Register
Register
Register

Luleå University of Technology-Division of Operation and Maintenance Engineering

About

Division of Operation and Maintenance Engineering – Luleå University of Technology

**Driving Intelligent Asset Management R&D through RAMS, Industrial AI, and innovative maintenance engineering and business solutions.

**The Division of Operation and Maintenance Engineering at Luleå University of Technology (LTU) leads internationally in research and innovation for Intelligent Asset Management, supporting the global transition toward sustainable, circular, and digitally enabled industrial systems.

Our work integrates Reliability, Availability, Maintainability, and Safety (RAMS) engineering with advanced Industrial AI, IIoT, and predictive analytics to create data-driven maintenance solutions and enable smarter decision-making across the asset lifecycle. We develop innovative methodologies and digital tools that not only enhance system performance and safety, but also promote resource efficiency, emissions reduction, and lifecycle optimization—core principles of sustainability and circular economy.

Our research contributes directly to the digital transformation of industry, supporting sectors such as railway, mining, energy, and manufacturing in their efforts to modernize infrastructure, reduce environmental impact, and boost competitiveness through intelligent maintenance strategies and business innovation.

Our activities are anchored in three key research centers:

  • 🔗 AI Factory: A collaborative platform for co-creating Industrial AI solutions, enabling real-time diagnostics, predictive maintenance, and autonomous operations.

  • 🔗 CIAM – Centre for Intelligent Asset Management: A strategic center advancing circular and risk-informed asset management for long-term value and resilience.

  • 🔗 JVTC – Luleå Railway Research Center: A leader in sustainable railway research, focusing on digital twins, condition-based monitoring, and maintenance optimization.

  • We, at the Division of Operation and Maintenance Engineering, specialize in optimizing the performance and reliability of critical systems and infrastructure. Our team is dedicated to providing innovative solutions that enhance operational efficiency and ensure the longevity of assets across various sectors. Through collaboration and comprehensive expertise, we strive to support businesses in achieving their maintenance goals while minimizing downtime and costs.

Join us in our commitment to excellence and proactive management in engineering operations.
Learn more about the Division

Data technologies, data ecosystems and cross-linking

Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.(AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths(AI based) process and system control technologiesSimulation models and predictive analytics to assess the scalability of circular processes across industriesAlgorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product

Other enabling technologies

Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled componentsIndustry 4.0 technologies (IoT, big data analytics) for monitoring and managing circular value chains(Advanced/smart) Sensors, e.g., enabling materials, components and product flows measurementLife cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product PassportNetwork design of reverse supply chains

Representatives

Alireza Ahmadi

Professor-Operation and Maintenance Engineering

Luleå University of Technology-Division of Operation and Maintenance Engineering

Marketplace (1)

  • Project cooperation

    Circular Adaptation for Road Vehicle Sustainability (CARS)

    Develop circular strategies using RAMS, Optimization, part-out, and digital tools to cut vehicle lifecycle impact and retain embedded value.

    • Early idea
    • Already defined
    • Consortium seeks Partners
    • Enabling technologies | Network design of reverse supply chains
    • Data technologies | (AI based) process and system control technologies
    • Data technologies | (AI based) Material and Product Design, Decomposition and Separation
    • Data technologies | Algorithm that shows the (positive) impact of a Circular Economy process or Circular Economy product
    • Enabling technologies | Life cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport
    • Enabling technologies | Tools and solutions addressing challenges emerging from product focused regulations (such as the ESPR)
    • Data technologies | Simulation models and predictive analytics to assess the scalability of circular processes across industries
    • Enabling technologies | Reverse Manufacturing (e.g. adaptive automation for high variance, sorting, sophisticated logistic systems)
    • Enabling technologies | AI-driven diagnostic systems, e.g., for assessing the viability of reused, remanufactured, and recycled components
    • Data technologies | Data ecosystems for the realisation of circular value creation exploiting the full potential of digitalisation – e.g., harnessing existing, purpose-built platform solutions.
    • Enabling technologies | Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)
    Author

    Alireza Ahmadi

    Professor-Operation and Maintenance Engineering at Luleå University of Technology-Division of Operation and Maintenance Engineering

    Luleå, Sweden