Technology and the supply chains

Operational Realism

Professor of Industrial Management at the University of Vaasa, focusing on logistics systems, digital operations, and supply chain management.

Operational Realism is an approach to operations management and industrial digitalisation that prioritises executable, physically and organisationally feasible solutions over purely theoretical optimisation. The concept emphasises that real operational performance emerges from variability, constraints, human interaction, material flow dynamics, and system level dependencies that cannot be fully captured through static mathematical models alone. Digital twins, simulation, industrial AI, and real time operational data act as mechanisms for validating whether proposed solutions remain feasible under realistic execution conditions.

My work focuses on industrial operations, logistics systems, and supply chains. The research combines analytical modelling, industrial software development, simulation, and practical collaboration with companies. Current focus areas include real-time supply chains, industrial AI, agent-based operational systems, sustainability analytics, and digital twin enabled decision making.

Research Contact
Petri Helo
Petri Helo

Professor of Industrial Management
University of Vaasa
Vaasa, Finland

Research

My team employs decision support systems, mathematical optimization, simulation, and artificial intelligence to build systems capable of solving real-world industrial problems. This work has contributed to methods and systems for managing complex products, engineer-to-order operations, industrial analytics, and digital operations.

Research topics include:

  • Supply chain management
  • Logistics systems
  • Industrial AI and analytics
  • Digital twins and simulation
  • Sustainable manufacturing
  • Cloud manufacturing ecosystems
  • Agent-based operational systems
  • Real-time supply chains
  • Industrial data integration
  • Product-service systems

Projects

Research projects are conducted in close collaboration with companies and international research partners, aiming to bridge academic research and industrial implementation. The projects focus on industrial digitalization, smart logistics, sustainability analytics, manufacturing systems, and operational decision support.

SuMEX project visual

SuMEX

Sustainable Manufacturing Excellence develops practical methods and tools for life-cycle assessment and sustainability improvement in manufacturing.

RouteSharp software screenshot

e-OPT

e-OPT develops digital tools to improve the cost and environmental efficiency of food ecosystem distribution logistics.

Software and Development

The work includes development of industrial software systems, digital configurators, educational tools, simulation environments, and operational analytics platforms. Development activities combine industrial engineering methods with practical software implementation.

Examples include:

  • Supply chain analysis software
  • Industrial configurators
  • Simulation environments
  • Production planning tools
  • Educational simulators
  • Cloud-based industrial applications

Publications

The publication portfolio includes journal articles, conference papers, books, and industrial research contributions in operations management, logistics, manufacturing systems, sustainability, and industrial digitalization.

Petri Helo serves as Associate Editor of Supply Chain Forum: An International Journal.

Supply Chain Forum editorial board Google Scholar
Supply Chain Forum: An International Journal cover

Selected recent publications:

  1. Huttunen, O., & Helo, P. (2026). Demand variability in engineer-to-order supply chains: insights from a DDMRP case study. International Journal of Production Research, 1-19.
  2. Helo, P., Hao, Y., & Gunasekaran, A. (2025). Use of non-fungible tokens in operations and supply chain management. International Journal of Production Research, 63(14), 5099-5121.
  3. Helo, P., Mayanti, B., Bejarano, R., & Sundman, C. (2024). Sustainable supply chains – Managing environmental impact data on product platforms. International Journal of Production Economics, 270, 109160.
  4. Ahmadov, Y., & Helo, P. (2023). Deep learning-based approach for forecasting intermittent online sales. Discover Artificial Intelligence, 3(1), 45.
  5. Helo, P., & Hao, Y. (2022). Artificial intelligence in operations management and supply chain management: an exploratory case study. Production Planning & Control, 33(16), 1573-1590.

Full publication list:

Google Scholar

Education

Teaching focuses on industrial management, operations, logistics, manufacturing systems, simulation, and digital transformation. Courses combine analytical methods with practical industrial cases and software-supported learning environments.

Supervision

Supervision activities include doctoral dissertations, master's theses, and industrial development projects in industrial engineering and management.

Guidebooks:

OMG! Operations Management Games

OMG! Operations Management Games

OMG is a collection of interactive educational tools and simulations for operations management, logistics, industrial engineering, and analytics education. The platform includes simulations, scheduling tools, inventory models, quality tools, and factory physics demonstrations designed for both university teaching and industrial training.

OMG! Operations Management Games

Examples include:

Labs and Research Infrastructure

The laboratory and infrastructure activities focus on digital factories, supply chain visibility, industrial simulation, IoT-enabled operations, and sustainability analytics. Current developments include digital twin environments, agent-based modelling platforms, industrial data integration, and experimental logistics systems for resilient manufacturing and supply chain research.

Technobothnia VR and AR Laboratory Technobothnia VR and AR Laboratory Metal Additive Manufacturing Lab Metal Additive Manufacturing Lab

Industry Collaboration

The work is conducted in close collaboration with industrial partners across manufacturing, energy technology, logistics, automation, and software industries. Activities include applied research projects, executive education, industrial case studies, software development, and operational improvement initiatives.

Wapice Summium CPQ NoSwing KotiCharge ScopSim 
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  "title": "Operational Realism",
  "subtitle": "technology and the supply chains",
  "person": {
    "name": "Petri Helo",
    "role": "Professor of Industrial Management",
    "institution": "University of Vaasa",
    "location": "Vaasa, Finland",
    "email": "phelo@uwasa.fi",
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  "summary": [
    "Professor of Industrial Management at the University of Vaasa, focusing on logistics systems, digital operations, and supply chain management.",
    "Operational Realism is an approach to operations management and industrial digitalisation that prioritises executable, physically and organisationally feasible solutions over purely theoretical optimisation. The concept emphasises that real operational performance emerges from variability, constraints, human interaction, material flow dynamics, and system level dependencies that cannot be fully captured through static mathematical models alone. Digital twins, simulation, industrial AI, and real time operational data act as mechanisms for validating whether proposed solutions remain feasible under realistic execution conditions.",
    "My work focuses on industrial operations, logistics systems, and supply chains. The research combines analytical modelling, industrial software development, simulation, and practical collaboration with companies. Current focus areas include real-time supply chains, industrial AI, agent-based operational systems, sustainability analytics, and digital twin enabled decision making."
  ],
  "research": {
    "description": "My team employs decision support systems, mathematical optimization, simulation, and artificial intelligence to build systems capable of solving real-world industrial problems. This work has contributed to methods and systems for managing complex products, engineer-to-order operations, industrial analytics, and digital operations.",
    "topics": [
      "Supply chain management",
      "Logistics systems",
      "Industrial AI and analytics",
      "Digital twins and simulation",
      "Sustainable manufacturing",
      "Cloud manufacturing ecosystems",
      "Agent-based operational systems",
      "Real-time supply chains",
      "Industrial data integration",
      "Product-service systems"
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  "projects": {
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        "url": "https://doi.org/10.1080/00207543.2026.2625958"
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      {
        "citation": "Helo, P., Hao, Y., & Gunasekaran, A. (2025). Use of non-fungible tokens in operations and supply chain management. International Journal of Production Research, 63(14), 5099-5121.",
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      },
      {
        "citation": "Helo, P., Mayanti, B., Bejarano, R., & Sundman, C. (2024). Sustainable supply chains – Managing environmental impact data on product platforms. International Journal of Production Economics, 270, 109160.",
        "url": "https://doi.org/10.1016/j.ijpe.2024.109160"
      },
      {
        "citation": "Ahmadov, Y., & Helo, P. (2023). Deep learning-based approach for forecasting intermittent online sales. Discover Artificial Intelligence, 3(1), 45.",
        "url": "https://doi.org/10.1007/s44163-023-00085-1"
      },
      {
        "citation": "Helo, P., & Hao, Y. (2022). Artificial intelligence in operations management and supply chain management: an exploratory case study. Production Planning & Control, 33(16), 1573-1590.",
        "url": "https://doi.org/10.1080/09537287.2021.1882690"
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