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Home * Courses * Modular Programmes * Data Mining Techniques

Data mining techniques are increasingly important for data-intensive manufacturing operations as the industry faces a number of challenges such as equipment and material condition variations, trial-and-error in process parameter setting, product quality inconsistencies, low capability of root cause discovery, process performance prediction and process parameters/recipe auto tuning. By applying data mining techniques, a company can improve its product quality and manufacturing productivity.

This WSQ course aims to provide a good understanding of the fundamentals of data analytics and data mining techniques for different manufacturing applications. Participants will learn techniques for advanced clustering methods for product quality management, correlation modelling, and data pattern methods for root cause analyses and neural networks for process performance prediction.

Data Mining Software

Module | Implement Manufacturing Data Mining Techniques

Since 3 November 2014, electronic certificates (e-Certs) are issued by SkillsFuture Singapore (SSG) to participants who have attended and attained competency in the Singapore Skills Framework training modules.. Visit here for more information about the e-Cert.

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  • Designed to specially cater to local industry demand
  • Highly practical and intensive
  • Latest knowledge and up-to-date technology
  • Case studies highlighting industrial applications
  • Expert trainers in the field with industrial experience

This course is designed for operation directors and managers, production/process engineers, R&D Engineers and IT support staff working on processes, production and quality improvement in manufacturing industries such as precision engineering, aerospace, automotive electronics, semiconductor, oil and gas, pharmaceutical and medtech.

Fundamentals of Data Mining

  • Introduction to data mining concept and applications in manufacturing
  • Process correlation modelling and data pattern analyses through statistical methods
  • Advanced data clustering technologies for anomaly detection and classification
  • Process performance prediction using artificial intelligence (neural networks, etc)

Case Studies by Grouping Projects Using Real Production Data

  • Data preparation
    • Problem statement
    • Technical challenges
    • Project objectives
    • Data collection and pre-processing
  • Data analysis
    • Major factor identification by correlation efficient analysis
    • Correlation modeling by multiple regression method and root cause analysis
    • K-means clustering and pattern based regression modeling
    • Correlation modeling by fuzzy neural networks method for quality estimation
    • What-if predictive analysis for process improvement & DOE design
    • Root cause analysis for major factor identification
    • Project conclusion
  • Improving plan
    • Identifying yield improvement areas
    • Production/process improvement plan

  Dr Li Xiang is a Senior Scientist and Team Lead in SIMTech. She has more than 20 years of experience in research on computational intelligence, data mining, and statistical analyses such as neural networks, fuzzy logic systems, unsupervised data clustering, and regression modelling. Her research expertise includes data mining and knowledge discovery, decision support systems, in-situ process monitoring and quality control. She is a member of the IEEE.

View Dr Li Xiang's researcher portfolio here.

Click here to view the above video on YouTube.

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  • Applicants should possess a degree in any discipline or a diploma with a minimum of 3 years of related working experience.
  • Proficiency in written and spoken English

Module Names

Full Course Fee (before SkillsFuture Funding and GST)

Type of Sponsorship
Implement Manufacturing Data Mining Techniques

    Funding Schemes for this Programme:

    Please note that fees and funding amount are subject to change.

    For more information on the SkillsFuture funding you are eligible for, please visit

    Singapore Institute of Manufacturing Technology
    2 Fusionopolis Way Innovis Level 8
    Singapore 138634

    How to Reach SIMTech@Fusionopolis Two
    Visitor Parking at Fusionopolis Two

    This programme is associated with the below SIMTech centre. Click on the image to visit its website.

    PE WSQ Programme in Implement Manufacturing Data Mining Techniques

    Module Name

    Skills Course Reference Number

    Schedule Dates


    Implement Manufacturing Data Mining Techniques (42 hours)

    CRS-Q-0033851-PRE 6 Jan 2020 - 20 Apr 2020  
    Click here to visit the programme webpage.

    Click here to view/download the programme collaterals.

    Click on the schedule dates to view the module calendar.


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    Only attendees will receive the email link to access the photo album from GC2019.


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