Access the latest publications of the ACCURATE project partners here.
Authors: Dmitry Ivanov
Journal: International Journal of Production Research
Year: 2026
Agentic AI (artificial intelligence) can profoundly impact model-based decision-making support. This paper conceptualises the notion of agentic supply chain digital twins (A-SCDT) triangulating the composition of agentic AI, digital twins, and model-based optimisation and simulation. Our contribution is twofold. First, we conceptualise the A-SCDT as a distinct and novel area of practical and theoretical importance. Second, we offer a framework named ICARUS (Interaction, Creativity, Adaptation, Reasoning, Ubiquity, and Synchronization), which allows to structure and systematically consider the A-SCDT impacts on future developments of model-based methods in the era of agentic AI systems. Grounding into the ICARUS framework, we elaborate on how the A-SCDT can aid in decision processes describing two industry cases and deducing some generalised insights. We propose a research agenda to stay impactful and relevant in the times of AI-powered supply chains and operations, discussing new topics, barriers, and limitations stemming from AI. Finally, we elaborate on the managerial implications of A-SCDTs and conclude that agentic AI and digital twins are triggering tectonic shifts towards a new era in supply chain and operations management, bridging model-based and model-free, AI-driven decision-making support.
Open Access: Yes
Authors: Dmitry Ivanov
Journal: Computers & Operations Research
Year: 2026
Operations and supply chains have witnessed spectacular transformations through Industry 4.0 and Industry 5.0. Is the next industrial revolution – Industry 6.0 – unfolding in the context of artificial intelligence (AI) and human-AI collaboration? And, possibly, even Industry 7.0 and superintelligence (SI) are just around the corner? In this paper, we conceptualize the transition toward Industry 6.0 as the Ecosystem Age that builds upon technologies developed in Industry 4.0 and viability-centric socio-ecological principles proposed in Industry 5.0, emerging into a cyber-socio-technical-ecological industrial revolution. We create a taxonomy of industrial revolutions based on the types of work that have been replaced/transformed by machines over time, and utilize it to delineate Industry 6.0 and forecast Industry 7.0 framed in technology (e.g., generative AI, agentic AI, edge AI, and humanoid robots), organization (i.e., decentralized, autonomous, agentic-driven planning and control), and modelling (Operations Research (OR) dimensions. Second, we discuss potential impacts of the transition toward Industry 6.0 on OR with associated challenges and chances, outlining a 7-layer architecture of OR-AI symbiosis in digital twins. We elaborate on the technology and viability principles that frame Industry 6.0 and discuss scenarios for further transitioning toward next industrial revolutions and cyber-virtual, AI-driven networks that learn, adapt, self-organize, and regenerate. We conclude by outlining research opportunities for OR in the new era of supply chain and operations management in the AI and superintelligence age.
Open Access: Yes
Authors: Dmitry Ivanov
Journal: International Transactions in Operational Research
Year: 2026
Supply chain resilience is concerned with establishing disruption-resistant operational practices and ensuring the achievement of some planned performance responding to shocks. Thus, resilience is both a quality and a quantity. The existing literature is rich in analyzing each of these two parts separately. However, studies connecting quantity and quality perspectives are rare. We position our study in the context of debates about the impact of localization on supply chain resilience. We depart from some industrial practices that use a localization degree to measure resilience. Two substantial contributions emerge from this study. First, we define a localization index of manufacturing activities in the supply chain. Second, we test two hypotheses using a discrete-event simulation model in anyLogistix: (i) Does a localization ratio impact supply chain resilience, and (ii) what role does the severity of shocks play in the impact of localization on supply chain resilience? Our findings suggest that localization impacts supply chain resilience. A positive effect of localization can be observed in scenarios with short-term disruptions, and it decreases with an increase in shock duration and severity. A mixed strategy combining local and global footprints can be recommended as a resilient supply chain strategy.
Open Access: Yes
Authors: Dmitry Ivanov
Journal: Annals of Operations Research
Year: 2026
In this paper, we present a conceptual design for a decision-support system to address tariff-induced uncertainty and disruptions. The system is comprised of predictive (simulation) and prescriptive (optimization) supply chain analytics supplemented by an LLM module for real-time disruption detection. We illustrate applications of the system developed in AnyLogistix supply chain optimization and simulation software and offer generalized mathematical formulations. The experimental part includes several supply chain stress tests under different tariff scenarios, conducted using discrete-event simulation, and recommendations for proactive supply chain reconfiguration via network optimization. This study has both theoretical contributions and practical implications. For the first time, we conceptualize a decision-support system specifically tailored to the specifics of tariff-induced uncertainty. We also show how the decision-support system proposed can be extended toward a digital twin. Our models can be used immediately in practice for stress testing supply chain resilience and for reconfiguration in response to tariff shocks.
Open Access: Yes
Authors: Dmitry Ivanov
Journal: International Journal of Systems Science
Year: 2025
Supply chain resilience and viability are increasingly important in business profitability, competitive edge, and society’s survival. In this paper, we summarise system-cybernetic views of supply chain resilience and viability. Systems and control sciences provide a broad range of principles and mathematical apparatus that allow enhancing research on resilience from an integrated, multi-disciplinary perspective. Departing from the Viable Supply Chain Model, we show some formal models of viable systems with structural dynamics control. Subsequently, we elaborate on system-cybernetic principles underlying AI-based digital twins and ecosystems.
Open Access: Yes
Authors: Vathoopan, Milan; Boudjadar, Jalil; Ramanujan, Devarajan
Journal: 2025 International Conference on Industrial Engineering and Applications
Year: 2025
The transition to a Circular Economy (CE) is becoming increasingly popular within the manufacturing industries. State-of-the-art approaches for establishing a CE involve identifying suitable CE initiatives/strategies and subsequently assessing their circularity and sustainability performance to ensure successful implementation. This process can be quite complex and tedious for manufacturing companies aiming to employ agility principles such as Manufacturing as a Service (MaaS). The complexity arises from the need to consider all possible combinations of MaaS providers, potential suppliers, machinery, and process configurations, and to assess the sustainability of each combination. This paper aims to address this problem using a top-down approach by setting an overall sustainability score and then identifying an optimized configuration of the manufacturing ecosystem for a selected circularity initiative. We propose a solution based on a two-step methodology. The first step involves information integration and retrieval using ontology as a core model, with a sustainability score as the target. To this end, the initial ontology model integrating the concept of MaaS is implemented by extending the Industry Ontology Foundry (IOF) ontology and is evaluated using a usecase. The second step, that involves the derivation of an optimized manufacturing ecosystem using digital twins, is seen as future work.
Open Access: No
Authors: Vathoopan, M.; Boudjadar, J.; Hertwig, M. M.; Lentes, J.
Journal: DS-RT 2025 – 29th International Symposium on Distributed Simulation and Real Time Applications
Year: 2025
The recent disruptions in manufacturing value creation showed the fragility of currently dominating linear value chains. Transformation of manufacturing to a service-oriented approach is a promising solution to achieve resiliency and flexibility. Service-oriented production is enabled by the “Manufacturing Service” approach, which is a core element of the Manufacturing-as-a-Service (MaaS) paradigm. In aMaaS enabled manufacturing ecosystem, consumers can avail manu-facturing services from providers, making the products transit across networked MaaS providers. Hence, an efficient decision support system is required for MaaS consumers, to ensure the viability of production in terms of cost, technology, and further requirements such as sustainability prior to ordering aMaaS from providers. This paper proposes a platform architecture for a MaaS enabled manufacturing ecosystem. Essential elements in the platform and a methodology to leverage simulation models backed by ontologies for automated quantified discovery of MaaS from providers are introduced. We anticipate that such a decision support system will boost the adoption of the MaaS paradigm. A case study is used to outline the applicability of our solution in a distributed manufacturing ecosystem.
Open Access: Yes
Authors: Hertwig Michael; Lentes Joachim; Komenda Thomas
Journal: Werkstatttechnik Online (German)
Year: 2025
Language: German
Enabled by digitalisation, Industry 4.0 was born, facilitating the production of small batch sizes under conditions that stimulate competitiveness. Small-scale, demand-orientated value creation enables manufacturing capacities to be offered as a service. This forms the basis for the implementation of manufacturing-as-a-service approaches. Service-based manufacturing approaches offer the potential to increase flexibility in order to realise more resilient and sustainable production.
Open Access: Yes
Authors: Hertwig Michael, Lentes Joachim, Riedel Oliver
Conference: 28th International Conference on Production Research, Chia, 14 to 17 July 2025
Year: 2025
Numerous global events are challenging the manufacturing industry, which must respond flexible to increased uncertainty and disruptions. In order to remain competitive, value and production systems must be adaptable and agile. In this context, the restructuring of value creation with an increasing share of service-oriented, high-mix, low-volume manufacturing—manufacturing as a service—can be a promising approach. The article seeks to perform a structured analysis of manufacturing as a service. Systematic literature review will be conducted to determine the current state of research. Based on this, the topic will be positioned within current research streams. By analyzing known ongoing initiatives, the objective is to derive relevant issues from the perspective of industry. By identifying gaps in current research, future development perspectives will be specified. A clear focal point will be set on enabling implementation and use in industrial production environments.
Open Access: Not yet
Authors: Joachim Lentes, Michael Hertwig, Frauke Schuseil
Affiliations:Fraunhofer Institute for Industrial Engineering, Stuttgart, Germany
Conference: 11th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2025, Trondheim, Norway, 30 June–03 July 2025
Year: 2025
A promising approach to advance the resilience of industrial value creation is the transition of manufacturing networks and systems towards Manufacturing-as-a-Service (MaaS). In this paradigm, manufacturing services are offered and consumed to create products. To realize MaaS, platforms are needed to bring service providers and consumers based on a matchmaking together. An approach to ensure the future-proofness of suchlike platforms and the related matchmaking is to use semantic technologies, which enable the extension of models, on which platforms and matchmaking are based, over time.
Open Access: Yes
Authors: Michael Hertwig, Frauke Schuseil, Joachim Lentes, Valeria Borodin, Cristian Duran-Mateluna, Alexandre Dolgui, Simon Thevenin
Journal: Procedia CIRP
Year: 2025
The pressure to develop a resilient value chain is currently a significant challenge due to a wide range of influences and disruptive factors. In achieving resilience, Manufacturing as a Service (MaaS) is a new approach with the potential to increase the responsiveness, flexibility, and scalability of manufacturing industries. The manufacturing services offered must match the specific requirements of the companies requesting them. Based on the analysis of the current state of knowledge, a three-stage ontology-based matchmaking approach is proposed to support human decision-makers in satisfying on-demand needs through the use of shared manufacturing resources offered as services. The capability of the proposed approach to semantically connect MaaS users is demonstrated for a MaaS scheduling service, which coordinates the execution of a set of on-demand manufacturing jobs by shared resources. Despite the constraints associated with the technical and organizational dimensions of industrial sectors, as well as with the complexity of supply chain dynamics, several key levers for expanding the adoption of MaaS are discussed throughout this paper
Open Access: Yes
Authors: Phu Nguyen, Dmitry Ivanov
Conference: 15th IFAC Workshop on Intelligent Manufacturing Systems IMS 2025: Koszalin, Poland, September 11-12, 2025
Year: 2025
Contemporary supply chains have evolved into highly complex systems characterized by multifaceted interactions between entities within and across firms. The linear and isolated view of the supply chain often fails to capture the operational inter-dependencies when addressing a supply chain problem. Our study proposes to view supply chains through the lens of a multilayer network perspective. First, we propose the principal layer, the so-called direct supplier-buyer network, encompassing the focal firm, its immediate supplier, and buying firms. Second, we extend to a deep-tier supply network layer, capturing firms with indirect relationships. Firms do not typically have good visibility for deep-tier suppliers and sometimes suffer a significant impact of the ripple effect. Third, to facilitate more effective management of material dependencies, we introduce the product-integrated network mapping the products and required materials. Finally, we propose a process-integrated network to represent how materials are transformed into final products. The four-layer network framework, therefore, offers a unified, integrated, and interoperable approach to better manage supply chain operations. We also present a case study from a leading European manufacturing firm and highlight how the presentation of a four-layer supply network supports digital transformation and enhances supply chain resilience.
Open Access: Yes
Authors: Phu Nguyen, Dmitry Ivanov
Conference: 11th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2025: Trondheim, Norway, June 30 – July 03, 2025
Year: 2025
While most research tends to examine resilience capabilities through the lens of a single strategy, supply chain management teams in practice often pursue integrated solutions that combine multiple strategies to achieve desired levels of resilience. Our study introduces an innovative two-layer digital supply chain twins (DSCTs) framework that connects the shop floor layer with the broader supply chain network layer. The DSCTs facilitate the simultaneous application of various resilience strategies. We then investigate the synergy of implementing six resilience strategies, which encompass operational and strategic levels, across different stages of disruption. The first four strategies are allocating available material inventory, activating backup suppliers, and deploying flexible on-demand resources such as labor and transportation. The other two strategies are strategic reserves for material substitution and repurposing. Combining six strategies into a unified decision-making framework allows us to assess the coevolution of decision processes and environmental conditions. Finally, we propose a set of structured experiments to find the best combination of strategies across various disruption profiles, considering supplier lead-time and supplier structural network characteristics. Our results include a framework for combining resilience strategies and a method to identify the best combination of such strategies—an essential component of any DSCTs solution.
Open Access: Yes
Process Simulations Models
Authors: Oscar Daniel Wilches Sarmiento, Valeria Borodin, Alexandre Dolgui.
Journal: Conference proceedings of the ROADEF 2025 – 26ème congrès annuel de la Société Française de Recherche Opérationnelle et d’Aide à la Décision
Year: 2025
Open Access: Yes
Process Simulations Models
Authors: Cristian Duran-Mateluna, Valeria Borodin, Alexandre Dolgui, Simon Thevenin.
Journal: Conference proceedings of the ROADEF 2025 : 26ème congrès annuel de la Société Française de Recherche Opérationnelle et d’Aide à la Décision, École Nationale des Ponts et Chaussées
Year: 2025
Manufacturing-as-a-Service (MaaS) is a transformative trend in modern manufacturing, that relies on the servitization of manufacturing resources enabled by cloud manufacturing . The development of MaaS applications can contribute significantly to increasing the resilience and sustainability of supply chains due to the flexibility, responsiveness, and scalability they offer. Distributed by definition, a MaaS system includes three decision makers: (i) customers of services, (ii) service providers, and (iii) the MaaS framework that centralizes and coordinates the provisioning and release of services . To support manufacturers in sharing and using manufacturing resources, let us consider a MaaS framework that manages the scheduling of requested tasks on shared unrelated parallel machines in a centralized way. In this work, we extend a state-of-the-art problem by incorporating task-resource eligibility scores, generated by a matchmaking process, as input to the scheduling problem and propose a list of Key Performance Indicators (KPIs) to analyze the quality of solutions proposed by the MaaS framework from the perspective of resource providers and customers.
Open Access: Yes
Process Simulations Models
Authors: Dmitry, Ivanov
Journal: International Journal of Production Research
Year: 2025
DOI: https://doi.org/10.1080/00207543.2025.2454331
Disruptions can adversely impact supply chain resilience, and measurement of these impacts is a challenging problem in research and practice. Using a practical set of resilience indicators characterising preparedness, recovery, network, and process areas, we analyse how different indicators can support analysis and decision-making from customer and operational perspectives of resilience. Disruptions and performance impacts are modelled with the help of discrete-event simulation in anyLogistix supply chain analytics software. For simulation, we construct three distinct network designs and analyse their resilience using three indicators: on-time delivery (OTD), fill rate (FR), and time-to-recover (TTR). We derive some useful theoretical and practical insights. OTD is a suitable indicator of a customer resilience perspective. However, there may be delays in reporting disruptions in the supply chain using OTD. FR can immediately alert users about interruptions in material flows and so it is better suited to the operational resilience perspective. Moreover, we propose a new interpretation of the TTR indicator by considering it from the customer resilience perspective. We reveal the role of OTD and FR as disruption indicators when measuring TTR and provide associated managerial insights. Our study can be helpful for development of multi-stakeholder-oriented resilience performance assessment systems.
Open Access: Upon registration
Process Simulations Models
Authors: Schuseil, F., Hertwig, M., Lentes, J., Zimmermann, N., Hölzle, K.
Journal: Conference proceedings of the AHFE (2024) International Conference: Human Factors in Design, Engineering, and Computing (Vol. 159). AHFE International.
Year: 2024
DOI: http://doi.org/10.54941/ahfe1005751
Fragile and unreliable supply chains, due to environmental disasters or other disruptions are a challenge for modern production companies. The concept of Manufacturing-as-a-Service (MaaS) marks a shift from traditional manufacturing, focusing on shared, networked infrastructures. In MaaS environments, effective management of demand for manufacturing capabilities and supply of production capacity is crucial, while final decisions remain with human operators. The EU project ACCURATE (Achieving Resilience through Manufacturing-as-a-Service, Digital Twins and Ecosystems) aims to create a distributed MaaS ecosystem that offers a collaborative, human-centered Decision Support System (DSS) for robust planning and resilient operations. A primary challenge is aligning services from suppliers with the demand for physical goods, which includes transportation, warehousing, and information, in addition to manufacturing. Semantic approaches and ontologies can describe these services comparably. This paper introduces a semantic matchmaking concept in MaaS networks to empower human decision makers in supply chain management. To support this, related concepts of service-oriented manufacturing concepts are analyzed and a working definition of MaaS is derived. Based on this, an approach is presented that matches supply and demand for manufacturing services while considering product process requirements. Importantly, this is not a standalone decision-making tool but a foundation for informed choices, enabling users, like order fulfilment managers, to receive tailored offers from suitable providers based on recommendations from the semantic matchmaking service.
Open Access: Yes
Process Simulations Models
Authors: Dmitry, Ivanov
Journal: International Transactions in Operational Research
Year: 2025
DOI: https://doi.org/10.1111/itor.13612
Supply chain resilience has been extensively investigated at the network and firm levels. More granular studies at the level of product supply chain resilience are scarce. In this paper, we examine relationships between product supply chain resilience, firm resilience, and network resilience. We simulate supply chains with two products in different settings of structural and process diversity, connectivity, and flexibility. The methodology is based on discrete-event simulation. The focus of the analysis is on managerial insights. Our main insights show that the resilience of product supply chains depends on the firm and network resilience, and higher firm and network resilience do not always automatically translate into higher resilience at the product level. Managerial implications are discussed and generalized. The outcomes of our study can be used by supply chain and operations managers to improve the resilience of supply chain with consideration of both product and network levels. We contribute to the literature by offering novel insights on the interrelations between firm and network resilience practices and product supply chain resilience.
Open Access: Yes
Process Simulations Models
Authors: IVANOV Dmitry
Journal: Publications Office of the European Union
Year: 2025
DOI: https://data.europa.eu/doi/10.2760/9174136
This report presents the results of a literature review on stress tests developed and applied in non-food supply chains. The primary focus of the project is on quantitative and qualitative methodologies applied in the literature for stress testing non-food supply chains, their advantages and disadvantages, data used, and identification of stress test typologies applied in different methodologies. We also identify methodological gaps in the literature, especially those related to real-world applications of stress testing. The focus of the literature review is on identifying generalisations, categorizations, and patterns rather than on the specific description of individual papers. We analyze the progress of stress testing methodologies and their applications using 61 papers identified through a SCOPUS search performed in May 2024. We identify objectives of stress tests, disruptions/shocks used in stress tests, different methodological approaches used for stress tests, design and typologies of disruption scenarios used for stress tests, data used for stress tests, and indicators used to analyse impacts/responses to different stress factors. Likewise, we analyse managerial recommendations resulting from stress tests and evaluate the advantages and disadvantages of different methodologies developed and applied for stress tests.
Open Access: Yes
Process Simulations Models
Authors: Valeria, Borodin; Vincent, Fischer; Agnès, Roussy; Claude, Yugma
Journal: 2024 35th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC)
Year: 2024
DOI: 10.1109/ASMC61125.2024.10545483
This paper focuses on a scheduling problem encountered in shop floors of Research and Development (R&D) semiconductor manufacturing facilities. R&D facilities are characterized by a large product mix in very small quantities with unique/non-standard/varying processing routes, little process control of engineering experiments, dynamic prioritization of research activities, and pre-process checks. In contrast to typical scheduling problems found in semiconductor manufacturing systems, we provide and discuss the implications of factors of complexity (unknown parameters, evolving settings, R&D fab characteristics, etc.) on operations’ scheduling specific to R&D environments. An existing dispatching rule-based heuristic, running in R&D settings, is challenged, investigated, and improved. Numerical experiments are conducted on a real-life instance and analyzed in terms of: (i) the sequence performance and quality, and (ii) the approximation accuracy of uncertain processing times and its impact on the decision performance.
Open Access: Upon registration
Institution: IMT Atlantique
Process Simulations Models
Authors: Aher, Gaurav; Ramanujan, Devarajan
Journal: DS 130: Proceedings of NordDesign 2024, Reykjavik, Iceland, 12th – 14th August 2024
Year: 2024
DOI: 10.35199/NORDDESIGN2024.71
To identify the use of simulation models in design for circular economy (DfCE) this paper reviews prior work in this domain and classifies them according to the primary application objectives. Our review suggests there is limited prior work utilizing unit-level manufacturing process simulation models for DfCE. To this end, our paper illustrates a methodology for supporting DfCE using unit manufacturing process simulations through modeling the effects of design and manufacturing parameters on product CE performance.
Open Access: Yes
