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Cyber-Physical Production Systems (CPPS) enable Smart Production by linking physical processes with digital systems across the entire value chain. For a holistic integration both a vertical integration of production processes and a horizontal integration across Enterprise Information Systems (EIS) is necessary, which makes CPPS complex systems with a large number of constituents and connections. The goal is a flexible and intelligent production system based on a decentralized architecture that connects the entire value chain. Literature provides generalized reference architecture models, such as RAMI 4.0 or 5C, and a variety of specific architectures, that have mainly been implemented in academic environment. There is a lack of examples and guidelines on how to integrate the proposed generic high-level architectures and to achieve truly decentralized ones, which results in a scarcity in actual implementations of CPPS in reality. Historically, automation systems are based on the hierarchical ISA-95 automation pyramid with an intentional separation of layers, and the step for industrial companies towards decentralized CPPS architectures is large and full of uncertainties. This paper investigates actual reasons that impede industrial companies in adopting decentralized CPPS architectures. A case study assesses the situation in a large global manufacturing company based in Sweden by following ongoing activities towards a flexible and end-to-end connected production system. Findings concern the integration of ERP and PLM systems with the production system, architectural and technological constraints, and structural and organizational aspects.

Battery swapping has re-emerged as a complementary solution to plug-in charging in the global transition to electric mobility. While the technical feasibility of battery swapping is increasingly evident, its commercial success depends on the viability of underlying business models. This paper presents preliminary findings from an ongoing research project on business model design and strategic deployment of battery swapping services. Based on a focused literature review and case analysis, we identify four main business model archetypes: integrated provider, independent service provider, partnership-based, and Battery-as-a-Service. We examine real-world examples from Gogoro, SUN Mobility, and CATL to illustrate diverse approaches and contextual factors. The analysis highlights critical success factors such as pricing strategies, deployment planning, capital management, consumer adoption levers, and circular economy considerations. These initial results provide a foundation for further inquiry. Future phases of the project will involve workshops and interviews with industry stakeholders to validate and refine the proposed framework.

This paper has through empirics and dialogue with industry experts and practitioners collected industrial circular battery production challenges that call for research and development. By workshop visits to vehicle companies and focus group discussions with professionals and researchers in Swedish manufacturing research and development clusters, both general challenges and specific circularity challenges for battery production with focus on cell to module and cell to pack were discussed and analysed. Further research paths for the future were concluded. A joint view of circularity development of the product design and the production system design may be beneficial. Researchers who seek industrial impact may combine detailed development with systemic research together with practitioners.

The large-scale electrification of transport is accelerating globally, resulting i n a g rowing in flux o f end-of-first-life batteries from electric vehicles (EVs). Repurposing these batteries into second- life battery energy storage systems (SL-BESS) offers a promising pathway to extend battery lifecycles, reduce environmental impacts, and support circular value creation. Despite significant technological progress and numerous pilot projects, the adoption of SL-BESS in scalable business practice remains limited. A key challenge lies in defining viable and context-specific value propositions that can guide actors in designing circular business models. This paper presents an explorative qualitative study examining how circular value propositions for SL-BESS can be defined and contextualized within EV charging infrastructure. Empirical data was gathered through semistructured interviews and co-creative workshops involving multiple actors in the Swedish EV ecosystem. The analysis resulted in three business scenarios: resilient energy hubs within municipalities, mobility-integrated energy for flexible and bidirectional bus charging, and circular Battery-as-a-Service solutions for industrial and mining applications. The findings indicate that while SL-BESS technologies have reached a relatively high level of maturity, business model development lags due to regulatory uncertainty, fragmented market structures, and unclear revenue and ownership arrangements. By abstracting across scenarios, the study identifies recurring patterns in how second-life batteries can function as enabling infrastructure for flexible operations, shared resource use, and industrial-societal symbiosis. The paper contributes to the circular business model literature by presenting scenario-based circular value propositions, crossscenario comparison criteria, and strategic patterns that can support actors in positioning themselves within emerging markets for circular energy storage and charging infrastructure.

The rapid growth of the electric vehicle (EV) industry has significantly increased the demand for EV batteries, raising concerns about their environmental impact and end-of-life management. EV batteries face several challenges throughout their lifespan, including performance degradation, limited usability during their first life, and complex recycling processes. Addressing these issues requires a fundamental shift toward circular economy (CE) principles. This study examines how circular strategies—particularly those outlined in the 10R framework: Refuse, Rethink, Reduce, Reuse, Repair, Refurbish, Remanufacture, Repurpose, Recycle, and Recover—can be applied across the EV battery lifecycle to enhance value retention. Drawing on semi-structured interviews with key actors in the EV battery ecosystem—such as battery manufacturer, EV manufacturer, EV operator, battery recycler, and technology providers—this study investigates how 10R strategies are interpreted and implemented in practice and explores the role of advanced digital technologies in supporting these efforts. The results show that actors are currently adopting and planning to adopt diverse 10R strategies to promote a CE for EV batteries. All major digital technologies associated with Industry 4.0 are being applied, with AI, blockchain, IoT, big data analytics, cloud technology, simulation, and digital twins being among the most widely used. This study provides exploratory insights into the role of digital technologies in implementing circular strategies in the EV battery circularity sector, which helps understand how these technologies and collaboration can close the loop.

The smart circular economy (SCE) refers to the systematic use of advanced digital technologies to operationalize one or more circular R strategies, such as reduce, repair, reuse, and remanufacture, across the product life cycle. While the existing SCE literature is expanding, it remains largely conceptually driven and predominantly theoretical, with limited empirical grounding in industrial contexts. This study addresses this gap by empirically conceptualizing and characterizing SCE through five use cases drawn from diverse manufacturing and service-related industries. Data were collected through site visits, semi-structured interviews, and workshops with five companies. The use cases were systematically analyzed using analytical dimensions such as context, circularity objective, digital enablers, stakeholders' value creation, and sustainability impact. These dimensions helped to structure and operationalize the SCE concept across heterogeneous industrial contexts. Cross-case analysis reveals five recurring categories of challenges influencing the feasibility of SCE implementation: technological integration and data management; product recovery and collection; design and product complexity; market acceptance and user adoption; and economic viability and scalability. The study contributes to the literature on SCE by providing an empirically grounded conceptualization and proposing replicable analytical dimensions that support manufacturing companies in exploring, comparing, and selecting suitable SCE business use case opportunities.

Smart and sustainable production is increasingly critical for companies aiming to reduce environmental impact while maintaining competitiveness. Digital technologies play a key role by enabling data-driven decision-making to optimize production processes, reduce waste, and extend product lifecycles through the deployment of circular strategies such as reuse and remanufacturing. However, realizing the full potential of digital technologies for smart and sustainable production requires thoughtful selection and effective integration, both of which must account for the contextual complexity of the production environment. Despite this, limited research has examined how factors such as multi-actor involvement, system heterogeneity, and data uncertainty influence the selection and integration of digital technologies. This paper addresses this gap by examining how contextual complexity influences the selection and integration of digital technologies in smart and sustainable production. A multiple case study design was applied, examining one case within a remanufacturing ecosystem and another focused on performance monitoring of production equipment. The study identifies seven dimensions of contextual complexity - spanning process maturity, organizational landscape, stakeholder environment, system architecture, data uncertainty, integration demands, and transformation challenges - that influence how technologies should be selected and integrated. The findings reveal that in low-to-medium complexity settings, greater emphasis should be placed on making a suitable technology selection, supported by standardized platforms and centralized governance. In contrast, high-complexity environments require stronger focus on integration, emphasizing interoperability, federated governance, and adaptable data strategies. Based on these insights, the paper presents a framework to guide platform strategy, visualization, governance, data storage, and data handling according to the complexity level of the deployment context. © 2026 The Author(s).

The manufacturing sector is undergoing a paradigm shift driven by the dual imperatives of sustainability and digital transformation. The convergence of circular economy strategies and advanced digitalization-often described as Smart Circularity-offers new pathways for creating economic, environmental, and social value simultaneously. However, translating Smart Circularity into concrete industrial practices remains a challenge, particularly within the manufacturing sector. This study addresses this gap by examining one of the key starting points in business modelling: the kind of value a company creates for its customers through its products and services, commonly referred to as the value proposition. The paper explores how manufacturing companies conceptualize and approach Smart Circularity through the design of value propositions that are embedded in manufacturing systems and lifecycle activities. The study is based on qualitative data consisting of semi-structured interviews with five companies and two multi-company workshops involving ten organizations. The analysis identifies three overarching value propositions that characterize Smart Circularity in manufacturing: (1) Smart life extension and circular services, (2) Sustainable material and digital integration, and (3) Circular intelligence and system integration. Together, these value propositions form the basis of a proposed guiding model that connects material circularity, product longevity, and digital intelligence within manufacturing systems into a single systemic framework for Smart Circularity. The findings contribute to the emerging discourse on smart circular economy and circular manufacturing by providing a preliminary empirical understanding of how firms can operationalize Smart Circularity through production-oriented, data-driven approaches to circular value creation.

The transition to electric vehicles (EVs) presents new challenges and opportunities for sustainable transport systems, particularly concerning battery degradation, lifecycle management, and long-term system reliability. While numerous decision-support models exist for vehicle routing, charging infrastructure planning, and investment analysis, few integrate battery aging dynamics into a comprehensive circularity-oriented decision framework. This paper proposes a novel Battery Circularity Decision Support Framework that links operational, tactical, and strategic decision-making with a semi-empirical battery degradation model. The framework enables stakeholders to evaluate the impacts of driving behavior, duty cycles, charging strategies, and thermal environments on battery state-of-health (SoH), extending into future reuse, repurposing, and recycling pathways. Drawing on recent literature and experimental data, we highlight how various decisions, ranging from energy-efficient routing to battery end-of-life planning, can be informed through degradation-aware simulations.

To demonstrate the practical utility of the framework, we apply it to a real-world use case involving an electric bus operating in Sweden. The framework enabled the evaluation of battery degradation over time under consistent operational conditions, revealing the projected timeframe during which the bus could continue to reliably perform the same route. As SoH decreased, the framework supported a strategic decision to reassign the bus to a less power-demanding route, thereby extending its operational life and reducing the risk of service interruptions. This example illustrates how our framework enables data-driven decisions that align with circular economy goals and sustainable fleet operations. By integrating battery aging into system-level planning, the framework fills a crucial gap in current EV battery management and battery circularity methodologies.

With the development towards Industry 5.0, manufacturing companies are developing towards Smart Production - namely, using data as a resource to interconnect the elements in the production system for a more resource-efficient and sustainable production. Selection and integration of digital technologies are crucial steps to ensure that suitable technology is chosen and properly introduced in the production system. However, having one digital technology is not enough; rather there is a need to combine several synergising technologies for smart production. There are many challenges when selecting and integrating a combination of synergising digital technologies for smart production. Therefore, the purpose of this paper is to support manufacturing companies in systematically selecting and integrating suitable digital technologies for efficiently benefiting data value chains for smart production. This paper employed a multiple case study involving manufacturing companies within different industries and of different sizes. The paper analyses the current challenges related to the selection and integration of digital technologies and proposes a data flow framework with possible ways of combining digital technologies. The proposed framework shows alternative data flows between a combination of technologies depending on what digital technologies are selected and how they are integrated.