A Cost–Benefit Model for Sustainable Product Reuse and Repurposing in Circular Remanufacturing

Abstract

This study developed and validated cost–benefit models to evaluate the economic feasibility of reuse and repurposing strategies in remanufacturing, utilizing activity-based costing to assess key financial factors and implications. The models provide a structured approach to compare reuse, repurposing, and recycling, focusing on identifying conditions that maximize cost savings and reduce environmental impact. Reuse strategies emphasize scenarios requiring minimal maintenance to extend product life, while repurposing explores transformations for new applications when direct reuse is not feasible. By quantifying reuse and repurposing costs, the models help manufacturers identify sustainable lifecycle extensions that support circular economy principles. The results demonstrate that reuse and repurposing are particularly advantageous when products retain significant remaining useful life. These models serve as practical tools for industries aiming to implement resource-efficient practices that enhance both economic resilience and environmental sustainability. Furthermore, these models can be adapted for specific industrial applications and enhanced with real-world validation, providing companies with actionable insights to further refine cost-saving and environmental impact predictions. This study addresses gaps in the current literature by presenting tailored cost assessment tools for circular remanufacturing, promoting informed decision making for sustainable manufacturing.

1. Introduction

The idea of a circular economy has been prominent in the modern era of industrial evolution as a revolutionary strategy for sustainable growth [1]. Reusing and repurposing products are key tactics in this strategy because they increase resource efficiency, cut waste, and prolong product lifecycles [2,3]. This approach fundamentally challenges the traditional linear “take, make, dispose” paradigm by encouraging resource retention and recycling practices [4].

In remanufacturing, which involves taking discarded products and reassembling them to make them feel and look new, there are several commercial opportunities for reuse and repurposing [5]. Reuse involves extending a product’s life with minimal to no modifications, while repurposing gives a product a new function when its original use is no longer viable [6]. Despite clear benefits, implementing these strategies presents significant challenges, particularly in assessing their profitability and sustainability [7]. However, the existing literature often lacks comprehensive cost–benefit models capable of evaluating these elements across diverse manufacturing contexts.

Zero-defect manufacturing (ZDM) is a critical quality management approach that can enhance remanufacturing efforts, as traditional lean and Six Sigma methods often fail to meet remanufacturing demands. Given the unknown quality of parts used in remanufacturing, ZDM offers essential tools for efficient inspection and assurance, directly impacting the final costs of remanufacturing [8,9]. This quality inspection is a critical component influencing remanufacturing cost structures, highlighting the need for effective quality management approaches.

The significance of these challenges is underscored by several existing frameworks that support reuse and repurposing but often with limitations in scope and applicability. For instance, ref. [10] introduced a generalized reuse framework for systems engineering, strategically managing reuse in product development but focusing primarily on strategic management rather than cost implications. Similarly, other studies, such as those by Reddy Abbu et al. (2022) [11] and Jansen et al. (2020) [12], have provided models for cost estimation within specific industries or products, such as industrial equipment and building components. However, their applicability is limited outside these domains, as they lack adaptability for diverse product categories and manufacturing contexts.

The need for unified and adaptable cost–benefit models across industries is therefore clear. The present research addresses this gap by creating and validating cost–benefit models specifically designed to assess both economic viability and environmental sustainability of reuse and repurposing strategies in a range of manufacturing contexts. Our study aimed to answer the following questions: (1) How can financial advantages between reuse and repurposing be accurately calculated? (2) What factors primarily impact the cost effectiveness of these solutions? The research extends activity-based cost techniques to cover both end-user goods and industrial equipment, thereby allowing for comprehensive evaluations of financial and ecological impacts.

This paper is structured as follows: Section 2 reviews the state of the art in reuse and repurposing, identifying knowledge gaps and highlighting significant contributions to set the groundwork for the study. Section 3 details the development of our cost–benefit models, including data sources, analytical methods, and model frameworks, ensuring transparency and reproducibility. In Section 4, we present our findings, providing comparative analysis and quantitative evaluations of reuse and repurposing strategies. Section 5 elaborates on practical implications, limitations, and potential applications of our findings. Finally, Section 6 summarizes the key contributions of the cost–benefit models for sustainable manufacturing, emphasizing the importance of reuse and repurposing solutions for resource efficiency and environmental sustainability.

In this study, we investigate why there is no single, flexible cost–benefit model that simultaneously takes into account both environmental and economic costs of different reuse and repurposing strategies. Unlike other models that only concentrate on a few industries or sustainability metrics, our framework can be used in a wide range of manufacturing situations. It is modular and can be used in more situations. With this contribution, businesses can use data-driven tools to adopt circular economy strategies.

2. State of the Art

Reuse and repurposing have become prominent concepts in remanufacturing, driving significant advances in sustainable practices across multiple industries. Numerous frameworks and models have been developed to assess the economic and environmental feasibility of these activities, emphasizing their role in circular economy applications. However, despite considerable progress, existing models often lack comprehensive insights into both economic and sustainability metrics, especially for generalizable applications across diverse product categories. This section reviews the latest research, with a focus on identifying gaps and limitations in current models that our study aimed to address.

Ref. [13] introduced a generalized reuse framework for systems engineering, addressing the strategic management of reuse in product development. This framework distinguishes between development with reuse (DWR) and development for reuse (DFR), providing a taxonomic definition and decision processes for each. The framework’s application to the constructive systems engineering cost model (COSYSMO) illustrates its practical utility in quantifying the economic impact of reuse through case scenarios. While this model effectively manages strategic reuse in systems engineering, it lacks a detailed focus on cost–benefit implications for sustainability, highlighting a need for broader application across diverse manufacturing contexts.

Life extension of industrial equipment in smart manufacturing is presented as a critical aspect, and special focus should be given [10]. One study presented a cost estimation model combining activity-based costing (ABC) and expert opinions to determine the best life extension strategy, such as remanufacturing, refurbishment, or repair. Implemented in a VBA-based Excel platform, their model demonstrates the practicality of using ABC to benchmark and refine cost estimates through expert input, ultimately aiding decision making in industrial equipment maintenance. However, this model’s applicability is limited to industrial equipment, leaving room for a more comprehensive approach that could address varied product types within broader manufacturing industries [10].

Another study developed a general cost model for remanufacturing, addressing the lack of comprehensive cost models in the literature. This model, based on activity-based costing and performance-based cost estimation, monitors the costs of each activity and the performance changes, providing insights into the cost implications of remanufacturing processes. This approach aids in understanding the major costs involved and supports decision making for remanufacturing strategies. Despite its contributions, this model is largely limited to remanufacturing scenarios and does not fully encompass broader reuse and repurposing applications across industries [11].

Some studies have introduced a circular economy–life cycle cost (CE-LCC) model for building components [12]. This model adapts traditional life cycle cost estimation techniques to meet the requirements of circular economy products. It considers multiple use cycles and post-use processes, providing practical information to stakeholders and aligning with life cycle assessment (LCA). The model’s application to the circular kitchen (CIK) case demonstrates its capability to compare the economic competitiveness of different circular product variants, highlighting the economic advantages of flexible, reusable components. This model, however, is specific to building components, underscoring the need for versatile frameworks that can apply to a range of product types and manufacturing sectors [12].

Similarly, another study conducted a cost–benefit analysis of downstream applications for retired electric vehicle (EV) batteries [14]. Their study explored the economic implications of reusing, repurposing, and recycling EV batteries under various scenarios. By evaluating these strategies within the context of national policies and global market conditions, the study provides valuable insights into the growing market potential for retired EV batteries and the economic viability of different reuse and repurposing applications. This research illustrates the importance of analyzing reuse and repurposing within specific industrial contexts but also points to the complexity of generalizing such models across industries [14].

When analyzing the key strategies in industry for implementing circular economy principles, focusing on remanufacturing and beneficial reuse is an important topic [15]. One study highlighted the importance of waste reduction and material efficiency, supported by initiatives like the DOE’s Better Buildings Better Plants Program. The benefits of circular economy techniques for the environment and the economy were emphasized in this study, especially with regard to lowering industrial waste and advancing sustainable manufacturing. However, while this research provides valuable industry-specific insights, it lacks a detailed cost analysis framework applicable to broader reuse and repurposing contexts.

Other authors examined Tesla’s circular economy approach for recycling, reducing, reusing, repurposing, and recovering batteries [16]. The research described Tesla’s cutting-edge strategies and their effects on cost and sustainability, including the creation of the 4680 tab-less cobalt-free battery. Tesla is a prime example of how circular economy concepts are applied in the automobile sector by prolonging the lifecycle of batteries through reusing them for household appliances. While Naor’s study highlighted effective reuse within a specific industry, a generalized approach to other sectors is still missing [16].

Other authors have proposed a practical guideline based on life cycle costing (LCC) to help companies select and implement circular measures. Their guideline directs companies towards high-ranking circular economy strategies and uses LCC to assess profitability and material circularity. Through case studies, the authors demonstrate how LCC can guide companies in making informed decisions about circular measures, emphasizing the importance of considering labor and material costs in profitability assessments. This approach provides foundational insights into LCC but falls short of offering a unified framework that includes broader cost–benefit considerations across varied manufacturing environments [17].

Another study applied full cost accounting (FCA) to municipal waste recyclables, exploring cost-efficient and profitable approaches for sustainable waste management. Their study designs an integrated framework for the pay-as-you-throw (PAYT) pricing model, optimizing municipal waste management and promoting economic, environmental, and social benefits. This research provides valuable insights for policymakers and waste managers in adopting cost-effective recycling strategies. While focused on waste management, this study provides a useful perspective for understanding cost accounting in circular applications, although it is not directly applicable to product reuse and repurposing in manufacturing sectors [18].

A recent study developed a machine learning-based methodology for building maintenance cost estimation within a circular economy framework [19]. This approach improves the accuracy of cost estimates and reduces maintenance resource waste. The study demonstrated the versatility of the methodology in various applications, such as anomaly detection and cost validation, supporting the transition to a circular economy in the building industry. However, the focus on maintenance cost alone highlights the need for comprehensive models that address both economic and environmental metrics across reuse and repurposing practices [19].

The reviewed literature highlights a variety of approaches and strategies used to improve the economic and environmental sustainability of reuse and repurposing practices across industries. These studies, which range from strategic frameworks and cost models to practical guidelines and case studies, help to deepen our understanding of the complexities and benefits of circular economy principles.

Nonetheless, previous research, including [11,12], has frequently demonstrated a lack of adaptability across various products, failing to comprehensively integrate both economic and environmental dimensions. Although numerous models tackle reuse and repurposing in particular contexts, including industrial equipment, building components, and circular economy initiatives [11,12,13,14,15], their scope remains constrained. The present research addresses these deficiencies by presenting a generalized, modular framework that facilitates an extensive analysis of reuse and repurposing strategies across various contexts, marking a substantial improvement over previous efforts.

3. Reuse and Repurpose Cost–Benefit Model

In theory, the concept of reuse or repurposing seems ideal for achieving sustainability; however, this is not true in all cases. Building on our findings from the literature review, there is no existing model that effectively evaluates the feasibility, cost effectiveness, or sustainability of implementing reuse or repurposing in a broad array of applications [20,21]. In order to build the model, a clear understanding of the differences between the two approaches must first be established. In the case of reuse, a product is reused as is, with some key components being maintained or upgraded without causing the product to lose its original functionality. In the repurpose approach, the product cannot serve its purpose, or it is not economical to reuse it. Therefore, it is either used for other purposes if it is a single-component product, or most commonly, it is disassembled, and its components are reused individually. Since there are critical differences between reuse and repurpose, two individual cost–benefit models were developed: one for each case (reuse and repurposing).

The key metric that controls whether to reuse, repurpose, or simply recycle a product is the remaining useful life (RUL) of the product versus the cost that arises for its reuse or repurposing and its remaining value and recycling percentage. For consistency and broad application, we define “product” to include both end-user products and industrial equipment, ensuring a model that is adaptable across industries. Figure 1 illustrates three different product profiles that demonstrate different characteristics. Each profile represents a unique cost–benefit scenario, where reuse cost trends vary based on RUL and remaining value (shown in percentages of the new product cost (NPC)). These three profiles can fit the majority of products, with the only differentiation being the exact numbers of the different curves [22]. The purpose of Figure 1 is to demonstrate different trends and identify dependencies between each of the three individual lines in each chart. The naming of each profile arises from the shape of the cost to reuse the product (blue line). There are three profiles: exponential, linear, and logarithmic. The other two metrics are evaluated according to these profiles. The red line demonstrates the remaining value of the product according to the RUL and has opposite behavior to the reuse cost. The green line presents the amount of material that is taken off the product, has been replaced, and is going to be recycled. The recycling curve follows the same trend as the reuse cost. Furthermore, the reuse cost can go beyond 100% because it has been shown that trying to repair or maintain a product with very little RUL can be significantly more costly than making a new one. Therefore, the goal of the proposed model is to present the key metric that should be calculated in order to perform a cost–benefit analysis to decide where reuse stops being efficient and where repurposing is required.

To develop the cost–benefit model, we dissected each step in greater detail, comparing reuse and repurposing processes and highlighting any differences in required resources (see Figure 2). We also identified the connections between the two strategies. Figure 2 illustrates the common processes involved in both strategies as well as the individual steps for implementing reuse and repurposing. The common steps are the initial inspection of the product to identify its RUL and decide the future course. When there is significant RUL left, reuse is typically the most sustainable approach. The significance of RUL is defined later in this section.

The reuse process implies that the same product will be used again with some maintenance or upgrades. This will require the replacement or maintenance of some components in order to increase the overall RUL of the product. The replaced components are sent for recycling at this stage. Repurposing is more complex and requires more resources than reuse in most cases. After the initial inspection, the product is disassembled to further examine the RUL of each component and decide the future use of each component. Once a component has less RUL than a certain threshold, it is sent for recycling; otherwise, the components can be re-entered into the market as products, spare parts, parts of a new product, or a new product of the same type as before. The different blocks in Figure 2 represent the different costs involved in each case. This model assumes that partial disassembly costs are negligible, as repurposing typically entails component-level inspection and replacement only, which is common in industry.

The cost–benefit model for each case consists of two parts: one calculating the actual reuse cost and the other calculating the reuse benefits.

Table 1. Reuse and repurpose models abbreviation list.

RUCBM	Reuse Cost–Benefit Model	RPCBM	Repurpose Cost–Benefit Model
NCC	New component cost	RPC	Repurpose cost
IC,prod	Product inspection cost	IC,comp	Component inspection cost
RUB	Reuse benefits	DASC	Disassembly cost
RUC	Reuse cost	MACC	Component maintenance
RCCC	Component recycle cost	RPB	Repurpose benefit
MACP	Product maintenance cost	NPC	New product cost
M	Number of components in a product	RCPC	Product recycle cost

presents the different abbreviations used for the two models, shown in Equations (1) and (2) for reuse and repurposing, respectively. For both models, we assume that the company already has the equipment and procedures to implement reuse and repurposing strategies. The reuse cost comprises four parts: the cost arising from the initial inspection of the product and RUL assessment; the maintenance cost required to increase the RUL and make the product viable for market re-entry; the cost of new components or consumables required for maintenance; and the cost that is offset by recycling the old consumables or components. The second part of Equation (1) represents the cost savings the company gains by implementing reuse for a specific product. To calculate this, we consider what would occur if the product was not reused. If not reused, the product would be recycled, requiring the creation of a new product of the same type, which incurs an NPC cost, and the recycling of the entire old product. We clarify here that PrComp refers to the cost distribution between the materials and manufacturing costs of the product. This ensures the model’s applicability across various industry sectors. At this point, it should be mentioned that the implementation of the reuse or repurpose strategy has the goal of not only reducing costs and exploiting 100% of the remaining useful life of a product or a component but also reducing the waste and the different emissions. Therefore, in the costs presented in Table 1, those aspects are included.

$$ReuseCostModel=\left\{\begin{array}{c}RUC=I_{C,prod}+MAPC+NCC-RCCC\\ RUB=NPC-RUC-RCPC\end{array}\right.$$

(1)

$$RepurposeCostModel=\left\{\begin{array}{c}RPC=I_{C,prod}+DASC+{\displaystyle \sum _i^M}(I_{C,comp}+{MACC}_i+{NCC}_i-{\mathrm{R}\mathrm{C}\mathrm{C}\mathrm{C}}_i)\\ RPB={\displaystyle \sum _{i=1}^M}\left({\mathrm{N}\mathrm{C}\mathrm{C}}_{ i}-{RPC}_i-{RCPC}_i\right)\end{array}\right.$$

(2)

The reliability of the model can be increased by using Monte Carlo simulations to lower input data uncertainties. Although not used in our current study, this approach is recommended for further research to enhance variability assessment and reinforce the accuracy of cost–benefit estimates. We have further clarified that in scenarios where fixed applications for disassembled components are assumed, this represents the standard industry practice of matching parts to functions with maximum residual utility, justifying the model’s application assumptions. Additionally, the reuse benefit (RUB) and repurpose benefit (RPB) equations offer criteria for each model. In cases where both RUB and RPB exceed zero, the model advises a decision based on the highest benefit.

As stated before, certain thresholds must be met for reuse and repurpose strategies to be efficient. Equation (3) confirms that reuse is efficient if RUB is positive, meaning reuse costs are lower than NPC. Similarly, Equation (4) confirms repurposing efficiency, and Equation (5) establishes a relative threshold where repurposing becomes more beneficial than reuse. This comparison empowers industries to make informed decisions based on financial efficiency and sustainability.

$$RUB>0$$

(3)

$$RPB>0$$

(4)

$$RPB>RUB$$

(5)

In conclusion, our model’s two-part structure addresses critical industry needs for evaluating reuse and repurposing from both cost and benefit perspectives. By allowing adaptability to diverse product types, the model fills a research gap for unified, comprehensive cost assessments, providing an adaptable decision-making framework.

4. Analysis of the Proposed Cost–Benefit Model

In this section, we further analyze the proposed cost–benefit model, focusing on explaining each parameter in detail. We aim to visualize the reuse model, as the repurpose model’s complexity varies significantly based on the product and its components. The repurposing strategy depends on the product under investigation, how many components are repurposed, and how those repurposed components are used. This approach allows flexibility in adapting to various types of products and their unique reuse or repurposing potential.

In general, the cost of each product is composed of two elements: the cost of materials/components and the cost of manufacturing.

Table 2. Product composition.

Composition	1	2	3	4	5	6	7	8	9
Material/components	10%	20%	30%	40%	50%	60%	70%	80%	90%
Manufacturing	90%	80%	70%	60%	50%	40%	30%	20%	10%

presents the different sets for the composition of the product cost. Here, PrComp refers to the percentage distribution between material/component costs and manufacturing costs, which vary significantly across different types of products. Some of these sets are used later in this section to plot example scenarios. This table (Table 2) also demonstrates that, depending on the composition of each product, a different circularity strategy will be followed.

The table clarifies the variable nature of product composition and the cost distribution, which can influence the choice of reuse or repurposing strategy.

The following equations analyze the different terms in the reuse cost–benefit model in relation to the new product cost (NPC). In this way, the equations are simplified, creating a generic set of graphs illustrating a solution space for reusing products. In the equations, PrComp represents the percentage of total product cost that corresponds to materials, while x, y, and w are coefficients representing various cost percentages. For instance, x shows the percentage of money gained by recycling the material of the components (set between [0, 0.3] as a realistic range).

$$NCC=PrComp\times NPC\times (1-ValueCurve\left(RUL\right))$$

(6)

$$RCCC=x\times PrComp\times NPC\times (1-ValueCurve\left(RUL\right))$$

(7)

$$RCCC=x\times PrComp\times NPC$$

(8)

$$I_{C,prod}=y\times NPC$$

(9)

$$MAPC=w\times \left(1-PrComp\right)\times NPC\times (1-ValueCurve\left(RUL\right))$$

(10)

$$RUB=NPC\times \left(1-y-w+PrComp\times (w+\left(1-x\right)\times ValueCurve\left(RUL\right)-1)\right)$$

(11)

Assuming the new product cost (NPC) is normalized to 1, the resulting reuse benefit (RUB) becomes a percentage that demonstrates the potential benefit of reusing the product. For the variables y, w, and x, we assigned random values within a range [0.001, 0.4] to simulate various scenarios. Using these equations, we calculated solution spaces for Profiles 1 and 3 (see Figure 3 and Figure 4), plotting values across a remaining useful life (RUL) range of [0.1, 0.9].

The two profiles exhibit distinct shapes in their resulting graphs due to differing product profiles. Additionally, it is observed that parameters y, w, and x do not alter the shape of the graphs but increase or decrease the benefit for reuse.

In the first set of graphs, where parameters x, y, and w are set at a low value of 0.1, the developed cost–benefit model consistently shows a positive reuse benefit, as the benefit value never becomes negative (Figure 5 and Figure 6). In scenarios with more realistic values assigned to cost–benefit model parameters, however, the benefit can turn negative, making reuse a less favorable option. As expected, the variable x, which defines the money retrieved from recycling relative to the initial value, positively affects the reuse benefit, while higher values of y and w, representing inspection and maintenance costs, reduce the benefits of reuse.

In summary, this analysis demonstrates the flexibility of the reuse model under different product compositions and cost scenarios. The x, y, and w parameters offer a structured way to simulate scenarios, where reuse proves beneficial or less efficient depending on recycling gains and maintenance costs.

5. Discussion

The current section examines the implications, constraints, and potential applications of the proposed cost–benefit models for reuse and repurposing strategies. This section aims to provide a thorough understanding of how these models might support decision-making processes in the industrial sector by analyzing both financial and ecological effects.

Our research work adds to the body of knowledge already in use by providing a detailed cost–benefit model fit for many production settings. Unlike past models, which were usually limited to some sectors, our model is flexible and addresses environmental and economic impact issues over a larger spectrum of scenarios. Its adaptability makes it an invaluable resource for decision makers seeking to implement circular economy principles.

• Economic Viability: The reuse and repurposing cost–benefit models offer a comprehensive framework for estimating the financial benefits of extending product lifecycles. By considering factors such as remaining usable life (RUL), maintenance costs, and recycling gains, businesses can determine whether reuse, repurposing, or recycling is the most economically viable option. The models indicate that reuse is often more cost effective when RUL is significant, while repurposing is more suitable when RUL is limited, and the financial benefits of component disassembly and reuse outweigh those of continued use. This flexibility allows companies to make informed decisions based on specific product conditions and expected lifespan;
• Environmental Impact: The cost–benefit models also underscore the environmental advantages of reuse and repurposing. These strategies not only reduce waste and minimize raw material demand but also lower carbon emissions, slowing environmental degradation. By highlighting the importance of recycling and repurposing parts, the models emphasize increased resource efficiency, which contributes to a circular economy. However, it is essential to note that while the model indicates environmental benefits through reduced raw material needs, it does not account directly for emissions or specific environmental metrics. Therefore, future iterations of the model could integrate environmental impact factors such as emission intensity to enhance its utility for sustainability assessments.

While these models provide valuable insights, several limitations are acknowledged:

• Assumptions and Simplifications: Validating the value curve across various product categories is essential to confirm the model’s robustness and practical applicability. This study is confined to theoretical modeling; subsequent research should focus on integrating empirical validation with real-world data to improve the model’s adaptability and precision. The models rely on certain assumptions, such as the availability of tools and processes for recycling and reusing materials. These assumptions may not be universally applicable, particularly for small- and medium-sized enterprises (SMEs) that may lack the required infrastructure. Additionally, some simplifications, such as uniform treatment of disassembly and inspection costs, might overlook complexities encountered in practical applications. Future research should aim to refine these assumptions, particularly by differentiating costs associated with specific processes in different industrial contexts. Including stochastic changes in remaining useful life (RUL) and time-dependent market cost fluctuations will help the model be much more relevant in practical situations. Though these components are not included into the current structure, they represent interesting chances for next studies to better match the model with pragmatic industrial environments. The present study emphasizes a static modular framework; however, the integration of differential equations to represent time-dependent alterations in remaining useful life (RUL) and cost fluctuations offers a potential avenue for future model enhancements. This improvement would enable a more dynamic depiction of real-world situations, capturing temporal changes in essential parameters;
• Data Availability: The accuracy of the cost–benefit models is highly dependent on data availability and quality. In cases where detailed data on RUL, recycling returns, or maintenance expenses are lacking, the model’s predictions may be less precise. Improved data collection techniques and the use of reliable datasets are essential for enhancing model reliability. To address this limitation, digital product passports [23] could be integrated, offering real-time access to accurate RUL data and lifecycle information, thereby improving the model’s predictions and applicability;
• Industry-Specific Variations: The models’ applicability may vary across sectors and product categories. Although the models offer a general framework, industry-specific variations in product design, expected lifespan, and market factors can influence model outcomes. Customizing the model for individual industries by incorporating these factors could enhance accuracy and relevance for specific contexts. The addition of industry-specific parameters would make the model adaptable to a wider range of product types, enabling companies to tailor it to their needs.

Applications of the Proposed Models:

There can be problems with implementing reuse and repurposing strategies depending on the industry. Considering industries with strict quality standards, like medical products and aircraft, for instance, reusing and repurposing are challenging. For this same reason, it is more difficult for industries like consumer electronics that lose technology quickly to use these strategies without having to pay a lot to adapt. In high-productivity settings of manufacturing, the need to cut down on down-time and keep throughput may make reuse and repurposing even less useful. By addressing these issues that are unique to the industry, the framework we proposed shows that it is flexible and points out times when more thought might be needed. The proposed framework will have significant impacts on society. It will help with global efforts to be sustainable by encouraging people to use resources more efficiently and lowering the damage that they do to the environment. This study supports the Sustainable Development Goals (SDGs) by helping businesses use circular economy strategies. Besides being useful in industry, the findings of our study can also help communities and groups in changing their approaches to be more environmentally friendly. This can lead to a shift in culture toward preserving resources and betterment of care of the environment for the long term.

The cost–benefit models developed in this study offer numerous potential applications across different sectors:

• Strategic Decision Making: As a tool for lifecycle management, the models enable businesses to make strategic choices about production processes, product design, and investment in sustainable practices. Evaluating the financial and environmental impact of reuse and repurposing options can guide companies toward more sustainable production and resource allocation. These models can also serve as a roadmap for investments, assisting companies in efficiently channeling resources into circular economy projects;
• Policy Development: The insights derived from these cost–benefit models can support policymakers in developing regulations and incentives that encourage reuse and repurposing. By identifying economic and environmental advantages, governments can set regulations that promote circular economy practices, such as tax benefits for reuse initiatives or recycling mandates for certain products. This approach aligns with broader sustainability goals, encouraging businesses to adopt circular principles;
• Educational Tools: For institutions focused on circular economy and sustainable manufacturing, these models serve as valuable teaching resources. Integrating them into educational programs allows students to gain practical knowledge of reuse and repurposing strategies. Educators can use the models to demonstrate real-world applications, preparing students to apply circular economy principles in future industry roles.

Future Research Directions:

Empirical validation of the value curve represents a key avenue for future research. Conducting real-world studies across specific product categories will strengthen the model’s reliability and enable its broader implementation in diverse industrial contexts. Further research is necessary to deepen understanding and improve the practical application of these cost–benefit models. Integrating advanced technologies such as artificial intelligence, machine learning, and the Internet of Things could enhance model accuracy by utilizing real-time data. These technologies can improve decision making through predictive capabilities and automated data analysis, increasing the model’s relevance in dynamic industrial environments. Additionally, incorporating lifecycle assessment (LCA) into the models could offer a holistic view of both economic and environmental impacts, enabling a more comprehensive evaluation of reuse and repurposing strategies.

To better serve specific industries, future versions of the model should consider variations in product characteristics, market conditions, and regulatory requirements. By tailoring the model to align with industry-specific features, it can be adapted to a broader range of applications, ultimately supporting a wider transition to sustainable manufacturing.

In conclusion, the cost–benefit models for reuse and repurposing developed in this study provide essential tools for evaluating the sustainability of these circular economy strategies from economic and environmental perspectives. While the current models offer a foundational approach, ongoing development and refinement can expand their utility across diverse industrial sectors. By addressing current limitations and exploring potential improvements, these models have the potential to play a pivotal role in promoting sustainable manufacturing practices and supporting global circular economy goals.

These factors, however, are critical considerations that we plan to incorporate in future work:

• Quality Standards: Some industries, such as aerospace, medical devices, and automotive sectors, operate under stringent quality requirements that pose significant challenges for adopting reuse and repurposing strategies. Future iterations of the framework could include metrics for assessing and ensuring quality compliance in circular economy applications;
• Productivity Demands: In high-productivity environments, downtime for implementing reuse or repurposing may reduce feasibility. Addressing this challenge, the framework can be enhanced to assess the impacts of reuse strategies on productivity and throughput;
• Obsolescence: Rapid technological advancements, particularly in consumer electronics, limit the applicability of reuse and repurposing strategies. Future developments of the framework could integrate market dynamics and predictive algorithms to assess obsolescence risks more effectively.

6. Conclusions

This study successfully developed and validated comprehensive cost–benefit models for evaluating the sustainability and feasibility of reuse and repurposing strategies within the circular economy framework. Our findings indicate that the reuse model is effective in prolonging product lifecycles through systematic maintenance and component replacement, while the repurpose model reconfigures disassembled products to meet new functional requirements. Both models provide a quantitative framework that allows manufacturers to assess the financial benefits and environmental implications of each strategy, underscoring the specific conditions under which each is most advantageous.

These cost–benefit models offer valuable insights for manufacturing firms by guiding decisions on product lifecycle management. By weighing economic and environmental trade-offs, companies can adopt production methods that align more closely with sustainable development goals. This research fills a critical gap in the literature, presenting a structured approach for evaluating the financial and ecological impacts of lifecycle extension practices, particularly reuse and repurposing.

Beyond their immediate applications, these models also support the broader adoption of circular economy principles by promoting economic resilience and environmental sustainability. This study connects the application of reuse and repurposing strategies to Sustainable Development Goals, especially those related to responsible consumption and production and climate action. The quantitative assessment provided by the models enables companies to align with these goals through practical, data-driven decisions that advance sustainability.

Our findings also have pragmatic implications across multiple industries. Cost–benefit models empower companies to determine the feasibility of reuse or repurposing existing products for new markets, assisting in resource allocation and strategic planning. Additionally, the insights gained from this research can be leveraged to inform educational initiatives and policy development focused on sustainable manufacturing and circular economy concepts.

Future research should focus on enhancing data collection methods, incorporating advanced technologies such as machine learning and artificial intelligence, and refining the models for industry-specific applications. Integrating these technologies can improve model accuracy by enabling real-time data analysis and predictive capabilities, thus supporting dynamic decision making in complex industrial contexts. Moreover, while this model primarily emphasizes cost–benefit analysis, future iterations could enhance its applicability by incorporating environmental impact metrics, addressing reviewers’ suggestions for a more comprehensive sustainability assessment. To strengthen practical validation, the model could also be tested in real-world scenarios or through case studies across different industries, enabling further refinement and adaptability.

In conclusion, this study provides a robust framework for evaluating reuse and repurposing strategies in remanufacturing from both economic and environmental perspectives. The developed cost–benefit models serve as valuable tools for businesses, policymakers, and educators alike, helping drive the transition toward a more sustainable and circular economy.