanding. There will be no MCQ questions.  

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

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Distinction

75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Credit

65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Pass

50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

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:

5% per day up to 50% of available marks for each assessment in accordance with Business School guidelines. Assessment tasks more than 10 days overdue will receive a zero mark.

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 operations and operations strategy Lecture and tutorial (3 hr)  
Week 02 Forecasting demand Lecture and tutorial (3 hr)  
Week 03 Analysing processes and capacity Lecture and tutorial (3 hr)  
Week 04 Quality management Lecture and tutorial (3 hr)  
Week 05 Statistic Process Control Lecture and tutorial (3 hr)  
Week 06 Layout strategies Lecture and tutorial (3 hr)  
Week 07 Location strategies Lecture and tutorial (3 hr)  
Week 08 Supply chain management Lecture and tutorial (3 hr)  
Week 09 Inventory management Lecture and tutorial (3 hr)  
Week 10 Scheduling Lecture and tutorial (3 hr)  
Week 11 Queues and congestion Lecture and tutorial (3 hr)  
Week 12 Lean operations Lecture and tutorial (3 hr)  
Week 13 Course and exam review Lecture and tutorial (3 hr)  

Attendance and class requirements

Lecture recordings: All lectures and seminars are recorded and will be available on Canvas for student use. Please note the Business School does not own the system and cannot guarantee that the system will operate or that every class will be recorded. Students should ensure they attend and participate in all classes.

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.

  • Heizer, J., Render, B., and Munson, C., 2019, Operations Management, 13th Edition, Global Edition, Pearson.

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. employ the tools and techniques of operations management that are used to drive competitive advantage for the firm
  • LO2. apply the concepts of lean operations and total quality management to improve the effectiveness, efficiency and quality of business processes
  • LO3. use analytical methods such as forecasting, linear programming and statistical process control to optimise operational decision making
  • LO4. identify how inventory management models, scheduling strategies and supply chain management techniques are used to improve the operational performance of companies.

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.

No changes have been made since this unit was last offered.

Work, health and safety

Full compliance with current Covid 19 regulations for F2F lectures and tutorials.

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.