ULMS Electronic Module Catalogue

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title OPERATIONS MODELLING AND SIMULATION
Code EBUS504
Coordinator Dr X Xing
Operations and Supply Chain Management
X.Xing3@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2023-24 Level 7 FHEQ First Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

 

Modules for which this module is a pre-requisite:

 

Programme(s) (including Year of Study) to which this module is available on a required basis:

 

Programme(s) (including Year of Study) to which this module is available on an optional basis:

 

Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours 20

    10

    30
Timetable (if known)              
Private Study 120
TOTAL HOURS 150

Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
             
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Simulation There is a resit opportunity. Standard UoL penalty applies for late submission. This is an anonymous assessment. Assessment Schedule (When): Semester 1    100       

Aims

To understand a range of modelling analytical methods and their appropriate applications;

To understand the dynamic nature of systems and their behavioural characteristics;

To understand how real system modules are developed, tested and validated;

To develop confidence in the use of commercially available simulation tools such as Excel, Witness, Matlab and Vensim.


Learning Outcomes

(LO1) Be able to design models for business process reengineering;

(LO2) Be able to specify and justify a computer simulation for business process modelling;

(LO3) Be able to apply statistical and analytical techniques for business optimisation and evaluation.

(S1) Adaptability
Students will develop adaptability by engaging with case studies from their lab sessions in order to understand modelling and simulation processes and the features of different modelling tools.

(S2) Problem solving skills
Students will develop problem solving skills through lab sessions and case studies as part of their assignment.

(S3) Commercial awareness
Students will develop knowledge of commercial contexts of technology applications.

(S4) Teamwork
Students will be expected to work together in groups for some lab sessions.

(S5) Organisation skills
Students will be expected to work together to solve some hands-on case studies jointly.

(S6) Communication skills
Students will develop communication skills by engaging with case studies, report writing and working in groups.

(S7) IT skills
IT skills will be developed during practical lab sessions.

(S8) International awareness
Students will develop international awareness through case studies of business and technologies in an international context.

(S9) Lifelong learning skills
Students will develop skills of lifelong learning through preparation for their assessments and self-directed study of cases in preparation for class discussions.

(S10) Ethical awareness
Students will develop their awareness of ethical issues through research and preparation for assessment.

(S11) Leadership
Leadership skills will be developed during in-lecture discussions and lab session practices.


Teaching and Learning Strategies

2 hour lecture x 10 weeks
2 hour lab x 5 weeks
120 hours self-directed learning


Syllabus

 

Introduction to modelling theory.

The use of modelling to support Inventory management, the witness interface for process simulation.

The use of Discrete event simulation, industry examples.

Flow diagram approaches and the application in case studies from industry.

Data analytics tools to support data processing, modelling and simulations, data analysis techniques.

The use of System dynamic Modelling.

Demonstrating the practical aspects of developing simulation models with a review of the benefits and problems encountered.

Assignment Exercises.


Recommended Texts

Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.