Course syllabus - Industrial Internet of Things for Manufacturing Industry

Objectives

The purpose of this course is to provide the student with knowledge of the infrastructure and technologies needed to generate, transport and manage data in the Industrial Internet of Things (IIoT) system. The course will provide students with insights into different components included in the IIoT, sensor technologies, smart labels, data management, data communication and cloud computing.

Learning outcomes

After completion of the course the student should be able to:  
1. Describe and understand IIoT systems and data transfer requirements.  
2. Describe and understand computer communication technologies and their possibilities, limitations and expected role in the development of IIoT  
3. Explain the safety aspects of data communication and understand appropriate measures against common security issues  
4. Understand how different sensor types can be used in the manufacturing industry and know the characteristics of each type  5. Describe the advantages and disadvantages in using cloud computing and describe the most important driving forces and obstacles for using Cloud Computing in the Manufacturing industry 
6. Demonstrate the ability to practically and theoretically translate their knowledge within the IIoT to applications in production, logistics and product development

Course content

The course contains lectures, project work, laboratory exercises and assignments where the student gets knowledge of different applications of IIoT in the manufacturing industry. For example, Ethernet, WiFi, 5G and IP over wireless networks and smart cloud platforms.

Specific requirements

Completed courses of 30 credits within product and process development at level G2F. In addition, Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.

Examination

Assignment (INL1), 1 credit, marks Fail (U) or Pass (G) (examines learning outcomes 1 and 6) 
Project (PRO1), 3 credits, marks Fail (U), 3, 4 or 5 (examines learing outcomes 1-6) 
Written examination (TEN1),  2,5 credits, marks Fail (U), 3, 4 or 5 (examines learning outcomes 1-6) 
Laboratory work (LAB1), Laboratory work with applications of IIoT, 1 credit, marks Fail or Pass (G) (examines learning outcomes 2-5)

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

Interim Regulations and Other Regulations

The course overlaps 7.5 credits with PPU434 Industrial Internet of Things for Manufacturing Industry, 7.5 credits with PPU446 Industrial Internet of Things for Manufacturing Industry, 3 credits with PPU474 Internet of Things Platforms for Manufacturing Industry and 2 credits with PPU322 Introduction to Internet of Things for Manufacturing Industry.