Study Guide

Learning outcomes

The student is able to
- understand Automation system hardware principles and control models
- implement PLC principles and programming, HMI panel and SCADA software
- utilize Distribution and communication using std industrial protocols and buses
- understands Sensors and actuators (operation principles and connection types)
- implement simple digital twins
- understands principles and programming of industrial robots as a part of an automation system

Implementation and methods of teaching

Lectures, exercises, exam, returnable assignments.

Learning material and recommended literature

Study material will be announced at the beginning of the course.
Material to be distributed on the course website.

Contents

The student
- knows the main application areas of automation and understands the overview of the industry.
- is able to name different components of hydraulic and pneumatic systems.
- is able to make and connect hydraulic and pneumatic connections and design hydraulic and pneumatic circuits.
- is able to build and simulate a simple PLC based automation system.
- know the differences between automation solutions in different application areas of automation
(especially process and piece goods automation) and the structures and main functions of

Assessment criteria

Basic level (1-2): the student can implement a simple piece goods automation application using programmable logic software, utilizing electro pneumatics / hydraulics.

Good level (3-4):The student will be able to implement a more advanced piece goods automation application using programmable logic software.

Excellent level (5): The student is able to implement a complex piece goods automation application using programmable logic software.

Assessment scale

1-5

Failed (0)

Level 1 of the competences described below is not met.

Assessment criteria: level 1 (assessment scale 1–5)

The student will be able to implement a simple piece goods automation application using programmable logic software.

Participates actively in class (80% of the classroom teaching) and successfully completes the exercises according to the given schedule.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to implement a more advanced piece goods automation application with programmable logic software.

Actively participates in class (80% of the classroom teaching) and successfully completes the exercises according to the given timetable.

Assessment criteria: level 5 (assessment scale 1–5)

The student will be able to implement a complex piece goods automation application using programmable logic software.

Actively participates in class (80% of the classroom time) and successfully completes the exercises according to the given schedule.

Willing to guide others in solving problems.

Learning outcomes

The student is able to
- utilize modern analyzing, ML, and AI tools to solve engineering problems
- visualize and report the processed data in a suitable way using modern tools
- create a data visualization using HTML and backend services
- understand digital twin operation principles
- understand the importance and principles of leading, law, marketing and business economy as a part of a company operations
- write a technical report and represent it

Implementation and methods of teaching

Course consists of many individual assignments and some group assignments. Some of the assignments requires attending on the premises.

Timing and attendance

Attending classes is required according to the schedules in the Time-edit.

Learning material and recommended literature

Material is shared in the Moodle platform and some presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Exam retakes

The course grading is based on assigments given during the classes and some group assignments.

In case there are exams during the course, then the LAB's rules and regulations are applied to the exam (two or more changes to take a replacement exam.)

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying, containing the scheduled lectures and self-studying.

Contents

Digital Twin
AI/ML tools
Leading Law, Marketing and business economy

Additional information for students: previous knowledge etc.

Object-oriented programming

Assessment criteria

Assessment will be based on exercises, individual and team assignments and possible exams.
Student activity will affect grading.

Assessment scale

1-5

Failed (0)

Student doesn't reach the course's competence goals.

Assessment criteria: level 1 (assessment scale 1–5)

Understands the course topics and can contribute to RDI processes.

Assessment criteria: level 3 (assessment scale 1–5)

Can utilize modern analyzing, ML and AI tools to solve engineering problems. Is able to visualize data using modern web development related tools and understands the importance of the leading, law, marketing and business economy as a part of a company operations.

Assessment criteria: level 5 (assessment scale 1–5)

Rules the level 3 matters and can take leading role in RDI processes

Learning outcomes

The student is able to
- describe the roles and methods of agile software development environments
- understand software architecture importance and use std patterns
- develop front and backend services using Javascript (and Node)
- operate according to DevOps principles (CI/CD)

Implementation and methods of teaching

Course consists of many individual assignments and some group assignments. Many software development tools are also being introduced during this course, which means that some individual guidance might be required.

Timing and attendance

Attending classes is required so that the groups can be constructed and the guidance during the classes can be given. There will be no recordings related to the supporting classes. Only some short clips if necessary.

Learning material and recommended literature

The learning material is the material found on the internet and the material presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Exam retakes

The course grading is mostly based on practical assignments with their respective schedules for the last return date and some extra tasks for compensatory points.

In case there are exams during the course, then the LAB's rules and regulations are applied to the exam (two or more changes to take a replacement exam.)

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying.

Contents

Describe the roles and methods of agile software development environments.
Understand software architecture importance and use std patterns.
Develop front and backend services using Javascript (and Node).
Operate according to DevOps principles (CI/CD).

Additional information for students: previous knowledge etc.

Previous experiences with NodeJS runtime and/or some Linux shell like BASH can help with the studies. Also knowning some basics of web-development can benefit, but none of the previously mentioned are requirements for the participation on the course.

Student must have previous experiences with programming on the basics level.

Assessment criteria

Course grading will be mostly based on the assessed partial assignments. All of the partial assignments will contribute to the course grade with specified weights or points. The proposed grade will be rounded with traditional rounding rules to match 0-5 grading scale.

Assessment scale

1-5

Failed (0)

Student doesn't reach the course's competence goals.

Assessment criteria: level 1 (assessment scale 1–5)

Student is able to contribute minimally to the team efforts and also able to understand and explain the course topics.

Assessment criteria: level 3 (assessment scale 1–5)

Student is able to participate into the team development efforts and also develop maintainable and testable software using devops principles.

Assessment criteria: level 5 (assessment scale 1–5)

Student shows ability to lead development team and instruct other developers to contribute. Student is also able to develop software with devops principles and can maintain devops related tool ecosystem.

Learning outcomes

The student is able to
- Recognize the main components of an embedded system and understand the system architecture
- Describe the properties of different electronics components and choose appropriate components for the application
- Design and implement embedded software in the C programming language
- Design and implement a simple embedded device

Assessment scale

1-5

Learning outcomes

The student is able to
- understands the role of ICT in engineering
- describe the automation system at a general level
- describe the concepts and principles of industrial ICT
- understand the role of the data in ICT engineering
- use common digital documentation and communication tools in the work of an engineering
- understand project based team work methods and principles in engineering
- create a program using structured programming language
- understand HTML and CSS basics
- understand the basics of statistical thinking

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material is shared in the Moodle platform and some presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying. This includes the defined lectures, self-studying and exercises.

Contents

The course consists of four sub-areas:

Programming

- Basics with Python3 - programming paradigm: imperative

Digitalisation, ICT and automation

Tähän lyhyt kuvaus sisällöstä

Web Developing

-Focus on html5, css3, Javascript and their role in Web Developing. Additionally, we leverage Github.

Digital Tools and Data

Skills needed for studies in using Excel, Word and PowerPoint

Additional information for students: previous knowledge etc.

None

Assessment scale

1-5

Learning outcomes

The student is able to
- create a program using object-oriented programming language with databases (in the cloud too)
- understand the principles of user interfaces
- understand operating systems principles
- understand the role of the cloud platform in an IoT pipeline
- explain the structure of the IoT data pipeline, the meaning of the parts of the pipeline and principles of the machine learning and artificial intelligence
- understand the requirements of sensor data in the data value chain.
- understand the basic principles of the secure data transfer from the IoT device to the IoT data pipeline

Implementation and methods of teaching

Lectures and classes will be held at the Lappeenranta campus

Timing and attendance

Course is held during the second semester.

Lectures will be held according to the timetable.

Attending on the lectures is highly desirable.

Learning material and recommended literature

Material provided during the lectures and in the course's Moodle page.

Learning environment

Study material and instructions in the Moodle platform.

Lectures on the Lappeenranta campus

Student time use and work load

Course (15 ECTs) is divided into three sub modules.
Each submodule requires approximately 135h studying, which totals to 405 h.

The actual workload depends on the student. The required course assignments must be completed.

Estimated time division:
- 100h lectures
- 150h self studying
- 150h exercises

Contents

Topics:
- Object-oriented programming
- Operating system
- IoT Pipeline
- Cloud platform
- ML, AI
- Data to applications

Additional information for students: previous knowledge etc.

Programming basics with Python

Assessment criteria

Grade scale: 0-5

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criterias.

Assessment criteria: level 1 (assessment scale 1–5)

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

Assessment criteria: level 3 (assessment scale 1–5)

Student and group presentations are clear and logical. They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's presentations reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

Assessment criteria: level 5 (assessment scale 1–5)

The student's and group's presentations also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- use containers and virtualization as a programming and production platform for software systems
- design, create and manage a virtualized environment for an application project
- compare different hypervisors and cloud services to identify the strengths and weaknesses relevant to the solution
- utilize and maintain different operating systems (Linux/Windows) efficiently in a virtualized environment
- manage (private) cloud platform efficiently and securely and understand private/public cloud notable differences

Timing and attendance

The course will be delivered at the Lappeenranta Campus.

Learning material and recommended literature

Material delivered in Moodle, during classes, www*.

Learning environment

Moodle, class (possibly zoom)

Student time use and work load

The indicative amount of work is 405 hrs. The actual amount of work depends on the student.

The required course assignments must be completed.

Contents

Material delivered in Moodle, during classes, www*.

These will be clarified during the class hours.

Assessment criteria

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criteria.

Assessment criteria: level 1 (assessment scale 1–5)

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

Assessment criteria: level 3 (assessment scale 1–5)

The student and group deliverables (for example, presentations) are clear and logical.

They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's deliverables reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

Assessment criteria: level 5 (assessment scale 1–5)

Student and group deliverables (for example, presentations) are clear and logical.

The student's and group's deliverables also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- create a program using object-oriented programming language with databases (in the cloud too)
- understand the principles of user interfaces
- understand operating systems principles
- understand the role of the cloud platform in an IoT pipeline
- explain the structure of the IoT data pipeline, the meaning of the parts of the pipeline and principles of the machine learning and artificial intelligence
- understand the requirements of sensor data in the data value chain.
- understand the basic principles of the secure data transfer from the IoT device to the IoT data pipeline

Implementation and methods of teaching

Lectures and classes will be held at the Lappeenranta campus

Timing and attendance

Course is held during the second semester.

Lectures will be held according to the timetable.

Attending on the lectures is highly desirable.

Learning material and recommended literature

Material provided during the lectures and in the course's Moodle page.

Learning environment

Study material and instructions in the Moodle platform.

Lectures on the Lappeenranta campus

Student time use and work load

Course (15 ECTs) is divided into three sub modules.
Each submodule requires approximately 135h studying, which totals to 405 h.

The actual workload depends on the student. The required course assignments must be completed.

Estimated time division:
- 100h lectures
- 150h self studying
- 150h exercises

Contents

Topics:
- Object-oriented programming
- Operating system
- IoT Pipeline
- Cloud platform
- ML, AI
- Data to applications

Additional information for students: previous knowledge etc.

Programming basics with Python

Assessment criteria

Grade scale: 0-5

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criterias.

Assessment criteria: level 1 (assessment scale 1–5)

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

Assessment criteria: level 3 (assessment scale 1–5)

Student and group presentations are clear and logical. They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's presentations reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

Assessment criteria: level 5 (assessment scale 1–5)

The student's and group's presentations also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- use containers and virtualization as a programming and production platform for software systems
- design, create and manage a virtualized environment for an application project
- compare different hypervisors and cloud services to identify the strengths and weaknesses relevant to the solution
- utilize and maintain different operating systems (Linux/Windows) efficiently in a virtualized environment
- manage (private) cloud platform efficiently and securely and understand private/public cloud notable differences

Timing and attendance

The course will be delivered at the Lappeenranta Campus.

Learning material and recommended literature

Material delivered in Moodle, during classes, www*.

Learning environment

Moodle, class (possibly zoom)

Student time use and work load

The indicative amount of work is 405 hrs. The actual amount of work depends on the student.

The required course assignments must be completed.

Contents

Material delivered in Moodle, during classes, www*.

These will be clarified during the class hours.

Assessment criteria

Course evaluation consists of the weekly tasks and possibly exams.

Assessment scale

1-5

Failed (0)

Not able to reach level 1 criteria.

Assessment criteria: level 1 (assessment scale 1–5)

The student and the group have been able to cooperate productively and document their work. The student and the group are able to present their output to other students as instructed. The output mainly meets the criteria of the assignments.

Assessment criteria: level 3 (assessment scale 1–5)

The student and group deliverables (for example, presentations) are clear and logical.

They clearly show the implementation in accordance with the tasks given and any deviations have been reported. The student's and group's deliverables reflect an understanding of the work, e.g. the terms and professional words are correct. The student and group members also talk about what they have learned and solutions to challenges (reflection).

Assessment criteria: level 5 (assessment scale 1–5)

Student and group deliverables (for example, presentations) are clear and logical.

The student's and group's deliverables also contain a link to the theory of the course, and you can compare and justify with facts the solutions that have been used in the work. The student and the group have been able to add something extra they came up with to the work. The presentations are illustrative and things are explained with the help of examples

Learning outcomes

The student is able to
- understand Automation system hardware principles and control models
- implement PLC principles and programming, HMI panel and SCADA software
- utilize Distribution and communication using std industrial protocols and buses
- understands Sensors and actuators (operation principles and connection types)
- implement simple digital twins
- understands principles and programming of industrial robots as a part of an automation system

Implementation and methods of teaching

Lectures, exercises, exam, returnable assignments.

Learning material and recommended literature

Study material will be announced at the beginning of the course.
Material to be distributed on the course website.

Contents

The student
- knows the main application areas of automation and understands the overview of the industry.
- is able to name different components of hydraulic and pneumatic systems.
- is able to make and connect hydraulic and pneumatic connections and design hydraulic and pneumatic circuits.
- is able to build and simulate a simple PLC based automation system.
- know the differences between automation solutions in different application areas of automation
(especially process and piece goods automation) and the structures and main functions of

Assessment criteria

Basic level (1-2): the student can implement a simple piece goods automation application using programmable logic software, utilizing electro pneumatics / hydraulics.

Good level (3-4):The student will be able to implement a more advanced piece goods automation application using programmable logic software.

Excellent level (5): The student is able to implement a complex piece goods automation application using programmable logic software.

Assessment scale

1-5

Failed (0)

Level 1 of the competences described below is not met.

Assessment criteria: level 1 (assessment scale 1–5)

The student will be able to implement a simple piece goods automation application using programmable logic software.

Participates actively in class (80% of the classroom teaching) and successfully completes the exercises according to the given schedule.

Assessment criteria: level 3 (assessment scale 1–5)

The student is able to implement a more advanced piece goods automation application with programmable logic software.

Actively participates in class (80% of the classroom teaching) and successfully completes the exercises according to the given timetable.

Assessment criteria: level 5 (assessment scale 1–5)

The student will be able to implement a complex piece goods automation application using programmable logic software.

Actively participates in class (80% of the classroom time) and successfully completes the exercises according to the given schedule.

Willing to guide others in solving problems.

Learning outcomes

The student is able to
- describe the roles and methods of agile software development environments
- understand software architecture importance and use std patterns
- develop front and backend services using Javascript (and Node)
- operate according to DevOps principles (CI/CD)

Implementation and methods of teaching

Course consists of many individual assignments and some group assignments. Many software development tools are also being introduced during this course, which means that some individual guidance might be required.

Timing and attendance

Attending classes is required so that the groups can be constructed and the guidance during the classes can be given. There will be no recordings related to the supporting classes. Only some short clips if necessary.

Learning material and recommended literature

The learning material is the material found on the internet and the material presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Exam retakes

The course grading is mostly based on practical assignments with their respective schedules for the last return date and some extra tasks for compensatory points.

In case there are exams during the course, then the LAB's rules and regulations are applied to the exam (two or more changes to take a replacement exam.)

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying.

Contents

Describe the roles and methods of agile software development environments.
Understand software architecture importance and use std patterns.
Develop front and backend services using Javascript (and Node).
Operate according to DevOps principles (CI/CD).

Additional information for students: previous knowledge etc.

Previous experiences with NodeJS runtime and/or some Linux shell like BASH can help with the studies. Also knowning some basics of web-development can benefit, but none of the previously mentioned are requirements for the participation on the course.

Student must have previous experiences with programming on the basics level.

Assessment criteria

Course grading will be mostly based on the assessed partial assignments. All of the partial assignments will contribute to the course grade with specified weights or points. The proposed grade will be rounded with traditional rounding rules to match 0-5 grading scale.

Assessment scale

1-5

Failed (0)

Student doesn't reach the course's competence goals.

Assessment criteria: level 1 (assessment scale 1–5)

Student is able to contribute minimally to the team efforts and also able to understand and explain the course topics.

Assessment criteria: level 3 (assessment scale 1–5)

Student is able to participate into the team development efforts and also develop maintainable and testable software using devops principles.

Assessment criteria: level 5 (assessment scale 1–5)

Student shows ability to lead development team and instruct other developers to contribute. Student is also able to develop software with devops principles and can maintain devops related tool ecosystem.

Learning outcomes

The student is able to
- utilize modern analyzing, ML, and AI tools to solve engineering problems
- visualize and report the processed data in a suitable way using modern tools
- create a data visualization using HTML and backend services
- understand digital twin operation principles
- understand the importance and principles of leading, law, marketing and business economy as a part of a company operations
- write a technical report and represent it

Implementation and methods of teaching

Course consists of many individual assignments and some group assignments. Some of the assignments requires attending on the premises.

Timing and attendance

Attending classes is required according to the schedules in the Time-edit.

Learning material and recommended literature

Material is shared in the Moodle platform and some presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Exam retakes

The course grading is based on assigments given during the classes and some group assignments.

In case there are exams during the course, then the LAB's rules and regulations are applied to the exam (two or more changes to take a replacement exam.)

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying, containing the scheduled lectures and self-studying.

Contents

Digital Twin
AI/ML tools
Leading Law, Marketing and business economy

Additional information for students: previous knowledge etc.

Object-oriented programming

Assessment criteria

Assessment will be based on exercises, individual and team assignments and possible exams.
Student activity will affect grading.

Assessment scale

1-5

Failed (0)

Student doesn't reach the course's competence goals.

Assessment criteria: level 1 (assessment scale 1–5)

Understands the course topics and can contribute to RDI processes.

Assessment criteria: level 3 (assessment scale 1–5)

Can utilize modern analyzing, ML and AI tools to solve engineering problems. Is able to visualize data using modern web development related tools and understands the importance of the leading, law, marketing and business economy as a part of a company operations.

Assessment criteria: level 5 (assessment scale 1–5)

Rules the level 3 matters and can take leading role in RDI processes

Learning outcomes

The student is able to
- Recognize the main components of an embedded system and understand the system architecture
- Describe the properties of different electronics components and choose appropriate components for the application
- Design and implement embedded software in the C programming language
- Design and implement a simple embedded device

Assessment scale

1-5

Learning outcomes

The student is able to
- understands the role of ICT in engineering
- describe the automation system at a general level
- describe the concepts and principles of industrial ICT
- understand the role of the data in ICT engineering
- use common digital documentation and communication tools in the work of an engineering
- understand project based team work methods and principles in engineering
- create a program using structured programming language
- understand HTML and CSS basics
- understand the basics of statistical thinking

Timing and attendance

Attending classes is required according to the schedules defined in the Time-edit.

Learning material and recommended literature

Material is shared in the Moodle platform and some presented during the lessons.

Alternative completion methods

None

Working life cooperation

None

Learning environment

Lappeenranta Campus & Moodle

Student time use and work load

The scope of the course is 15 credits, which corresponds to an average of 412 hours of studying. This includes the defined lectures, self-studying and exercises.

Contents

The course consists of four sub-areas:

Programming

- Basics with Python3 - programming paradigm: imperative

Digitalisation, ICT and automation

Tähän lyhyt kuvaus sisällöstä

Web Developing

-Focus on html5, css3, Javascript and their role in Web Developing. Additionally, we leverage Github.

Digital Tools and Data

Skills needed for studies in using Excel, Word and PowerPoint

Additional information for students: previous knowledge etc.

None

Assessment scale

1-5