LEARNING OUTCOMES
The actual learning outcomes of the course vary from year to year according to the content.
Project work:
Learning outcomes
After the course the student:
- Knows the structure and requirements for current automation systems;
- Is able to configure a small DCS system for lab unit processes using ABB 800xA system and information systems environment;
- Knows the basics in process automation programming and Python languages;
- Knows the meaning of process system interfaces (OPC UA, ODBC);
- Knows the benefits, limitations and properties of industrial field buses and can apply this knowledge in the automation system design;
- Knows how to collect the data from measurements and making data analysis in the cloud computing system;
- Knows what wireless smart sensors are and how to configure and connect them into the cloud computing system;
- Knows what is the benefit of 5G wireless network and how to utilize it in the automation system.
- Knows how to connect Raspberry and Arduino into the cloud computing system
Credits: 5
Schedule: 25.02.2025 - 09.04.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Jukka Kortela
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
Postgraduate level knowledge in process systems engineering (dynamics, control, optimisation, automation systems or machine learning). The actual contents of the course vary from year to year.
Project work:
In this course the student learns to configure and operate the current automation systems, utilizing the latest technological tools "Industry 4.0", Industrial Internet of Things, Cloud computing and 5G. The automation setup used in the course will prepare the students for the future automation challenges with the latest tools and merges data analytics, cloud computing and wireless network studies with process automation.
Assessment Methods and Criteria
valid for whole curriculum period:
Home assignments and/or seminars and/or project work, and/or exam.
Workload
valid for whole curriculum period:
Lectures/Seminars (32h) and Exercises/Seminars (16h)
Home assignments and independent study (80h)
Exam (4h)
DETAILS
Study Material
valid for whole curriculum period:
Study book or a collection of articles or a project.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
7 Affordable and Clean Energy
9 Industry, Innovation and Infrastructure
11 Sustainable Cities and Communities
12 Responsible Production and Consumption
13 Climate Action
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Spring IV
2025-2026 Spring IVRegistration:
A maximum number of 15 students is admitted to the course. Priority is given to degree students taking in Chemical and Process Engineering as their major. If space, other students (exchange students and Aalto degree students) will be admitted to the course based on registration order. A course implementation may be cancelled if the number of students enrolled to the course implementation does not meet the required minimum of five students. In the case of cancelled course implementations, the students enrolled to them must be provided with an alternative way of completing the course or be advised to take some other applicable course.