04 Jun 2019
01 Apr to 17 May 2019
8 hours / 1 day
9am to 6pm
Mode of Training:
Predictive Analytics is the science of engaging statistical and data driven approaches to build models to represent real processes, for the purpose of comparative analysis as well as making predictions / forecasts. This is particularly so in the manufacturing environment where process monitoring and predictive models are very critical in pre-empting failure. In an automated manufacturing environment, process data is produced as at incredible rate and the ability to collect, store, analyse, model and predict process behaviour has become increasingly more important. Predictive Analytics for maintenance is an integral approach that unifies analysis, modelling and predictive approaches to help pre-empt failure and thus better manage maintenance activities. This course introduces basic skills to perform analytics for maintenance.
This is a basic course in Predictive Analytics for Maintenance The course aims to equip the participant with the following:
1. An appreciation of statistical concepts that underpin Predictive Maintenance ideas
2. An understanding of simple statistical process monitoring techniques used in tracking developments of critical measurements
3. An understanding of Correlation and Simple Regression Analysis used in degradation data monitoring / modelling
4. Simple ideas in failure time modelling that are useful in scheduling of preventive maintenance activities.
By the end of the course, learners will be able to:
• Recognise and apply simple statistical concepts used in Predictive Maintenance analysis
• Apply simple statistical process monitoring techniques to moniitor process outputs
• Use simple regression analysis to model degradation data in order to predict expected failure time
• Model failure time of product / system to better manage maintenance activities
• Basic Statistical Concepts and Distributions
• Statistical Process Monitoring of measurements
• Correlation and Simple Regression Analysis of Degradation Data
• Failure Time Modelling
Manufacturing Engineers, Engineers monitoring process/product / system degradation or failure
Minimum Entry Requirements / Assumed Skills and Knowledge
Participants with an engineering background who are involved in
monitoring manufacturing processes or equipment failure.
Award / Certification / Accreditation
• Certificate of Attendance
A Certificate of Attendance will be awarded to participants who meet at least 75% attendance rate
• Certificate of Performance
A Certificate of Performance will be awarded to participants who pass the examination and meet at least 75% attendance rate
Course Fees payable:
|Singapore Citizens aged below 40 and Singapore PRs||Singapore Citizens||Others|
|Non-SME sponsored||1Sponsored by SME||2Aged 40 and above||3Aged 35 and above, and earn ≤ $2,000 per month|
Singaporeans aged 25 years and above may use **SkillsFuture Credit balance to offset respective course fees.1 Under the Enhanced Training Support for Small & Medium Enterprises (SMEs) Scheme. For more information, click here2 Under the SkillsFuture Mid-career Enhanced Subsidy. For more information, visit the SkillsFuture website here.3 Under the Workfare Training Support (WTS) scheme. For more information on the scheme, click here.
1. SkillsFuture (SF) Series
Singaporeans and Singapore PRs are eligible for 70% course fee funding for registration with effect from 28 October 2017. This funding is applicable to both individual and company-sponsored participants. Participants are required to achieve at least 75% attendance and/or sit and pass any prescribed examinations/assessments or submit any course/project work (if any) under the course requirement.
Singaporeans aged 40 years and above will enjoy a 90% subsidy of course fee.
Funding Validity Period: Till 31 Dec 2020
2. SkillsFuture Credit** (SFC)
With effect from January 2016, Singaporeans aged 25 years and above who received their SkillsFuture Credit account activation letter will be eligible for an initial credit of $500 which can be used to pay for course fees for a range of eligible skills-related courses. The credits can be used on top of existing course fee subsidies/funding.
This is only applicable for self-sponsored applicants. Application via SkillsFuture Portal can only be made starting from 60 days before the course commencement date.
Withdrawal and Deferment
Withdrawal and deferment notice must be made in writing to the Professional & Adult Continuing Education (PACE) Academy, Singapore Polytechnic via email accordingly:Online Courses
- firstname.lastname@example.orgAll other Courses
For withdrawal cases, the portion of course fee to be refunded is based on the date of notice as follows:Classroom
- 2 weeks before the commencement of the course - Full refund
- Less than 2 weeks before commencement of the course - 70% refund
- On or after date of commencement - No refund
There will be no refund or transfer of course once the account has been created.
The Singapore Polytechnic reserves the right to cancel or postpone any of the courses. Applicants will be duly notified and where applicable, the full fees will be refunded.
The Singapore Polytechnic also reserves the right to amend the fees charged or the period and duration of the courses.
The data provided to Singapore Polytechnic will be kept strictly confidential and will be used for the purpose of course administration. The data may be passed on to the relevant organisations that require the information related to the course.
1. All applications must be made via Online Registration at www.pace.sp.edu.sg
Course fees can be paid by the following payment modes:
Credit Cards, Internet Banking, NETS (Not Applicable for company sponsored)
a) For e-payment using Visa/Master cards and Internet Banking, please click on the ‘Make e-Payment’ button on the acknowledgement page to proceed.
b) For NETS payment, you can pay at:
Blk T1A, Level 1
Mon-Fri: 8:30am to 7:30pm
c) Please make cheques payable to “Singapore Polytechnic”. Please cross the cheque and write the Registration Reference ID, Applicant Name and NRIC/FIN number on the back of the cheque. Mail the cheque to:
s 500 Dover Road
Blk T1A, Level 1
Please note that an administrative charge of $15 will be imposed for any returned cheques from the bank or financial institution.
2. All successful applicants will be notified with a letter of confirmation via email.