Courses Catalogue

Uncertainty Modeling For Industrial Engineering

COURSE CODE: MEC4224
COURSE CREDIT UNIT: 3
ACADEMIC PROGRAMME: Mechanical Engineering, Bsc
COLLEGE/SCHOOL/FACULTY: School of Engineering and Applied Sciences
STATUS: Elective
PROGRAMME TYPE: Undergraduate

Course Description


The course covers models and methods based on probability and statistics for industrial

engineering applications; random variables, expectation, distribution fitting, the reliability of systems, central limit theorem and interval estimates in the context of production and service systems.

COURSE JUSTIFICATION/RATIONALE:

To study how a computer can be applied in industrial engineering design.

COURSE OBJECTIVES

At the end of this course, the student should be able to:

  •    characterize uncertainty to perform decision-making under uncertainty,
  •  apply  probability  and  statistics  based  methods  for  analysis  and  prediction  in engineering systems 

LEARNING OUTCOMES

A student on completing this course is expected to:

  •    perform decision-making under uncertainty,
  •    use  probability  and  statistics  based  methods  to  analyse  and  predict  engineering systems.