1. Introduction
The growing importance of sustainability in engineering design has led to the integration of new approaches aimed at reducing the environmental impact of products throughout their entire lifecycle. Circular Economy (CE) emphasizes closing resource loops to maximize resource efficiency. CE strategies can be categorized into three main core strategies: narrowing, slowing and closing loops (Reference Bocken and RitalaBocken & Ritala, 2022). Each strategy is implemented by so-called R-strategies, such as reuse, recycle, remanufacture and rethink (Reference Potting, Hekkert, Worrell and HanemaaijerPotting et al., 2017). These R-strategies require specific design approaches with regard to the product as well as information needed for decision-making. This results in interrelated or conflicting properties of products and drives complexity within the design process. At the same time early stages of the design process are critical, as decisions made at these stages significantly influence the product’s overall environmental footprint as well as the implementation of specific lifecycle options like recycling or reuse (Reference InkermannInkermann, 2022). This is especially relevant for complex products, where properties such as energy efficiency, material use, and recyclability must be considered throughout the entire lifecycle. This work extends the principles of CE to the digital domain by leveraging SysML (v1) models to extract additional value, supporting the goal of improving the ratio of benefits to resource consumption. Model-Based Systems Engineering (MBSE) approaches were developed as a basis for decisions in development, which can create an information basis through a networked and semantically enriched description of information. In the systematic literature review (SLR) (Reference Lipšinić, Pavković and HusungLipšinić et al., 2025), MBSE approaches supporting sustainability in product design were analysed, consolidated and classified. The SLR followed the PRISMA methodology and included 135 papers for analysis. The findings of the SLR indicate a rise in the application of MBSE approaches in the development of sustainable systems. Building upon the classification from the SLR, this paper focuses specifically on the CE strategy of remanufacturing. Accordingly, the research focus has been narrowed and refined to the analysis of the lifecycle of products designed for remanufacturing. Remanufacturing is the process of restoring a used product to a like-new condition, meeting or exceeding original specifications (Reference Geist and BalleGeist & Balle, 2024). According to Reference Lee, Woo and RohLee et al. (2017), the remanufacturing process involves several steps: disassembly, cleaning, inspection, repair or replacement of components and reassembly. Reference Butzer, Schötz and SteinhilperButzer et al. (2016) expand the remanufacturing process by adding an entrance diagnosis to assess the initial product’s condition and a final testing phase to ensure it meets original requirements. The process step which commonly includes repair, refurbishment, replacement or upgrading of selected components is referred to as the value retaining or increasing step. Certification or warranty assurance is also commonly required in industrial practice (Reference Baghdadi, Shafiee and AlkaliBaghdadi et al., 2022). Additionally, remanufacturing requires extensive process planning, which is heavily influenced by strategic business decisions. The necessary processes, which need to be planned depend on the specific product variant and its condition. Research in the field of DfRem (Reference MesaMesa, 2023) mainly addresses detailed and domain-specific design. From a Systems Engineering perspective, remanufacturing is particularly noteworthy among R-strategies as the process can be applied to various hierarchical levels within a system’s architecture, ranging from component-level to overall system-level remanufacturing operations.
The objective of this paper is to analyse the challenges stated in the literature and to leverage the advantages of SysML models created during the early design phase. An essential challenge in the remanufacturing process is to manage uncertainties stemming from the variable conditions of returned components (often referred to as “cores”). This challenge should be addressed during the design phase to ensure that the subsequent remanufacturing process is as efficient as possible (Reference Lipšinić, Husung, Pavković and WeberLipšinić et al., 2024). Yet, the challenge lies in making well-informed decisions with limited information, as the long-term impacts of design decisions may not be fully realized until much later in the product’s lifecycle. MBSE is a suitable methodology for developing complex products by supporting the handling of complexity, particularly during the early stages of design.
1.1. Research objectives and methodology
While related studies (Reference Eigner, Dickopf and ApostolovEigner et al., 2017; Reference Lipšinić and PavkovićLipšinić & Pavković, 2023) have demonstrated the use of MBSE for various sustainability assessments, there is a clear need for a more focused investigation into how MBSE, with the utilisation of SysML models, can support the remanufacturing R-strategy at the product design stage as well as later lifecycle stages (Reference Lipšinić, Pavković and HusungLipšinić et al., 2025). The primary objective of this paper is to determine recurring issues within the lifecycle of products designed for remanufacture (DfRem) from literature. The basis for the literature analysis is formed on the classification of MBSE supports for sustainability presented in (Reference Lipšinić, Pavković and HusungLipšinić et al., 2025), including five classes, namely: “Requirements Definition Support”, “Structure and Behaviour Definition Support”, “Integration of Sustainable Solutions”, “Lifecycle Parameters and Data Integration” and “Lifecycle Analysis Support”.
The classes detail the current state of research regarding the different types, or modalities of methods or tools integrated with the MBSE approach with the common goal of providing support for the development of sustainable products. To derive issues specific to remanufacturable products, the previous SLR (Reference Lipšinić, Pavković and HusungLipšinić et al., 2025) is extended by a new literature review in the general field of remanufacturing research. The research goal is to leverage the strengths of MBSE and extend the utilisation of SysML models (Reference Wilking, Horber, Goetz and WartzackWilking et al., 2024) created during the design phase to support the later lifecycle phase of remanufacturing by addressing the issues found in the literature review. Against this background, two research questions are formed:
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1. What are the specific issues and needs in the remanufacturing process that could be supported by the utilisation of SysML models created during the design process?
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2. What modelling strategies and SysML-elements are suitable for addressing the previously identified issues?
Research question 1 is addressed through an extended state-of-the-art literature analysis, which is used to identify and synthesise remanufacturing-specific issues and needs that could be supported by SysML models created during the design phase. For research question 2, the literature is then examined for methodological and technological approaches that respond to the identified needs. These approaches are analysed to derive suitable SysML elements and views. The rationale for focusing on SysML as the modelling language in this research is grounded in findings from the previous SLR (Reference Lipšinić, Pavković and HusungLipšinić et al., 2025). The review revealed that SysML is the dominant language applied in studies related to MBSE for sustainable product development (Reference Berschik, Schumacher, Laukotka, Krause and InkermannBerschik et al., 2023). Other modelling languages did not show a significant increase in papers when included in the extended search. For the derivation of issues relevant for the lifecycle of remanufacturable products, literature review papers which included keywords such as “limitations” and “barriers” were first selected for analysis. These papers provided the baseline for more detailed analysis. The next section provides insights into existing research about applying the MBSE approach to designing sustainable products. Section 3 describes the derived issues from the literature and opportunities for the utilisation of SysML models. Section 4 provides suggestions for the implementation of the model utilisation. The implementation is discussed for each issue as an isolated case, which should provide a better foundation towards a “brick-by-brick” type industrial implementation (Reference Blott and BuchholzBlott & Buchholz, 2023). The last section discusses the findings and concludes this work with limitations of the research and further research opportunities.
2. Related works
Design of complex sustainable products in the context of CE has been addressed by numerous studies in recent literature. Among these contributions, Reference Albers, Tusch, Jäckle, Seidler and KempfAlbers et al. (2024) argue that achieving a truly circular economy in engineering requires forward-looking approaches such as System Generation Engineering (SGE). When combined with CE principles, SGE is intended to guide product development across generations and optimise strategies for long-term value preservation. In this context, MBSE based support systems are proposed. Reference Schwahn, Potinecke, Block, Werner and TarlosySchwahn et al. (2024) present an approach aimed at helping designers apply circularity measures when addressing critical or undesired product states. In addition to embedding such measures into the MBSE model, Reference Bougain and GerhardBougain and Gerhard (2017) propose the inclusion of environmental impacts. Their approach has been demonstrated on a SysML model with the aim of enabling designers to evaluate and make more sustainable decisions. In other literature, selection of R-strategies is referred to as Lifecycle Options (LCO). According to this view, Reference InkermannInkermann (2022) defines the dimensions of lifetime and identifies essential degradation mechanisms relevant to LCO decision-making, while also proposing an MBSE supported method to evaluate the uncertainties associated with these mechanisms and their impact on the LCO selection process. In this approach, the role of MBSE is to provide essential data, such as detailed use case definitions and architecture descriptions. Beyond these general CE related approaches, research has examined certain R-strategies in greater depth. For example, Reference Everding, Cudok, Raulf and VietorEverding et al. (2024), Reference Meyer, Lipšinić, Li, Husung, Inkermann, Pavković and AutorMeyer et al. (2025) and Reference Meyer and InkermannMeyer and Inkermann (2025) focus on the application of MBSE for the reuse strategy. Reference Everding, Cudok, Raulf and VietorEverding et al. (2024) supplement the system model with reuse specific requirements derived from modelled use cases. Lastly, Reference Meyer and InkermannMeyer and Inkermann (2025) examine the specific challenges present during the integration of reused components in future product generations. Overall, recent MBSE research trends support the development of sustainable products. Reuse, as an R-strategy, has received the most attention, while remanufacturing remains underexplored. In particular, there is little synthesised guidance on leveraging design-phase SysML models to address remanufacturing-specific needs.
3. Remanufacturing challenges and issues
To address the first research question, recurring issues and needs across the lifecycle of a remanufacturable product are derived from the literature review. This section focuses on determining the main issues reported in the literature. While this list is not exhaustive, it reflects the most frequently reported and recurring issues identified across the reviewed literature. Reference Golinska-Dawson, Sakao, Sundin and Werner-LewandowskaGolinska-Dawson et al. (2025) provide a more detailed and broader overview of remanufacturing challenges, encompassing perspectives such as customer and market dynamics, business models, and policy or legislative aspects. In contrast, this study concentrates on the technical dimension of these challenges, differentiating methodological and technological solutions. Technological solutions like the Digital Twin (DT) are methodologically supported by SysML through systematic design. In the following subsections, the individual issues are detailed. The subsections are structured according to how they can be addressed through specific model utilisation opportunities, following the classification of MBSE supports for sustainability established in (Reference Lipšinić, Pavković and HusungLipšinić et al., 2025) and stated in Section 1.1.
3.1. Requirements definition support
During the later phases of the remanufacturing process, products and their components are inspected and tested to determine whether their relevant functional properties and overall performance have been retained, improved, or degraded (Reference Salah, Ziout, Alkahtani, Alatefi, Abd Elgawad, Badwelan and SyarifSalah et al., 2021). To support these evaluations, it is essential to maintain traceability between the product requirements and the condition of the returned components. Such traceability links within the SysML model can improve the planning and execution of remanufacturing processes like inspection and testing. Within a MBSE approach, these relationships can be explicitly represented using SysML models. For example, incorporating remanufacturing-specific requirements derived from the original system model can guide inspection and testing activities. The derivation of remanufacturing related requirements from SysML modelled remanufacturing process use cases has also been explored by Reference Everding, Käberich and VietorEverding et al. (2025). The authors suggest the integration of Design for Sustainability guidelines into the system model. Furthermore, the mecPro2 Model Framework (Reference Eigner, Dickopf and ApostolovEigner et al., 2017) provides one example of how SysML can be used to manage system complexity and ensure traceability across different engineering domains. In the case of remanufacturing, for example, the traceability of inspection and testing results to the product requirements can be achieved.
3.2. Integration of sustainable solutions
The need for reconfiguration often arises when certain components are replaced, upgraded, or redesigned during the remanufacturing process with the purpose of extending the product functionality or to meet new requirements stated by the users. In this case, used components may no longer be compatible with the new configurations of future product generation (Reference Albers, Tusch, Jäckle, Seidler and KempfAlbers et al., 2024). This issue is particularly relevant for complex systems, where compatibility must be ensured across mechanical, electronic, and software domains. Such updates can introduce behavioural changes that affect the functionality or performance. To address these challenges, compatibility must be assessed. SysML enables the explicit modelling of compatibility-relevant information to support such assessments.
3.3. Structure and behaviour definition support and lifecycle analysis support
Effective remanufacturing planning depends on reliable information about the condition, performance, and availability of product components after their use phase. However, the absence of such data remains a persistent challenge. When the condition and quantity of components are uncertain, scheduling, resource allocation, and decision-making during remanufacturing become inefficient and risk-prone. According to Reference Mejía-Moncayo, Kenné and HofMejía-Moncayo et al. (2023), the lack of product lifecycle information (PLCI) represents a central barrier to remanufacturing. Missing or incomplete data about product usage, deterioration, or location leads to inefficiencies across the entire value chain. Similarly, Reference Taddei, Sassanelli, Rosa and TerziTaddei et al. (2022) note that inadequate information on product use history and quality affect the feasibility analysis for component remanufacturing. In the context of complex products, such as Product-Service Systems (PSS), the challenge of lifecycle data collection is particularly relevant. As highlighted by Reference Apostolov, Fischer, Olivotti, Dreyer, Breitner and EignerApostolov et al. (2018), PSS architectures enable new opportunities for sustainability by integrating monitoring technologies throughout the product lifecycle. Among these technologies, the concept of the DT has received significant attention. DTs allow continuous data acquisition from different lifecycle phases, providing insights into real product behaviour. Beyond monitoring, such data can also be used to perform domain specific simulations that estimate the current state of components, thereby reducing uncertainty in remanufacturing planning. Nonetheless, the deployment of DTs and related data-driven systems is not without limitations. As highlighted by Reference Lobo, Trevisan, Liu, Yang and MascarenhasLobo et al. (2022), several technological barriers persist, including data collection difficulties caused by insufficient expertise, model inaccuracy, sensor malfunctions, and the lack of interoperability due to multiple, non-standardized technologies. Synchronizing data from the physical condition of products with digital records is difficult but necessary for accurate remanufacturing decisions (Reference Liu, Song and LiuLiu et al., 2023). In order for the DT to be able to collect and evaluate the relevant usage data, its integration must be considered already during product development. This requires the concurrent design of appropriate sensing, data acquisition, and processing capabilities. Consequently, the DT architecture should be systematically defined based on product-specific requirements and the characteristics that are intended to be monitored or evaluated. By enabling continuous monitoring and state simulation of components, DT-based approaches provide the data basis needed for lifecycle analyses that assess the feasibility of component remanufacturing.
3.4. Lifecycle parameters and data integration
While lifecycle data collection and monitoring technologies can significantly reduce uncertainty in remanufacturing planning, their effectiveness ultimately depends on how this information is communicated and utilised across stakeholders. One of the persistent challenges lies in ensuring that the collected data about product condition, performance, and history is adequately shared and interpreted by all relevant actors in the value chain. Insufficient information exchange between design and remanufacturing teams often leads to inefficiencies (Reference Teixeira, Tjahjono, Beltran and JuliãoTeixeira et al., 2022). This issue reflects a broader need for maintaining traceability of product information throughout the lifecycle, not only between requirements and system elements, as discussed in Section 3.1, but also between the digital records created during the design phase and the physical product instances assessed during remanufacturing. A promising emerging approach to address these information gaps is the Digital Product Passport (DPP) (Reference Walden, Steinbrecher and MarinkovicWalden et al., 2021) which is currently being formalized within EU CE policy. The literature on CE also emphasizes the importance of effective knowledge transfer mechanisms in this context (Reference Halstenberg, Dönmez, Mennenga, Herrmann and StarkHalstenberg et al., 2021). Here, MBSE’s role is to capture stakeholders and information needs and to define views and viewpoints that enable structured, decision-relevant knowledge transfer.
4. Addressing the challenges through SysML utilisation
Building on the issues identified in Section 3, this section examines how SysML models can be utilised to address each issue in a focused and manageable way. This section provides the answers for research question 2. Corresponding opportunities for model utilisation are outlined, and the implementation details, such as modelling elements for the proposed approaches are discussed. In the broader context of model utilisation, Reference Wilking, Horber, Goetz and WartzackWilking et al. (2024) provide a comprehensive classification that helps clarify how system models created within the MBSE approach, particularly SysML models, can be applied and reused across different engineering activities. Ongoing work by the authors of this paper on the integration of safety-related data sources into SysML models in an industrial case study has shown that substantial planning and effort are required to implement concepts such as product line model import and management. In more complex applications such as those examined in the following subsections, this experience highlights the need for an incremental implementation procedure. For this reason, the issues have been deliberately scoped and treated as relatively isolated topics, allowing the implementation steps to be defined in a manageable and structured way. At the end of Section 4.2, the identified issues, together with the proposals on how to address them are summarised in Table 1, where they are linked to the corresponding segments in Section 3 and presented as a part of the overall contribution.
4.1. SysML modelling strategies and concepts
The requirement definition support and traceability discussed in Section 3.1 considers the need to specify remanufacturing process requirements, like acceptable initial component condition requirements. Deriving such requirements necessitates a detailed process model of the remanufacturing activities. Process-oriented diagrams such as use case (UC), activity (ACT) and sequence (SEQ) diagrams are therefore recommended because they capture the logical and temporal dependencies that drive requirement formulation. For the definition of the system architecture, additional knowledge about key components and the technologies applied during the value-retaining process phase is required. This knowledge supports the functional grouping of the architecture and informs the integration of monitoring elements. As a result, a higher effort is required during the requirements engineering phase, yet the expected benefits are the systematically defined and traceable requirements which improve the efficiency and feasibility of remanufacturing planning, support later verification during inspection and entrance diagnosis by providing testing criteria, and reduce uncertainty in later lifecycle stages, as outlined in Section 3.1 and summarised in Table 1.
Determining the remanufacturing feasibility of components is challenged by the lack of reliable information about component condition at the end of the use phase. Addressing this issue requires that the use-phase data collection is considered already during system design. Within the MBSE approach, SysML models provide a structured means to represent and manage the requirements, functions and architectures that support such data acquisition. Model elements can define monitoring use cases, specify the key components that require sensor instrumentation and represent the data interfaces needed for lifecycle information exchange. MBSE methodologies have already been applied successfully to the development of DTs (Reference Bickford, Van Bossuyt, Beery and PollmanBickford et al., 2020). SysML can be used not only to describe the logical and functional relationships within monitoring systems, but also to support the derivation of executable code for DT implementation (Reference Wilking, Sauer, Schleich and WartzackWilking et al., 2022).
Building on the monitoring-based data collection discussed above, the next step is to use these lifecycle data to estimate product and component conditions at end of life (EoL). Predicting these conditions requires careful consideration of suitable simulation methods. While state machine diagrams can represent discrete states and transitions, they do not provide the level of behavioural detail needed to estimate system lifetimes accurately. For this purpose, physics-based domain specific simulations are required because they account for real-world operating conditions and component durability. Within the MBSE approach, SysML can support the planning of these simulations by systematically defining boundary conditions and modelling constraints (Reference Zhang, Höpfner, Berroth, Pasch and JacobsY. Zhang et al., 2021). Once the simulations are conducted, whether based on estimated or collected lifecycle data, their results can be incorporated into the model as discrete states or instance-specific lifecycle parameters. Such simulations support remanufacturing process planning, including reverse logistics, by reducing uncertainty regarding the quantity and condition of returned products. Another useful MBSE capability is the execution of system parameter calculations. Based on collected lifecycle data, MBSE can perform static calculations of remanufacturing-related parameters, such as the warranty period, and system or component health indicators (Reference Turner, Okorie, Emmanouilidis and OyekanTurner et al., 2022). Based on this, lifecycle options can be determined for each component according to predefined entrance diagnosis criteria and processes. Due to the complexity of parametric modelling and the required information for such calculations, the feasibility of the utilisation of this MBSE capability should be further investigated.
The concern discussed in Section 3.2 relates to managing compatibility across product generations and remanufactured configurations. Within the MBSE approach, system models created in SysML can capture and manage the compatibility information required for assessing whether components, interfaces or subsystems can be combined in a feasible configuration. Beyond representing the current system, the MBSE approach also enables the creation and evaluation of alternative product configurations, which allows engineers to explore behavioural aspects similarly to design space exploration. Product Line Engineering (PLE) (Reference Navas, Bonnet, Voirin and GongoraNavas et al., 2021) provides suitable modelling strategies for this purpose, since it supports the systematic organisation of variability and the controlled definition of configuration options. To support this, the system structure must incorporate different system variants that may be estimated during early design stages or modelled as the system evolves. These variants can be represented within a product line model, often referred to as the 150% model. The model-based product configuration framework proposed by Reference Wyrwich, Jacobs, Siebrecht and KonradWyrwich et al. (2020) illustrates how such data can be used to support configuration tasks by drawing directly on information stored in the system model. Although these capabilities provide a foundation for systematic compatibility assessment, further research is required to enable automated compatibility analysis specifically for remanufactured product configurations, where deviations from the original specification are common and must be evaluated efficiently.
Section 3.4 highlights the challenge of transferring and using lifecycle information among different stakeholders. The literature on MBSE emphasises improved communication during the design phase as one of the key strengths of formal system models, yet this benefit can only be realised when the model utilisation is planned in advance. Before creating the system model, explicit consideration must therefore be given to how information will be exchanged with stakeholders who do not work directly with SysML. This includes defining specialised views that provide targeted access to model content. Such views can, for example, allow remanufacturing specialists to perform compatibility checks based on available configurations without requiring SysML expertise. To enhance the usability of the model as a central source of system information, a strategic approach to information sharing is necessary. A persistent challenge is that model information is typically represented through domain-specific notations, which can hinder understanding for non-modellers. Structuring model views so that information is accessible and understandable to these users is therefore essential. Several approaches for facilitating such information transfer have been proposed, including interaction with the model through HTML interfaces (Reference Cohen, Arai, Rakalina, Griffin, Heiser, Urbina, McGuire, Rubin, Seigel, Shah, Ramachandran, Dixit, Legaspi, Mindock, Bardina and HaileyCohen et al., 2021) or through the capabilities of PLM systems.
4.2. Implementation with SysML modelling elements
To demonstrate the utilisation of MBSE for addressing the previously stated issues, the modelling method and language needs to be expanded to include newly proposed elements (e.g., views, stereotypes). This involves enhancing the system model by defining new system parameters using SysML language extensions (stereotypes). Stereotypes allow the creation of domain-specific attributes that extend SysML’s modelling capabilities. The newly created stereotypes provide a structured way to incorporate unique characteristics into the model. These product characteristics, together with the process model (which includes decision points), help different stakeholders in making informed decisions. For example, component health indicator values might help the remanufacturing process planning stakeholders determine the timing of product returns. In another example, estimated lifetime parameters can help the product architect to define a more suitable product structure (eBOM) for the remanufacturing process. An overview of the modelling elements applied for each issue is provided in Table 1. Methodologically, this approach builds on (Reference Husung, Weber, Mahboob and KleinerHusung et al., 2021), in which individual methods and their associated information requirements were analysed, and corresponding MBSE artefacts and views were derived.
Overview of challenges and SysML utilisation opportunities
Table 1 Long description
A table with six columns and eight rows, including a header row. The columns are labeled Challenges and issues, Modeling strategy, Modeling elements, Implementation steps, Required effort and prerequisites, and Expected benefit. The rows detail specific challenges and issues related to remanufacturing requirements, requirements traceability, product state uncertainty, product reconfigurations, and information exchange. Each row provides corresponding modeling strategies, modeling elements, implementation steps, required effort and prerequisites, and expected benefits. The table captures the structured approach to addressing each issue with SysML models, highlighting the incremental implementation procedure and manageable steps for each challenge.
Regarding the issue discussed in section 3.1, the requirements derived from the behaviour diagrams need to be further linked to the corresponding modelling elements. For example, the requirement should be linked to a constraint block that describes the component condition parameter with the <<verified by>> relation. The constraint block is further linked to the product component via the <<constraint>> relation enabling full traceability from component to use case. Furthermore, the modelling elements required for the development of DTs include a significant part of the SysML metamodel. Literature on DT-oriented MBSE provides detailed discussions of suitable modelling strategies and indicates how specific elements, such as internal block diagrams, state machine diagrams and parametric diagrams, can be applied to support lifecycle data collection, simulation and synchronisation (Reference Bickford, Van Bossuyt, Beery and PollmanBickford et al., 2020). The next issue arises during the replacement of components, which results in a new product configuration. Suitable configurations can be determined based on a compatibility matrix. The matrix is enabled by the <<Compatible>> SysML relation. Lastly, the elements used for the definition of information sharing is done through the definition of <<View>> and <<Viewpoint>> elements.
4.3. Preparation of validation case study
This section describes the initial steps of the ongoing work undertaken to implement the large-scale case study for validating the proposed modelling strategies. Collaboration was initiated with a manufacturer of power transformers. MBSE implementation is under consideration in their current engineering practice. Although the products were not remanufactured at scale, remanufacturing potential was identified. Case study modelling was initiated from the company eBOM, which was used to model the hierarchical product structure through BDD diagrams. The eBOM was imported via PLM services into the SysML modeller software. The imported items were used to represent the physical layer in an RFLP-oriented approach. This physical layer is treated as a prerequisite for later utilisation opportunities, since remanufacturing was considered fundamentally physical. From this physical layer, a logical structure is abstracted, and a functional structure was modelled based on the requirements. A key implementation challenge is encountered in naming conventions, as many eBOM items are defined through part ID numbers, limiting model navigability. To improve navigation, descriptive names are assigned within the SysML model, while the original identifiers are retained as properties of the physical parts to preserve traceability to the source data. Requirements, largely derived from industry standards, are extracted from specification documents and are modelled in SysML. A dedicated requirements management tool is not used by the company, and increased effort is therefore required for extraction, updates, and traceability maintenance. Transformer testing procedures are captured to represent the verification process. This verification modelling is treated as analogous to incoming inspection in remanufacturing, since defined procedures and criteria are relied upon to assess compliance and to support pass or fail routing decisions. As the next step, the energy grid system, including the monitoring station, should be modelled with the relevant data channels and model views.
5. Discussion and conclusion
In alignment with the overarching principles of the CE, which aim to extract and retain value throughout a product’s lifecycle, this work extends that notion to the digital domain by seeking to extract additional value from SysML models themselves. By enabling their reuse beyond the design phase, SysML models can support circular strategies such as remanufacturing through improved information continuity and decision support across lifecycle stages. This study examines how MBSE can support remanufacturing activities within the CE, focusing on specific lifecycle issues of remanufacturable products. By analysing remanufacturing challenges and linking them to distinct MBSE utilisation opportunities, the study establishes an overview of how benefits from early system models can be exploited in later phases. The findings address two research questions. First, the study identifies key challenges such as component state uncertainty, information transfer, system element compatibility and requirements traceability. Second, it recognises modelling strategies and SysML elements suitable for addressing these challenges, as summarised in Table 1. The integration of DTs is highlighted for enabling use monitoring, which reduces uncertainties in remanufacturing planning. These findings emphasise the versatility and cross-phase applicability of MBSE and show that its main benefits lie in the planning and simulation of system behaviour and in the extraction and use of information from a unified model source. While MBSE provides a robust framework for system modelling, it is not sufficient on its own. To ensure informed decision-making, SysML models must be linked to knowledge descriptions, enabling the incorporation of relevant empirical knowledge. Furthermore, several barriers to broader MBSE adoption in remanufacturing remain. A major barrier is the limited engagement of original equipment manufacturers in remanufacturing processes (Reference Fofou, Jiang and WangFofou et al., 2021). Since OEMs typically develop system models, their collaboration with remanufacturers is essential for effective model reuse. SysML v2 offers a promising solution (Reference Li, Faheem and HusungLi et al., 2024) through improved data exchange capabilities, although industrial adoption is still emerging. Future work should include detailed industry case studies to validate the proposed utilisation approaches, as well as investigations into how model complexity influences stakeholder capabilities and the balance between complexity and usability. Although complex systems remanufacturing remains relatively uncommon in industry and limits current research opportunities, initiatives like the Circular Car Initiative (CCI) signal potential for future advancement.
Acknowledgement
This work is funded by Ministry of Science, Education and Sports of Republic of Croatia, and Croatian Science Foundation project IP-2022-10-7775: Data-driven Methods and Tools for Design Innovation (DATA-MATION).
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