Valid from: Autumn 2025
Decided by: FUN2 / Jonas Johansson
Date of establishment: 2025-02-26
Division: Productions and Materials Engineering
Course type: Third-cycle course
Teaching language: English
The aim is to equip PhD students with comprehensive knowledge of sensor technologies and their integration into sustainable manufacturing systems. The course focuses on understanding sensor applications, signal types, limitations, and material selection, as well as life cycle perspective. Students will explore how sensors fit into the manufacturing ecosystem, contributing valuable data to enhance efficiency. Through group projects, study visits, and collaborations, the course emphasizes how sensor technologies deliver value to partners, customers, and society, preparing students for leadership in this emerging field.
Knowledge and Understanding
For a passing grade the doctoral student must To achieve a passing grade, the student must demonstrate a solid understanding (in their own field) of sensor technologies, their applications in sustainable production, and their role within manufacturing ecosystems. This includes the ability to critically review relevant literature, comprehend the state-of-the-art, and recognize the limitations and advantages of various sensor types and materials. Students should also grasp how sensors complement data in production systems and contribute to sustainability efforts.
Competences and Skills
For a passing grade the doctoral student must For a passing grade, the student must exhibit the ability to apply theoretical knowledge to practical scenarios. This includes selecting appropriate sensors for specific applications, evaluating sensor performance, and understanding the major drivers needed for conducting life cycle anslyses and be able to compare different technologies and thier implementation from a sustainability perspective. The student should also effectively collaborate in group projects, communicate findings through presentations, and integrate insights from study visits, showcasing the capacity to work both independently and within teams.
Judgement and Approach
For a passing grade the doctoral student must To pass, the student must demonstrate sound judgement in evaluating different sensor technologies and their environmental impacts. This includes the ability to critically assess the role of sensors in sustainable production and make informed decisions regarding material selection, application suitability, and system integration. Additionally, students must show a reflective and ethical approach to how sensor technologies add value to industrial partners, customers, and society at large.
The course will cover, based on the study area, a detailed literature review and explore the state-of-the-art in sensor technology. Topics include sensor production, applications for different signal types (e.g., temperature, gas), and the limitations and advantages of specific sensor types. Students will compare different sensor technologies for similar applications and learn about material selection and life cycle perspective. The course also explores how sensors complement existing manufacturing data and integrate into production ecosystems. Study visits to partners, group work, and presentations and knowledge transfrer activities will foster collaboration and synergies between PhD projects, focusing on real-world industry value.
The students will conduct a literature review and use that literature as course material throughout the course.
Types of instruction: Lectures, seminars, project, self-study literature review, study visit. The course begins with common lectures providing an overview. Midway, students focus on individual projects, engage in case studies, attend study visits, and participate in student-led seminars.
Examination formats: Written report, seminars given by participants.
The course is examined through a seminar where students present their results, which are also summarised in a written report.
Grading scale: Failed, pass
Examiner:
Admission requirements: Enrolled as a PhD
Selection criteria: priority for PhD students belonging Department of Industrial and Mechanical Sciences, Centre for Mathematical Sciences, Department of Physics.
Course coordinators:
Web page: https://www.sentio.lu.se/