Big Data, Machine Learning and Sensors

This module covers main aspects of Big Data and AI in manufacturing processes, beginning from machin-ing operations and ending with production.

STARTING DATE: 2021-09-27

Overview
The module on “Big data, Machine learning and Sensors” covers main aspects of Big Data (BD) and AI in manufacturing processes, beginning from machining operations and ending with production quality control and production costs analysis.

The module includes the brief introduction to machining operations, more detailed consideration of machining dynamics and its influence on the process and production quality, monitoring the process parameters, sensors and data acquisition systems. A particular attention is given to Big Data analytics, data processing and data organization, development of Machine Learning (ML) algorithms and their implementation in manufacturing processes.

Learning objectives

  • Achieve a deeper understanding and competence in machining operations with focus on machining processes, machining dynamics and surface metrology (production quality)
  • Achieve a deeper understanding of the role of monitoring and measured data for strengthening the production sustainability.
  • Obtain knowledges on the data collection and analysis with focus on the Big Data (BD) problem on manufacturing level
  • Obtain knowledge and skills of use of Machine Learning (ML) means to solve Big Data (BD) analytics problems in manufacturing.
  • Obtain practical skills though implementation of AI methods in prediction, classification and optimization of production processes with focus on cutting processes, machining dynamics and surface quality analysis.

Module structure

The module is a mixture of self-study, webinars, and cross-company exercises.

Content

Five themes covering:

  • Manufacturing processes and parameters to be controlled
  • Introduction to data collection and analysis and Big Data
  • General introduction to Machine Learning and Neural Network
  • Machine Learning for Surface metrology applications

Expect videos, exercises, reflections that you share with other participants and much more.

Time commitment

To complete this module, the participant is expected to schedule approximately 4 hours per week over 5 weeks (20 hours in total).

The schedule

September 27 – The module starts
TBD – Program Module kick-off Webinar
TBD – Learning Team Workshop Meet your learning team for the first time

Important

After applying to the program, please secure dates in your calendar to be able to join planned webinars and assure time available required for learning.

A unique module created in co-operation between academic partners

This module is developed in collaborations with Lund University and Halmstad University.

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