Students Industrial Work Experience III

Students on Industrial Work Experience Scheme (SIWES) are expected to: 1. be exposed and prepared for the Industrial work situation they are likely to meet after graduation, by developing their occupational competencies; 2. bridge the existing gap between theory and practice of programmes through exposure to real-life situations, including machines and equipment handling, professional work methods and ethics, human relations, key performance assessment methods, and ways of safeguarding the work environment – human and materials; 3. experience/simulate the transition phase of students from school to the world of work and the environment seamlessly,and expose them to contacts for eventual job placements after graduation; 4. be motivated to identify the industrial and practice engineering challenges of their place of engagement and the larger society and creatively device impactful solutions to them; and 5. exploit the opportunity to improve and utilise their acquired critical thinking and innate creativity skills, during the program and SIWES Seminar presentation respectively.

On- the -job experience in industry chosen for practical working experience but not necessarily limited to the student’s major (24 weeks from the end of the first semester at 400-Level to the beginning of the first semester of the following session. Thus, the second semester at 400-Level is spent in industry). Each student is expected to work in a programme related industry, research institute or regulatory agencies etc, for a period of 6 months under the guidance of an appropriate personnel in the establishment but supervised by an academic staff of the Department. On completion of the training, the student submits the completed Log book on the experience at the establishment., Also, there will be a comprehensive report covering the whole of the student’s industrial training experiences (GET 299, GET 399 and GET 499), on which a seminar will be presented to the Department for overall assessment. IPE 411 Some Mathematical Methods in Industrial and Production Engineering (3 Units C: LH 45) Learning Outcomes At the end, the student should be able to: 1. solve higher order linear and non-linear differential equations and apply them to modelling and design of systems. 2. state Lagragian functions and discuss its importance and application in engineering optimisation problem solving. 3. apply Laplace and Fourier transforms techniques to solve differential equations in industrial and production systems. 4. apply statistical methods like correlation, regression analysis in analysing, interpreting experimental data and probability theory in testing and quality control. Course Contents Integral Transforms: Laplace and Fourier transforms. Application to boundary value problems in Engineering Calculus of Variations: Langrange’s equation and applications to Industrial and Production Engineering Scenarios Probability: Probability laws, Conditional Probability and dependence of events. Discrete and continuous Probability distribution. Probability functions: Density function and Distribution Function. Expected Values, Moments. Standard Distributions involving Binomial, Poisson and Normal Distributions. Statistics: Regression and Correlation: Method of least squares, Linear and Introductory Non- Linear regressions, Total and Partial Correlation. Sampling theory: Sampling distribution of mean. Confidence Interval for mean and Proportion. Test of Hypotheses: Development of Null and Alternate Hypotheses. Decision making with Hypothesis. Types I and II errors. Industrial Application of statistics and probability theories.