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Course Date:
TBA
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Registration Period:
TBA
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Duration/Frequency:
8 hours / 1 day
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Mode of Training:
Practical Training
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Venue:
Singapore Polytechnic
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Funding:
Eligible for SkillsFuture Credit
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 monitor 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