Special Session / Track Proposal

Confirmed Special Sessions/ Tracks

IFIP WG5.7 Research Workshop on Advances in Production Management Systems

Description: The aim of this special session is to provide an extended forum for technical discussions of innovative research activities among members of IFIP WG5.7. The session organizers invite their fellow colleagues to put forward proposals for extended presentations of their ongoing research activities on production management systems. The presentations will be passed on to two members of the scientific committee for review and discussion. One of the members will act as a discussant of the presentation in the research workshop.

  • Hermann Lödding, Hamburg University of Technology, Germany, loedding@tuhh.de
  • Gregor von Cieminski, ZF Friedrichshafen AG, Chairperson of IFIP WG 5.7, Germany, gregor.cieminski@zf.com
  • Erlend Alfnes, Norwegian University of Science and Technology, Norway, erlend.alfnes@ntnu.no

Workshop on Circular and Efficient Industrial Systems – Sharing Lessons Learnt From Case Studies

Description: The session’s objective is to share and discuss lessons learnt from three case studies (Stena Recycling, Volvo AB and DyeCoo/IKEA GreenTech) with the community of researchers and practitioners in the field of Circular Economy. It is critical to understand the challenges faced by companies and how to overcome them in order to accelerate the uptake of best practices for circular and efficient industrial systems. Moving towards a Circular Economy requires industrial solutions deployed at scale while meeting the goals of sustainable development. This is the vision of the REWIND project* which will be presented and discussed in this session.


  • Mélanie Despeisse, Chalmers University of Technology, Sweden, melanie.despeisse@chalmers.se
  • Arpita Chari, Chalmers University of Technology, Sweden, arpitac@chalmers.se
  • Clarissa González, Chalmers University of Technology, Sweden, clarissa.gonzalez@chalmers.se
  • Xiaoxia Chen, Chalmers University of Technology, Sweden, xiaoxia.chen@chalmers.se
  • Víctor Igelmo, University of Skövde, Sweden, victor.igelmo.garcia@his.se
  • Tarek Abdulfatah, Volvo Group Trucks Operations, Sweden, tarek.abdulfatah.2@volvo.com
  • Magnus Johnson, Lund University, Sweden magnus.johnson@chem.lu.se
  • Ernst Siewers, DyeCoo, Netherlands, e.siewers@dyecoo.com

Meta-Heuristics and Optimization Techniques for Energy-Oriented Manufacturing Systems

Description: World energy consumption has been increasing in recent years. As a major consumer, industrial activities use about one third of the energy over the last few decades. Meanwhile, due to the high-energy price and the high correlation between the energy and environment, manufacturers are facing competing pressure from profit, long-term brand image, and environmental policies. Thus, it is critical to understand the energy usage and optimize the operation to achieve the best overall objective.The aim of this session is to discuss models and techniques for energy optimization in the manufacturing systems. The topics of the session include, but are not limited to:

  • Optimization techniques for production systems under energy considerations.
  • Metaheuristics for sustainable production.
  • Optimal design of the facilities for energy production.
  • Heuristics, meta-heuristics and hyper-heuristics for multi-sources energy scheduling.
  • Simulation based optimization for sustainable energy systems.
  • Stochastic optimization methods for energy management in large-scale systems.


  • Taha Arbaoui, University of Technology of Troyes, France, taha.arbaoui@utt.fr
  • Yassine Ouazene, University of Technology of Troyes, France, yassine.ouazene@utt.fr
  • Alice Yalaoui, University of Technology of Troyes, France, alice.yalaoui@utt.fr
  • Mohsen Aghelinejad, University of Technology of Troyes, France, mohsen.aghelinejad@utt.fr

Finance-Driven Supply Chain

Description: The objective of this special session is to explore mathematical models and solution methods that jointly optimize industrial systems and financial systems. This implies taking into account both the impact of financial decisions on industrial logistical choices and their consequences on the whole supply chain. All contributions that incorporate financial choice into quantitative supply chain management models (e.g., production planning, supply chain design, etc.) are welcome.


  • Vincent Hovelaque, IGR-IAE Rennes, CREM, France, vincent.hovelaque@univ-rennes1.fr
  • David Lemoine, IMT Atlantique, LS2N, France, david.lemoine@imt-atlantique.fr
  • Olivier Péton, IMT Atlantique, LS2N, France, olivier.peton@imt-atlantique.fr
  • Jean-Laurent Viviani, IGR-IAE Rennes, CREM, France, jean-laurent.viviani@univ-rennes1.fr

AI for Resilience in Global Supply Chain Networks in the Context of Pandemic Disruptions

Description: This topic is at the boundary between the digital supply networks and Artificial Intelligence: papers are expected to show how AI can help in building resilience in supply networks by stopping the ripple effect that pandemics have on the production capacity of partners in networks.


  • Xavier Brusset, Université Côte d’Azur, France, xavier.brusset@skema.edu
  • Aseem Kinra, Bremen University, Germany, kinra@uni-bremen.de
  • Morteza Davari, Université Côte d’Azur, France, morteza.davari@skema.edu

Hybrid Approaches for Production Planning and Scheduling

Description: In the Industry 4.0, the concept of “smart factory” has emerged: thanks to a strong integration between information flows and production decision processes, it becomes possible to develop decision tools based on a better consideration of specificities of the production systems (for example, by using digital twins to evaluate the performance of manufacturing processes). In this context, the development of hybrid methods combining optimization and discrete-event simulation is a major challenge: the aim of this special session proposed by the French Research Groups Bermudes and SED is therefore to focus on these hybrid methods for planning and scheduling problems.


  • Alexis Aubry, Université de Lorraine, CRAN, France, alexis.aubry@univ-lorraine.fr
  • Christelle Bloch, Université de Franche Comté, Femto-ST, France, christelle.bloch@univ-fcomte.fr
  • David Lemoine, IMT-Atlantique, LS2N, France, david.lemoine@imt-atlantique.fr
  • Pascale Marangé, Université de Lorraine, CRAN, France, pascale.marange@univ-lorraine.fr
  • Sylvie Norre, Université de Clermont Auvergne, LIMOS, France, sylvie.norre@uca.fr

Recent Advances in Sustainable Manufacturing

Description: In nowadays highly competitive markets, achieving sustainability is quickly becoming a priority for manufacturing companies alongside being simultaneously, cost-effective and time. Moreover, a sustainable future is characterized by a continuously improved quality of human life in terms of satisfaction and prosperity, associated with sanitation, education, job satisfaction, etc. Since sustainability is the evolution that joins the requirements of the present without compromising the ability of future generations to join their own needs, three pillars are necessary respectively, economic, environmental, and social—also known informally as profits, planet, and people. Furthermore, the multiple new environmental legislations, the increase of electricity tariffs and fuel prices, reducing carbon footprint and energy consumption are considered as high priority. In this context, adapting sustainability in manufacturing requires a comprehensive look covering not just the product but also manufacturing processes involved in its production. This special session will provide a forum to investigate, exchange novel ideas and disseminate knowledge covering the broad area of sustainable manufacturing in nowadays industry. Experts and professionals from academia, industry, and the public sector are invited to submit papers on their recent research and professional experiences on the subject. High quality papers reporting on relevant reviews of existing literature, theoretical studies, case studies, inter-disciplinary research are all very welcome.


  • Hichem Haddou-Benderbal, IMT Atlantique, Nantes, France, hichem.haddou-ben-derbal@imt-atlantique.fr
  • Lyes Benyoucef, Aix-Marseille University, Marseille, France, lyes.benyoucef@lis-lab.fr
  • Vipul Jain, Victoria University of Wellington, Wellington, New Zealand, Vipul.Jain@vuw.ac.nz

Optimizing Reconfigurable Manufacturing Systems

Description: The objective of this session is to present new optimization problems and/or optimization algorithms that emerge in the field of RMS Design and Management. This includes, but not limited to, any contributions on mathematical programming modeling and exact or heuristic algorithms using techniques such as dynamic programming, branch and bound, MILP based heuristics, metaheuristics, etc. Studies on stochastic problems and robust optimization are welcome to this session as well. Applications of advanced optimization approaches in real life situations will be appreciated.


  • Nadjib Brahimi, Rennes School of Business, France, nadjib.brahimi@rennes-sb.com
  • Alexandre Dolgui, IMT Atlantique, Nantes, France, alexandre.dolgui@imt-atlantique.fr
  • Evgeny Gurevsky, University of Nantes, France, evgeny.gurevsky@univ-nantes.fr

Smart Methods and Techniques for Sustainable Supply Chain Management

Description: Nowadays, the spread of innovative digital technologies has been profoundly transforming the way industrial systems are operated. The scope of business activities has been expanded to include their social and environmental performance along with economic/financial ones and has pushed companies, from all industry sectors, toward a radical rethinking of entire supply chains and their operations. The aim of this special session is to gather contributions investigating the role and capabilities of artificial intelligence for sustainable development. Contributions, coming from both researchers and practitioners, may include theoretical approaches as well as successful implementations and applications of these concepts.


  • Davide Castellano, University of Naples “Federico II”, Italy, davide.castellano@unina.it
  • Mosè Gallo, University of Naples “Federico II”, Italy, mose.gallo@unina.it
  • Teresa Murino, University of Naples “Federico II”, Italy, murino@unina.it
  • Dongping Song, University of Liverpool, UK, dongping.song@liverpool.ac.uk

Sustainability in Production Planning and Lot-Sizing

Description: This special session seeks contributions to cover recent advances in production planning and lot-sizing with a focus on sustainability: Lot-Sizing and Circular Economy; Disassembly, Remanufacturing and Reassembly Systems; Lot-Sizing for Energy Management; Green Production Planning, … These contributions should focus on the development of new models and original solution approaches (i.e., exact methods, heuristics, metaheuristics, or hybrid approaches) on such applications. Industrial case studies are also welcome.


  • Kedad-Sidhoum Safia, Conservatoire National des Arts et Métiers, CEDRIC, France, safia.kedad_sidhoum@cnam.fr
  • Absi Nabil, Mines Saint-Etienne, UMR CNRS LIMOS, France, absi@emse.fr

Metaheuristics for Production Systems

Description: This session deals with metaheuristics approaches for optimization of production systems. In an increasingly competitive economical context, managers seek to optimize the performance of their system in order to produce goods at the lowest cost. From an operations research point of view, finding good solutions results in solving large NP-hard optimization problems (network design, planning and scheduling problems, line balancing problems, vehicle scheduling problems,…). The use of approximate methods, and in particular metaheuristics, is often the most appropriate approach. The aim of this session is to exchange views on the application of these metaheuristics for recent trends in production systems.


  • Laurent Deroussi, LIMOS, Université Clermont Auvergne, France, Laurent.deroussi@uca.fr
  • Patrick Siarry, LISSI, Université Paris-Est Créteil, France, siarry@u-pec.fr
  • El-Ghazali Talbi, LIFL, University of Lille, France, el-ghazali.talbi@lifl.fr

Industry 4.0 Technologies for Manufacturing Sustainability

Description: This special track aims to provide the opportunities to scholars, researchers and industries to reflect and enhance the knowledge about both the negative and the positive effect of Industry 4.0 technologies with respect to sustainability goals. Also, this track aims to increase the public awareness about the Industry 4.0 technologies, how sustainability practices can be addressed in Industry 4.0? What are the different measures and how to evaluate these practices? How roadmaps for successful implementation of these technologies can be addressed for developing nations? The contributions from the authors are not limited to:

  • How Industry 4.0 technologies can help to improve the sustainability? What will be benefits and constraints of new technologies for developing nations?
  • How man-machine and human-robot communication and interface will affect the future of industries?
  • How Industry 4.0 technologies can help to achieve 2030 SDG goals?
  • What organizational changes are needed to integrate the sustainability and Industry 4.0 technologies?
  • What are the relevant policies for emerging economies which will help in the Industry 4.0 transition with sustainability focus?
  • What will be negative and positive effect of Industry 4.0 technologies for the sustainability goals?


  • Rajeev Agrawal, Department of Mechanical Engineering, Malaviya National Institute of Technology, Jaipur, India, ragrawal.mech@mnit.ac.in

Machine Learning and Data-Driven Production Management

Description: Machine learning has been mostly intended during the current few years, mainly within the business, academic, finance, health, supply chain, cyber crime etc. Therefore, the present session aims to provide an extensive overview of the scientific literature about the study of machine learning and supply chain network and applications.


  • Monalisha Pattnaik, Department of Statistics, School of Mathematical Sciences Sambalpur University, Sambalpur, Odisha, India, ID-monalisha_1977@yahoo.com

Smart and Sustainable Production and Supply Chains

Description: The session aims to provide an excellent opportunity for international researchers to present the latest development on smart and sustainable production and supply chain management. We expect the session can attract several international experts on the areas. The session particularly welcomes the study on the impacts of new technologies (such as machine learning, blockchain) and COVID-19 pandemic on production and supply chains.


  • Runliang Dou, Department of Information Management and Management Science, Tianjin University, China, drl@tju.edu.cn
  • Guoqing Zhang, Department of Mechanical, Automotive & Materials Engineering, University of Windsor, Supply Chain and Logistics Optimization Lab., Ontario, Canada, gzhang@uwindsor.ca

Novel Approaches in Designing, Balancing and Sequencing of Stochastic Assembly, Disassembly and Machining Lines

Description: The objective of the session is to provide state-of-the-art research in designing, balancing and sequencing of assembly, disassembly and machining lines under uncertainty. During the last two decades, there is a growth in this research field. Formerly conventional techniques such as formerly stability analysis, stochastic programming, and robust optimization techniques have been used. However, recently distributionally robust optimization which interrelates robust optimization in terms of its conservatism and stochastic programming in terms of its specificity has also been utilized. Moreover, integrating mathematical programming with machine learning might improve the efficiency and effectiveness of the proposed algorithms.


  • Oncu Hazir, Rennes School of Business, France, oncu.hazir@rennes-sb.com
  • F. Tevhide Altekin, Sabanci Business School, Sabanci University, Turkey, tevhide.altekin@sabanciuniv.edu
  • Alexandre Dolgui, IMT Atlantique, France, alexandre.dolgui@imt-atlantique.fr

System Identification for Manufacturing Control Applications

Description: The session aims to bring together scientists working in all branches of control theory to discuss, in the light of manufacturing control problems, issues relating to development of the theory and methodology of identification, corresponding mathematical problems, parameter and nonparametric identification, structure identification and expert analysis, problems of selection and data analysis, control systems with an identifier, identification in intelligent systems, simulation procedures and software for identification and modeling, digital identification, intelligent model predictive control, predictive cognitive issues of identification, verification and problems of software quality for complex systems, global network resources of support processes of identification, modeling, and control.


  • Natalia Bakhtadze, V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow, Russia, sung7@yandex.ru

Natural Language Processing in Industry 4.0 and Supply Chain Management

Description: Modern manufacturing systems produce tremendous amounts of data through sensors, cyber-physical systems, and software. Among them, text and speech data, directly generated by humans may encapsulate meaningful knowledge to create intelligent decision support systems. For example, harnessing text and speech data is likely to improve customer relations in the supply chain, quality control in manufacturing, distribution, maintenance and production planning and control. Nevertheless, natural language data can be chaotic and highly unstructured, which poses big challenges when exploiting it. To tackle this problem, Natural Language Processing (NLP) has been widely used to process and analyze large volumes of natural language data. It is an active and growing research domain with potentially promising applications. For instance, chatbots are now widespread in customer service, sentiment analysis techniques allow efficient recommendation systems that support marketing strategies, and virtual assistants embedded in smartphones have automated tedious tasks. However, text mining and NLP seem to be seldom employed in manufacturing and supply chain management when compared to consumer applications. Hence, this invited session aims to gather original research regarding novel systems, tools or theoretical frameworks involving NLP and text mining to tackle the challenges of the industry of the future. Examples of these are mass customization, environmental sustainability, enhanced customer service, predictive maintenance, and human interaction with machines. This invited session calls for research papers or case studies providing original contributions to the enhancement of manufacturing and supply chain management through text mining and NLP.


  • Bernard Grabot, INP/ENIT, LGP,  Tarbes, France, bernard.grabot@enit.fr
  • Samir Lamouri, Arts et Métiers ParisTech, LAMIH UMR CNRS 8201, France, samir.lamouri@ensam.eu
  • Robert Pellerin, Polytechnique Montréal, Cirrelt, Canada

Learning and Robust Decision Support Systems for Agile Manufacturing Environments

Description: Despite the explosion of sensors and data generated from the shop floor, advanced planning and process control systems suffer from the absence of well-integrated solutions that deliver the full potential of digitalization. How to make efficient decisions with this plethora of data? In practice, very often, decision-makers and operators rely mainly on their experience. The challenge now is to integrate the latest advances in analytics and machine learning into manufacturing decision-support technologies to fully benefit from AI and digitalization on the manufacturing shop floor. The data available nowadays in manufacturing systems allow the integration of AI technics in all manufacturing decisions: process design, planning, scheduling, and production execution control. In this session, we expect presentations on the fields of digital twins, methods to deal with uncertainty in the design, planning, scheduling, and execution of manufacturing decision, explainable artificial intelligence, machine learning for manufacturing, automatic data cleaning, adaptable optimization models for manufacturing decisions, human-centric decision support systems.


  • Alexandre Dolgui, IMT Atlantique, LS2N, France, alexandre.dolgui@imt-atlantique.fr
  • Sotiris Makris, University of Patras, Laboratory for Manufacturing Systems & Automation,  Greece, makris@lms.mech.upatras.gr
  • Simon Thevenin, IMT Atlantique, LS2N, France, simon.thevenin@imt-atlantique.fr
  • Michael Zaeh, Technical University of Munich, Institute for Machine Tools and Industrial Management,  Germany, michael.zaeh@iwb.tum.de

Lean and Six Sigma in Services Healthcare

Description: This track aims to deepen the academic foundations of lean healthcare. In this moment of the COVID-19, we are looking for papers that contribute to our understanding of how to reduce waste, unevenness, and overburden along the entire value chain. Areas of interest include lean hospital, lean healthcare, lean shop-floor control, lean and green, lean in services. Case reports of practical experiences in healthcare services approaches are very welcome. Topics of interest include, but are not limited to, the following:

  • Lean hospital
  • Planning and control in healthcare
  • Lean six sigma in services healthcare
  • Fast track in healthcare
  • Humanization in healthcare


  • Robisom Damasceno Calado, Federal Fluminense University (UFF), Brazil, robisomcalado@id.uff.br
  • Helder Gomes Costa, Federal Fluminense University (UFF), Brazil, heldergc@id.uff.br
  • Adalberto da Cruz lima, Federal University of Pará (UFPA), Brazil, aclima@ufpa.br
  • Christiane lima Barbosa, Federal University of Pará (UFPA), Brazil, cllima@ufpa.br
  • Li Li Min, Campinas State University (UNICAMP), Brazil, limin@fcm.unicamp.br
  • Messias Borges Silva, Paulista State University (UNESP), Brazil, messias.silva@feg.unesp.br

Low-Code and Model-Driven Engineering for Production Systems

Description: Low-code development platforms combine model-driven engineering, platform-as-a-service architectures, and machine learning, to shift software-production tasks from software engineers to domain experts. The major market analysis firms have highlighted the current impressive investments by vendors and customers in low-code for business applications, and consider digital transformation in manufacturing as the next promising ground for these solutions. This session will illustrate applications and needs of low-code in production systems. We invite researchers and practitioners in low-code and related topics such as model-driven engineering and AI-assisted software engineering, to demonstrate new concepts, methods, and applications to low-code development for production systems.


  • Massimo Tisi, IMT Atlantique, France, massimo.tisi@imt-atlantique.fr
  • Manuel Wimmer, Johannes Kepler University Linz, Austria, manuel.wimmer@jku.at
  • Andreas Wortmann, University of Stuttgart, Germany, andreas.wortmann@isw.uni-stuttgart.de
  • Alois Zoitl, Johannes Kepler University Linz, Austria, alois.zoitl@jku.at

Data-Based Services as Key Enablers for Smart Products, Manufacturing and Assembly

Description: Smart products and intelligent solutions for manufacturing and assembly rely on the analysis of massive amounts of data. A decisive fraction of their value is provided by data-based services, which thus can be considered as key enablers. The functionality of these services is generated through different technologies, such as sensor networks, cloud platforms, or artificial intelligence and can be applied in various settings, such as product development, monitoring of energy flows, or assembly processes. The objective of this session is to discuss the potential of data-based services to enable smart products, manufacturing and assembly. This includes:

  • Acquisition of requirements for Smart Products and Services along the life-cycle
  • Services to enable assisted assembly operations based on Artificial Intelligence
  • Services for sustainable production (energy monitoring, circular material flow)
  • Industrial use cases for the application of data-based services


  • Stefan Wiesner, BIBA – Bremer Institut für Produktion und Logistik GmbH, Germany, wie@biba.uni-bremen.de
  • Johannes Dümmel, KIT – Institut für Fördertechnik und Logistiksysteme, Germany, johannes.duemmel@kit.edu
  • Khaled Medini, Mines Saint-Etienne, France, khaled.medini@emse.fr

Ramp-Up & Ramp-Down Management Challenges in Times of Volatility and Uncertainty

Description: Evolving customer demands and market dynamics under current global circumstances require more agile, and resilient manufacturing enterprises. COVID 19 crisis uncovered urgent challenges such as the need for quicker and more agile and transparent production ramp-ups to ensure the rapid and sustained availability of products and services (e.g. medical equipment, consumer goods, pharmaceuticals) and even ramp downs when operations continuity was no longer possible to safeguard production systems. This puts higher pressure on the manufacturing and service industries, already confronted with a tough and global competition; ramp-up and ramp-down management approaches come into play at this point as a driver for agility, flexibility, and resilience to adapt production systems to accommodate unexpected disruptions of various kind. This special session is concerned with concepts, methods, models, practices and challenges related to ramp-up and also the to date less developed ramp-down management approaches in times of the current crisis and beyond. State of the art papers, innovative case studies, and new or adapted methods are welcome.


  • Khaled Medini , Mines Saint Etienne , France, khaled.medini@emse.fr
  • David Romero, Tecnológico de Monterrey, Mexico, dromero@tec.mx
  • Thorsten Wuest, West Virginia University, USA, thwuest@mail.wvu.edu
  • Stefan Wiesner, BIBA Bremer Institut für Produktion und Logistik, Germany, wie@biba.uni bremen.de

Smart Supply Chain and Production in Society 5.0 Era

Description: Recently, with the development of new technologies such as IoT and Cyber Physical Systems (CPS) based on ICT or data science, the roles of supply chain and production are also changing. It is obvious that the traditional business model based on engineering chains has limitations for further growth. In supply chain and production, it is necessary to consider also a value chain for stakeholders in their management and operations. “Smart” is an important keyword to realize a sustainable ecosystem. This special session focuses on theory and practice on smart supply chain and production in Society 5.0 era.


  • Toshiya Kaihara, Kobe University, Japan, kaihara@kobe-u.ac.jp
  • Tatsushi Nishi, Okayama University, Japan, nishi.tatsushi@okayama-u.ac.jp

Gastronomic Service System Design

Description: Improving productivity and added value in the gastronomic service system field are urgent issues. The scope of application is to improve productivity and added value in a series of value chains through food manufacturing, distribution, sales, and service provision, and to develop food, cooking recipes, and menus using human preference and sensitivity data. Gastronomic sciences are closely related to not only engineering and science but also to multiple disciplines, so it is desirable to study with a multidisciplinary approach from various perspectives. Therefore, this session deals with a wide range of service system design research from basics to applications.


  • Tomomi Nonaka, Ritsumeikan University, Japan, nonaka@fc.ritsumei.ac.jp
  • Nobutada Fuji, Kobe University, Japan, nfujii@phoenix.kobe-u.ac.jp

Integrated Manufacturing & Service Operations Management for Product-Service Systems

Description: Over the past 12-months, there has been an acceleration of the use of digital within the PSS context as remote forms of support have been developed and deployed in the field allowing new collaborative approaches that support value co-creation. This shows new models of integration of manufacturing operations and service management initiatives, enabled by digital that allow these formats to be delivered. Specifically, the implementation of new formats of digitally-enabled value propositions supports innovative forms of asset management, operations and maintenance during the product-service lifecycle. This leads companies to capture new aspects into their product-service system and allows conversions, modifications and upgrades to extend the asset’s overall useful life with both a sustainable and circular view. Different analytical tools can enable new value propositions as well as improving service experience and operational efficiencies. Moreover, the new digitalized solutions help create the ideal conditions to allow the integration of third-party services; namely, system installers, maintenance-focused supplier or existing business partners (e.g. agents or distributors), who may provide service on the operational assets in place of either the customer or the manufacturer. With the advent of new forms of integrated value propositions focusing on product-service life-cycle, process support services, asset efficiency services or processes delegation services, may thus mean that the traditional PSS models (e.g., Tukker) might no longer be valid in their existing forms. However, additional studies are needed to find new integration schemes, that support the development of emerging business modes, their value propositions, as well as to identify the best underlying technologies. This special session aims to explore different forms of integration within a product-service system context. The objectives support the aim are to:

  • Develop new frameworks to describe an integrated value proposition within a PSS context.
  • Understand and characterize different digitally-enabled value propositions.
  • Identify how new technologies enable new value propositions.
  • Describe how to better integrate circular economy aspects into the existing value propositions and business models.


  • Shaun West, HSLU, Switzerland, shaun.west@hslu.ch
  • Paolo Gaiardelli, University of Bergamo, Italy, paolo.gaiardelli@unibg.it
  • Federico Adrodegari, University of Brescia, Italy, federico.adrodegari@unibs.it
  • David Romero, Tecnológico de Monterrey, Mexico, dromero@tec.mx

Product and Asset Life Cycle Management for Smart and Sustainable Manufacturing Systems

Description: Sustainability, together with the opportunities brought by Industry 4.0 technologies ask for an entirely new attitude to system design, operation, maintenance and decommissioning and for value-generation beyond the end-of-use. This special session, promoted by the IFIP WG5.7 SIG on PALM, focuses on the role of technology-enhanced lifecycle management on final products and manufacturing assets to support sustainability strategies in manufacturing operations. It also will be an opportunity for scientists and engineers to present research results-oriented on advanced management methodologies, digital technologies and new management concepts for lifecycle risks, performance and costs. Topics of interest include, but are not limited to:

  • Lifecycle data management for sustainability and circular economy.
  • End-of-life management strategies/methods/tools.
  • Cascade use, remanufacturing, and data-driven design for upgradability.
  • Zero-defect manufacturing strategies/methods/tools.
  • Zero-carbon manufacturing strategies/methods/tools.
  • PHM systems to support sustainable operations.
  • Assessment of operations and maintenance impact on sustainability.


  • Chiara Franciosi, University of Salerno, Italy, cfranciosi@unisa.it
  • Maria Holgado, University of Sussex, UK, m.holgado@sussex.ac.uk
  • Malgorzata Jasiulewicz-Kaczmarek, Poznan University of Technology, Poland, malgorzata.jasiulewicz-kaczmarek@put.poznan.pl
  • Irene Roda, Politecnico di Milano, Italy, irene.roda@polimi.it
  • Alexandre Voisin, Université de Lorraine, CRAN, France, alexandre.voisin@univ-lorraine.fr

Sustaining Manufacturing Production on the Pandemic Backdrop

Description: Pandemic of the 2019 brought on many challenges. Sustaining manufacturing production is of course one of them. Some market segments may experience reductions in demands, while other market segments may experience explosions. Companies have to deal with these changing needs and supply uncertainties while keeping employees safe, under diverse safety regulations of various regions. In this special session, the organizers would like to invite submission of papers or presentation proposals that document thoughts or real experiences of manufacturing production issues and innovations born by the pandemic. The aim is to discuss about these issues and share solutions so that our society can better prepare for a future pandemic albeit we hope not to ever come.


  • Serm Kulvatunyou, NIST, USA, boonserm.kulvatunyou@nist.gov
  • Rebeca Arista, Airbus, France, rebeca.arista@airbus.com
  • Vittal Prabhu, Penn State University, USA, vittal.prabhu@psu.edu

Engineering of Smart-Product-Service-Systems of the Future

Description: Technological innovation and new digital technologies are radically changing the world of services and manufacturing. In particular, there is an attempt to convert business models focused on one-time sales into business models with recurring revenues, e.g., via supplementary (digital) services. Thereby, products are combined with additional services, whereas this integration of both disciplines causes a new complexity. This complexity, combined with a technology-oriented perspective, requires new systematic approaches to develop and implement these smart-product-service systems. Core aspects are the reduction of uncertainty and better preparation for future evolvements of the customer needs. This track welcomes research contributions on the design and development of Smart-Product-Service-Systems and as-a-Service Business Models as well as challenges and success factors in the implementation of these new Smart-Product-Service-Systems of the Future. In particular, in the following the most relevant topics are highlighted:

  • Engineering of Smart and Digital Product Service.
  • Technologies enabling new service and PSS offering.
  • Development of PSS and as-a-Service Business Models.
  • Challenges and opportunities in the implementation of Smart Service strategies.
  • Industrial cases and applications.


  • Jana Frank, Institute for Industrial Management (FIR) at RWTH Aachen University, Germany, Jana.Frank@fir.rwth-aachen.de
  • Jan Frick, University of Stavanger, Norway, Jan.Frick@uis.no
  • Giuditta Pezzotta, University of Bergamo, Italy, giuditta.pezzotta@unibg.it
  • Vittal Prabhu, Penn State University, USA, vittal.prabhu@psu.edu

Data-Driven Methods for Supply Chain Optimization

Description: The digitalization initiated by Industry 4.0 promoted data as a central focus of modern industrial supply chains. Recently, a new optimization paradigm has emerged, where the data available are directly embedded into the models as input to improve the decision making under uncertainty. In particular, the articulation between data analysis and optimization methods becomes crucial for the success of such techniques. This session focuses on these so-called data-driven approaches. Specifically, new results and discussions on the design of optimization techniques, coordination mechanisms and/or successful applications where data turn into value from improved operations will be considered.


  • Guillaume Massonnet, IMT Atlantique, France, guillaume.massonnet@imt-atlantique.fr
  • Fabien Lehuédé, IMT Atlantique, France, fabien.lehuede@imt-atlantique.fr
  • Alexandre Dolgui, IMT Atlantique, France, alexandre.dolgui@imt-atlantique.fr
  • Stefan Minner, TUM School of Management, Munich, Germany, stefan.minner@tum.de

Optimization of Reverse Logistics Systems Based on Artificial Intelligence

Description: Due to the potential economic benefits and environmental regulations, a growing number of factories are devoted to recovering and reconditioning used products. Consequently, over the past few decades, the optimization of the reverse logistics systems has been receiving increasing attention from researchers and factories leaders. By integrating Artificial Intelligence (AI) tools in the reverse supply chain management, leaders provide a high system performance in terms of delivery, recovery of used products, stock shortage anticipation and the environment respect. From this point of view, authors are invited to submit research papers pertaining to design, analyzing and optimizing reverse supply chain systems.


  • Sadok Turki, University of Lorraine, LGIPM Lab., France, sadok.turki@univ-lorraine.fr
  • Oussama Ben-Ammar, SFL Departement, Mines Saint-Étienne, France, oussama.ben-ammar@emse.fr
  • Ilhem Slama, IMT Atlantique, LS2N, France, ilhem.slama@imt-atlantique.fr

Modern Analytics and New AI-based Smart Techniques for Replenishment and Production Planning under Uncertainty

Description: Managing uncertainty and risks is becoming one of the most important challenges in Supply Chain optimization. In fact, uncertainty causes several difficulties in production planning and inventory control. The sources of uncertainty are various and can take place at several levels of the Supply Chain: lead times, demand, prices, yield and capacities, etc. Many approaches were developed to production and replenishment planning under uncertainty. Recently, Artificial Intelligence tools start to be employed to improve decision support systems at strategic, tactical and operational levels in uncertain environments.
This special session aims to present the state of the art on traditional and new operations research and operations management techniques, as well as on AI-based research concepts, approaches and achievements for managing uncertainty for replenishment and production planning at different levels of the production systems and logistics.


  • Oussama Ben-Ammar, Mines Saint-Étienne, Campus de Gardanne, France, oussama.ben-ammar@emse.fr
  • Belgacem Bettayeb, CESI Group, LINEACT Lab., Campus de Lille, France
  • Alexandre Dolgui, IMT Atlantique, Campus de Nantes, France, alexandre.dolgui@imt-atlantique.fr
  • Mohamed Aly Ould Louly, Université de Nouakchott Al-Aasriya, Mauritania, ma.louly@esp.mr

Robotics Technologies for Control, Smart Manufacturing and Logistics

Description: The objective of the special track is to bring together specialists in different fields of industrial robots modeling, control, and their application in manufacturing and service. It addresses scientific and engineering problems that arise in the automation of various technological processes and robot-based transportation in the industrial environment. Particular topics covering by the track include optimal design, simulation and modeling of robotic manipulators and robotic manufacturing cells, robot calibration and estimation model parameters, manipulator accuracy improvement, advanced and intelligent robot control, human-robot collaboration, cooperation and interaction, robot application in assembling, milling and welding. Particular emphasis is given to the innovative methodologies and advanced technologies in the area of modern industrial robotics and multi-robot cooperation.


  • Anatol Pashkevich, IMT Atlantique, France, anatol.pashkevich@imt-atlantique.fr
  • Alexandr Klimchik, Innopolis University, Russia, a.klimchik@innopolis.ru

Digital Transformations Towards Supply Chain Resiliency

Description: The main scope of this special track is to discuss the tools, resources, technologies, applications, and case studies of digital supply chain transformations towards supply chain resiliency. The session can be broadly clustered into two aspects of the discussion as mentioned below.

  1. Data analytics/Modelling approaches/Optimization.
    • Industry 4.0 technologies (Cyber-physical production system, control tower, digital twins, AR/VR, IoT) to improve supply chain resilience using AI/ML/DL/data visualization / big data analytics/ blockchain.
  2. Practical application of digital technology in case studies towards supply chain resiliency.
    • Impact of digitalization on supply chain ripple effect and resilience.
    • Intelligent transportation systems and Logistics management (smart warehousing, etc.).
    • Empowering supply chain challenges through digital competencies (Network design/Additive manufacturing/ Location/Transportation/ Routing problems).
    • Application of digital supply chain platform coping with Epidemics/Pandemic challenges.


  • Manoj Kumar Tiwari, National Institute of Industrial Engineering (NITIE), Mumbai and Indian Institute of Technology, Kharagpur, India, director@nitie.ac.in

Data-Driven Platforms and Applications in Production and Logistics: Digital Twins and AI for Sustainability

Description: Recent advancements in technology infrastructure for capturing real-time data are key enablers of smart manufacturing and are expected to empower companies to adopt data-driven strategies for more responsive, efficient, and sustainable production, supply chain and intra-site logistic systems. This session explores recent advancements in data-driven digital twins and AI for planning and operation of production and logistics. We welcome research contributions and case reports on practical experiences of implementing and using digital twins and AI in manufacturing and production logistics. Discussions on extended benefits concerning sustainability dimensions are specifically welcome.


  • Magnus Wiktorsson, KTH Royal Institute of Technology, Sweden, magwik@kth.se
  • Sang Do Noh, Sungkyunkwan University, South Korea, sdnoh@skku.edu

Blockchain in the Operations and Supply Chain Management

Description: Nowadays, Blockchain Technologies (BCT) is transforming traditional fields like Operations and Supply Chain Management (OSCM), mainly because of its disruptive characteristics. With BCT, OSCM-related fields can improve the entire production process and the journey of the products. The prominent features of BCT enable the OSCM to achieve unprecedented performance through a decentralized and safe model to validate the transactions. With BCT, the OSCM can improve visibility, traceability, transparency, cooperation, information sharing, trust, transaction costs minimization, etc. Therefore, this track aims to discuss and advance the role of BCT in OSCM, focusing on empirical papers (quantitative/qualitative), reporting theoretical and managerial contributions.


  • Samuel Fosso Wamba, TBS Business School, France, s.fosso-wamba@tbs-education.fr
  • Maciel M. Queiroz, Paulista University, Brazil and Mackenzie Presbyterian University, Brazil, maciel.m.queiroz@gmail.com

The Role of Emerging Technologies in Disaster Relief Operations: Lessons from COVID-19

Description: In recent years we have witnessed unprecedented rises in natural disasters. The natural disasters are often caused by irresponsible consumption and production practices by humans. Such natural disasters may be hard to forecast. The impact of these disasters on human lives and properties can be immediate (e.g. instant death, destruction of property) whilst also slowly unfolding over the longer term (e.g. community and family relationships and kinships). In recent studies, scholars found that from the Indian Ocean Tsunami, to the Haiti Earthquake, the Ebola outbreak in West Africa, through to the recent COVID-19 pandemic, the disaster relief workers on the ground commonly identify a lack of visibility, poor information sharing and poor leadership as important constraints to effective operations. Whilst there is a rich body of literature on coordination and collaboration among the humanitarian actors engaged in disaster relief operations, research on technologically-mediated interactions on collaborations among disaster relief agencies is scant. Moreover, how humanitarian organisations manage collaboration among the humanitarian actors under the moderating influence of AI driven big data analytics capability is not well understood. Hence, in response to these research gaps and to advance knowledge in this rapidly emerging sub-field of technologically-mediated disaster responses we aim to organize a special track.


  • Rameshwar Dubey, Liverpool Business School, Liverpool John Moore’s University, Liverpool, UK, r.dubey@ljmu.ac.uk
  • David J. Bryde, Liverpool Business School, Liverpool John Moore’s University, Liverpool, UK, D.J.Bryde@ljmu.ac.uk
  • Samuel Fosso Wamba, Toulouse Business School, Toulouse , France, s.fosso-wamba@tbs-education.fr
  • Gary Graham, Leeds University Business School, University of Leeds, Maurice Keyworth Building, Leeds, UK, G.Graham@lubs.leeds.ac.uk
  • Cyril Foropon, Montpellier Business School, Montpellier Research in Management, Montpellier, France, c.foropon@montpellier-bs.com

Modern Scheduling and Applications in Industry 4.0

Description: Industry 4.0 provides new production paradigms for the manufacturing processes. New production paradigms lead to the emergence of modern production and scheduling models. However, unpredictable events in new production paradigms also lead to inevitable uncertainties. The objective of this session is to bring together experts in this field to introduce novel production and scheduling paradigms, and develop new formulations and solution methods for them. This proposal supposes to give state-of-the-art of stochastic production scheduling management methods under industry 4.0 environments in manufacturing systems. Scholar or engineer who is interested in this proposal can contribute related research papers.


  • Feifeng Zheng, Glorious Sun School of Business and Management, Donghua University, China, ffzheng@dhu.edu.cn
  • Ming Liu, School of Economics and Management, Tongji University, China, mingliu@tongji.edu.cn
  • Zhaojie Wang, Glorious Sun School of Business and Management, Donghua University, China, 1189194@mail.dhu.edu.cn

New Trends and Challenges in Reconfigurable, Flexible or Agile Production Systems

Description: To face the constantly changing customer requirements, companies have to adapt their production systems. Reconfigurable Manufacturing Systems are still relatively scarce in the industry, and their integration to improve flexibility all along the supply chain remains challenging, however digitalization and human-machine interactions are important levers to support this evolution. In addition to dealing with uncertainty, the agility of these systems could also provide innovative ways to deal with new societal challenges such as sustainability (e.g. energy or life-cycle management) and allow evolving toward new business models (e.g. servitization). This session welcomes both theoretical and applied research contributions on these questions.


  • Xavier Delorme, Mines Saint Etienne, France, delorme@emse.fr
  • Alexandre Dolgui, IMT Mines Nantes, France, alexandre.dolgui@imt-atlantique.fr
  • Michael Zäh, Technical University of Munich, Germany, michael.zaeh@iwb.tum.de
  • Fabian Dillinger, Technical University of Munich, Germany, fabian.dillinger@iwb.tum.de

Cognitive IoT Applications in Performance Management of Discrete Part Manufacturing

Description: Today’s discrete product manufacturing firms are challenged by increased disruption and disturbances in production schedules due to unforeseen delays in data availability and information interoperability. An efficient information system should communicate within the domain specific information systems. In addition, these should also interface with multiple related information systems within the enterprise as well as the extended enterprise. For example, life cycle, value chain and enterprise domain information systems should build effective interoperable interfaces to compose reusable abstractions of information model to seamlessly build KPI definitions and performance models. Recently, cognitive systems have helped discrete product manufacturing firms to build on-the-fly KPI metrics by using natural language processing and machine learning algorithms. Such systems have the capability to use cognitive IoT principles to increase the visibility and coordination of various information sources and acts as a bridge between multiple performance objectives required to be achieved by various stakeholders.


  • Senthilkumaran Kumaraguru, Centre for Smart Manufacturing, Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram Chennai, India, skumaran@iiitdm.ac.in

Intelligent Systems for Manufacturing Planning and Control in the Industry 4.0

Description: Nowadays, Information Technology (IT) merges with Operation Technology creating a new Information Operation Technology (IOT) paradigm. The use of artificial intelligence in Manufacturing Planning and Control systems (MPC) has become increasingly widespread to control management knobs in order to optimize performance in terms of production, cost and resilience of industrial processes. This challenge represents a significant break-through in production logic. This session aims to investigate the advantages and risks of IOT integration for the MPC in an Industry 4.0 scenario. The main topic should concern analytical models, quantitative approaches and simulation studies, but also qualitative approaches and case studies that give insights into behavioral issues and interactions between different management levels of a manufacturing plant using artificial intelligence approach.


  • Julia Christine Arlinghaus, Otto-von-Guericke University Magdeburg, Germany, julia.arlinghaus@ovgu.de
  • Andrea Grassi, Università degli Studi di Napoli Federico II, Italy, andrea.grassi@unina.it
  • Guido Guizzi, Università degli Studi di Napoli Federico II, Italy, guido.guizzi@unina.it
  • Frank Ortmeier, Otto-von-Guericke University of Magdeburg, Germany, frank.ortmeier@ovgu.de
  • Silvestro Vespoli, Università degli Studi di Napoli Federico II, Italy, silvestro.vespoli@unina.it

Digital Transformation Approaches in Production Management

Description: Digital Transformation has disrupted every production management domain, from product design and engineering to innovations in value propositions, materials, manufacturing processes, and production planning and control approaches. Digital Technologies, Big Data, and Data Analytics influence the design, business, engineering, and manufacturing at the emerging smart factories under the promise of supporting industrial business process management in manufacturing enterprises. In challenging times such as COVID-19, adopting such technologies with innovative methods is needed to improve and innovate their production processes and adapt to the continually changing market conditions such as personalization and mass-customization at competitive costs and production time.
This special session aims to attract theoretical and practice-oriented papers and case studies trying to answer the questions of (i) What is the reality of digital transformation in today’s (manufacturing) enterprises? (ii) What approaches, models, methods, technologies, and tools are used today for their digital transformations? (iii) What are the challenges that (manufacturing) enterprises face when digitally transforming their value propositions, production processes, and sustainable and resilient production systems?


  • Selver, Softic, IT & Business Informatics, CAMPUS 02 University of Applied Sciences, Austria, selver.softic@campus02.at
  • Egon Lüftenegger, IT & Business Informatics, CAMPUS 02 University of Applied Sciences, Austria, egon.lueftenegger@campus02.at
  • Ugljesa Marjanovic, Faculty of Technical Sciences, University of Novi Sad, Serbia, umarjano@uns.ac.rs
  • Bahrudin Hrnjica, Faculty of Technical Engineering, University of Bihac. Bosnia & Herzegovina, bahrudin.hrnjica@unbi.ba
  • Ioan Turcin, Automation Technologies, CAMPUS 02 University of Applied Science, Austria, ioan.turcin@campus02.at
  • Vlad Bocanet, Faculty of Machine Building, Technical University Cluj-Napoca, Romania, vlad.bocanet@tcm.utcluj.ro

Supply Chain Risk Management Under Coronavirus

Description: This session is to aid decision-making for supply chain management under coronavirus. Researchers who are interested in this proposal can contribute related research papers including but not limited to the following objectives and scope:

  • Analyze and assess various partners in supply chain risk management under different stages of coronavirus.
  • Establish mathematical model, tools, theories, and perspective for supply chain risk management under coronavirus.
  • Provide managers with methods for supply chain risk management under the epidemic.
  • Summarize the enlightenment of the outbreak of the epidemic on supply chain risk management.


  • Feng Chu, Univ Evry/University of Paris-Saclay, IBISC Lab., Evry, France, feng.chu@univ-evry.fr
  • Ming Liu, School of Economics & Management, Tongji University, Shanghai, China, mingliu@tongji.edu.cn
  • Zhongzheng Liu, School of Economics & Management, Tongji University, Shanghai, China, 1830351@tongji.edu.cn

The Future of Lean Thinking and Practice

Description: The session seeks to deepen the academic foundations of lean thinking. In collaboration with IFIP WG5.7 special interest group (SIG) for The Future of Lean Thinking and Practice, we are looking for papers that contribute to our understanding of how to reduce waste, unevenness, and overburden along entire value streams. Areas of interest include lean manufacturing, lean management, lean shop-floor control, lean and green, lean in services, and the role of lean in Industry 4.0. Particularly valuable is research that merges academic rigor with practical applications in industry. Case reports of practical experiences in manufacturing and comparison of manufacturing approaches are also very welcome.


  • Daryl Powell, SINTEF Manufacturing, Norway, daryl.powell@sintef.no
  • Torbjørn Netland, ETH Zurich, Switzerland, tnetland@ethz.ch
  • Christoph Roser, Karlsruhe University of Applied Sciences, Germany, Christoph.Roser@hs-karlsruhe.de

Production Management in Food Supply Chains

Description: “Production Management in Food Supply Chains” has the objective of discussing the processes and actions related to the production management alongside food supply chains from farm to fork. The researchers and practitioners in this SIG are committed to reduce food losses and waste, enhance food production, improve logistics operations, reduce environmental impacts and create value for the stakeholders: farmers, industry, retailers, and the final consumer. The topics may also consider national strategies, policy initiatives, incentives, government regulations, standards, networking and partnership, technology transfer and innovation opportunities, corporative governance, and smart food supply chains.


  • Irenilza de Alencar Nääs, Paulista University-UNIP, Brazil, Irenilza.naas@docente.unip.br
  • João Gilberto Mendes dos Reis, Paulista University-UNIP, Brazil, joao.reis@docente.unip.br
  • Jan Ola Strandhagen, Norwegian University of Science and Technology, Norway, ola.strandhagen@ntnu.no

Operations Management in Engineer-to-Order Manufacturing

Description: Engineer-To-Order (ETO) is a manufacturing approach where design and engineering activities are included in the order fulfillment process. ETO manufacturing is used when engineering specifications of products are not known in detail upon receipt of customer order, and is common in mechanical industries, construction, shipbuilding, off shore supplier industries, and other types of project-based manufacturing, industries typically facing several unique challenges as the products are often one-of-a-kind and/or highly customized. This track welcomes research contributions on operations management enabling effective ETO manufacturing, including Industry 4.0 technologies, supply chain management, lean operations, planning and control, production strategies and product platforms.


  • Erlend Alfnes, Norwegian University of Science and Technology, Norway, erlend.alfnes@ntnu.no
  • Martin Rudberg, Linköping University, Sweden, martin.rudberg@liu.se

The New Digital Lean Manufacturing Paradigm

Description: Digital technologies have given rise to a new era of “digital lean manufacturing” practices, which extends the lean philosophy to the “digital world”. This special track aims to attract papers exploring the new “digital frontier” for lean thinking and its emerging practices in the lean manufacturing domain. In this sense, we define the Digital Lean paradigm as the convergence between the principles and practices of lean thinking and the technology-driven vision of Industry 4.0 in order to support digital transformation initiatives at the shop-floor, combining different digital technologies with lean methods and tools. This special track welcomes research contributions on, but not limited to, digital waste, cyber-physical waste, digital quality management systems, digital Kanban systems, Jidoka 4.0 systems, digital poka-yokes, etc


  • David Romero, Tecnológico de Monterrey, Mexico, dromero@tec.mx
  • Paolo Gaiardelli, University of Bergamo, Italy, paolo.gaiardelli@unibg.it
  • Daryl Powell, SINTEF Manufacturing, Norway, daryl.powell@sintef.no
  • Thorsten Wuest, West Virginia University, USA, thwuest@mail.wvu.edu

Human-centered Artificial Intelligence in Smart Manufacturing for the Operator 4.0

Description: The scope of this session is on Human-Centered Artificial Intelligence (HCAI) systems. Such systems view AI as a critical component for augmenting human work and extending human capabilities, thus they can be considered the AI-enablers for the Operator 4.0 concept. The aim is that AI systems and humans solve problems together to achieve goals that were unreachable by either humans or machines alone. In this context, the special track welcomes research contributions on, but not limited to, topics like: design issues for multimodal human-AI interactions in the industrial environment, digital intelligent assistants, software robots (softbots) and chatbots for production management, Artificial Intelligence for the Operator 4.0, explainable and transparent AI in manufacturing, methods and tools to manage and monitor HCAI systems, applications of HCAI systems in manufacturing, and business models and processes based on HCAI systems.


  • Gregoris Mentzas, National Technical University of Athens, Greece, gmentzas@mail.ntua.gr
  • Stefan Wellsandt, Bremer Institut für Produktion und Logistik, Germany, wel@biba.uni-bremen.de
  • David Romero, Tecnológico de Monterrey, Mexico, dromero@tec.mx
  • Karl A. Hribernik, Bremer Institut für Produktion und Logistik, Germany, hri@biba.uni-bremen.de
  • John Soldatos, University of Glasgow / Intrasoft International, Scotland, john.soldatos@glasgow.ac.uk
  • Ricardo Raberlo, Federal University of Santa Catarina, Brazil, ricardo.rabelo@ufsc.br
  • Johan Stahre, Chalmers University of Technology, Sweden, johan.stahre@chalmers.se
  • Alexandre Voisin, Université de Lorraine, France, alexandre.voisin@univ-lorraine.fr

Digital Transformation of SME Manufacturers: The Crucial Role of Standards

Description: This special session invites papers that address the crucial need to support SMEs in their digital transformation journey. To-date, SMEs have largely relied on their own skills to implement digital solutions for Industry 4.0 and supply chain connectivity, and have found the work to be daunting and expensive. Moving forward it is crucial to better understand the various reasons why SMEs are struggling with this adoption and how they can begin to make up for the lost time. One approach to breaking down these barriers is to make commercial and open-source software more accessible, responsive to changing market needs, and adaptive using plug-and-play standard integrations, enabling any business – small and large – on their digital journey. In this session, we particularly invite contributions with interesting case studies and industry insights that investigate barriers, challenges, and lessons learned. Topics of interest include but are not limited to:

  • Standards and standard development for smart manufacturing and SME interoperability.
  • Automated messaging and data exchange standards.
  • Information mapping and semantic integration.
  • Interoperability across the value chain.
  • Skills-gaps in the available workforce.
  • Policy action to support SMEs.
  • Industrial case studies.
  • Applications and software for SMEs (incl. open-source, platforms, etc.).


  • Thorsten Wuest, West Virginia University, USA, thwuest@mail.wvu.edu
  • Makenzie Keepers, West Virginia University, USA, mk0004@mix.wvu.edu
  • Serm Kulvatunyou, NIST, USA, serm@nist.gov
  • Nenad Ivezic, NIST, USA, nenad.ivezic@nist.gov
  • Peter Denno, NIST, USA, peter.denno@nist.gov
  • Scott Nieman, Land’O Lakes, USA, stnieman@landolakes.com
  • Jim Wilson, OAGI, USA, jim.wilson@oagi.org
  • Michael Figura, OAGI, USA, mfigura@oagi.org
  • Hyunbo Cho, Postech, South Korea, hcho@postech.ac.kr
  • David Romero, Tecnológico de Monterrey, Mexico, dromero@tec.mx

Serious Games Analytics: Improving Games and Learning Support

Description: This special track calls for a combination of papers, short presentations, tutorials, and demos such as videos, short-game plays, or similar that based on “games analytics” and/or “learners analytics” can demonstrate the impact of serious games and gamification for learning, and training. As it has been in previous years, the special track is intended not only as a set of papers presentations but also as a workshop that aims to bring together researchers, developers, and users of serious games and co-creation models in the fields of business, industrial engineering and management, and multiple other disciplines to exchange ideas and best practices on how to improve serious games and learning support for the players, and the facilitator as well. The focus of this years’ workshop is on “serious games analytics”, including strategies for data collection, analysis, and visualization about the game and the players (the learners).


  • Jannicke Baalsrud Hauge, Bremer Institut für Produktion und Logistik GmbH at the University of Bremen, Germany, baa@biba.uni-bremen.de
  • Nick Szirbik, University of Groningen, The Netherlands, nick.szirbik@gmail.com
  • Makenzie Keepers, West Virginia University, USA, mk0004@mix.wvu.edu
  • David Romero, Tecnológico de Monterrey, Mexico, dromero@tec.mx
  • Riitta Smeds, Aalto University School of Science, Finland, riitta.smeds@aalto.fi
  • Mélanie Despeisse, Chalmers University of Technology, Sweden, melanie.despeisse@chalmers.se

Digital Twins Based on Systems Engineering and Semantic Modeling (DT SE&SM)

Description: Digital Twins (DT) are proposed to support the service management of entire lifecycle with different perspectives in industry. Lack of systematic analysis of DT concepts leads to various definitions and services which challenges the DT developers for data integration and integrated service delivery. Currently, systems engineering approaches are proposed to identify the requirements, use cases and ontology of DT, to construct DTs, and to integrate DTs in order to provide the systematic DT solutions for the specific purposes. Moreover, semantic modeling is widely used to capture information description during DT integration based on unified ontology across lifecycle and multi-domains. This track welcomes research contributions on DT management enabling effective complex system development and manufacturing, including Industry 4.0 technologies, cyber physical system, DT development platform, model-based digital twins and product platforms.


  • Jinzhi Lu, EPFL, Switzerland, jinzhi.lu@epfl.ch
  • Dimitrios Kyritsis, EPFL, Switzerland, dimitris.kiritsis@epfl.ch
  • David Cameron, UIO, Norway, davidbc@ifi.uio.no
  • Kostas Kalaboukas, MAGGIOLI, Italy, kostas.kalaboukas@maggioli.it

Artificial Intelligence Based Optimization Techniques for Demand-Driven Manufacturing

Description: In recent years, the rapid development of Artificial Intelligence (AI) has profoundly affected industrial manufacturing, leading to smart manufacturing (SM). At the same time, sustainable issues require a reduction of waste and energy consumption. In this context, Demand-Driven Manufacturing (DDM) emerges as a suitable strategy. AI techniques open new opportunities to switch from mass production to demand-driven production. The special session aims at collecting papers on new AI techniques for DDM including demand-driven production, production monitoring, cybersecurity, etc. This special session will bring together researchers and practitioners to discuss and explore the most promising AI applications for DDM.


  • Kim Phuc Tran, ENSAIT & GEMTEX, France, kim-phuc.tran@ensait.fr
  • Sébastien Thomassey, ENSAIT & GEMTEX, France, sebastien.thomassey@ensait.fr
  • Xianyi Zeng, ENSAIT & GEMTEX, France, xianyi.zeng@ensait.fr

Digital Twins in Companies: First Developments and Future Challenges

Description: Advances in Artificial Intelligence and the Internet of Things have been the trigger for an increasingly digitized business world. All areas of a business can benefit from the use of digital twin (DT) services. These systems reflect the structure of the organization of a business, its processes, and workflows. implementation of DT is still an incipient issue, but new markets are constantly evolving. This special session seeks to motivate dialogue and exchange of new ideas for the design and development of digital twins in companies. Researchers, graduate students, and professionals dedicated to the improvement of processes in organizations are invited.


  • Jose Antonio Marmolejo-Saucedo, Universidad Panamericana, Facultad de Ingeniería, Mexico, jmarmolejo@up.edu.mx
  • Roman Rodriguez-Aguilar, Universidad Panamericana, Facultad de Ciencias Económicas y Empresariales, Mexico, rrodrigueza@up.edu.mx

Supply chain pricing and risk control under the background of low carbon

Description: In order to cope with the ecological problems caused by climate deterioration, more and more countries are participating in the ranks of controlling greenhouse gas emissions. In 2019, China proposed that its carbon emissions peak in 2030 and plans to achieve carbon neutrality in 2060. In order to achieve this goal as soon as possible, governments and enterprises are actively implementing low-carbon transformation to adapt to the economy and society development. New and complex phenomena and problems will also appear in this process. Discovering and studying these complex problems will be the future development trend and challenge.


  • Junhai Ma, College of Management and Economics, Tianjin University, China, mjhtju@aliyun.com

Autonomous Robots in Delivery Logistics

Description: Autonomous delivery robots such as aerial drones, ground robots, and those used for material handling within a facility, offer distinguished benefits in delivery speed and cost savings. Broad adoption of autonomous delivery robots will lead to a fundamental transformation in how deliveries are conducted to fulfill society’s needs. The aim of this session is to discuss optimization models and techniques for autonomous robot-based delivery logistics in production and service systems, which will contribute to the efficiency of robot delivery systems and thereby help overcome their potential challenges and limitations.


  • Seokcheon Lee, Purdue University, USA, stonesky@purdue.edu
  • Mohammad Moshref-Javadi, Northeastern University, USA, m.moshref@northeastern.edu
  • Sungbum Jun, Dongguk University, South Korea, sbjun@dgu.ac.kr

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