Research focus
My work sits where industrial engineering meets applied AI. I look at manufacturing processes one step at a time and ask what AI can responsibly take over, what people must keep, and how the two work together in Industry 5.0.
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AI readiness of manufacturing processes
Deciding whether, when and to what extent a process step should be automated with AI, and what human oversight goes with it.
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AI agents on the shop floor
Multi-agent systems and operator assistants built on workflow orchestration in n8n, the Model Context Protocol and language models that run inside the company.
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Process innovation and improvement
Matching the method to the problem: Kaizen, Lean Six Sigma or a full process innovation.
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People in automated work
Mental workload, motivation and retention when processes change, so that automation serves the people who work with it.
Dissertation
Assessing Process Readiness for AI Automation in Manufacturing: A Method for Determining the Extent of Automation and Human Oversight
A manufacturing company rarely decides about adopting AI as a whole. It decides about one step in one workflow: can an AI system classify defects at final inspection, or draft a non-conformity report?
My dissertation develops a method for that decision. Its answer is not yes or no. It says how much of the step AI should do and what human oversight must go with it, taking the requirements of the EU AI Act into account.
- StageSecond year of study, literature review and method design
- Supervisordoc. Ing. Martin Gašo, PhD.
- Study programmeIndustrial Engineering
- WorkplaceDepartment of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina
The title is a working title and may change before the thesis is submitted.
Projects
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2026 – 2027
Principal investigator
Research and implementation of multi-agent systems based on the n8n platform and the MCP protocol for intelligent process control in Industry 5.0
A working prototype in which AI agents orchestrated in n8n read data from a network of IoT sensors and a simulated MES/ERP system through the Model Context Protocol.
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2025 – 2027
Team member
Implementation of a digital twin platform in the educational process
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2025 – 2027
Team member
Innovative methods and approaches in preparing graduates for intelligent manufacturing using Industry 4.0 technologies
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2024 – 2026
Team member
Research and support of the synergistic effect of assembly process optimisation
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2024 – 2026
Team member
Increasing the effectiveness of teaching quality-oriented subjects using virtual reality tools
Publications
Published
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2025
Journal article
The Methodology for Data Collection from a Holonic Manufacturing System
Mičieta, B., Biňasová, V., Gašo, M., Kabát, A.
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2025
Conference paper
A Proposal for Sustainable Human Resource Improvement: Optimizing Employee Motivation and Retention in Real Estate Property Management – Case Study
Kabát, A., Máchová, M., Gašo, M.
In press
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2026
In press
Utilization of Model Context Protocol as a Key Element of Interoperability in Heterogeneous Industrial Systems of Industry 4.0 and 5.0
Kabát, A., Mičieta, B., Mičietová, A.
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2026
In press
Classification of Process Improvement Methodologies in Industrial Engineering: A Hierarchical Selection Model for Kaizen, Lean Six Sigma and Process Innovation
Kabát, A., Marčan, M., Máchová, M.
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2026
In press
A Three-Layer Agentic Operator Assistant for Industry 5.0: Integrating RAG, Model Context Protocol and Workflow Orchestration
Kabát, A., Gašo, M., Dulina, Ľ., Matys, M.
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2026
In press
A Proactive Work Humanisation Model as a Tool for Preventing Psychosocial Risks in Process Innovation
Kabát, A.
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2026
In press
System One Decision Models in Industrial Automation: A Critical Assessment of TypeSafe’s Jev and a Confidence-Gated Architecture for n8n Workflows
Kabát, A., Buzalka, M., Gašo, M.
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2026
In press
Discrete-Event Simulation of a Hybrid Continuous–Discrete Production Line: A Modelling and Validation Methodology
Hrivnáková, E., Kabát, A., Furmannová, B.
Teaching
Management for first-year bachelor’s students in the Industrial Engineering study programme, University of Žilina.
Work experience
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2025 – now
PhD student
University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering
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2024 – 2025
SME banker
Tatra banka, a. s.
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2023 – 2024
HR generalist
SCONTO Nábytok, s. r. o.
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2022 – 2023
HR manager, paid internship
PRIMA ZDROJ Považská Bystrica, spol. s r. o.
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2020 – 2024
Own business
WESE, s. r. o.
Education
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2025 – now
PhD, Industrial Engineering
University of Žilina, Faculty of Mechanical Engineering, Department of Industrial Engineering
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2021 – 2023
Ing., Industrial Management
Slovak University of Technology (STU), module Human Resources in an Industrial Enterprise
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2018 – 2021
Bc., Industrial Engineering
University of Žilina, Department of Industrial Engineering
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2014 – 2018
Mechatronics
Secondary Industrial Technical School, Trnava
Skills and languages
- AI and automationn8n workflows, Model Context Protocol, LLM-based agents
- Data and office toolsPower BI, MS Office, VBA
- CADFusion 360, SolidWorks, Solid Edge
- LanguagesSlovak (native), English (B2), German (A1)
- CoursesMicrosoft Power BI I and II (2023, 2024), Java programming at Green Fox Academy (2023)
About Aderon
Aderon is the name of this site and of an idea in its early days: a research initiative that helps manufacturing companies bring AI into their processes, with a clear view of what to automate and what to leave with people.
Let’s work together
I welcome contact about joint projects, whether you come from industry or from research.
adam.kabat@fstroj.uniza.skDepartment of Industrial Engineering, Faculty of Mechanical Engineering
University of Žilina, Univerzitná 8215/1, 010 26 Žilina, Slovakia
