✓ Relevance: Does it matter in the field/setting/industry?

✓ Sufficiency: Are the mentioned methodologies sufficient to answer the RQ?
✓ Implementation: Are the data collection and data analysis techniques appropriate?

✓ Timeline: Is the timeline feasible for addressing the RQ?

Bonus ✓ Generalizability: Can the RQ be generalized to other settings/industries/areas?

If needed, revise your RQs based on the provided assessment and indicate which criteria led to revisions.

1. Formulate a clear and focused RQ (you can also include sub-questions to address several aspects in depth)

2. Post the RQ in either Case Study or Action Research columns

3. Describe the specific context/setting/industry in which the RQ will be addressed

4. Explain why case study / action research is the appropriate research methodology to answer the RQ

5. What other research methods/methodologies might be applied in addition to address the RQ?

6. How will you collect data?

7. How will you analyze data?

8. What is the approximate timeline to carry out the project to answer the RQ?

   
   

   
   Provide feedback on peers' RQs using the "Score" 1-10 scale and comments (if necessary) under each RQ using the Checklist

(Context: 3D Printer introduction course)

1. What motivates students to use or not use VPNs? 2. In what contexts do students use VPNs, and what goals do they pursue? 3. How do students perceive the security function and protective effect of VPNs?

why case study because it observes the answer from students

How do I collect the data? Survey by me for students, for example, at FH St. Pölten

Sub-questions:

1. What are the main functional components of an LTE/5G base station, and how do they interact?

2. How does the signal processing chain—from data input to antenna output—operate in practice?

3. How do modern antenna systems (e.g., MIMO and beamforming) influence the radiation of electromagnetic waves?

4. What differences exist in the emission process between LTE and 5G systems?

Sub-questions:

1. What are the current knowledge gaps and practical challenges faced by technicians during LTE/5G deployments?

2. How can collaborative learning or updated documentation improve understanding of the emission process and antenna configuration?

3. What effect does targeted technical training (e.g. regarding beamforming or signal routing) have on error reduction and maintenance efficiency?

Sub-Questions:

• Are homeowners more willing than tenants to make larger investments in smart home technologies?

• How do tenants and homeowners perceive the importance of smart home technologies in terms of energy savings?

How can vibration diagnostics using vibration sensors and Motion Amplification be optimized for the early detection of damage in winding axes and rails in high-bay storage, ultimately improving maintenance processes?

1. Clear and Focused RQ:

• My main research question (RQ) is:
  How can vibration diagnostics be optimized to ensure early damage detection in winding axes and high-bay storage rails?

• Sub-questions:

  1. What types of vibration sensors are most effective for detecting anomalies in winding axes and rails?

  2. How can Motion Amplification be integrated to enhance the visualization of vibration patterns?

  3. What specific vibration patterns indicate potential damage?

  4. How can real-time data analysis be applied to improve diagnostic accuracy?

  5. What measures are necessary to transform the diagnostic data into actionable maintenance insights?

2. Classification:

• This RQ will be posted under the Action Research column because the project involves continuous monitoring, evaluation, and improvement of vibration diagnostics.

3. Specific Context/Setting/Industry:

• The research will be conducted in an industrial environment at a manufacturing facility with a focus on two main areas:

  • Winding axes in the aluminum processing section.

  • Rails in the high-bay storage area.

4. Justification for Using Action Research:

• Action Research is appropriate because it enables a cyclic process of planning, implementing, monitoring, and improving the diagnostic methods.

• It aligns with the project’s goal of continuous optimization and adjustment of diagnostic strategies based on real-time feedback.

5. Additional Research Methods:

• Literature review on vibration diagnostics and sensor technologies.

• Comparative analysis of different sensor types and Motion Amplification techniques.

• Expert interviews to gain insights into best practices for vibration monitoring.

6. Data Collection:

• Vibration data will be collected using:

  • Vibration sensors installed on the winding axes and rails.

  • Motion Amplification for visual analysis of vibrations.

• Data will be recorded in real-time using an industrial monitoring system.

7. Data Analysis:

• Fast Fourier Transform (FFT) will be used to analyze frequency patterns.

• Data visualization through Motion Amplification to identify critical vibration modes.

• Machine learning techniques may be explored for anomaly detection.

8. Approximate Timeline:

• Week 1-2: Sensor setup and calibration, configuration of the Motion Amplification system.

• Week 3-4: Initial data collection and baseline analysis.

• Week 5-6: Continuous data collection, evaluation, and adjustment of diagnostic methods.

• Week 7-8: Final analysis, optimization of diagnostic settings, and reporting.

Sub-Questions:
🔧 Usability: What challenges do users typically face when configuring or repairing 3D printers without technical assistance?
👓 AR Effectiveness: How does the use of AR-based instructions affect the accuracy, speed, and success rate of repair and configuration processes?
🧑‍🏫 User Experience: How do users perceive the clarity, helpfulness, and interactivity of the AR interface compared to conventional manuals?
🏫 Educational Impact: In what ways does AR use improve learning outcomes and user confidence in a university setting?

Context/Setting:
The research will be conducted at the Makerspace of the FH St. Pölten, focusing on typical users such as students, researchers, and teaching staff with varying technical backgrounds.

Methodology Justification:
A case study approach is appropriate because it allows an in-depth investigation of AR technology use in a real-world, bounded environment with authentic user interactions.

Additional Methods:
Usability testing, direct observation, and post-task interviews will complement the case study. Surveys and questionnaires may be used to collect broader user feedback.

Data Collection:
Data will be gathered via screen recordings, time measurements, error tracking, observation logs, and structured user feedback.

Data Analysis:
Qualitative data (interviews, observations) will be thematically analyzed. Quantitative performance metrics (task time, error rate) will be statistically compared.

Timeline:
The research will be carried out over a 3-month period, including planning, development of AR content, user testing, and data analysis.

How do digital management mechanisms affect operational efficiency and cost structures in Austrian industrial companies?

case study: try to understand how and why digital mechanisms are used in companies

alternatives: interviews with employees and managers; surveys

data collection: analysis of company reports; industry reports (secondary data)

data analysis methods: thematic analysis (python scripts) for big data

timeline

Literature Review: 8 weeks

Case Selection & Planning: 7 weeks

Data Collection: 12 weeks

Data Analysis: 13 weeks

Writing & Review: 8 weeks

Final Submission: 6 weeks

Sub-questions:

• What risks and failure scenarios are associated with autonomous fault clearing?

• How can the ASIDI (Average System Interruption Index) be calculated without a physical test environment?

• Are current network infrastructures sufficient for reliable deployment of AFC?

Context:
The study will focus on a medium-voltage distribution network, examining existing infrastructure, operational protocols, and regulatory frameworks.

Justification for Case Study:
A case study allows in-depth investigation of real-world practices and constraints in a specific operational context, which is ideal for assessing practical feasibility and risks.

Additional Methods:

• Expert interviews (engineers, planners, regulatory staff)

• Technical document analysis

• Simulated fault scenarios using network simulation tools

Data Collection:

• Internal technical reports

• System performance logs

• Expert interviews and industry standards

Data Analysis:

• Qualitative analysis of interview transcripts

• Comparative analysis of pre/post-AFC implementation scenarios using network modeling tools

Timeline:

• Literature Review: 2 weeks

• Data Collection: 4 weeks

• Analysis: 3 weeks

• Writing and Review: 3 weeks

• Total Duration: ~12 weeks

How does the average drilling time per hole change?

After how many holes does the assembly and disassembly of the robot pay off?

What new potential hazards arise?

How do the workers react to the presence of the robot?

Industrie: Automation and Construction

Case study: because I can take times from one or two projects and then compare them. I don't intervene but rather record what happens

1.

Research Question (RQ)

“How does process automation change the skills, tasks, and job structure in the pharmaceutical industry?”

Sub-questions:

• How do daily tasks change?

• What new skills are needed?

• How do employees feel about the changes?

2.

Case Study or Action Research?

Case Study – to study real companies and real changes.

3.

Context/Setting

Pharmaceutical industry, focusing on production and quality departments in medium and large companies.

4.

Why Case Study?

It helps to understand real examples and deep insights that surveys alone cannot show.

5.

Other Methods

• Interviews with employees and managers.

• Surveys for more opinions.

• Analysis of job documents before and after automation.

6.

Data Collection

• Interviews.

• Surveys.

• Collecting job documents.

7.

Data Analysis

• Code interview answers by themes.

• Use simple statistics for surveys.

• Compare old and new job documents.

8.

Timeline

• Month 1-2: Research plan and literature.

• Month 3: Permissions and choosing companies.

• Month 4-5: Data collection.

• Month 6: Data analysis.

• Month 7: Write results.

• Month 8: Final report.

How can the internal black matt lacquering process be optimized to reduce quality issues and support the insourcing of the external face plate lacquering?

Context:
The project takes place at Dormakaba Austria GmbH, in the surface engineering department. It focuses on improving the black matt lacquering process for door components and evaluating whether the currently outsourced face plate lacquering can be done in-house.

Why action research?
Because I'm directly involved in the process and applying improvements step by step. Action research fits best since it’s hands-on, practical, and allows changes to be tested and adapted in real time.

Other methods:
I’m using root cause analysis (Ishikawa), process planning (Gantt), surface quality tests (like scratch and adhesion), and an economic evaluation for the insourcing option.

Data collection:
Mainly through observation, defect tracking, quality reports, pilot test results, and feedback from staff in production and quality assurance.

Data analysis:
I compare quality outcomes before and after changes, track improvement trends, and assess the technical and financial viability of insourcing.

Timeline:
The project is ongoing and aligns with the semester. Ishikawa and planning are done — now I’m starting process testing and evaluation, to finish by the end of the term.

Possible sub-questions:

What are the most common security vulnerabilities in these wireless technologies?

Which types of attacks (e.g., jamming, spoofing, replay) are practically relevant?

Which protection strategies are technically and economically viable? The research will involve productions in Austria to both analyze existing wireless security issues and develop or evaluate practical protection measures. The study focuses on industrial production environments, particularly within the Industry 4.0 or IIOT context. Why Action Research: enables close collaboration with practitioners to directly identify problems, implement solutions, and evaluate outcomes in real time. Additional Methods: Literature review of current research’s. Interviews with OT Security Experts. Data Analysis: Results of log files; miss configurations and incidents. (Qualitativ). Timeline 1-2 months literature review. Months 3-4: selection of productions and analysis of current security implementation of companies. Months 5-6: designing out a solution with partners month 7: evaluation of the results month 8-10 improvements and final analysis -Rahman Qamar

1. To what extent do data collected through energy monitoring contribute to the optimization of grid operation and to ensuring security of electricity supply?

2. This research question will be addressed using a case study approach, focusing on existing systems and practices in real-world grid operations.

3. The context is the Austrian electricity sector, especially distribution networks using smart grid technologies.

4. A case study is appropriate as it allows analysis of real monitoring systems without requiring direct intervention.

5. Additional methods may include document analysis (e.g., regulatory reports, technical studies) and brief expert interviews.

6. Data will be gathered from public monitoring reports and technical publications.

How can resource utilization in project management be improved?

How can planning and implementation errors be avoided?

Context: The study focuses on a manufacturing firm adopting Industry 4.0 technologies to reduce machine downtime and optimize maintenance.