Morteza Ghobakhloo is a Senior Lecturer and Researcher at Uppsala University , affiliated with the Department of Civil Engineering and Industrial Engineering (Industrial Engineering) and the Institute for Research on Conflicts of Goals in Sustainable Social Transition . His email is morteza.ghobakhloo@angstrom.uu.se . He focuses on digital transformation, sustainability, and human-centric technologies. Research Interests: Morteza’s work bridges Industry 4.0/5.0 , Sustainable Manufacturing , and Generative AI applications. His studies explore blockchain, big data analytics, and smart technologies in supply chain resilience, energy efficiency, and organizational innovation. Article Trends: Recent publications highlight Industry 5.0’s role in sustainable supply chains, AI-driven healthcare optimization, and blockchain for socioenvironmental solutions. He employs hybrid methodologies like PLS-fsQCA, ANN, and simulation modeling across sectors including energy, healthcare, and tourism.
Micael Derelöv is an Associate Professor at Linköping University's Department of Management and Engineering (IEI), specializing in Product Realisation (PROD). His work focuses on optimizing safety, reliability, and efficiency in industrial and aerospace systems. He contributes to sustainable product development through advanced methodologies in design optimization and failure analysis. His research integrates robotics, manufacturing systems, and systems engineering to address challenges in collaborative assembly, aircraft design, and risk management. Dr. Derelöv’s research interests include multi-objective optimization for balancing safety and weight in aircraft systems, industrial safety demonstrators, and reliability-centric design processes. He has developed frameworks for evaluating design concepts and identifying potential failures in early-stage engineering projects. His work also explores the application of genetic algorithms in concept synthesis and the use of qualitative modeling for risk assessment. His publications highlight trends in industrial safety, systems reliability, and aerospace engineering. Recent work includes advancements in safe collaborative robotics on assembly lines and methodologies for industrial safety demonstrators. Earlier contributions address cost optimization in reliability-focused design and bio-mechatronic product development. While no specific scientific awards are listed, his active research and academic role reflect a commitment to advancing engineering practices. He collaborates on student projects, such as a recent initiative designing a pressure-resistant device for space exploration, demonstrating engagement in applied and interdisciplinary research. Micael Derelöv’s affiliation with the Department of Management and Engineering positions him at the intersection of academic research and industrial innovation, particularly within the Product Realisation group. His work emphasizes sustainable, integrated approaches to product development, blending theoretical insights with practical applications in manufacturing and aerospace sectors.
Pedram Beldar is a researcher affiliated with the University of Skövde , specifically the School of Engineering Science and Department of Engineering . He actively contributes to the fields of Industrial Engineering , Operations Research , and Production Optimization . His research focuses on optimization algorithms for manufacturing processes, including batch processing , flexible transfer lines , and energy-efficient production . He has collaborated on projects like Digitalized and optimized production planning for energy-efficient production (May 2022 - April 2025) and Virtual Engineering . His work emphasizes sustainable manufacturing and smart Industry 4.0 solutions. The trends in his publications highlight applications of operations research to non-identical parallel machines , cross-docking systems , and teaching-learning-based optimization , with a growing emphasis on sustainable production in recent years. He is involved in course coordination for bachelor-level industrial engineering courses and collaborates with researchers such as Masood Fathi , Amir Nourmohammadi , and Gilbert Laporte .
Amos H.C. Ng is a Professor of Automation Engineering at the School of Engineering Science, University West (Högskolan i Skövde). His academic qualifications include BEng, MPhil, and PhD degrees, complemented by professional certifications such as Chartered Engineer (UK) and membership in the Institution of Engineering and Technology (UK). His research focuses on production simulation, multi-objective optimization, simulation-based innovization, and digital human modeling, with applications in manufacturing systems, Industry 4.0, and smart manufacturing. Ng has contributed to over 150 publications since 2000, spanning topics like decision support systems, maintenance optimization, and reconfigurable manufacturing. His work integrates simulation, data mining, and evolutionary algorithms to address challenges in production systems, including bottleneck analysis, energy efficiency, and human-robot collaboration. Notable projects include developing the Mimer knowledge discovery tool and frameworks for digital twin applications in production lines. His research emphasizes practical industry applications, collaborating with organizations to improve production processes through advanced methods like trend mining and cloud-based optimization. Ng also serves as a course coordinator and contributes to educational initiatives in automation engineering.
Dr. Erik Billing is a researcher at the University of Skövde , actively contributing to the School of Informatics and affiliated with the Interaction Lab (ILAB) . His work focuses on human-robot interaction (HRI), cognitive ergonomics, and extended reality (XR) applications in industrial and educational contexts. Research Pillars : Human-Robot Interaction, Cognitive Ergonomics, Eye-Tracking, Virtual/Augmented Reality, Digital Human Modeling Key Projects : RO-LIV (social robots for elderly), EWASS (industrial HRI), OKAVIM (XR competency) Funding : Supported by AFA Insurance and Vinnova grants His recent work includes investigating body language in social robots, expectation formation in HRI, and gaze-based worker behavior prediction. Dr. Billing serves as editor for SweCog conference proceedings and contributes to VR/XR motor learning research.
Masood Fathi is an Associate Professor of Production Engineering at the University of Skövde, Sweden. He holds a position within the School of Engineering Science and Department of Engineering. As an academic, he focuses on advanced manufacturing systems, Industry 4.0/5.0 technologies, and optimization methodologies. His research integrates AI applications, sustainability, and human-robot collaboration in production environments. Education: Formal academic qualifications (specific details not explicitly provided in text). Research Interests: Professor Fathi's work centers on optimizing production systems through advanced algorithms and technologies. Key areas include assembly line balancing, energy-efficient manufacturing, supply chain optimization, and the application of generative AI in industrial processes. He also explores resilience in production systems and sustainable practices such as healthcare waste management and remanufacturing. Recent Trends in Publications: Recent work emphasizes Industry 5.0 sustainability goals, human-robot collaboration, and AI-driven quality inspection. Articles highlight multi-objective optimization challenges, resilient worker performance under disturbances, and the integration of simulation-based decision support systems. Grants & Projects: Lead researcher on projects like 'Enhancing Hospital Services Under Resource Constraints' (2025) and 'Virtual Engineering Agile Manufacturing in Industry 4.0' (2021–2025). Focus areas include smart manufacturing, digital twins, and resilient production systems. Labs/Teams: Collaborates with interdisciplinary teams on projects involving augmented reality for quality inspection, blockchain in supply chains, and lean-green manufacturing integration.
Gary Linnéusson is a Senior Lecturer in Production Engineering at the School of Engineering Science , University of Skövde. His research focuses on system dynamics, manufacturing systems sustainability, healthcare operations, and transdisciplinary approaches to complex challenges. He is actively involved in projects like the REFUSE initiative to enhance resource-efficient manufacturing systems and has contributed to initiatives like Skaraborg Health Technology Center . Key research interests include reconfigurable production systems, maintenance optimization, and policy modeling for healthcare and energy systems. His work bridges theoretical frameworks with practical applications in industries and public sectors, emphasizing systems thinking and collaborative innovation. He has published extensively on topics ranging from system dynamics in healthcare operations to strategic maintenance frameworks in automotive contexts. His interdisciplinary approach is evident in projects addressing regional development and sustainable energy planning. Gary also serves as a course coordinator in engineering education, integrating cutting-edge research into teaching.
Dr. Anna Syberfeldt is a Professor in Production Engineering at the Department of Engineering Science, University of Skövde. She leads the Virtual Production Development research group and serves as research director at the ASSAR Industrial Innovation Arena. With a background in computer science from De Montfort University and habilitation in automation engineering, her work bridges AI, robotics, and immersive technologies with industrial production systems. Professor in Production Technology Research Director at ASSAR Industrial Innovation Arena University of Skövde Affiliation Her research focuses on developing innovative industrial solutions through: Artificial Intelligence and Machine Learning Collaborative Robotics and Human-Robot Interaction Digital Twins and Simulation-Based Optimization Augmented/Virtual/Mixed Reality Applications Smart Manufacturing and Industry 4.0 Worker Well-Being and Productivity Optimization Recent publications demonstrate her leadership in simulation-based optimization, collaborative robotics, and mixed reality applications in manufacturing. Her work emphasizes creating ultra-flexible production systems through cyber-physical approaches while prioritizing environmental sustainability and human-centric design. Key trends in her research include: Unified frameworks for virtual commissioning Knowledge graph applications in production systems Multi-objective optimization balancing productivity and ergonomics Smart glasses evaluation for industrial operators Evolutionary algorithms for complex manufacturing problems Her projects demonstrate practical implementations of: MAXLabs distributed cyber-physical testbed ERAIVA posture identification software Virtual environments for human-robot collaboration testing Digital support functions for factory layout planning
Enrique Ruiz Zuniga serves as Associate Professor in Production Engineering at the University of Skövde's School of Engineering Science in Sweden, while simultaneously holding a JSPS research fellowship at Kyoto University's Systems Design Laboratory and collaborating with Japan Manned Space Systems Corporation (JAMSS). His career bridges academic research and industrial applications across Europe and Asia, focusing on optimizing complex manufacturing and logistics systems through advanced computational methods. University of Skövde, School of Engineering Science JSPS Research Fellow, Kyoto University Japan Manned Space Systems Corporation (JAMSS) collaborator Dr. Ruiz Zuniga's educational background includes a B.Eng. in industrial engineering from the University of Malaga, Spain, a BSc in automation engineering from the University of Skövde, Sweden, followed by an MSc in industrial informatics and a 2020 PhD in informatics from the University of Skövde, completed in partnership with Xylem Water Solutions Manufacturing. His doctoral research focused on facility layout design using simulation-based optimization methodologies. His primary research interests encompass the design, verification, and improvement of logistics, robotics, and complex production systems, with methodological expertise in Lean Production, Discrete-Event Simulation, System Dynamics, Simulation-Based Optimization, and the Functional Resonance Analysis Method. Dr. Ruiz Zuniga's work demonstrates a consistent focus on international collaboration and practical implementation of theoretical models in real-world industrial settings across healthcare and manufacturing sectors. Analysis of his publication record reveals an evolution from foundational work in facility layout design toward more recent explorations of AI integration, human-centered design, and resilient production systems. His research shows increasing sophistication in combining simulation approaches with functional analysis methods, with a growing emphasis on human factors and system resilience in complex production environments. REFUSE (2023-2026): Resource efficient use of reconfigurable machining systems Dynamic SALSA (2023-2024): AI scheduling for assembly and logistics systems Envisioned world problems (2021-2023): Functional approaches for system design Emergency Department Modeling (2012-2016): Healthcare production systems Dr. Ruiz Zuniga has coordinated international engineering programs in Industrial Engineering, Product Design Engineering, and Mechanical Engineering (all 60 credits), while teaching courses including Introduction to Lean Philosophy, Methods Engineering, Mechatronics/Electronics, and Production and Logistic Simulation. His work demonstrates a strong commitment to bridging theoretical research with practical industrial applications in production engineering through international collaboration and methodological innovation.
Gary Linnaeusson is a Senior Lecturer in Production Engineering at the University of Skövde, working within the School of Engineering Science's Department of Engineering. His office is located in Room PA210P, and he can be contacted at gary.linneusson@his.se or by phone at 0500-448537. Dr. Linnaeusson's research interests focus on applying system dynamics to complex production and manufacturing systems. His work spans multiple domains including reconfigurable manufacturing systems, production platforming, maintenance optimization, and increasingly, healthcare systems simulation. His research demonstrates a strong interdisciplinary approach, bridging engineering principles with practical applications in both industrial and healthcare contexts. His publication record shows consistent research output from 2006 through 2025, with recent work emphasizing the economic sustainability of reconfigurable modularization, manufacturing reshoring decision processes, and healthcare optimization through system dynamics modeling. His articles appear in reputable journals such as the Journal of Simulation, European Journal of Operational Research, International Journal of Production Economics, and Journal of Health Organization & Management. Dr. Linnaeusson is actively involved in multiple research projects including REFUSE (Resource efficient use and development of reconfigurable machining systems, 2022-2025), Digital Models to Develop the Energy Systems of the Future (2022-2024), and The future healthcare system in the region of Västra Götaland (2024-2025). He has also completed significant projects such as Strategy Network City Skaraborg, The Innovation System of a Hospital, and Simulation of interventions for close care for the sickest elderly. His work demonstrates strong collaborative research practices, with frequent co-authorship across disciplinary boundaries, particularly between engineering and healthcare domains. While no specific awards are mentioned in the available information, his extensive publication record in high-impact journals suggests recognition within his research community.
Aitor Iriondo Pascual is a researcher at the University of Skövde's School of Engineering Science , specializing in digital human modeling (DHM) and simulation-based multi-objective optimization (MBOO) for ergonomics and productivity in manufacturing systems. His work bridges industrial engineering with human factors research, focusing on automating ergonomic assessments using motion capture technology and machine learning algorithms. PhD in User-Centered Product Design (University of Skövde, 2023) Active in Virtual Production Development (VPD) and Synergy Virtual Ergonomics (SVE) research profiles Collaborator in international projects like MOSIM and VIVA Key contributor to DHM toolchain development with IPS IMMA and LUA scripting His research interests center on: Integrating motion capture with DHM for objective ergonomic evaluations Automated hand posture classification using random forest algorithms Concurrent optimization of productivity and worker well-being in factory layout design Standardization of 3D body shape prediction models for virtual simulations Machine learning applications in biomechanical exposure assessments Digital twin development for sustainable manufacturing systems Recent publications demonstrate his expertise in combining genetic algorithms with DHM tools for occupant packaging design and logistics area optimization. He has also developed open-source statistical body shape prediction models shared under MIT License on GitHub. Key collaborators include: Prof. Lars Hanson (ergonomics) Dr. Dan Högberg (simulation methods) Dr. Anna Syberfeldt (optimization frameworks) Dr. Erik Brolin (DHM tools) His methodological innovations include: Automating REBA / RULA assessments via motion capture data Developing Pugh's method implementation for DHM concept evaluation Creating cross-disciplinary optimization frameworks for production systems
Andreas Dagman is a Senior Lecturer in Product Development at Chalmers University of Technology, Sweden. His research spans sustainability , robust design , variation simulation , and Computer-Aided Design (CAD) , with a focus on integrating industrial practices into academic frameworks. Key projects: DigiGeo (2019) for geometry data management Academic leadership: Co-authored 30+ publications (2002-2024), including studies on tolerance optimization and XR-based quality evaluation His work emphasizes multi-objective design balancing economic, ecological, and social sustainability. Recent studies explore AI tools in education and pandemic-era CAD teaching , while early research focused on automotive split-line design and geometrical variation .
Ou Tang is a Professor of Production Economics at Linköping University (Sweden), serving as editor for the International Journal of Production Economics and past president of the International Society of Inventory Research (ISIR). His research focuses on inventory modeling, sustainable supply chains, closed-loop systems, and China-related operations management. He has authored over 100 scientific articles in top journals like European Journal of Operational Research and Production and Operations Management. Notable contributions include analyzing supply chain risk management strategies and exploring dynamics of remanufacturing systems. His work frequently addresses global challenges such as low-carbon urban development and policy impacts on photovoltaic exports. Tang is part of the Royal Swedish Academy of Engineering Sciences (IVA) 100 list and features in Stanford's top 2% most cited researchers. He leads research projects like PERSEUS, advancing the 15-minute city concept through sustainable transport systems. Tang's interdisciplinary approach integrates logistics, manufacturing, and environmental policies, reflecting his commitment to bridging theory and real-world applications.
Amos H. C. Ng is a Professor at the School of Engineering Science, University of Skövde, specializing in simulation-based optimization and Industry 4.0 technologies. His research bridges production engineering with human-robot collaboration, ergonomics evaluation, and cloud-based cyber-physical systems for manufacturing efficiency. Key Affiliations: University of Skövde (School of Engineering Science), Uppsala University (Industrial Engineering and Management) Research Themes: Multi-objective optimization, Digital Twin frameworks, Human-centric production systems, Reconfigurable manufacturing, Throughput bottleneck analysis Projects: ACCURATE 4.0 (Knowledge Foundation), VF-KDO (Virtual Factories with Knowledge-Driven Optimization), EWASS (Wire Harness Assembly Optimization) His recent publications demonstrate expertise in applying evolutionary algorithms, machine learning models, and digital human modeling tools to solve complex manufacturing problems ranging from crankshaft machining to wood supply chain robustness. Current work integrates motion capture technology with DHM tools for objective ergonomic assessments in assembly stations. Amos collaborates extensively with industrial partners like Volvo Penta and academic institutions, utilizing simulation-based approaches to enhance decision-making in production systems. His methodological focus includes non-dominated sorting genetic algorithms, surrogate modeling, and parallel computing architectures for optimization tasks.
