MEEN41090 Eng. Decision Support Systems

Academic Year 2021/2022

An engineering decision support system (Eng. DSS) is an interactive computer-based system that serves the decision-making needs of engineering managers. It provides them with information that enables them to make both semi-structured and unstructured decisions. An Eng. DSS employs various analytical models to perform a low-level analysis of data and produce information. The DSSs can be classified into five types, namely Communication-driven DSS, Data-driven DSS, Document-driven DSS, Knowledge-driven DSS, and Model-Driven DSS. In this module, the Model-Driven DSS will be covered where quantitative models embedded in a Model-Driven (DSS) can help managers make better decisions.

Model-driven DSS use algebraic, financial, simulation, and optimisation models to provide decision support. Throughout this module, Discrete-Event Simulation (DES) and Mathematical modelling and analysis principles will be covered. The application of these models will be demonstrated on various problems from various disciplines such as logistics, production, service and network type systems. Model-Driven DSS provides the engineering managers and business analysts with an approach and set of tools to construct and analyse a model of a decision problem involving single or multiple objectives.

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Curricular information is subject to change

Learning Outcomes:

1. Relate the theoretical underpinnings of Eng. DSS analytics to managerial decision making.
2. Develop simulation and mathematical models of basic manufacturing, logistics, and service systems.
3. Apply various solution algorithms to solve linear, network, integer, and binary programming models.
4. Utilize simulation and mathematical computer software to solve modelled problems.
5. Demonstrate a high level of competency in applying the covered simulation and mathematical models to a variety of real-world business operational problems and projects.

Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities

45

Autonomous Student Learning

56

Lectures

24

Total

125

Approaches to Teaching and Learning:
This module utilized some of the key teaching and learning approaches used in higher education such as:
(1) Active/task-based learning; which is an approach where the planning of learning materials and teaching sessions are based around doing a task.

(2) Peer and group work: which is a form of voluntary association of members benefiting from cooperative learning, that enhances the total output of the activity than when done individually.

(3) Lectures: face-to-face presentation and discussions with module lecturers related to each topic.

(4) lab and tutorials: various types of related problems will be covered during these sessions.

(5) Case/Problem-based learning; which is a student-centered pedagogy in which students learn about a subject through the experience of solving a related project/problem.

(6) Student presentations: which requires students to present the outcomes of their projects individually or in a group. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Individual assignment Varies over the Trimester n/a Standard conversion grade scale 40% No

50

Examination: Examination assessment accounts for the final exam. 2 hour End of Trimester Exam Yes Standard conversion grade scale 40% No

50


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Summer Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Peer review activities

How will my Feedback be Delivered?

Not yet recorded.