Updated on 19 May 2023
Overview
In line with the need for companies in the manufacturing-related industry to strengthen their capabilities in quality assurance and yield optimisation, this GC will introduce key topics relevant to product design, process improvements, quality control and productivity improvements. Students are required to complete two courses from the following list of four courses:
ST5203 Design of Experiments for Product Design and Process Improvements
ST5208 Analytics for Quality Control and Productivity Improvements
ST5210 Multivariate Data Analysis
ST5212 Survival Analysis
Course Information
Admission Criteria
The minimum requirements for admission to the GC in QAYO are:
(i) Bachelor’s (without Honours classification) in one of the following degrees, or their equivalent-
(ii) Preferably with relevant work experience in quality assurance, productivity improvements or related areas.
(iii) Candidates with other qualifications and experience may be considered on a case-by-case basis, subject to approval by DSDS.
Maximum Candidature
The maximum period of candidature for the GC in QAYO is 36 months.
Award of Graduate Certificate
Students who have taken and completed the two (out of four) courses required for the proposed GC in a ‘stand-alone’ mode with a GPA of at least 2.50, within a period of not more than 36 months (equivalent to the maximum GC candidature period) will be awarded the Graduate Certificate in Quality Assurance and Yield Optimisation.
Students may repeat courses (with fees) to improve their GPA provided the maximum candidature is not yet exceeded and as per conditions imposed by the Department/Faculty.
List of Courses
The proposed courses in this GC will introduce key topics relevant to quality assurance and yield optimisation. This proposal recommends that students are required to complete two courses from the following list of four courses:
* ST5203 Design of Experiments for Product Design and Process Improvements
ST5208 Analytics for Quality Control and Productivity Improvements
ST5210 Multivariate Data Analysis
ST5212 Survival Analysis
*ST5203 introduces the students to techniques for investigating the product or process variables that affect product quality, with the objective of enhancing a product’s manufacturability, quality and field performance. ST5208 introduces the students to analytics that can be applied to product characteristics data for the purpose of process monitoring and control so as to maintain product quality. Methodologies for analysing multivariate data and survival data are introduced in ST5210 and ST5212, thereby equipping the students with the ability to carry out multivariate process control and reliability analysis.
All four courses are existing 4-units courses offered to undergraduate and postgraduate students for fulfilment of their respective programme requirements. We propose that they may also be offered as ‘stand-alone’ courses towards the GC, subject to the satisfaction of courses pre-requisites.
NUS will adopt three new academic terminologies from 1 August 2023 – “Module” will be renamed “Course”, “Modular Credit (MC)” will be renamed “Unit”, and ‘Cumulative Average Point (CAP)” will be renamed “Grade Point Average (GPA)”. For more information, please click here (undergraduate) or here (graduate).
Application and Programme Fees
Application
Candidates interested in the Graduate Certificate/modules within the Graduate Certificate must submit their applications via the Online Application portal under ‘Lifelong Learning Initiatives’ during the application period.
Programme Fees
Modular course fees are reflected on the application portal.
Alternatively, visit https://scale.nus.edu.sg/ . All enrolled candidates will also be required to pay the Student Services Fee per semester.
The University reserves the right to review and adjust the course fees and make changes to the programme structure and requirements as necessary and accordingly without prior notice.