Industrial Information Technology is a fairly wide term that involve any computer system applied in industrial environments. Since the area is so wide, the course is constrained to the use of computers to control and monitor industrial systems in general, bearing in mind the issues of designing proper Human-Machine Interfaces for those systems, of taking care of the Data Acquisition and signal generation needed for these purposes, of making communications possible between computers of the industrial plant and, finally, being able to program industrial (and not industrial) computers.



It is strongly recommended that the students have passed basic computer science courses (such as 25977) as well as control and automation courses (26511) before starting the present course.

(Check the official documents of the degree)



(TEEOI10) Industrial Information Technology and communications



(C3) Basic technology

(C4) Problem solving

(C5) Measuring and reporting

(C10) Multilingual / Multidisciplinary work environments

(C13) Scientific methodology



And the expected learning results are these:



- To be able to interpret technical documents

- To design Control and Supervisory systems

- To analyse industrial systems

- To design and implement informatics systems for the industry



We will also tackle some transversal competences, ask the teachers if you need further information.

The UPV/EHU Catalogue of Transversal Competences has not been translated yet, but it is available in Spanish in the following link:



https://www.ehu.eus/documents/1432750/12757375/Cat%C3%A1logo+de+Competencias+trasnversales_cas.pdf

1.- Industrial IT in our industrial environment

2.- Industrial IT fundamentals

3.- Fast Prototyping and IoT

4.- Communications and the Cloud

The evaluation type of this course is continuous. During the four-month period, the student may conduct laboratory practices and classroom exercises to acquire skills. Although class hours are by definition lectures, the resolution of exercises, teamwork, and discussion of problems will be the usual dynamic. The subject is face-to-face, and attendance is mandatory, as indicated in the Student Guide. It is also mandatory to monitor eGela activities by keeping an eye on messages and following established deadlines.

• Continuous Assessment System
• Final Assessment System
• Tools and qualification percentages:
  • Realization of Practical Work (exercises, cases or problems) (%): 25
  • Team projects (problem solving, project design)) (%): 50
  • Laboratory practical test (%): 25

Briefly, the subject has five evaluation items, and the student needs to get 50% of the points in each item to pass the course.



The items are the following:



1.- Laboratory practical test 25% (minimum 50%)



2.- Team work on industrial applications 50% (minimum 50%)



3.- Individual work about laboratory sessions (minimum 50%)



The student must pass all the parts to pass the course.



Students who want to avoid the continuous assessment method or to avoid sitting the exam should follow current regulations. Do not hesitate to contact the coordinator of the course if you have any question about the assessment.

The considerations of the ordinary call apply to the extraordinary call too. The parts passed in the first call are kept for the second call.

Documents available in eGela. If you have any issue accessing eGela, just ask the teachers.

It is strongly recommended to install LabVIEW 2021 in your own laptop. The UPV/EHU has a student license available (https://www.ehu.eus/liz/niacademic/).

Basic bibliography

https://egela.ehu.eus/

In-depth bibliography

- Lutz Mark. Learning Python: Powerful Object-Oriented Programming. Ed. O'Reilly Media, USA, 2013.
- Usmani Zeeshan. Kaggle for Beginners: with Kernel Code. Ed. Gufhtugu, 2017.
- Ed Doering. NI myRIO Project Essentials Guide. Ed. National Technology and Science Press, 2013.

Journals

Revista Iberoamericana de Automática e Informática Industrial RIAI
ISSN: 1697-7912
https://polipapers.upv.es/index.php/RIAI

Computers & Industrial Engineering
ISSN: 0360-8352
https://www.journals.elsevier.com/computers-and-industrial-engineering

IEEE Transactions on Industrial Informatics
ISSN 1551-3203
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=9424

Web addresses

https://informatics.industriainformatika.pw/

LabVIEW:
https://www.ni.com/
https://labviewwiki.org/wiki/Home

Python:
https://www.python.org/
https://www.kaggle.com/
https://www.pythonanywhere.com/

Industry IoT Consortium:
https://www.iiconsortium.org/