Print Course syllabus
Course syllabus - Data Analytics in Virtual Production
Scope
2.5 credits
Course code
PPU320
Valid from
Autumn semester 2023
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
2023-01-19
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
Guide to industrial analytics : solving data science problems for manufacturing and the internet of things / Richard Hill, Stuart Berry
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Objectives
Syftet med denna kurs är att utveckla förståelse och kompetens inom analys och utvärdering av produktionssystem, samt dataanalys och artificiell intelligens relaterad till virtuell produktion.
Learning outcomes
After completion of the course the student should be able to:
1. Perform sensitivity analysis on different production systems using models
2. Analyze and evaluate the performance of production systems
3. Utilize artificial intelligence for modelling production systems
Course content
- Model development, scenario analysis and evaluation using industrial software
- Sensitivity analysis and bottleneck identification
- AI methods and applications
- Post-processing of results
Specific requirements
60 credits in mechanical engineering, production engineering, product and process development, computer engineering and/or computer science or equivalent or 40 credits in engineering/technology and at least 2 years of work experience in full-time from a relevant area within industry.
Examination
Individual Assignment (INL1), 0.5 credits, examines learning outcomes 1-3, marks Fail (U) or Pass (G)
Project (PRO1), 2 credits, examines learning outcomes 1-3, marks Fail (U) or Pass (G)
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, Fail
Interim Regulations and Other Regulations
The course overlaps 2,5 credits with PPU460 Industry 4.0 - Optimization of production systems and 2,5 credits with PPU452 Optimization of Production Systems.