Scope and Working Groups
The activities of the Manufacturing Modelling for Management and Control Technical Committee are devoted to promote the development of management decision-support systems in digital, resilient and sustainable manufacturing and supply chain systems in the era of Industry 4.0 based on combination of Industrial Engineering, OR and Data Science
The TC members are very active in the success of eight working groups:
1- Working group 'Digital Supply Network Engineering and Management'
Chairs: Prof. Alexandre Dolgui and Prof. Dmitry Ivanov
The working group explores and generates novel solutions for digital supply chain design and management. This scientific domain concerns the methodical evaluation and optimization of production systems, logistics networks, and their management policies to increase the effectiveness of multifaceted demand and supply chains in the age of digitalization and Industry 4.0. The major industrial problems and various effective approaches of supply chain design, planning and control with the use of digital technologies are being examined. Radical changes in the criteria that express the new objectives of production systems and logistics are on-going: customized assembly systems, dynamic scheduling, dynamic pricing, etc. In this WG, various methodologies and tools are being analysed to understand the influence of digitalization on management decision-making in supply chains.
During last years, the working group has contributed to TC events such as
IFAC symposium INCOM 2015 (special Tracks and Sessions) in Ottawa, Canada http://www.incom2015.org/
IFAC conference MIM 2016 (special Tracks and Sessions) in Troyes, France http://mim2016.utt.fr/
IFAC World Congress 2017 (Open Invited Tracks and Special Sessions) in Toulouse, France http://www.ifac2017.org
IFAC symposium INCOM 2018 (special Tracks and Sessions) in Bergamo, Italy http://www.incom2018.org/
IFAC conference MIM 2019 (special Tracks and Sessions) in Berlin, Germany http://blog.hwr-berlin.de/mim2019
2- Working group 'Advanced multi-criteria applications in manufacturing and logistics'
Chairs: Prof. Lyes Benyoucef, Dr. Aguirre Hernan and Prof. Farouk Yalaoui
The new competition is a major upheaval affecting every aspect of how enterprises organize and operate. The evolution from single enterprise with a high vertical range of activities toward enterprise networks offers new business opportunities especially for small and medium enterprises (SMEs) that are usually more flexible than larger companies. However, in order to make a successful commitment to an enterprise network, expected performance and benefits have to be carefully evaluated and balanced for a company to become a partner of the right network and for the right tasks. All these issues have to be taken into account in order to find an efficient, flexible, and sustainable solution.
In the area of manufacturing and logistics, supply chain networks involve transformation processes from raw materials to finished products, through several stages of manufacturing, assembly, distribution, and delivery to customers. They also rely on information and monetary flows in addition to material flows. Each stage of material transformation or distribution may involve inputs coming from several suppliers and outputs going to several intermediate customers. Furthermore, each stage may involve information and material flows connected with some intermediate and distant stages. The underlying logistic networks are complex and their analysis requires a carefully defined approach. As technological complexity has increased, logistic networks have become more dynamic and complex to handle.
Multi-criteria approaches have been put to use in multiple segments of manufacturing and logistics. They have taken a prominent role to integrate people, information and products across integrated supply chain boundaries including management of various manufacturing, logistics and retailing operations such as in manufacturing, warehousing and distribution of goods and services. Decisions involving customer profiling, new product development, retail marketing, and sales patterns are immensely refined using innovative multi-criteria approaches. Also, as such decisions have an impact on the overall integrated logistic network processes, it is important that innovative multi-criteria-based tools also be linked to integrated supply chain management applications. The working group aims to align latest practice, innovation and case studies with academic frameworks and theories. It will cover the latest research results and efforts at different levels including quick-response system, theoretical performance analysis, performance and capability demonstration, hoping to cover the role of multi-criteria approaches in optimizing manufacturing and logistics. The working group aims to focus on the following topics including:
- Manufacturing and logistics systems reconfiguration and design;
- Manufacturing and logistics systems performances evaluation and benchmarking;
- Manufacturing and logistics systems scheduling and planning;
- Adaptive manufacturing and logistics systems trading, coordination and negotiation;
- Green and Eco-manufacturing and logistics systems management;
- Risk management in manufacturing and logistics systems;
- Secure manufacturing and logistics systems collaboration;
- Impacts of cultural difference for manufacturing and logistics systems management.
During last years, the working group has contributed to TC events such as
IFAC symposium INCOM 2015 (special Tracks and Sessions) in Ottawa, Canada http://www.incom2015.org/
IFAC conference MIM 2016 (special Tracks and Sessions) in Troyes, France http://mim2016.utt.fr/
IFAC World Congress 2017 (Open Invited Tracks and Special Sessions) in Toulouse, France http://www.ifac2017.org
IFAC symposium INCOM 2018 (special Tracks and Sessions) in Bergamo, Italy http://www.incom2018.org/
IFAC conference MIM 2019 (special Tracks and Sessions) in Berlin, Germany http://blog.hwr-berlin.de/mim2019
3- Working group ' Design and modelling of flexible and reconfigurable manufacturing systems'
Chairs: Dr. Olga Battaia, Dr. Xavier Delorme, Dr. Rita Gamberini and Prof. Manoj Kumar Tiwari
The working group investigates and develops novel modelling approaches for designing and management of reconfigurable machining, assembly and disassembly systems. One of the main characteristics of these automated systems is that they use reconfigurable manufacturing technologies for fast adaptation to changes in the quantity and mix of products. Indeed, the industry's new requirements for manufacturing systems given the shorter and shorter product runs and the need for more customization. The production systems should be designed to be able to make changes in its physical configuration to answer market fluctuations in both volume and type of product. One of the principal characteristics of reconfigurable manufacturing systems (RMS) is modularity: in a reconfigurable manufacturing system, all the major components are modular (system, software, control, machines and process). Selection of basic modules and the way they can be connected provide systems that can be easily integrated, diagnosed, customized, and converted. An RMS is also supposed to quickly integrate new technologies to improve its efficiency. RMS is assumed to be the perfect tool for the new era of mass customization that requires simultaneously the productivity of dedicated system and the flexibility of agile manufacturing system. The aim of this working group is a review on this topic, more particularly on the challenges of flexibility and reconfigurability for assembly, disassembly and machining systems by study of several problems:
- Equipment selection and process planning;
- Production system dimensioning;
- Assembly and disassembly line design and balancing;
- Robotic cell design;
- Scheduling and planning;
- Operations management and flow analysis.
During last years, the working group has contributed to TC events such as
IFAC symposium INCOM 2015 (special Tracks and Sessions) in Ottawa, Canada http://www.incom2015.org/
IFAC conference MIM 2016 (special Tracks and Sessions) in Troyes, France http://mim2016.utt.fr/
IFAC World Congress 2017 (Open Invited Tracks and Special Sessions) in Toulouse, France http://www.ifac2017.org
IFAC conference MIM 2019 (special Tracks and Sessions) in Berlin, Germany http://blog.hwr-berlin.de/mim2019
4- Working group "Zero-Defect Remanufacturing and Quality Management (ZDR-QM)"
Chairs: Dr. Foivos Psarommatis (UiO, Norway), Dr. Sotirios Panagou (NTNU, Norway)
Remanufacturing has become a core enabler of the circular and sustainable manufacturing paradigm, yet it introduces complex challenges for modelling, management, and control. Key issues include:
• High variability in product condition, timing, and quantity of returns;
• Uncertainty propagation across disassembly, inspection, and reassembly stages;
• The need for decision-support and scheduling methods that account for quality-driven constraints;
• Integration of digital technologies, (such as AI, machine learning, and Digital Product Passports) for data-driven quality and defect management.
This WG extends TC 5.2’s scope toward circular manufacturing control, reinforce its contribution to sustainability and resilience, and complement ongoing IFAC initiatives under Industry 5.0 and digital transformation.
WG 4 serves as an international platform for advancing research and practice on modelling, management, and control of remanufacturing systems focusing, not only, on quality and uncertainty. Main objectives are:
• Develop and disseminate mathematical, simulation, and AI-based models for planning, scheduling, and control of circular production systems;
• Design decision-support systems for managing uncertainty in product returns, condition assessment, and process outcomes;
• Promote zero-defect strategies that integrate in-process sensing, adaptive control, and predictive maintenance;
• Foster human-centric and socio-technical approaches enabling operator involvement and customer-feedback loops in remanufacturing quality management;
• Link remanufacturing research with digital transformation, supply-chain integration, and resilient production networks, strengthening TC 5.2’s connections to sustainability and Industry 5.0.
WG 4 strengthens TC 5.2’s role in addressing challenges at the intersection of remanufacturing, quality, and sustainability, aligning IFAC with current global policy and industrial agendas. It will create a long-term platform for knowledge exchange and position TC 5.2 at the forefront of circular manufacturing system research.
5- Working group "Challenges and opportunities in applying Additive Manufacturing in Supply Chains"
Chairs: Associate Prof. Mirco Peron, Dr. Nils Knofius, Associate Prof. Francesco Lolli, Prof. Fabio Sgarbossa , Prof. Tsan-Ming Choi
Additive Manufacturing (AM) has recently emerged as a disruptive manufacturing technology since it allows to produce in a fast and simple way parts with a level of complexity not even imaginably achievable with conventional manufacturing (CM) techniques (e.g., casting, rolling, etc.). Aerospace and automotive sectors were the pioneers in exploiting the possibilities achievable via producing parts in AM, and its use has now expanded to other sectors and applications. The biomedical sector, for example, has started producing implants via AM since it enables to produce implants that matches the human body requirements closer than what achievable via CM techniques, while after-sales companies have been attracted by the possibility provided by AM to reduce the stock levels by producing spare parts on demand. Furthermore, the possibility of AM to produce parts on the site of use makes so that AM has repercussions not only on the production phase, but on the whole supply chain. In fact, by producing parts on the site of use, the supply chain complexity can be decreased (less echelons are required), as well as its environmental footprint, while its responsiveness can be highly increased. This is particularly important considering the current times where the Covid-19 pandemic is still affecting our lives and the frequency of natural disasters might increase due to the global warming. In such a context, AM can increase the resilience and viability of supply chains, as well as support humanitarian organizations in the first recovery phase after the occurrence of natural disasters or other disruptive events.
However, despite all the above-mentioned potentialities and benefits of AM, its deployment is still limited. Some main limitations, in fact, hamper its diffusion. Firstly, AM parts are more expensive than CM counterparts, hence reducing or even cancelling some of the above-mentioned economic benefits achievable. Secondly, the still high investments necessary for buying an AM machine limit the cases where producing parts on the site of use is economically convenient. Finally, some dilemmas arise also from an environmental perspective. In fact, on the one hand, AM allows to reduce the environmental footprint by producing parts on the site of use, but, on the other hand, the AM production process is very demanding in terms of energetic consumptions. Consequently, the overall environmental footprint might not be reduced if the whole product lifecycle is considered. It is hence still not clear when it is really convenient to adopt AM, and this becomes even more uncertain if we include in the analysis the risks of disruptions: the adoption of AM might lead to higher costs, but it might ensure the viability of the supply chain.
This working group aims at investigating the development of novel and innovative studies that support the adoption of AM by identifying under which conditions the benefits of AM are such to overcome their limitations. Topics may include (but are not limited to):
- Adoption of AM in supply chains
- Impact of AM on supply chain design
- AM for supply chain resilience/viability
- AM for spare parts supply chains
- AM for biomedical supply chains
- AM for humanitarian supply chains
- AM for sustainable supply chains
- Environmental footprint of AM life cycle
Members of this working group have contributed to the MIM2022 TC5.2 event by proposing the special session “Challenges and opportunities in applying Additive Manufacturing in Supply Chains” which received 13 papers. Moreover, in the future, the working group plans to further contribute to TC5.2 events proposing other special sessions and to further increase the interest of researchers and practitioners in the topic by proposing special issues in high level international journals and by presenting the results in relevant conferences and industrial workshops.
6- Working group 'Intelligent methods and systems supporting supply chain decision making'
Chairs: Prof. Michael Freitag, Prof. Enzo Morosini Frazzon, and Prof. Dr. Raphaël Oger
The activities of the working group cover the technology-based integration of different supply chain tasks, such as: production planning, scheduling and control, transportation and logistics planning, scheduling and control, inventory planning and warehouse management and operations, manufacturing systems operations as well as coupled services and technologies which can lead to improved supply chains. It includes such topics such as modeling, simulation, analysis, and control of manufacturing processes; Monitoring, diagnosis and maintenance of manufacturing systems; Smart manufacturing systems and Industry 4.0 technologies. Special attention will be directed towards practical relevance and approaches that can foster innovation in manufacturing supply chains.
During last years, the working group has contributed to TC events such as
IFAC conference MIM 2016 (special Tracks and Sessions) in Troyes, France http://mim2016.utt.fr/
IFAC World Congress 2017 (Open Invited Tracks and Special Sessions) in Toulouse, France http://www.ifac2017.org
IFAC symposium INCOM 2018 (special Tracks and Sessions) in Bergamo, Italy http://www.incom2018.org/
IFAC conference MIM 2019 (special Tracks and Sessions) in Berlin, Germany http://blog.hwr-berlin.de/mim2019
7- Working group 'Human factors and ergonomics in industrial and logistic system design and management'
Chairs: Prof. Daria Battini, Prof. Fabio Sgarbossa, Prof. Christoph Glock, Prof. Eric Grosse, Prof. Martina Calzavara
Despite the opportunities the automatization of industrial and logistic systems offers, many companies still rely on human work in many areas. Most planning models that have been proposed in the past to support managerial decision making in industrial and logistic systems have neglected the specific characteristics of human workers, which often led to unrealistic planning outcomes or work schedules that may even be harmful to workers employed in the system. To guarantee a high level of productivity and efficiency and to make sure that decision support models reflect reality as good as possible, it is necessary to consider human factors in addition to economic aspects in designing industrial and logistic systems. Even though recent research has started to integrate human factors issues into decision support models – for example by modelling learning effects or human energy expenditure –, there still seems to be a large gap in the literature concerning the development of decision support models for industrial and logistic systems that take account of the interaction between the human worker and the work environment. The latter can, to a large extent, be influenced by the system designer.
Generally, human factors (perceptual, mental, physical and psychosocial aspects) determine the performance of industrial and logistic systems to a large extent if human operators are employed. This aspect becomes more challenging in light of demographic changes, which will likely put human factor-related issues in logistics – such as the risk of developing musculoskeletal disorders in labor-intensive work environments, for example – on top of the agendas in many companies. In addition, the consequences of using innovative technical solutions to support industrial and logistics processes, such as augmented reality or motion capturing, is not yet fully understood in light of human performance and errors.
This working group aims at investigating the development of innovative approaches for the integration of human factors in industrial and logistic system design. Topics may include, but are not limited to:
- Ergonomics in operations and logistics management
- Learning and forgetting aspects in industrial systems
- The impact of system design on human errors
- Error-free systems
- Reduction of injury risks in manual operations
- The impact of demographic changes on industrial systems
During last years, the working group has contributed to TC events such as
IFAC conference MIM 2016 (special Tracks and Sessions) in Troyes, France http://mim2016.utt.fr/
IFAC World Congress 2017 (Open Invited Tracks and Special Sessions) in Toulouse, France http://www.ifac2017.org
IFAC symposium INCOM 2018 (special Tracks and Sessions) in Bergamo, Italy http://www.incom2018.org/
IFAC conference MIM 2019 (special Tracks and Sessions) in Berlin, Germany http://blog.hwr-berlin.de/mim2019
IFAC World Congress 2020 (invited session,associate editors)
Forward thinking paper published by the WG chairs: Human factors in production and logistics systems of the future, Annual Reviews in Control 49 (2020) 295–305.
IFAC INCOM 2021 (invited session, associate editors)
IFAC MIM 2022 (invited track, associate editors)
IFAC World Congress 2023 (invited session,associate editors)
IFAC INCOM 2024 (invited session, associate editors)
8- Working group 'Smart, Reliable and Sustainable Manufacturing-Distribution Systems'
Chairs: Dr. Abdelhakim Khatab, Prof. Lyes Benyoucef, Prof. Claver Diallo, Prof. El Houssaine Aghezzaf, Prof. Uday Venkatadri
For companies to survive in nowadays highly competitive markets, their manufacturing systems must be cost-effective, time-efficient, resilient, agile, and sustainable. Sustainability has become a crucial performance indicator and customer attraction feature. Sustainability concerns relate to the material and energy consumption and greenhouse gas emissions from raw material extraction to production processes and distribution. Guided by the 17 United Nations’ Sustainable Development Goals (SDGs), many countries have enacted legislation to protect the environment and the planet. Many of these regulations target the reduction of the carbon footprint and energy consumption of our activities. Integrating sustainability with manufacturing requires a comprehensive consideration of all elements in the value chain: the materials, products, manufacturing processes, equipment used, design and methods, remanufacturing activities, etc. Moreover, a sustainable future is characterized by a continuously improved quality of life in terms of satisfaction and prosperity associated with sanitation, education, job satisfaction, etc. Sustainability requirement is thus an evolution that reconciles the satisfaction of the present generation's needs without compromising the ability of future generations to meet their own needs. Therefore, the design of both the product and the manufacturing system and its operations should be carried out based on three pillars/perspectives (economic, environmental, and social), also known as the 3Ps: profits, planet, and people. The objectives of this working group fall under Goal 8 (economic growth), Goal 9 (Industry, innovation, and infrastructure), and Goal 12 (Responsible consumption and production) of the United Nations’ SDGs. The working group aims to provide a forum to investigate, exchange novel ideas and disseminate knowledge covering the broad area of sustainable manufacturing in smart humancentric factories. Experts and professionals from academia, industry, and the public sector are invited to communicate their recent research and professional experiences on the subject. This WG will provide a collaborative space to reflect, innovate, adopt, and implement digital technologies to support sustainable practices in manufacturing.
List of topics: All problems and approaches dedicated to sustainable manufacturing.
Optimization of manufacturing and remanufacturing systems, design of green supply chains, optimal maintenance for extending engineered products lifecycle and remanufacturing, industry 4.0 and smart factories.
9- Working group 'Digital Twins in Manufacturing and Logistics Systems'
Chairs: Prof. Serena Finco, Prof. Mirco Peron, Prof. Audrey Cerqueus, Prof. Olga Battaïa, Prof. Xavier Delorme, Prof. Daria Battini
Digitalization in Manufacturing and Logistics (M&L) systems is a crucial driver of higher levels of productivity, resilience, sustainability, and flexibility. Digital technologies, such as the Internet of Things, Cloud Computing, Artificial Intelligence, Virtual Reality, Augmented Reality, and the new generation of Information Technologies, enable intelligent integration and interconnection among all actors involved in M&L processes. These technologies enable real-time monitoring, control, and data collection, as well as the development of cyber-physical systems that integrate physical and virtual environments.
In this context, the Digital Twin (DT) concept is an emerging and rapidly evolving research topic in M&L systems. DT is defined in several ways depending on the application domain; however, in the context of M&L systems, it can be described as a dynamic virtual representation of physical assets, processes, or systems, designed to evaluate, predict, and optimize their states and future behavior. DTs integrate bidirectional data flows between physical and virtual entities, meaning that a change in the physical system can influence the virtual model and, conversely, insights generated in the virtual environment can trigger decisions or actions in the physical system.
Through this continuous synchronization, DTs process historical data, monitor the present in real time, and support predictive and prescriptive decision-making.
The rapid development of Artificial Intelligence (AI) has recently opened new perspectives for the evolution of DT-enabled M&L systems, particularly through the emerging paradigm of Agentic Artificial Intelligence. This paradigm introduces intelligent software agents capable of autonomously reasoning, planning actions, interacting with digital environments, and supporting complex decision-making processes. When integrated with Digital Twins, agentic AI systems can continuously analyze real-time data streams generated by DT models, interpret system states, and proactively suggest or implement operational adjustments. This collaboration is especially powerful because DTs provide accurate and continuously updated representations of physical systems, while agentic AI systems interpret these representations to autonomously support operational decisions such as production scheduling, resource allocation, maintenance planning, and logistics coordination.
This integration is particularly relevant in the current industrial context, where companies operate in highly dynamic, uncertain, and interconnected environments. Manufacturing and logistics systems must therefore become increasingly reactive, agile, and adaptive to respond quickly to disruptions, demand variability, and operational disturbances. Moreover, agentic AI can assist managers by continuously monitoring operational data through DT infrastructures, detecting anomalies, identifying optimization opportunities, and generating decision alternatives in real time. These intelligent agents can collaborate with human decision-makers, augmenting managerial capabilities and enabling more informed, data-driven, and timely decisions. As a result, the DT–agentic AI integration supports a transition from traditional reactive management approaches toward proactive and adaptive operational control.
The relevance of DT in M&L is well established in the scientific literature, with applications spanning production planning and control, workpiece quality prediction, machine and human-robot collaboration, real-time monitoring of M&L systems, product traceability, performance prediction, and supply chain resilience. The integration of agentic AI further extends these capabilities, enabling autonomous or semi-autonomous decision support across these domains in complex, dynamic operational contexts.
Despite these opportunities, several critical challenges must be addressed to fully realize the potential of DT-enabled intelligent systems. These include difficulties in sharing DT infrastructures across multiple application systems and stakeholders, challenges in efficiently storing, processing and analyzing large volumes of heterogeneous data, and ensuring reliability, robustness and trustworthiness of DT and AI-based decision-support systems. The heterogeneity of digital technologies further complicates strategic decision-making around DT and AI adoption, as companies struggle to evaluate investments and align technological choices with organizational goals. Additional research challenges include the modelling of complex manufacturing systems, the integration of human factors, and the consideration of internal and external factors affecting machine degradation, workforce skills, and organizational adaptability.
This Working Group directly addresses these open challenges by investigating the development of original and innovative studies that implement Digital Twin concepts in M&L systems, with particular attention to the integration of advanced Artificial Intelligence paradigms such as agentic AI. Contributions are sought across a broad multidisciplinary spectrum (including statistics, Artificial Intelligence, computer science, operations research, industrial engineering, and management science) with the dual objective of advancing technical solutions and critically evaluating their benefits and limitations in real operational contexts.
Topics may include, but are not limited to:
• Using new emerging technologies for the DT implementation in M&L systems
• Conceptual frameworks to support DT and agentic AI development in M&L systems
• DT architectures in M&L systems
• Integration of Digital Twins and agentic AI for intelligent decision support
• Autonomous and collaborative AI agents for manufacturing and logistics management
• Real-time based models and algorithms for assembly line design, balancing and rebalancing techniques
• Simulation and optimization models based on real-time data for production planning and control in flexible manufacturing systems
• Real-time job scheduling and sequencing for complex M&L systems supported by intelligent agents
• DT models for improving M&L systems layout
• DT models for analyzing machine-to-machine interaction and human-robot collaboration
• DT methods and models to improve human factors in M&L systems
• Using DT concepts to improve M&L systems reliability, availability and efficiency
• DT as a tool to improve M&L system resilience
• Agentic AI for adaptive production planning, scheduling, and operational management
• DT-enabled intelligent monitoring and anomaly detection in M&L systems
• Quantitative and qualitative analysis concerning the implementation of DT in M&L systems
• DT and agentic AI applications from real M&L systems
10- Working group 'Smart intralogistics for warehousing and material handling in manufacturing and distribution systems'
Chairs: Prof. Martina Calzavara, Prof. Eric Grosse, Dr. Dominic Loske, Prof. Elena Tappia, Prof. Ilenia Zennaro
Recent market trends demand for an increasing variety of goods that have to be produced and delivered in ever shorter times. Since global markets continuously change, especially referring to the emerging e-commerce channel, industries need to be able to respond quickly and appropriately to these needs, working with constant uncertainties and aiming to be flexible and resilient at the same time. These aspects, associated with new material handling technologies, digital technologies that allow the introduction of new data-driven approaches for decision making, and the importance of a human-centric perspective, lead to challenges and trade-offs that have an important impact on the management and control of intralogistics activities, including material handling, warehousing, parts feeding, and products distribution. Therefore, the need of designing intralogistics systems that are flexible, synchronized, effective, and resilient emerges.
A rigorous design of intralogistics systems includes, for example, the feeding of the items to the assembly area, the right setting of the material handling system, the level of automation, and the location of the storage areas and the warehouse zones, including the appropriate transportation and products distribution. Moreover, the adoption of new technologies and assistive devices can relieve workers from high workload and enabler to ease and speed up manual activities, as well as warrant higher quality, reliability, traceability and sustainability of the intralogistics processes.
Technological developments towards smart warehouses enable new and increasingly competitive solutions for automation, information provision and integration, and worker assistance. However, there are still many open questions about the application of technology, for example with regard to cost-benefit analyses, decision support, system design, and human-technology interaction.
This working group aims at providing the opportunity of sharing new ideas, methods and technologies useful for the development and improvement of smart intralogistics for warehousing, material handling, and distribution systems. Topics of interest include (but are not limited to) the proposal of solutions and technologies as well as design, analysis, and evaluation methodologies for:
- Storing and warehousing
- Warehouse order picking
- Material handling systems
- Part feeding for manufacturing and assembly systems
- Materials distribution strategies and warehouse locations
- Delivery and transportation policies
- Intralogistics systems and strategies
- Forward-reverse logistics management
- Smart, automated, robotized warehousing
- Logistics 4.0
- Human-technology interaction in intralogistics
- Individual and group behavior in intralogistics
- Digital twins of intralogistics systems
- Data-driven evaluation of new technologies in intralogistics
- Digital nudges and human behavior in intralogistics
- Intersections of warehousing and transportation
During last years, the working group has contributed to TC events such as:
IFAC INCOM 2024 (invited session, associate editors)