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Industrial analysis 780


 
Module code BAN 780
Qualification Postgraduate
Faculty Faculty of Engineering, Built Environment and Information Technology
Module content

Descriptive models are used to describe how systems or processes operate, and the outputs of these models are used as inputs for prescriptive and predictive models. Therefore, the first part of this module focuses on descriptive modelling and covers the basic approaches to data and statistical analysis.

In cases with numerous design or redesign options, mathematical programming is a powerful modelling tool that can be used to find the best design to implement. Therefore, the second part of this module covers the basics of mathematical programming and optimisation, and teaches students how to formulate, solve, and interpret results of Linear Programming (LP) and Mixed Integer Linear Programming (MILP) models.

After the best design is identified, predictive models are used to predict whether a new design or improvement will have the desired effect, before its implementation. Therefore, the final theme of this module introduces students to discrete-event simulation modelling, a popular predictive modelling approach.
Module credits 16.00
NQF Level 08
Service modules Faculty of Natural and Agricultural Sciences
Prerequisites Industrial Engineering students may not register for this module
Contact time 24 contact hours per semester
Language of tuition Module is presented in English
Department Industrial and Systems Engineering
Period of presentation Semester 1 or Semester 2
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