Introduction
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.
Why This Course
- Designed specifically to meet Singapore’s 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
Who Should Attend
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.