Print Course syllabus
Course syllabus - Industrial Data Analytics
Scope
7.5 credits
Course code
PPU317
Valid from
Autumn semester 2022
Education level
First cycle
Progressive Specialisation
G2F (First cycle, has at least 60 credits in first-cycle course/s as entry requirements).
Main area(s)
Product and Process Development
School
School of Innovation, Design and Engineering
Ratified
2022-01-24
Literature lists
Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.
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Books
Ingen specifik litteratur
Objectives
The aim of the course is the use of data analytics for the improvement of industrial processes. The objective of the course is to apply data analytics to industrial data: acquire, process and analyse data in the Industry 4.0 framework.
Learning outcomes
After completing the course, the student shall be able to:
1. Classify different types of industrial data.
2. Describe the collection methods of industrial data.
3. Apply data preprocessing to industrial data.
4. Implement data analytics tools to add value to industrial data.
5. Discuss opportunities and limitations of the implementation of data analytics in industrial processes.
Course content
* Introduction to the Industry 4.0 framework and associated data requirements
* Types of industrial data
* Data acquisition and processing
* Data analytics: descriptive, predictive, prognostic
* Application of data analytics in industrial processes
Specific requirements
60 creditscompleted courses within Product and process development of which 30 credits within the area of Production and logistics and 7,5 credits Probability Theory and Statistical Inference.
Examination
Written assignment (INL1), 2,5 credits, examines the learning outcomes 1 and 2, marks Fail (U) or Pass (G)
Laboratory work (LAB1), 2,5 credits, examines the learning outcomes 3 och 4, marks Fail (U) or Pass (G)
Seminar (SEM1), 2,5 credits, examines the learning outcome 5, marks Fail (U), 3, 4 or 5
A student who has a certificate from MDU regarding a disability has the opportunity to submit a request for supportive measures during written examinations or other forms of examination, in accordance with the Rules and Regulations for Examinations at First-cycle and Second-cycle Level at Mälardalen University (2020/1655). It is the examiner who takes decisions on any supportive measures, based on what kind of certificate is issued, and in that case which measures are to be applied.
Suspicions of attempting to deceive in examinations (cheating) are reported to the Vice-Chancellor, in accordance with the Higher Education Ordinance, and are examined by the University’s Disciplinary Board. If the Disciplinary Board considers the student to be guilty of a disciplinary offence, the Board will take a decision on disciplinary action, which will be a warning or suspension.
Grade
Pass with distinction, Pass with credit, Pass, Fail