Chair: ^(a)Radu Godina

Affiliation: ^(a)UNIDEMI, FCT NOVA
Universidade NOVA de Lisboa (Portugal)

Track Description: In the global mission to reduce carbon emissions, excessive energy consumption, and waste generation, the Circular Economy (CE) emerges as a needed solution. A key approach within CE is Industrial Symbiosis (IS), where waste from one industry serves as a resource for another, reducing environmental impact while promoting economic efficiency. This track is dedicated to advancing IS by fostering collaboration between industries, policymakers, and researchers to transition away from the traditional linear economy.
Despite its benefits, IS adoption faces significant barriers, including lack of awareness, technical limitations, economic feasibility, regulatory challenges, and social resistance. These challenges can be addressed by promoting inclusive and knowledge-driven IS practices and creating synergies among stakeholders, and by generating robust strategies that support sustainable production and resource optimization.
The adoption of IS within CE frameworks will be instrumental in achieving long-term sustainability goals. Combined efforts from distinct stakeholders are crucial in transforming industrial processes, reducing waste, and enhancing environmental sustainability while ensuring economic benefits. By bridging knowledge gaps and facilitating cooperation, this Track is open to submissions form a broad range of topics addressing a balanced economic model that balances industrial growth with ecological responsibility.
This track proposal is part of the COST Action Project CA22110 – “Cooperation, development and cross-border transfer of Industrial Symbiosis among industry and stakeholders (LIAISE)”.

Chair: ^(a)Leonardo Leoni, ^(b)Alessandra Cantini, ^(c)Eleonora Bottani, ^(d)Filippo De Carlo, ^(e)Annalisa Santolamazza, ^(f)Francesco Mancusi, ^(g)Italo Cesidio Fantozzi, ^(h)Mario Tucci

Affiliation: ^(a)Università eCampus (Italy), (b)(c)Politecnico di Milano (Italy), (d)(h)Università degli Studi di Firenze (Italy), (e)(g)Tor Vergata Università di Roma (Italy), (f)Università degli Studi della Basilicata (Italy)

Track Description:The modern industrial landscape is undergoing a profound transformation driven by Artificial Intelligence (AI), data-driven analytics, and human-centricity. This special session invites research that explores these domains (either individually or as an integrated framework) to address the contemporary challenges of Operations Management (OM) and Supply Chain Management (SCM).

The session emphasizes the importance of human-centric approaches, ensuring that technological advancements augment human capabilities, improve workplace safety, and foster ergonomic industrial environments. This track also covers environmental sustainability and resilience. Regarding the former, contributions that demonstrate how intelligent technologies and data-informed strategies can minimize ecological footprints, optimize resource consumption, and promote circularity are welcomed. Regarding the latter, the employment of AI and data-driven techniques for navigating the market volatility are accepted. We encourage submissions ranging from theoretical frameworks to empirical studies and successful industrial experiments.

• Human-centric systems and human-robot interaction in logistics.
• AI applications for predictive maintenance and operational efficiency.
• Data-driven strategies for supply chain resilience and risk management.
• Impact of human-machine collaboration on productivity and safety.
• Environmental sustainability in warehousing and green operations.
• Innovative case studies and experimental trials in OM and SCM.
• Energy monitoring and energy efficiency improvements of industrial systems.

Co-Chairs: ^(a) Foivos Psarommatis, ^(b)Victor Azamfirei-Ionita

Affiliation: ^(a)University of Oslo (Norway), ^(b)NOVA School of Science and Technology (Portugal)

Track Description: Global competitiveness is driving manufacturing industries to tightly integrate design, production, and product lifecycle information to enhance quality, robustness, and sustainability. Contemporarily, even large manufacturers require high flexibility while adopting greener and more resource-efficient practices, accelerating the transition toward smart, data-driven, and AI-enabled manufacturing. Within this context, Zero Defect Manufacturing (ZDM) has emerged as an advanced quality management paradigm that combines traditional methods with Industry 4.0/5.0 technologies such as artificial intelligence, machine learning, robotics, cyber-physical systems, IoT, digital twins, and human–machine collaboration, enabling integrated, real-time quality strategies based on the four ZDM pillars of detect, predict, prevent, and repair. Digital manufacturing systems increasingly leverage simulation, optimization, and decision support to reduce cost, lead time, waste, and environmental impact while improving reliability, yet many organizations still lack the methodological and organizational capabilities to deploy such solutions at scale. Emerging technologies such as XR, metaverse environments, cognitive robotics, and human-robot teamwork are reshaping the entire value chain from R&D to end-of-life strategies, and as Industry 5.0 advances, the focus shifts toward human-centric, resilient, and circular manufacturing. This track brings together researchers and practitioners advancing ZDM and next-generation quality management solutions.

Co-Chairs: ^(a)Mario Di Nardo, ^(b)Luigi Monica

Affiliation: ^(a)Università Telematica Pegaso (Italy), ^(b)DIT- INAIL (Italy)

Track Description: The ongoing integration of Artificial Intelligence, Machine Learning and intelligent technologies into machinery is significantly changing the consolidated Safety and Maintenance Management, and Human–Machine interaction in industrial systems.
The increasing AI-enabled machinery offers new opportunities for predictive maintenance, fault diagnosis, Risk Assessment also through a more precise decision support introducing challenges related to reliability, explainability, human performance and trust.
In this evolving scenario, recent regulatory developments, such as the EU Machinery Regulation (EU) 2023/1230, further highlight the importance of Human-Centered, reliable and Safe AI-based solutions, without limiting the scope of methodological and application domains.
This track aims to attract theoretical, methodological and applied contributions addressing safety, maintenance and human factors in AI-enabled machinery, with reference to both industrial applications and emerging research trends.

• AI and Machine Learning for machinery safety and maintenance
• Fault diagnosis, prognostics and health management (PHM)
• Human reliability analysis and human error modeling
• Human–machine interaction and decision support systems
• Operator workload, stress and performance modeling
• AI-based risk assessment and safety analysis
• Explainable and trustworthy AI in safety-critical machinery
• Digital twins for machinery safety and maintenance
• Regulatory, standardization and compliance aspects of AI-enabled machinery
• Case studies and industrial applications

Co-Chairs: ^(a)Pedro Espadinha-Cruz

Affiliation: ^(a)UNIDEMI, NOVA School of Science and Technology (Portugal)

Track Description:
Supply chain management (SCM) is fundamental to industrial competitiveness, linking decisions on procurement, production and logistics. As supply chains become more complex and data‑driven, there is a growing need for applied research that bridges theory and practice through technology‑enabled, analytics‑driven and sustainable solutions.

This track focuses on applied research and education in SCM, emphasizing real-world problem solving and technology-enabled decision-making supported by digital technologies, data analytics, and business intelligence. Contributions should demonstrate empirical validation and practical impact through industrial case studies, operational data, implemented decision-support systems, or collaborative university–industry environments. Methodological approaches may include analytics, optimization, simulation, artificial intelligence, digital platforms, and hybrid decision-support systems.

The track encourages work on educational and training approaches that function as real‑world experimentation environments for supply chain decision-making — such as applied learning centers, SCM laboratories, simulation platforms, serious games and digital twins — grounded in real data and industrial collaboration.

Topics include:

• Planning and coordination
• Inventory and demand management
• Procurement
• Warehousing and distribution
• Transportation and network design
• Performance measurement
• Risk and resilience management
• Sustainability
• Digitalization
• and university-industry collaboration

Chair: ^(a)Tim Jeske

Affiliation: ^(a)ifaa – Institute of Applied Industrial Engineering and Ergonomics (Germany)

Track Description: Human work is crucial for a successful development of companies. Today, it is strongly influenced by the opportunities and increasing spread of digitalization. Digitalization facilitates existing forms of work and collaboration, enables innovative approaches and is the basis for the use of artificial intelligence. Examples include the increased proportion of employees working from home during the corona pandemic, a human-robot collaboration which combines the individual strengths of human and robots as well as self-adapting assistance systems. A successful application of digitalization and artificial intelligence requires changes not only in technological aspects but also in organizational circumstances and personal aspects like development of qualifications and skills. The focus of “Artificial Intelligence for Supporting Human Work” is the innovative design of socio-technical systems for supporting human work by using digitalization and artificial intelligence.

Co-Chairs: ^(a)Rui Pinto, ^(b)Gil Gonçalves, ^(c)Rodolfo Haber

Affiliation: ^(a)(b)SYSTEC-ARISE, Faculty of Engineering, University of Porto (Portugal), ^(c)Center for Automation and Robotics, CSIC-Universidad Politécnica de Madrid (Spain)

Track Description:

The next wave of industrial transformation demands more than human-centricity—it requires true collaboration between humans and AI. As Industry 5.0 evolves, the concept of Operator 5.0 must expand beyond upskilling into new paradigms of Human–AI co-learning, shared autonomy, and mutual adaptation. This track explores emerging methods, systems, and frameworks that enable humans and AI to learn together, work alongside each other, and co-adapt in dynamic industrial environments.

We invite contributions that examine how AI can support human skill development, creativity, and decision-making, as well as how humans can guide, fine-tune, and build trust in AI behavior. Topics include:

• Human–AI collaboration in manufacturing, logistics, and services
• Human–AI co-learning frameworks and feedback loops
• Adaptive and personalized training with AI tutors or copilots
• Multimodal interfaces and explainable AI for collaboration
• Agentic AI in human-in-the-loop scenarios
• Mixed reality and digital twins for collaborative training
• AI-augmented soft skill development (e.g., communication, leadership)
• Evaluation methodologies for Human–AI teamwork
• Ergonomic, cognitive, and ethical aspects of Human–AI interaction
• AI-mediated knowledge transfer and tacit skill capture

This track welcomes researchers, educators, and industry practitioners shaping the next generation of symbiotic Human–AI systems to enhance workforce resilience, inclusion, and capability in Industry 5.0.

Co-Chairs: ^(a)Prof. Dr.-Ing. Fabian Behrendt, ^(b)Dr. Niels Schmidtke

Affiliation: ^(a)Magdeburg-Stendal University of Applied
Sciences (Germany), ^(b)Fraunhofer Institute for Factory Operation and Automation IFF (Germany)

Track Description: This track highlights how companies in the Industry 4.0/5.0 environment are developing technologybased
business models and transforming themselves into resilient, data- and AI-driven “digital
enterprises.” The focus is on strategies for redesigning value propositions and value creation, even in the
face of uncertainty caused by disruptions, volatility, and regulation. There is a particular focus on the
design of transformation in the context of digital and AI transformation (roadmaps, scaling, etc.) and on
entrepreneurial resilience management as a management system for ensuring robustness, adaptability,
and continuity. Discussions will cover digital operating models, capability building, data and AI
governance, and the strategic and organizational prerequisites for scalable digitalization and AI use.
Possible topics: Platform and ecosystem strategies; Data/AI monetization, servitization, and digital
product services; AI/GenAI in planning; Resilience-by-Design (business continuity, supply chain
resilience), transformation design (portfolio management, change approaches), skills and workforce
transformation; Metrics for measuring digital maturity, productivity, and resilience.

Deutsch:
Dieser Track beleuchtet, wie Unternehmen im Umfeld von Industry 4.0/5.0 technologiebasierte
Geschäftsmodelle entwickeln und sich zu resilienten, daten- und KI-getriebenen „Digital Enterprises“
transformieren. Im Zentrum stehen Strategien zur Neugestaltung von Wertversprechen und
Wertschöpfung, auch unter Unsicherheit durch Störungen, Volatilität und Regulierung. Ein besonderer
Fokus liegt auf der Gestaltung von Transformation im Kontext der digitalen und KI-Transformation
(Roadmaps, Skalierung, u.W.) sowie auf unternehmerischem Resilienzmanagement als
Managementsystem zur Sicherung von Robustheit, Anpassungsfähigkeit und Kontinuität. Diskutiert
werden sollen digitale Operating Models, Capability Building sowie Data- und AI-Governance und die
strategischen und organisatorischen Voraussetzungen für skalierbare Digitalisierung und KI-Nutzung.
Mögliche Themen: Plattform- und Ökosystemstrategien; Data/AI-Monetarisierung, Servitization und
digitale Produkt-Services; KI/GenAI in Planung; Resilience-by-Design (Business Continuity, Supply-Chain-
Resilienz), Transformationsgestaltung (Portfoliosteuerung, Change-Ansätze), Skills- und Workforce-
Transformation; Metriken zur Messung von digitaler Reife, Produktivität und Resilienz

Co-Chairs: ^(a)Claudio Savaglio, ^(b)Vincenzo Barbuto, ^(c)Antonio Guerrieri, ^(d)Francesco Cauteruccio

Affiliation: ^(a)(b)University of Calabria (Italy), ^(c)Italian National Research Council (CNR)-ICAR (Italy), ^(d)University of Salerno (Italy)

Track Description: Cyber-Physical Systems (CPS) and Industrial Internet of Things (IIoT) technologies are key enabling factors for the creation of a connected value chain in Smart Factories. Integrated with other emerging paradigms like Digital Twins, Edge Computing and Blockchain, CPS and IIoT support advanced data sensing, transmission and analytics, thus fostering the creation of a Smart Factory ecosystem where humans, machines and products are seamlessly internetworked aiming at the maximum efficiency, effectiveness and safety. The way towards cognitive and autonomic Smart Factories necessarily goes through a multidisciplinary approach involving the latest advancements in the whole ICT landscape: the potentialities are huge as well as the challenges to face. As a consequence, the track aims at stimulating both practical and theoretical contributions focused on the integration of CPS and IIoT in the Smart Factory domain. Topics of interest include, but are not limited to: IIoT-based approaches for Smart Factories, Digital Twins and Digital Thread, Body Sensor Networks for Safety in Smart Factories, CyberSecurity, Privacy and Trust for Smart Factories, Development methodologies and simulation tools for Smart Factories, Smart Products and Business models for product-service hybrids, Edge-Cloud continuum for architecting Smart Factories, Cognitive Factories, Smart Factories Applications.

Co-Chairs: ^(a)Herbert Jodlbauer, ^(b)Julian Müller

Affiliation: ^(a)University of Applied Sciences Upper Austria (Austria), ^(b)Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)

Track Description: The triple transition requires manufacturers to jointly advance digital transformation, environmental sustainability, and social responsibility. Data-driven approaches are increasingly central to addressing these interconnected goals by enabling improved decision-making, performance monitoring, and optimization across manufacturing systems.
This track invites contributions that explore how manufacturers can leverage data-driven approaches to optimize resource efficiency, reduce environmental impact, and enhance social outcomes while pursuing digital transformation. We welcome research examining the role of data analytics and related approaches, such as AI and machine learning, digital twins, and the IoT, in supporting greener production processes, monitoring and optimizing sustainability performance, and enabling more inclusive workplaces.
Submissions may also address practical challenges associated with data-driven approaches, including the integration of heterogeneous data sources, ensuring data quality, and managing ethical and data governance considerations. Relevant topics include AI-supported decision-making for digital, green, and social objectives, machine learning for circular economy and closed-loop production systems, predictive analytics for reducing the carbon footprint and resource consumption, data analytics for social impact measurement, and IoT-enabled real-time optimization.
The track aims to foster dialogue between academia and industry by sharing case studies, best practices, and actionable frameworks that demonstrate how data-driven approaches can accelerate the triple transition in manufacturing.

Co-Chairs: ^(a)Maurizio Faccio, ^(b)Irene Granata

Affiliation: ^(a)(b)Università degli Studi di Padova (Italy)

Track Description: Among the recent technologies and methods constituting Industry 4.0, collaborative robots (or cobots) provide unique advantages. Introduced in the last decade, this new category of robots aims to physically interact with human operators in a shared environment thus, avoiding the need for the safety measures typical of traditional robotic systems. Workspace sharing, under proper condition, improves flexibility and reduces the cycle time. Moreover, the absence of safety fences allows to quickly change the layout, helping to implement a dynamic productive cell, capable of adapting to volume and model changes. However, the cobots’ ability to cooperate with human operators could decrease their efficiency if this interaction is not properly studied. When an operator works near an automatic system, safety is always a concern. Moreover, the needs and perceptions of the operator must be considered in terms of system performance, like productivity and production costs. This is in accordance with the human-centered direction of Industry 4.0, which introduces the concept of Operator 4.0, i.e., the augmentation of the human capabilities through these novel technologies. This open special session aims to gather the latest research achievements, findings, and ideas regarding collaborative robots, with particular attention to the influence of human factors. These include advanced technologies, mathematical models and methods, automation, management techniques and approaches; moreover, industrial case studies are also welcome.

Co-Chairs: ^(a)Fabio De Felice, ^(b)Antonella Petrillo

Affiliation: ^(a)(b)University of Napoli “Parthenope” (Italy)

Track Description: The increasing global competitiveness is driving the manufacturing sector to adopt more integrated solutions across design, manufacturing, and products, to improve quality and process efficiency. In today’s market, even large companies need to ensure flexibility and responsiveness. Over recent years, smart manufacturing technologies have evolved toward a new paradigm known as digital manufacturing. These solutions are characterized by an integrated approach that includes optimization capabilities to reduce time, costs, and improve operational efficiency. Despite the growing adoption of these technologies, many organizations still face gaps in their digital capabilities.
The digital revolution is no longer a distant future; it is the present reality shaping the industry today. Key tools driving digital manufacturing include for example artificial intelligence, automation, robotics, additive technologies, human-machine interaction, and the Internet of Things (IoT) and metaverse. It is clear that the tools defining digital manufacturing are set to evolve and diversify, pushing the boundaries of how we work and interact in the industrial ecosystem.
The digital revolution is now our “present” is not the future. In this context, digital manufacturing technologies are also fundamentally reshaping decision-making processes. The introduction of predictive algorithms, advanced data analytics, and autonomous decision-making systems allows companies to make faster, more accurate, and data-driven decisions. Decision-making has become a crucial aspect of adopting and implementing Industry 5.0 solutions.
The track aims to collect papers, case studies, and practical applications from researchers, academics, and practitioners that explore the integration of digital technologies with strategic decision-making providing significant insights in the context of Industry 4.0 towards Industry 5.0 to solve complex problems in the field of manufacturing planning, management, and control.

Co-Chairs: ^(a)Viola Gallina, ^(b)Carolynn Bernier, ^(c)Daniel Bachlechner, (d)Arko Steinwender, ^(e)Thomas Lampoltshammer

Affiliation: ^(a)(c)(d)Fraunhofer Austria Research Gmbh (Austria), (b)French Alternative Energies and Atomic Energy Commission (France), ^(e)Danube University Krems (Austria) 

Track Description: The Digital Product Passport (DPP) is a key initiative under the EU’s Ecodesign for Sustainable Products Regulation, aimed at enhancing transparency, traceability, and circularity. It provides structured product lifecycle data, including material composition, environmental impact, and repairability, to support the circular economy by enabling reuse, remanufacturing, and recycling. DPP will force companies to collect, standardize, and share interoperable data across global value chains while addressing privacy and security concerns. Technologies like blockchain and data spaces offer potential solutions by ensuring secure, decentralized, and controlled data exchange.
Implementing DPPs require careful requirements engineering and software architecture design, and novel methods and techniques to ensure continuous integration and deployment as well as architectural conformance and regulatory compliance. Integrating analytics and federated machine learning can unlock valuable insights from product lifecycle data, enabling predictive maintenance, optimizing resource efficiency, and enhancing decision-making throughout the circular economy.
DPPs also open doors for new business models, such as product-as-a-service, resale platforms, and digital marketplaces, by providing real-time product insights. While initially an EU-driven regulation, the concept has global relevance, influencing international sustainability policies and trade standards. Ensuring harmonization across industries and regulatory frameworks will be essential for global adoption and impact.

Co-Chairs: ^(a)Barbara Bigliardi, ^(b)Eleonora Bottani, (c)Laura Monferdini, (d)Benedetta Pini, ^(e)Vincenzo Corvello

Affiliation: ^(a)(b)(c)(d)University of Parma (Italy), ^(e)University of Messina (Italy)

Track Description: In recent years, complexity and requirements in industrial and public contexts have gradually increased. Factors such as demand for highly customized products, growing international competition and rising expectations for public service quality both companies and public organizations.
Technological progress in recent years has opened new commercial opportunities for private and public actors.
Concepts such as digitalization, internet of things and cyber-physical systems are gaining momentum across business environments and the public sector.
The term Industry 4.0 has become a key concept, encompassing several impacts: (i) greater transparency throughout the entire process from order to end of life cycle; (ii) enhanced inter-organizational collaboration across industrial and public ecosystems, involving firms, public institutions, and service providers; (iii) changes in supply chain (SC) structures and the emergence of new industrial and public service systems.
To understand the opportunities and potential threats arising from these technologies, this track addresses, but is not limited to, the following key areas:

• Advanced technologies application in SC and public sector contexts
• Diffusion of digital technologies and digital transformation in industrial and public organizations
• Effects of digitization on efficiency, effectiveness, and flexibility in SCs and public services
• Impacts of digitization on decision-making, leadership practices, and management practices across industry and the public sector
• Innovative SC models based on big data analytics
• Industry 4.0 and its impact on supply chain management (SCM) and public sector ecosystems
• Maturity models for digital transformation of SCM
• Emerging models of digital transformation in the public sector

Chair: Abbas Dashtimanesh

Affiliation: KTH Royal Institute of Technology (Sweden)

Track Description: The ” Digitalizing the Ship Life Cycle” track emphasizes the pivotal role of digitalization throughout every stage of a ship’s life, from concept design to decommissioning. It explores how integrating digital tools, methods and technologies revolutionizes traditional practices, enhancing efficiency, safety, and sustainability across the whole ship life cycle. Key areas of focus include design optimization through advanced simulations and virtual prototyping, streamlined production using digital twins and IoT technologies, operational efficiency via sensor networks and AI, and optimized maintenance schedules to extend component lifespan. The track invites researchers and industry experts to contribute papers showcasing the latest findings, innovations, and case studies in ship life cycle digitalization. Looking ahead, it aims to foster dialogue on advancing digitalization efforts within the maritime industry, with the ultimate goal of driving greater efficiency, safety, and sustainability across fleets. The call for papers encourages contributions that deepen our understanding of how digitalization shapes ship design, production, operation, maintenance, and beyond, paving the way for a more innovative and resilient maritime sector.

Co-Chairs: ^(a)Stefan Wagner, ^(b)Altendorfer Klaus

Affiliation: ^(a)University of Applied Sciences Upper Austria, Hagenberg Campus (Austria), ^(b)University of Applied Sciences Upper Austria, Steyr Campus (Austria)

Track Description:
From a management perspective, the increasing demand to expand the use of renewable energy sources has introduced an extra layer of complexity to production planning and control. Utilizing self-generated energy offers the potential not only to reduce reliance on external factors but also to lower costs. In the era of intelligent manufacturing, it is crucial to incorporate considerations of energy generation, availability, and consumption into the control and optimization of production systems.
We cordially invite researchers and managers to share their ideas, solution strategies, and research findings on modeling and optimizing production systems with a focus on the energy factor.
Topics of interest include, but are not limited to:

• Integrating energy aspects into the modeling and evaluation criteria for production planning problems.
• Modeling, forecasting, and simulating energy generation and consumption in production systems.
• Incorporating prescriptive analytics into the intelligent planning and control of manufacturing and logistics, considering both available and required energy.

Co-Chairs: ^(a)Ihsan Ullah, ^(b)Umair Ul Hassan, ^(c)Ali Intizar, ^(d)Michael Madden

Affiliation: ^(a)(b)(d)University of Galway (Ireland), ^(c)Dublin City University (Ireland)

Track Description: Majority of the industries are enthusiastic to use and adopt Deep Learning (DL) for Internet of things (DL on the edge). However, there are several concerns around this including privacy, cost, speed, reliability, security, networking, and trust in the systems that uses such models or approaches. One of the
limitations in DL is its data hungry nature i.e. it needs more data for training to give good results. However, after GDPR and other laws, data sharing became a big concern. Therefore, Google in 2016 presented its Federated Learning (FL) approach that does not need data to be stored on a central location for training rather the data remains at its own premises, but the model parameters are shared to be trained remotely over the data and then the trained model is sent back to be globally aggregated on the server. It helps in securely and efficiently training a model without violating any privacy concerns. Several researchers and practitioners have expressed their interest in this area with the expectation of profound effect in the context of Industry 4.0. However, the topic is still in early stages and needs to be investigated. There is a still more to do in literature from both a theoretical and empirical point of view. Therefore, this special track is dedicated to present the effectiveness and advantages of FL for advancing industrial loT, smart manufacturing, and related fields.

Co-Chairs: ^(a)Luca Silvestri, ^(b)Antonio Forcina, ^(c)Cecilia Silvestri

Affiliation: ^(c)Universitas Mercatorum (Italy), ^(b)University of Naples “Parthenope” (Italy), ^(a)University of “Tuscia” (Italy)

Track Description: Manufacturing has evolved through successive industrial revolutions, each introducing technologies and paradigms that reshaped production and logistics systems. Today, the digital transformation driven by Industry 4.0 is evolving towards the Industry 5.0 paradigm, which complements advanced digitalization with a focus on human-centricity, resilience, and sustainability. In this context, logistics and material handling systems represent key application domains where this transition can be effectively observed. While Industry 4.0 technologies, such as Cyber-Physical Systems, Internet of Things, Artificial Intelligence, and data analytics, enable real-time visibility, automation, and efficiency, Industry 5.0 redefines system objectives by emphasizing the role of human operators, adaptive operations, and reduced environmental impact. The integration of human-technology interaction solutions, including collaborative robotics, wearable devices, and Augmented Reality, enables safer, more ergonomic, and more flexible logistics and material handling operations. These solutions support operators cognitively and physically, enhance system adaptability to disruptions, and promote sustainable resource utilization. This track aims to stimulate interdisciplinary contributions addressing the design and performance evaluation of logistics and material handling systems in the Industry 5.0 era, with particular attention to holistic approaches integrating digital technologies, organizational strategies, and human factors.

Chair: ^(a)Valentina Di Pasquale, (b)Marta Rinaldi, ^(c)Valentina De Simone, ^(d)Mario Caterino 

Affiliation: ^(a)(b)University of Salerno (Italy), ^(c)(d)University of Campania “Luigi Vanvitelli”

Track Description: The transition to a circular economy makes manufacturing a key player in reducing waste, extending product life cycles, and making production sustainable through processes such as remanufacturing, refurbishment, and reconditioning. These processes are being reshaped by technologies such as robotics, artificial intelligence, and digital twins, improving efficiency while transforming work environments that still require human capabilities. Although the environmental and economic benefits of circular strategies have been demonstrated, the human and social implications remain insufficiently underexplored. Examining how workers, organizations, communities, and consumers engage with circularity is therefore essential to ensuring social sustainability in evolving industrial contexts. This call for papers invites contributions that investigate the role of humans in the broader circular economy paradigm by exploring topics, including, but not limited to, the following:

• Integration of technology and human roles in circular processes
• Development of human competencies, training, and upskilling strategies within circular processes
• Assessment of worker performance in circular processes supported by technologies such as Human–Robot Collaboration, Augmented Reality, or Virtual Reality
• Health and safety challenges in disassembly and restoration operations
• Ergonomic design and worker well-being in remanufacturing environments
• Social acceptance of remanufactured products, including customer perceptions of quality and value
• Approaches to promote circular consumption among consumers

Co-Chairs: ^(a)Giuseppina Ambrogio, ^(b)Luigino Filice, ^(c)Romina Conte

Affiliation: ^(a)(b)(c)DIMEG, University of Calabria (Italy)

Track Description:
Evolving industry needs and shorter product life cycle demand for new methods and services from production technologies and facilities. Manufacturing tries to innovate itself with a synergic use of creativity and technologies. Concepts of intelligent control of manufacturing system (extended to the whole supply chain), advanced manufacturing, hybrid manufacturing and sustainability are widely diffused and have changed the way to design the manufacturing processes. These new paradigms represent the way for making industry more competitive. According to these new approaches, papers based on the application of such methods are welcome.

Co-Chairs: ^(a)Domicián Máté, ^(b)Judit T. Kiss, ^(c)Tünde Jenei

Affiliation: ^(a)(b)(c)University of Debrecen, Faculty of Engineering, Department of Engineering Management and Enterprise (Hungary)

Track Description: The Global Industrial Processes and Sustainable Development track is related to the connections, challenges and opportunities of economic and industrial processes, economic growth and sustainable development. Due to their global impact, industrial activities are of paramount importance from the point of view of sustainable development. The session covers a number of research areas, including the analysis of the environmental and social effects of industrial production, methods of efficient use of resources, the impact of the integration of alternative energies into production processes, circular economy, and the management and recycling of industrial waste.

Co-Chairs: ^(a)Luigino Filice, ^(b)Francesco Cicione

Affiliation: ^(a)DIMEG, University of Calabria (Italy), ^(b)Entopan S.r.l. (Italy)

Track Description: The traditional development models based on the richness and growth pushed by the industry are demonstrating their points of weakness looking at the recent events all over the World. Actually, it is not only a matter of philosophy but industry commonly shows a limited resilience and antifragility giving not adequate answers to society needs. Harmonic industry is a way to gain human centrality, defining models and technologies able to bring together value and wellbeing, in a perspective of “long-term enterprises”, those that act beyond short-term interests and generate widespread value, ensuring freedom, stability and social welfare. This requires a transition toward new and smartest models, allowing a sustainable innovation in which linear development model becomes circular, both in material treatment and social welfare terms.
Technology is neutral vs society: the track is an opportunity to discuss its impact on the people belonging to the world community, today and tomorrow.
Topics include, but are not limited, to: Harmonic innovation; Transition models; Green society and manufacturing; Industry development models; Circular innovation; Impact of technology on society; Smart factories; Smart society; Human wellbeing; Social responsibility.

Co-Chairs: ^(a)Luca Silvestri, ^(b)Antonio Forcina

Affiliation: ^(a)Universitas Mercatorum (Italy),^(b)University of Naples “Parthenope” (Italy)

Track Description: Manufacturing systems are evolving from the digitalization and automation focus of Industry 4.0 towards the Industry 5.0 paradigm, which emphasizes human-centricity, resilience, and sustainability alongside advanced technologies. While Industry 4.0 has enabled connectivity, real-time data collection, and predictive capabilities through Cyber-Physical Systems, Industrial IoT, and Artificial Intelligence, Industry 5.0 redefines operational objectives by explicitly integrating human well-being, cognitive capabilities, and organizational adaptability. In this context, operations and maintenance management emerge as critical domains where the transition to Industry 5.0 can be concretely addressed. Recent studies highlight the importance of human-in-the-loop decision support systems, capable of supporting task assignment, maintenance planning, and operational decisions by considering not only technical requirements but also operators’ skills, cognitive workload, and psychophysical state. At the same time, successful digital transformation increasingly depends on the development of digital capabilities, including user-friendly digital tools, workforce upskilling, information sharing, and alignment between technology, organizational structures, and strategy. This track aims to stimulate interdisciplinary contributions addressing the design, management, and evaluation of operations and maintenance systems in the Industry 5.0 era, with particular attention to human-machine collaboration, decision support systems, digital capabilities, resilient operations, and sustainable performance improvement. Topics of interest include:

• Artificial Intelligence (AI) and Machine Learning (ML)
• Real-time Data Collection and Analytics
• Industrial Internet of Things (IIoT)
• Cyber-Physical Systems (CPS)
• Human-in-the-Loop Decision Support Systems
• Human-Centric Operations and Maintenance
• Smart and Sustainable Maintenance
• Digital Capabilities and Organizational Readiness
• Human-Machine Collaboration
• Lean Manufacturing in Industry 4.0 and 5.0 Contexts

Co-Chairs: ^(a)Frederik Schulte, ^(b)Yaxu Niu, ^(c)Reza Sabzevari

Affiliation: ^(a)(c) Delft University of Technology (The Netherlands), ^(b)North University of China (China)

Track Description: Human-robot collaboration is widely considered one of the greatest challenges in the final steps of the 4th Industrial Revolution and an anticipated central question of the 5th Industrial Revolution. Order-picking in e-commerce warehouses is one of the examples in which human-robot collaboration is expected maintain important despite in the light of ongoing automation. While Industry 4.0 focuses on cyber-physical (production) systems and their potential to create self-organizing operations, Industry 5.0, following a recent position paper of the European Commission, places the wellbeing of the worker in the center of production process. Building on the foundations of Industry 4.0, this naturally leads the operations management of Industry 5.0 to collecting human (sensor) data and learning to interpret and integrate this information into existing objectives. In this way, it may turn robots and intelligent machines into caring colleagues for workers. However, related integrated research is still limited. This open track aims to attract innovative research related, but not limited, to the following topics: Innovative works integrating human-robot collaboration in operations management; (Wearable) sensor data models to analyze human stress levels and recovery; Machine learning approaches to let robots understand human behavior and their conditions; Integration of physiological human models and operations management approaches.

Co-Chairs: ^(a)Giovanni Mirabelli, ^(a)Vittorio Solina, ^(b)Emilio Jiménez

Affiliation: ^(a)DIMEG, University of Calabria (Italy), ^(b)Universidad de La Rioja (Spain)

Track Description: In recent years, the agri-food sector has been undergoing a profound transformation driven by increasing environmental pressures, social expectations, regulatory requirements, and rapid technological advances. Agri-food supply chains are required not only to improve efficiency and transparency, but also to enhance resilience, sustainability, and adaptability in the face of climate change, resource scarcity, and market volatility.
In this context, digital and data-driven innovations are playing a central role. Technologies associated with Industry 4.0 and beyond such as the Internet of Things (IoT), artificial intelligence and machine learning, advanced analytics, digital twins, blockchain, and cloud-edge platforms are enabling real-time monitoring, predictive decision-making, and end-to-end visibility across the supply chain. At the same time, growing attention is being paid to circular economy models, energy efficiency, sustainable packaging, and consumer-centric transparency, as well as to the integration of sustainability metrics into operational and strategic decisions.
The main aim of this track is to promote an interdisciplinary discussion on how emerging technologies, innovative management practices, and data-driven approaches can support the development of smart, resilient, and sustainable agri-food supply chains, from farm to fork.

Co-Chairs: ^(a)Duarte Dinis, ^(b)Roberto Sala

Affiliation: ^(a)UNIDEMI, NOVA FCT (Portugal), ^(b)University of Bergamo (Italy)

Track Description: This conference track addresses the evolution of maintenance systems toward the Maintenance 5.0 paradigm in the context of Aeronautics, Space, and Defense, aligning with the Security Action for Europe (SAFE) programme and Europe’s current geopolitical and strategic challenges. In an environment marked by heightened security risks, supply-chain vulnerabilities, and the need for strategic autonomy, the track emphasizes resilient, secure, and human-centered maintenance of critical defense and aerospace assets. It explores how advanced digital technologies—such as artificial intelligence, digital twins, augmented and mixed reality, and intelligent sensing—can be integrated with human expertise to enhance mission readiness, asset availability, lifecycle sustainability, and operational sovereignty. Particular focus is placed on socio-technical approaches that balance automation with human oversight, including explainable and trustworthy AI, and adaptive human–machine interfaces suitable for safety- and mission-critical environments. Contributions address predictive and condition-based maintenance, workforce upskilling, and knowledge management under regulatory, ethical, and security constraints, supporting SAFE objectives related to preparedness, interoperability, and industrial resilience. Industrial case studies and methodological advances are encouraged, illustrating how Maintenance 5.0 can strengthen Europe’s defense capabilities and strategic autonomy while positioning maintenance as a core enabler of security, resilience, and value creation within Industry 5.0.

Co-Chairs: ^(a)Alessandro Persona, ^(b)Alessandro Peris, ^(c)Irene Granata, ^(d)Serena Finco, ^(e)Maurizio Faccio

Affiliation: ^{(a)(b)(c)(d)(e)}Università degli Studi di Padova (Italy)

Track Description: Material handling represents one of the main costs and efficiency drivers in manufacturing systems, making intralogistics as one of the most important aspect to be considered in today’s enterprises. Intralogistics, that is related to the internal transport within the physical boundaries of an enterprise, plays a critical role in organizing, controlling, executing, and optimizing internal material flows. The evolution of intralogistics systems, currently driven by digitalization and autonomous technologies, has to cope with the growing need for more flexible and responsive storage solutions, the growth of e-commerce and the increase in SKU variety. As a result, modern facilities are transitioning from rigid systems toward highly modular and scalable ones, integrating autonomous vehicles, intelligent storage systems, and real-time decision-support tools. This session welcomes contributions concerning the topics of material handling system design, material handling equipment selection, both on the production and warehousing sides. Particular emphasis is placed on optimization, control, and performance modeling, order batching, sequencing, routing, resource allocation, and traffic management. Analytical models, discrete-event simulations, queueing theory, and AI-driven approaches aimed at evaluating or improving system efficiency and scalability are of strong interest. Overall, this session aims to provide a high-level forum for discussing emerging challenges, sharing methodological advances, and presenting state-of-the-art automation solutions that define the next generation of material handling and warehousing systems.

Co-Chairs: ^(a)Vito Modesto Manghisi, ^(b)Alesandro Evangelista

Affiliation: ^(a)(b)Polytechnic University of Bari (Italy)

Track Description:
The “Mixed Reality, Ergonomics, and Physiological Metrics: Enhancing Well-Being and Safety in Industrial Settings” track explores the intersection of advanced technologies, occupational health, and industrial safety. This track examines how Mixed Reality (MR)—including augmented reality (AR) and virtual reality (VR)—can be leveraged to improve ergonomic practices, monitor physiological metrics, and enhance workplace safety in industrial environments.

The scope includes the design and implementation of MR tools for ergonomic and safety assessment, the integration of wearable sensors for real-time physiological data collection, and the development of adaptive systems that respond to worker needs and risk conditions. Contributions will address how MR technologies can support ergonomic interventions, reduce physical strain, promote optimal postures and movements, and increase awareness of potential hazards.

The track also covers the use of physiological metrics—such as heart rate variability, skin conductance, and muscle activity—to assess worker well-being and detect unsafe states related to fatigue, stress, or cognitive overload. By leveraging these metrics, it is possible to design personalized and preventive work environments that minimize risk and enhance resilience.

Through case studies, experimental research, and theoretical contributions, the track aims to advance integrated approaches to occupational health, safety, and sustainability in industrial settings.

Co-Chairs: ^(a)Vito Basile, ^(b)Luigino Filice

Affiliation: ^(a)CNR-STIIMA (Italy), ^(b)University of Calabria (Italy)

Track Description:
The forming processes, in a wider definition not limited to metals, represent a broad category of industrial manufacturing processes, that involve shaping raw materials into finished products. Forming processes include molding, casting, forging, extrusion, stamping, etc., and the material transformation is performed by means of shaped tools (molds, dies, etc.). Thus, the tools are the fundamental equipment in forming processes. The current research trends on these processes are pushing towards higher product quality and performance, higher throughput and efficiency, affordability, sustainability, carbon neutrality, and promotion of circular economy. But also still addressing current issues and overcoming specific process limitations.
This track is focused on new solutions, technologies, methods, and approaches that enable innovations in tools for the next-generation forming processes.
The track scope includes research and applications of:

• Manufacturing technologies;
• New materials;
• New architectures and structures;
• Design methodologies and digital design technologies;
• Surface functionalization and coatings;
• Multi-material manufacturing;
• Multiphysics modeling and simulation;
• Topology optimization;
• Artificial intelligence, and machine learning;
• Sensorization and data processing;
• Process monitoring;
• Life cycle analysis;
• Environmental impact and efficiency;
• Energy harvesting and reuse;
• Assisted and hybrid processes;
• Sustainability.
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Co-Chairs: ^(a)Abla Chaouni Benabdellah, ^(b)Kamar Zekhnini, ^(c)Zakaria Fattah

Affiliation: ^(a)Rabat Business School, International University of Rabat (Morocco), ^(b)University of Picardie Jules Verne (France), ^(c)Moulay Ismail University of Meknes (Morocco)

Track Description: As industries undergo digital transformation, technologies such as AI, IoT, big data, and blockchain are
revolutionizing traditional supply chain practices. Supply chain efficiency and resilience have become
critical concerns in an increasingly uncertain and highly challenging market. Addressing these challenges
requires optimization-support systems and control mechanisms that integrate operations management
tools, mathematical optimization techniques, emerging digital technologies, and Industry 5.0 practices.
Operations management leverages optimization methods, including linear and nonlinear programming,
convex optimization, and multi-objective optimization, to refine business processes, ensuring maximum
efficiency and cost-effectiveness. Meanwhile, control theory provides a robust framework for dynamically
adjusting supply chain parameters in response to disruptions, ensuring stability and adaptability in real-time
operations. Besides, Industry 4.0 technologies enable businesses to refine supply chain operations, offering
improved process optimization, visibility, and predictive capabilities for managing disruptions, while
Industry 5.0 further advances this evolution by introducing a human-centric approach. In this context, this
track explores the vital role of Operations Management and Optimization in driving digital supply chains’
excellence. This track invites research that addresses the integration of digital technologies with operational
strategies, control theory, or optimization techniques to enhance supply chain performance in the 4.0 and
5.0 eras. Contributions that demonstrate how these innovations streamline processes, create value, and
enable organizations to respond rapidly to market changes are welcomed.

Keywords: Operations Management; Optimization; Control Theory; Industry 4.0; Industry 5.0; Supply Chain Management; Digital technologies; Supply Chain Performance.

Co-Chairs: ^(a)Victor Azamfirei-Ionita, ^(b)Foivos Psarommatis

Affiliation: ^(a)NOVA School of Science and Technology (Portugal), ^(b)University of Oslo

Track Description: The transition to Industry 5.0 places people at the centre of quality excellence and sustainable manufacturing, requiring a fundamental shift in workforce development and continuous learning. As digital transformation accelerates skill obsolescence, strategic upskilling and reskilling are essential for organizational agility and competitiveness. Human resource management is evolving into a strategic function that enables effective collaboration between humans and intelligent systems while ensuring quality and sustainability outcomes. This track explores how lifelong learning, customizable training pathways, and enabling technologies can empower individuals and organizations in the Industry 5.0 era. Success depends on integrating technical and soft skills within inclusive learning cultures, supported by transformational leadership, robust digital infrastructure, and meaningful evaluation frameworks. Key challenges remain, including limited guidance on integrating AI, VR, AR, and blockchain into professional education, difficulties in measuring training impact, and skills gaps that may exacerbate social inequalities. Digital Product Passports (DPPs) offer additional opportunities for data-driven quality management and experiential learning by linking lifecycle data, traceability, and defect insights to workforce development. The track invites contributions proposing innovative frameworks and practical solutions for effective and equitable skills development in Industry 5.0.

Topics of Interest: upskilling strategies; personalized learning; job redesign; academia-industry knowledge transfer; regional adaptatio

Co-Chairs: ^(a)Michael Affenzeller, ^(b)Lukas Fischer, ^(c)Roxana Holom, ^(d)Kaifeng Yang

Affiliation: ^(a)(d)FHOOE, Hagenberg (Austria), ^(b)Software Competence Center Hagenberg (Austria), ^(c)RISC Software GmbH, RISC (Austria)

Track Description: Prescriptive analytics makes use of scientific disciplines like machine learning, simulation and optimization to analyze and optimize the effects of various options for action on a result. A profound and comprehensive prescriptive analytics is built on the results of descriptive, diagnostic, and predictive analytics. Therefore, the prescriptive analytic research topics demands various methods and algorithms from data mining, statistics, mathematics, machine learning, optimization algorithms, decision making, and operations research. In real-world applications, existing techniques in this field still face challenges in terms of explainability/interpretability of prediction models, dynamic optimization in data streams, robust/preference-based optimization, multi-criteria decision making, and visualization in high dimensional spaces.

This open track is dedicated to discovering and solving the current challenges and collecting review papers with new scientific innovations or practical applications of prescriptive analytics in the production field. Both practical and theoretical papers are welcome. Topics in this open track include, but are not limited to:

• Explainable/Interpretable machine learning
• Surrogate/White-box models
• Single-/multi-/many- objective (meta-)heuristic optimization
• Preference-based/Robust/Dynamic/ Surrogate-assisted (large-scale) optimization
• Multi-criteria decision making
• High-dimensional visualization

Chair: ^(a)Foivos Psarommatis, ^(b)Victor Azamfirei

Affiliation: ^(a)University of Oslo (Norway), ^(b)Politecnico Milano (Italy)

Track Description: The increase in global competitiveness challenges the manufacturing market to integrate design, manufacturing, and product in order to improve the quality of both the product and the process. In today’s market, even large companies need flexibility and also need to increase the level of sustainability of their systems and processes. Thus, in recent years, the focus on smart manufacturing systems is pushing companies toward a new variety of highly specific technical solutions. In the area of quality management is Zero Defect Manufacturing (ZDM) that combines all the best features of traditional quality management methods but also incorporates all the new digital technologies that Industry 4.0 and 5.0 can offer. These solutions are characterized by an integrated approach to manufacturing termed “digital manufacturing”. In fact, digital manufacturing systems often incorporate optimization capabilities to reduce time, cost, and improve the efficiency of most processes. Despite the recognition of importance for digital manufacturing, most organizations feel they lack the necessary capabilities. The digital revolution is now our “present” is not the future. There are many different tooling processes that digital manufacturing utilizes such as artificial intelligence, automation and robotics, additive technology, and human-machine interaction, IoT, etc. The metaverse has recently been added to these tools becoming an increasingly popular form of collaboration within virtual worlds. The tools characterizing digitization are destined to evolve and increase. In any case, these tools are unleashing innovations that will change the nature of manufacturing itself. Industry and academic leaders agree that digital manufacturing technologies will transform every link in the manufacturing value chain, from research and development, supply chain, and factory operations to marketing, sales, and service. This transformation is known as fourth industrial revolution, also referred to as Industry 4.0 but the real new trend refers to Industry 5.0, the future, already penetrating trend, of change processes directing towards closer cooperation between man and machine, and systematic prevention of waste and wasting including industrial upcycling. The aim of the track session is to host a selection of papers from researchers, academics, as well as practitioners providing significant insights in the context of Industry 4.0 towards Industry 5.0 to solve complex problems in the field of manufacturing planning, management, and control.

Co-Chairs: ^(a)Bernd Markus Zunk, ^(b)Manuel Woschank, ^(c)Corina Pacher, ^(d)Volker Koch, ^(e)Erwin Rauch, ^(f)Tanja Sajko, ^(g)Vanessa Stadlober

Affiliation: ^(a)(d)(f)(g)Graz University of Technology (Austria), ^(b)(c)Montanuniversität Leoben (Austria), ^(e)Free University of Bozen-Bolzano (Italy)

Track Description: Engineering Education 5.0 (EE5.0) represents a paradigm shift in educating engineers for a resilient, sustainable, and human-centric future shaped by Industry 5.0. While technological excellence remains essential, EE5.0 moves beyond purely technical skill development by deliberately integrating digital transformation, sustainability goals, and societal responsibility into engineering curricula. Human values, ethical awareness, interdisciplinary collaboration, and reflexive thinking are at the core of engineering education, enabling meaningful innovation. Future engineers must be empowered to address complex, uncertain, and rapidly evolving challenges. This requires the systematic development of essential competences such as systems thinking, creativity, problem-solving under uncertainty, sustainability literacy, digital and data fluency, and lifelong learning capabilities. Engineering Education 5.0, therefore, calls for a holistic, competence-oriented perspective that spans the entire student life cycle, from early study phases to transition into professional practice. This special track aims to advance Engineering Education 5.0 through empirically grounded and theory-informed research. Contributions are encouraged that investigate future-oriented engineering competences, design engaging, inclusive, and technology-enhanced teaching and learning environments, develop innovative instructional concepts, and apply robust methods for competence-oriented assessment and evaluation. We invite high-quality contributions that contribute to the systematic evolution of Engineering Education 5.0.

Co-Chairs: ^(a)Tânia Daniela Felgueiras de Miranda Lima, ^(b)Pedro Miguel de Figueiredo Dinis Oliveira Gaspar, ^(c)Joel Marques Alves

Affiliation: ^(a)(b)(c)University of Beira Interior (Portugal)

Track Description: Recent advances in the Industrial Metaverse, cyber-physical systems (CPS), and Digital Twins are enabling new levels of connectivity, virtualisation, and automation across product, process, and supply-chain lifecycles. This track explores how the convergence of these technologies reshapes smart manufacturing, involving coherent approaches that integrate technology, management, and socio-technical design.
The core challenge is to translate these capabilities into robust processes and procedures (interoperability and standardisation, data quality and governance, model validation and uncertainty management, cybersecurity, safety, and operational resilience) while addressing people-related requirements (competence development, trust and acceptance, human-AI collaboration, ergonomics, and sustainable workload).
We welcome conceptual frameworks, reference architectures, and evidence-based case studies, but not limited to, on: digital-twin for design–operation convergence; industrial metaverse; CPS and edge–cloud integration; and metrics to assess value, risk, and readiness.
Expected outcomes include transferable methods, demonstrators, and evaluation protocols that support decision-making for future smart manufacturing.

Co-Chairs: ^(a)Giovanna Rotella, ^(b)Maria Rosaria Saffioti, ^(c)Maria Teresa Caggiano

Affiliation: ^(a)(c)LUM University (Italy), ^(b)University of Calabria (Italy)

Track Description: With the advent of advanced materials, smart surface functionalization stands as a key factor, involving various industries ranging from biomedical to aerospace. Different surface characteristics can be achieved through functionalization processes that enable the accurate control of surface properties, including wettability, adhesion and biocompatibility, in order to manufacture products featured with effective surface modifications improving the overall product performance. Surface characteristics determine components’ performance and functionalities by various processes able to locally modify the surfaces giving properties that the bulk material does not naturally possess. Surface characteristics of industrial components, determined experimentally or by computer simulations, help to understand relationships between structure, function, process parameters, properties changes and degradation of the components. Nevertheless, characterization techniques are herein considered to assess the overall surface characteristics. 

Co-Chairs: ^(a)Vincenzo Corvello, ^(b)Gabriele Zangara

Affiliation: ^(a)University of Messina (Italy), ^(b)University of Calabria (Italy)

Track Description: Social sustainability in the supply chain implies striving to ensure the well-being of the whole linked community, from the end customer up to the last supplier. It requires that everybody, in the supply chain, pays particular attention to the choice of its supplier or customer, considering also social and ethical issues. The economic and environmental aspects of sustainability are driven by specific regulations, unlike the social issue which is more or less voluntary and related to the initiatives of managers and entrepreneurs. However, the need to become socially sustainable is increasingly felt by many different stakeholders and companies are aware of the need to pay more attention to the well being of people, designing strategies inspired by ethics. The track is an opportunity to discuss the future of social sustainability in terms of impact, strategies, awareness, people, to “meet the needs of the present without compromising the ability of future generations to meet their own needs”, to increase industry and community wellbeing. Topics include, but are not limited, to: Social sustainability; Ethics; Supply chain management; Green supply chain; Supply chain strategies; Ethical strategies; Human wellbeing; Social responsibility; Corporate social responsibility CSR); Social Sustainability and Innovation; Environmental and Social Governance (ESG); Entrepreneurship and social sustainability in supply chains.

Co-Chairs: ^(a)Florian Bachinger, ^(b)Stefan Habringer, ^(c)Florian Holzinger, ^(d)Philipp Neuhauser, ^(e)Jan Zenisek

Affiliation: ^{(a)(b)(c)(d)(e)}University of Applied Sciences Upper Austria (Austria)

Track Description:

Machine learning (ML) is increasingly used in industrial environments, creating challenges across the full lifecycle: data preparation and training, deployment, monitoring, adaptation, and high-availability, low-latency inference. Because industrial plants have long service lives and downtime is costly, ML solutions must be dependable, trustworthy, maintainable, and operable over years. This requires robust software architectures, engineering practices, and platform components tailored to industrial constraints.

This track invites researchers and practitioners to present software and system design solutions, as well as lessons learned from real-world deployments. Topics of interest include (but are not limited to):

• Industrial ML pipelines and workflows (e.g., traceability, reproducibility, governance)
• Distributed and scalable processing (e.g., parallelization, containerization, orchestration, edge–cloud patterns)
• Software engineering for ML systems (e.g., CI/CD, automated testing, version management)
• Pre-deployment validation and assurance, including functional safety (e.g., verification/validation, interpretability, trustworthiness)
• Integration of simulation and ML (e.g., digital twins, hybrid models, simulation-driven training/validation)
• Agentic AI software technologies and protocols (e.g., MCP, function calling, agent-to-agent communication), including observability and safe integration

Co-Chairs: ^(a)Gallab Maryam, ^(b)Bouloiz Hafida, ^(c)Di Nardo Mario, ^(d)Popolo Valentina

Affiliation: ^(a)Mines Rabat School (ENSMR) (Morocco), ^(b)National School of Applied Sciences (ENSA) (Morocco), ^(c)(d)Università Telematica Pegaso (Italy)

Track Description: The industries of the future are geared towards sustainable, digital and innovative development, based on the integration of new technologies to transform processes, reduce environmental impact and improve efficiency. This includes the use of Industry 4.0 with automation and IoT to optimise operations, additive manufacturing for more flexible and resource-efficient production, and the adoption of renewable energy and smart grids for greener energy management. Artificial intelligence and Big Data enable better prediction of needs and optimised management of supply chains, while the circular economy promotes the recycling and reuse of materials.
The healthcare industries have an essential role to play in building a sustainable future. Through technological innovation, the management of natural resources, the reduction of waste and improved access to healthcare, it is possible to achieve a balance between improving quality of life and preserving the environment. The transition to a sustainable healthcare system requires a collaborative approach between researchers, healthcare professionals, the pharmaceutical industry and the citizen.
This session aims to foster the exchange of the latest contributions in this field. Researchers and industry professionals are invited to present their recent work in the following or related areas:

• Healthcare.
• Digital Technologies.
• Sustainability.
• Industry X.0.
• Fuzzy Logic.

Co-Chairs: ^(a)Hajar Fatorachian, ^(b)Hadi Kazemi

Affiliation: ^(a)(b)Leeds Beckett University (United Kingdom)

Track Description: The “Sustainable Digitalisation of Manufacturing Supply Chain Operations” track focuses on the integration of digital transformation and sustainability within manufacturing supply chains, exploring how cutting-edge technologies can drive environmental, social, and economic value. As supply chains embrace digitalisation, aligning these advancements with sustainability goals is crucial to fostering resilience and achieving net-zero objectives.
This track invites academics, industry professionals, and policymakers to share research, case studies, and practical approaches for embedding sustainability into digital supply chain frameworks. Key topics include leveraging artificial intelligence (AI), the Internet of Things (IoT), blockchain, and digital twins to enhance resource efficiency, promote circular economies, and minimize carbon footprints within supply chain operations. Ethical considerations, digital equity, and strategies to mitigate the environmental impact of digital technologies are also central to the discussion.
The track aims to address the trade-offs between rapid technological adoption and long-term ecological impacts, providing actionable insights into sustainable supply chain governance. It encourages cross-sector collaboration, policy innovation, and industry partnerships to build sustainable and resilient digital ecosystems.
This platform is ideal for researchers, practitioners, and thought leaders to share innovative solutions, tackle emerging challenges, and collaboratively shape the future of sustainable supply chain digitalisation.

Co-Chairs: ^(a)Stefano Saetta, ^(b)Angelika Kmita

Affiliation: ^(a)University of Perugia (Italy), ^(b)AGH University of Krakow, Academic Centre for Materials and
Nanotechnology (Poland)

Track Description: The green industry is focused on developing innovative technologies and sustainable materials for the factory of the future. This includes energy-efficient manufacturing systems, low-impact production processes, and the use of renewable and recyclable materials. Smart automation reduces waste and emissions. These advancements aim to create industrial operations that are highly productive yet environmentally responsible.
Topics of interest include, but are not limited to:

1) Innovative Green Technologies

AI-driven energy optimization in smart factories

Industrial IT for monitoring carbon emissions

2) Sustainable & Advanced Materials

Biodegradable materials for industrial use

Recycled composites and metals for circular manufacturing

Bio-based resins and adhesives for eco-production

3D printing with biodegradable or recycled materials

3) Circular Economy

Life-cycle assessment tools integrated in manufacturing software

Closed recycling systems inside factories

Upcycling industrial by-products into new materials

Chair: ^(a)Francesco Longo, ^(a)Antonio Padovano, ^(b)David Romero, ^(c)Johan Stahre, ^(d)Thorsten Wuest

Affiliation: ^(a)DIMEG, University of Calabria (Italy), ^(b)Tecnológico de Monterrey (Mexico), ^(c)Chalmers University of Technology (Sweden), ^(d)West Virginia University (USA)

Track Description:
While the Industry 4.0 is idolizing the potential of an artificial intelligence embedded into “things”, it is neglecting the role of the human component which is still indispensable in different manufacturing activities. The 4th Industrial Revolution is inevitably changing not only what the human operators do and how they do it, but also who they are. After generations of operators that keep pace with the first three industrial revolutions, the Operator 4.0 (O4.0) came up as a new concept in the Industry 4.0 framework. Since debate around the O4.0 is still emerging, the definitions and applications that can be found in the recent literature are neither yet completely comprehensive nor exhaustive but represent good starting points for discussion. This track focuses on human-technology integration and collaboration aiming at demonstrating new ways factory workers and robots, automation, and artificial intelligence can operate in harmony to increase productivity, quality, and performance on the shop floor as well as work satisfaction and safety in the workforce.

Co-Chairs: ^(a)Isabella Bonacci, ^(b)Alena Fedorova, ^(c)Danila Scarozza, ^(d)Maria Menshikova

Affiliation: ^(a)(d)Universitas Mercatorum (Italy), ^(b)Ural Federal University (Russia), ^(b)Link University (Italy)

Track Description: The Industry 5.0 marks a paradigm shift from automation-centric approaches of Industry 4.0 to
a human-centric and sustainable framework. This transformation emphasises collaboration
between humans and advanced technologies: Artificial Intelligence (AI), Virtual Reality (VR),
Augmented Reality (AR), and blockchain (Zenjari et al., 2024), prioritising social justice,
sustainable development, ecological balance, and organisational resilience (Sołtysik et al.,
2024). Industry 5.0 challenges Human Resource Management (HRM) to redefine its practices
to align with this new vision by integrating digital tools while preserving the human touch and
lowering environmental impact (Adisa, 2024). In this framework HRM can become not only a
driver for sustainable growth in the Industry 5.0 era (Sołtysik et al., 2024), but also a paramount
in ensuring organizational success through hyper connectivity, virtual workspaces, talent
acquisition and management, skill development and continuous learning, human–machine
collaboration, ethics, well-being, and agile organizational structures (Kamal et al., 2024).
Central to this transformation are themes like trust, employee commitment, emotional
intelligence, cross-disciplinary teamwork (Ganer et al., 2022), innovative HR solutions and
strategic adoption of AI for enhance various HR practices: recruitment and talent acquisition,
performance management, learning and training, and employee experience (Boopathi, 2024).
This track invites contributions that explore the transformative role of HRM in Industry 5.0,
including topics such as digital HR strategies, sustainable HR practices, AI introduction in
HRM, ethical challenges of HRM specialists in Industry 5.0. Submissions may include
theoretical studies, empirical research, or case studies that deepen our understanding of how
HRM can drive sustainable growth and innovation in the dynamic Industry 5.0 landscape.

References:

• Adisa, T. A. (2024). HRM 5.0. Unpacking the Digitalisation of Human Resource Management. Springer
• Boopathi, S. (2024). Digital HR Implementation for Business Growth in Industrial 5.0. In Convergence of
  Human Resources Technologies and Industry 5.0 (pp. 1-22). IGI Global.
• Ganer, S. D., Kediya, S. O., Suchak, A. K., Dey, S. K., & Band, G. (2022, October). Analytical study of HRM
  practices in industry 5.0. In IOP Conference Series: Materials Science and Engineering (Vol. 1259, No. 1, p.
  012041). IOP Publishing.
• Kamal, C. R., Vovchok, S. V., Ladyka, Y. V., Ladyka, N. M., & Reznik, N. P. (2024). Human Resource
  Management in the 5.0 Economy: An Analytical Analysis. In AI in Business: Opportunities and Limitations:
  Volume 1 (pp. 599-607). Cham: Springer Nature Switzerland.
• Sołtysik, M., Tyrańska, M., Piwowar-Sulej, K., & Agustina, T. S. (Eds.). (2024). Sustainable Human Resource
  Management: Strategy, Organizational Innovation and Leadership in Industry 5.0. Taylor & Francis.
• Zenjari, A., Allouani, S. A., Zaki, A., & Sidqui, O. (2024). Technological Innovation and Human Resources
  Management (HRM) in the Era of Industry 5.0: Navigating Impacts and Opportunities. In Industry 5.0 and
  Emerging Technologies: Transformation Through Technology and Innovations (pp. 371-391). Cham: Springer
  Nature Switzerland.

Co-Chairs: ^(a)P. Emanuele De Girolamo, ^(b)Carmela Guarascio, ^(c)Dario Raspanti

Affiliation: ^(a)(c)Università degli Studi di Firenze (Italy), ^(b)University of Macerata (Italy)

Track Description: Innovation has always been a driver of organizational change and labour market transformation. As nano-bio-info-cogno technologies become ever more ubiquitous, their impacts extend beyond production processes: they reshape the nature of work, organizational structures, and skill requirements. Firms’ innovation capacity has become a key competitive factor in international markets. The technological transition is accelerating skills obsolescence by reducing the weight of routine tasks, whether manual or cognitive, while opening up the way for new kinds of jobs. Industry and engineering are privileged domains to study the consequences of these changes because they are the nexus for the development of emerging and converging technologies.
This open track aims to examine how industrial and innovation policies, reskilling strategies, and socially responsible design processes can help firms and regions manage this transition sustainably and inclusively. We invite contributions that reflect on the organizational, labour, and policy-oriented dimensions of technological change — particularly focusing on human and social capital, the governance of sociotechnical systems, and territorial development dynamics.
Topics of interest include, but are not limited to:

• Industrial and national/regional policies for Industry 4.0
• The role of artificial intelligence (AI) and other smart technologies in labour reskilling, shifting skill demands, and changing job profiles
• Accountability for value change in sociotechnical systems over time
• Social-responsibility frameworks and design strategies to embed human values, sustainability and ethics into industrial innovation.
• Design strategies specifically aimed at aligning artificial intelligence systems with human values in the context of Industry 4.0
• Analyses of the impact of emerging technologies on labour market and organizational structure (ex. Agile, teal organizations, CSR and innovation…)
• Empirical or conceptual analysis of how smart-manufacturing adoption impacts labour markets, organizational structures, and human-machine interaction.

Co-Chairs: ^(a)Sara Perotti, ^(b)Antonella Meneghetti, ^(c)Luca Cannava

Affiliation: ^(a)(c)Politecnico di Milano (Italy), ^(b)Università degli Studi di Udine (Italy)

Track Description: In the last decade logistics systems have been affected by increasing challenges and ever-demanding requirements, driven by various trends as well as recent disruptions. Within logistics networks, warehouses stand as crucial and complex nodes, addressing demand variability, combining orders for delivery optimization, and providing value-added services while meeting efficiency and service level targets. New opportunities, such as Logistics 4.0, have emerged to face increased complexity and challenging targets. Besides, the search for improved sustainability has come into play according to the Triple Bottom Line (TBL) perspective, in line with the Sustainable Development Goals (SDGs) set by the UN. Further directions towards resilience and human centricity have been provided by the EU with the Industry 5.0 concept which aims at extending the concept of Industry 4.0 by considering, besides economic and technological factors, also environmental and social dimensions, thus giving a central role to human workers and their well-being. These aspects have led companies to explore smarter and more sustainable approaches and applications at their warehouses. Sustainable and human centered warehousing practices should help reduce environmental impacts, improve employee well-being, and achieve economic benefits for industrial and/or logistics companies. In this context, digital technologies play a central role being able to facilitate the development of interconnected, automated, and decentralized logistics systems. Moreover, the use of digital technologies could speed up the transition towards more sustainable and resilient warehousing processes and pave the way for potential opportunities by overcoming the environmental, social, and economic challenges. This track encourages researchers from several fields to submit contributions analyzing and highlighting the challenges, benefits, and potential opportunities of adopting sustainable and human-centric warehousing practices in the transition towards Warehousing 5.0. Topics of interest include but are not limited to: Logistics 4.0/5.0 and warehousing-related applications; strategies, concepts, and energy-efficient technologies for sustainable warehousing; human factor and human-machine interaction at logistics facilities; modeling, simulation, and optimization of intra-logistics processes; circular economy in warehousing processes; environmental, social, economic and policy aspects.