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New Technologies (5 cr)

Code: TLTT4500-3004

General information


Enrollment

01.11.2021 - 23.01.2022

Timing

10.01.2022 - 29.04.2022

Number of ECTS credits allocated

5 op

Mode of delivery

Face-to-face

Unit

School of Technology

Campus

Main Campus

Teaching languages

  • English

Seats

0 - 30

Degree programmes

  • Bachelor's Degree Programme in Purchasing and Logistics Engineering

Teachers

  • Pasi Poutiainen

Teacher in charge

Pasi Poutiainen

Groups

  • TLP20S1
    Bachelor's Degree Programme in Purchasing and Logistics Engineering
  • TLP21VS
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies
  • TLP22VK
    Bachelor's Degree Programme in Purchasing and Logistics Engineering (AMK) vaihto-opiskelu/Exchange studies

Objectives

Technological development in today's work environments is accelerating. Logistics is already frontrunner of some technologies today. As a future engineer, you need to understand the concepts and capabilities of the latest technologies. The engineer must be able to utilize the opportunities provided by technology in accordance with the principles of continuous improvement. As an engineer of the future, you should have an innovative perspective on new technologies, so that companies have the courage to start using technologies to improve their performance.

In this course you will learn
- search information about new technologies
- know different technologies and their principles
- understand the potential of new technologies from logistic point of view
- apply the use of new technologies

After completing this course, you will have wide understanding about the terminology of the technologies covered in the course. You will understand what might are potential of new technologies in future. You gain understanding how technologies can be utilized for real applications. You will have the knowledge and skills to search information about the latest technologies.

Competencies: technological knowledge, engineering practise.

Learning outcome:
You will understand the terminology of new technologies and their relevance to your future work, be familiar with key concepts and theories.

Content

The course covers following main themes:
- modern robotization,
- wearable technologies,
- AI, Big Data & IoT,
- additive manufacturing,
- other technologies and trends.

Learning materials and recommended literature

Lecture materials related to the course can be found in the course workspace. Relevant open-source online material can also be used.

Teaching methods

Course includes lectures, returnable learning assignments and possible laboratory tasks.

Assignments are done as independent work. The assignments are described in the course workspace. All assignments are either individual assignments or group assignments (described in course workspace) and their due dates will be confirmed as the course progresses.

Practical training and working life connections

Trade fairs, seminars, webinars, etc. that take place during the course can be included in the course. This will be discussed in more detail during the course.

Exam dates and retake possibilities

The time of a possible exam is announced in the course start information.

Alternative completion methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Further information for students

Exchange students:

Evaluation scale

0-5

Evaluation criteria, satisfactory (1-2)

1: Student has gained knowledge at all the subjects described in the learning outcomes.

2: Student has gained knowledge at all the subjects described in the learning outcomes and is able to utilize this knowledge.

Evaluation criteria, good (3-4)

3: Student understands all the subjects described in the learning outcomes and is able to apply the skills one has learned.

4: Student has attained an excellent level in almost all the subjects described in the learning outcomes and is able to apply the skills one has learned.

Evaluation criteria, excellent (5)

5: The student has attained an excellent level in all subjects described in the learning outcomes and is able to apply the skills one has learned.