COURSE UNIT TITLE

: DIGITAL TECHNOLOGIES IN PRODUCTION

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PRD 4243 DIGITAL TECHNOLOGIES IN PRODUCTION ELECTIVE 3 0 0 5

Offered By

BUSINESS ADMINISTRATION (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR KEVSER YILMAZ

Offered to

BUSINESS ADMINISTRATION (English)

Course Objective

This course provides an in-depth understanding of the technological advancements shaping modern industry, from the historical evolution of manufacturing to the latest digital innovations. Students will explore key concepts such as additive manufacturing, digital twins, AI-driven automation, big data, cybersecurity, and system integration. Through theoretical discussions and practical applications, they will gain insights into how these technologies contribute to the transformation of smart factories and ethical considerations in the digital age.

Learning Outcomes of the Course Unit

1   To understand key digital technologies such as AI, big data, cloud computing, and system integration in modern manufacturing.
2   To analyze emerging technologies such as 3D printing, digital twins, AI, and system integration in real-world scenarios through practical assignments.
3   To analyze recent academic research, technological advancements, and ethical considerations related to Industry 4.0 through discussions and critical evaluations.
4   To develop problem-solving skills by identifying challenges in digital manufacturing and proposing innovative solutions.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction Gilchrist, A. (2016). Industry 4.0. Apress.
2 From Steam to Smart Factories: The Industrial Revolution 3D Printing, 3D Scanning, and Additive Manufacturing Kanabar, V. (2023). The AI Revolution in Project Management: Elevating Productivity with Generative AI. Sams Publishing.
3 Digital Twin/Simulation for Smart Manufacturing Virtual, Augmented and Mixed Reality Schmalstieg, D., & Hollerer, T. (2016). Augmented reality: principles and practice. Addison-Wesley Professional.
4 Assignment 1
5 Autonomous Robots and Artificial Intelligent Kanabar, V. (2023). The AI Revolution in Project Management: Elevating Productivity with Generative AI. Sams Publishing. Stephenson, D. (2018). Big Data Demystified: How to use big data, data science and AI to make better business decisions and gain competitive advantage. Pearson UK.
6 Big Data, Analytics, Cloud Computing and Cyber Security Stephenson, D. (2018). Big Data Demystified: How to use big data, data science and AI to make better business decisions and gain competitive advantage. Pearson UK. Laudon, K. C. And Laudon, J.P. (2021). Management Information Systems: Managing the Digital Firm, 17th edition, Pearson UK
7 Assignment 2
8 System Integration Laudon, K. C. And Laudon, J.P. (2021). Management Information Systems: Managing the Digital Firm, 17th edition, Pearson UK.
9 Digital Technologies and Ethics Laudon, K. C. And Laudon, J.P. (2021). Management Information Systems: Managing the Digital Firm, 17th edition, Pearson UK.
10 Term Project Presentation
11 Term Project Presentation
12 Term Project Presentation
13 Term Project Presentation
14 Term Project Presentation

Recomended or Required Reading

1. Kanabar, V. (2023). The AI Revolution in Project Management: Elevating Productivity with Generative AI. Sams Publishing.
2. Stephenson, D. (2018). Big Data Demystified: How to use big data, data science and AI to make better business decisions and gain competitive advantage. Pearson UK.
3. Laudon, K. C. & Laudon, J.P. (2021). Management Information Systems: Managing the Digital Firm, 17th edition, Pearson UK.
4. Schmalstieg, D., & Hollerer, T. (2016). Augmented reality: principles and practice. Addison-Wesley Professional.
5. Gilchrist, A. (2016). Industry 4.0. Apress.

Planned Learning Activities and Teaching Methods

1. Lecture: The instructor introduces the fundamental principles of digital technologies in manufacturing. The class will engage in interactive discussions, using case studies and current examples to reinforce students' understanding of how technologies like AI, big data, and automation are reshaping industries.
2. Class Discussions: Students will read and discuss recent articles each week related to a specific technology. Group discussions will foster critical thinking, encourage the exchange of ideas, and help students connect course concepts to real-world technological advancements.
3. Assignments:Students examine how operational functions have been transformed by the digital technologies discussed in class, taking into account both their current impact and their potential in the future.
4. Term Project: For the term project, students will select an industry and analyze the influence of key digital technologies such as AI, automation, and digital twins within that sector. The project will require students to demonstrate their ability to synthesize course content and research, culminating in a comprehensive written report and a class presentation.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 AS1 1.Assignment
2 AS2 2.Assignment
3 TP TermProject
4 PRS Presentation
5 FCG FINAL COURSE GRADE AS1 * 0.20 + AS2 * 0.20 + TP * 0.40 + PRS * 0.20


Further Notes About Assessment Methods

None

Assessment Criteria

Assessment Methods:
Assignments (40%): Groups will select an operational function (such as production, logistics, inventory management, or quality control) and analyze its transformation through the digital technologies discussed in class, both in terms of current impact and future potential. They will explore how technologies like AI, automation, big data, and digital twins are reshaping the chosen operational function. Each group will prepare a written report and deliver a presentation. Each assignment is worth 20%, and assignments that are not presented will not be graded.
The report worth is 20%. The reports are to be Times New Roman font, 12 sized, 1,5 spaced. The assignments that are not presented will not be graded. The term project that are not presented will not be graded. The following scale will be used for the assessment of all criteria. The criteria are also presented below the scale with point values.
This particular element is absent or falls short of expectations, and /or it is completely out of place within
the given context. -Poor (0%)
This particular element is somewhat absent and does not entirely fit the context. - Fair (40%)
This particular element is developed satisfactorily and fits the context at an acceptable standard. Good (60%)
This particular element is developed in a good and professional way and fits into the context. - Very good (80%)
The way this particular element is developed is noteworthy and fits perfectly into the context. - Excellent
(100%)
The presentation and discussion worth are 80%. The following criteria will be used for the assessment of
Presentation.
a. Having a good command of topic (30 points)
b. Being able to attract the attention of audience (20 points)
c. Discuss the given questions/topics in accordance with the tecnologies discussed in-class. (30 points)
Term Project and Presentation (60%): For the term project, students will choose an industry and analyze the current and future impact of the digital technologies covered in class (such as AI, automation, 3D printing, big data, digital twins, etc.) on that sector. They will evaluate how each technology is influencing various aspects of the industry and predict the future developments. Additionally, students will explore how the production functions within the chosen industry will evolve with the integration of these new technologies. The project will require a written report and a class presentation, where students will demonstrate their ability to synthesize course concepts and conduct industry-specific research.
Criteria used for the assessments of term project
The report worth is 40%. The reports are to be Times New Roman font, 12 sized, 1,5 spaced. The assignments that are not presented will not be graded. The term project that are not presented will not be graded. The following scale will be used for the assessment of all criteria. The criteria are also presented below the scale with point values.
This particular element is absent or falls short of expectations, and /or it is completely out of place within
the given context. -Poor (0%)
This particular element is somewhat absent and does not entirely fit the context. - Fair (40%)
This particular element is developed satisfactorily and fits the context at an acceptable standard. Good (60%)
This particular element is developed in a good and professional way and fits into the context. - Very good (80%)
The way this particular element is developed is noteworthy and fits perfectly into the context. - Excellent
(100%)
The presentation and discussion worth are 60%. The following criteria will be used for the assessment of
Presentation.
a. Having a good command of topic (30 points)
b. Being able to attract the attention of audience (20 points)
c. Presentation appearance and structure (10 points)

Language of Instruction

English

Course Policies and Rules

1. Attending at least 70 percent of lectures is mandatory.
2. Plagiarism of any type will result in disciplinary action.
3. Participation to the course and discussions during the classes is required.
4. Late arrivals to the class should be avoided.
5. All electronic devices should be kept close during the lectures

Contact Details for the Lecturer(s)

kevser.yilmaz@deu.edu.tr

Office Hours

Tuesday

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparing assignments 2 10 20
Project Preparation 1 30 30
Preparing presentations 1 10 10
TOTAL WORKLOAD (hours) 130

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14PO.15
LO.14
LO.2544
LO.3444
LO.453543