A design for EoL approach and metrics to favour closed-loop scenarios for products

Abstract

Recently, environmentally conscious design and extended producer responsibility have become key aspects for companies that need to develop products that are sustainable along their whole life cycle. Design for End of Life (EoL) is a strategy that aims to reduce landfill waste through the implementation of closed-loop product life cycles. It is important to consider disassembly and EoL scenario management as early as the design phase. For these reasons, this paper presents an approach to help designers in the evaluation and subsequent improvement in product EoL performance. The method is based on four innovative EoL indices that compare different EoL scenarios for each product component. In this way, the designer can modify the product structure or the liaisons to maximise the reuse and remanufacture of components as well as material recycling. The presented case studies confirm the validity of the approach in helping designers during the redesign phase of goods and products to reduce the quantity of materials and industrial wastes sent to landfill.

Keywords:

• Design for EoL
• EoL management
• EoL indices
• closed-loop scenarios

Introduction

In modern society, environmental problems are becoming some of the most important and complex issues that need to be efficiently faced to guarantee a liveable planet for future generations. In this context, waste management is a crucial aspect that needs to be considered because of the rapid growth of the worldwide population. Consumers, currently, dispose products at a higher rate due to a general improvement in worldwide economic conditions and the increasing pace of technology evolution. The demand for new products causes relevant consumption of economic and environmental resources necessary to manage their life cycle.

Considering this framework, environmental awareness is becoming a fundamental product design driver for a wide number of industries, through both legislative issues and market pressure. For example, in recent years, the EU (European Union) has issued directives on topics such as the disposal of electronic and electrical products and equipment as well as restrictions on the use of hazardous substances, which force manufacturers to respect environmental issues (European Parliament and Council 2000, 2002, 2012). Moreover, in certain geographical areas, such as northern Europe, consumers are becoming very exacting, and they are increasingly requiring eco-friendly products. For these reasons, designers are pushed to change the vision of products, considering not only the costs and the impacts related to material selection and manufacturing activities but also the whole product lifespan, including End of Life (EoL). An accurate definition of the EoL scenario in the early design stage is emerging as a key eco-design strategy for companies, which often must assume responsibility for ‘retiring’ the product at the end of its life (Rose and Ishii 1999). EoL is certainly the most critical phase of the entire life cycle because it is the moment furthest from product conception. However, it is a strategic phase because it represents the joining link to close the product life cycle. Thus, it is very important to consider these aspects during the design stage when designers can change product features, such as materials or geometries. Only in this way, the products can be configured to have closed-loop scenarios, which allow the reintroduction of parts or materials into the productive chain (reuse of the entire product or some components, remanufacture of components or recycling of materials). On the other hand, two alternative open-loop EoL scenarios can be considered: incineration, which only recovers energy from the combustion and reduces the original waste volume, or landfill, which is the worst scenario considering the environmental hierarchy (Fukushige, Yamamoto, and Umeda 2012). Furthermore, through the management of EoL strategies, the cost of product disposal could be reduced, increasing the revenues (Cappelli et al. 2007). Figure 1 describes both the closed-loop and open-loop scenarios with the involved stakeholders.

Figure 1. Closed-loop (green) vs. open-loop (black) scenarios.

The idea behind this paper is to define a quantitative approach for the evaluation of the most convenient EoL scenarios for product components, considering both environmental and economic aspects. The main novelty of this approach is represented by the definition of three EoL indices, one for each EoL closed-loop scenario (reuse, remanufacture and recycling). In addition, to have a more comprehensive view, one index for the open-loop scenario (incineration with energy recovery) has been defined. This latter is a useful metric whenever closed-loop scenarios are not economically feasible. The proposed indices are able to drive the design strategies for an optimised EoL product management and to take into account several cost and revenue items (e.g. disassembly cost, economic value of materials and/or second life parts and energy savings). These items are connected to the relative EoL scenario and are well known by the actors involved in the reverse supply chain (see Figure 1). The main step beyond the current state of the art is the possibility to create a relationship between the design choices and the feasibility assessment of reuse, remanufacture and recycling options. The final objective is to encourage the optimisation of product EoL performances, through the maximisation of materials and components with a closed-loop life cycle. This approach leads companies to design/re-design ‘green’ and ‘sustainable’ products and, in addition, to increase revenues from the correct management of EoL industrial wastes.

The paper is structured as follows: after this introduction, which explains the overall context, the next section presents a critical review of the main research items concerning design for disassembly (DfD), design for EoL and EoL management. Then, the core of the paper is the description of the four EoL indices, with the relative parameters and explanations on how to use and interpret the results calculated using the proposed method. Different case studies are described in detail, and finally, advantages, drawbacks and remarks of the presented approach are discussed in the last section.

Literature review on de-manufacturing and EoL management

This section describes the related research activities and the current state of the art about the design methodologies focused on de-manufacturing, disassembly and EoL management.

De-manufacturing and DfD

Currently, de-manufacturing is becoming an important strategy and a new sustainable business model for the EoL management of industrial products, which reduces environmental footprints while increasing corporate profits (Rizzi et al. 2013). De-manufacturing is a reversal process in which a product is separated into its components (non-destructive disassembly) or constituent materials (destructive disassembly) by manual or automatic operations (Mule 2012). The purpose of de-manufacturing operations is the fast and efficient separation of detailed product fractions and boosting EoL closed-loop scenarios such as reuse, remanufacture and recycling (Duflou et al. 2008). Therefore, a key role in the de-manufacturing process is played by product disassembly.

DfD is a class of target design methodologies that gives a set of guidelines to help engineers and designers in the early phase of product design. An efficient product disassembly allows the easy separation of components for product maintenance and/or EoL treatments (Dewhurst 1993; Takeuchi and Saitou 2006). DfD makes the de-manufacturing plans of goods and products more efficient, affecting EoL choices and strategies (Veerakamolmal and Gupta 2000).

Several studies address product disassembly for EoL from different perspectives. For example, the concept of disassembly depth was introduced by Dewhurst (1993) to establish the effective economic convenience for disassembly operations through the calculation of a disassembly index. On the other hand, selective disassembly focuses on efficiently extrapolating data from 3D CAD models or product structures, such as the best disassembly sequence or the feasible disassembly paths that minimise the disassembly times and costs (Dini, Failli, and Santochi 2001; Kara, Pornprasitpol, and Kaebernick 2005).

Currently, active disassembly (AD) is a promising technology that facilitates de-manufacturing operations using shape memory alloys. AD is able to create reversible fasteners and connectors among specific components in the product assembly. Furthermore, AD enables the rapid, non-destructive self-disassembly of products and encourages sustainable EoL treatments (Chiodo and Ijomah 2014; Duflou et al. 2008).

Nevertheless, the key outcome of DfD analysis is the estimation of disassembly time (Germani et al. 2014). Disassembly time is one of the main drivers for the disassembly cost calculation and, consequently, for the evaluation of the economic feasibility of EoL scenarios that require disassembly (Bogue 2007).

DfD and Design for EoL are interactive and complementary design methodologies. In fact, EoL-oriented design strategies require product analysis from the disassembly viewpoint. Currently, a tangible gap in this research field is characterised by the lack of integration between the two methodologies, i.e. the lack of a concrete tool that supports design strategies. EoL indices have been developed and proposed in this work to fill this gap and make the impacts on the different EoL options measurable. EoL indices represent a useful design tool to conceive the correct product architecture and to choose the most appropriate assembly connections between components.

Design for product EoL and EoL management

Currently, product EoL and the appropriate management of industrial wastes represent key aspects for sustainable product development. Although the costs and environmental impacts of design activities do not represent a relevant contribution in the whole product life cycle assessment, decisions taken during this stage greatly affect the product performance along its life cycle (Mihelcic et al. 2008). For this reason, to reduce the amount of waste going to landfill, favouring closed-loop scenarios, products need to be appropriately designed to also consider EoL aspects (Hauschild, Jeswiet, and Alting 2004). Many studies in the literature focus on the detailed assessment and comparison of different EoL operations (Abu Bakar and Rahimifard 2008), optimisation of EoL processes (Jun et al. 2007) or even selection of the best recovery strategies during EoL (Ziout, Azab, and Atwan 2014; Cheung et al. 2015a). All of these studies only try to improve the EoL treatments of post-consumer wastes without considering the possibility of improving products as early as the design stage.

With the diffusion of the extended producer responsibility (EPR) paradigm, many companies have been obliged to pay even more attention to the EoL of their products, trying to determine the best EoL option for entire products and critical components. The development of a decision model for selecting among these different options requires the consideration of various qualitative and quantitative factors, such as environmental impact, quality, legislative factors and cost (Ilgin and Gupta 2010).

Several studies have focused on this topic. Generally, target design methodologies developed for EoL emphasise single aspects or scenarios of the product EoL. For example, design for remanufacturing focuses on methods and tools for establishing or identifying the product properties with respect to remanufacturing. In this field, Zwolinski, Lopez-Ontiveros, and Brissaud (2006) developed a computer-aided tool (REPRO2 for Remanufacturing with PROduct PROfile) to help designers incorporate remanufacturing earlier in the design phase. Their work is based on the remanufacturable product profile (RPP), a concept that embraces knowledge of both remanufacturing contexts and remanufactured product properties. Kwak and Kim (2015) proposed a method to search the optimal product design to maximise economic profit and environmental impact savings, considering initial manufacturing and EoL stages. However, they only focused on remanufacturing activities, thus neglecting other possible EoL strategies.

Another common approach is design for material recycling, which aims to increase the recyclability of products at EoL using a material compatibility charts (e.g. thermoplastic material compatibility table for recycling, metals compatibility table, and glass and ceramic compatibility table). The main limitation of this methodology is the exclusion of more environmentally friendly scenarios, such as reuse or remanufacturing. Some specific material compatibility methods exist, such as the tool proposed by Le Pochat, Bertoluci, and Froelich (2007), which facilitates the choice of plastic materials by integrating the separation ability of the current recycling routes, the compatibility of mixed plastics combinations and the quality of the secondary material product. Mathieux, Froelich, and Moszkowicz (2008) proposed a method called ReSICLED to assess product recoverability.

Regarding Design for EoL methods and tools, several studies are available in the literature. Doi et al. (2010) proposed an optimisation method to incorporate life cycle considerations into the design process, aiming to reduce the use of raw materials and to facilitate the reuse of products or their parts. Kwak and Kim (2011) highlighted the importance of modularity to configure product families that are easy to treat at the EoL, maximising the recovery of parts or materials. Gehin, Zwolinski, and Brissaud (2008) proposed a new approach to integrate EoL strategies in the early design phases, considering the evolving architecture of the product and the translation of transversal information into design criteria. Bufardi et al. (2003) proposed a multiple criteria decision aid (MCDA) method to support designers in selecting the best scenario for treating an EoL product based on their preferences and the performances of the EoL scenarios. Chan (2008) extended this proposal using a Grey Relational Analysis (GRA) to rank the EoL options under the uncertainty condition of incomplete information.

Concerning the use of a design index, only a few examples can be found in the literature. An interesting index to evaluate the efficiency of EoL treatment is described by Dewhurst (1993). Designers can use this index for evaluating the break-even point at which disassembly operations should be stopped. Beyond this point, disassembly costs are greater than revenues. Rao and Padmanabha (2010) defined an EoL scenario selection index based on the relative importance of the different EoL scenarios to evaluate and rank alternative product EoL strategies. Lee, Lu, and Song (2014) developed a more complex index methodology. Their proposed index gives aggregate values representing the design performance under available EoL options and can act as an advisor to judge available design options. However, all these approaches are also based on qualitative information and on subjective preferences, which reduce their effectiveness or limit the field of application.

The literature review indicates a lack of approaches for quantitative analysis of EoL scenarios that are able to give practical design suggestions for EoL product management. None of the metrics previously described have been developed to take into account both economic and the environmental aspects. In this context, this paper aims to overcome these limitations by defining four EoL indices based on the most common EoL scenarios for industrial products. All these indices are calculated using typical data and parameters of the required treatments (e.g. cleaning and disassembly operations, recycling treatments and refurbishment) for each EoL strategy, and this guarantees the accuracy and significance of the analyses. The proposed approach gives a quantitative indication of the most convenient EoL treatment for each product component or sub-assembly. It is well-known that, although design costs represent approximatively 10% of the total budget for a new project, decisions made at the early design stages of the product development are typically responsible for up to 80% of all the environmental and financial impacts (Maxwell and van der Vorst 2003; Pahl et al. 2007; Favi and Germani 2012; Cheung et al. 2015b). Considering EoL aspects during the early phases of the design process, designers are guided to improve their product features with the aim of increasing the amount of materials and components with a closed-loop life cycle. This is the main advantage of the proposed approach.

Method

In this section, new metrics (EoL indices) for product EoL assessment and management are introduced and the relative design methodology is described in detail. These indices are fundamental metrics for the correct EoL management of industrial products, considering the opportunities offered by new circular economy business models. (e.g. to choose the correct EoL scenario, to discard not feasible scenarios, to optimise the product design focusing on a particular EoL business model). In this way, a better EoL management for specific products and components can be achieved.

The four new indices evaluate the feasibility of each considered EoL scenario (reuse, remanufacture, recycling and incineration) to optimise the product EoL management early in the design process.

The final goal of the proposed design methodology is to improve the product sustainability by increasing the percentage of components with a closed-loop life cycle, encouraging the reuse, remanufacture and recycling scenarios. The assessment of EoL indices, together with the analysis of preferable disassembly paths, allows designers to control product sustainability in terms of economic and environmental impacts. A general framework of the proposed method is presented in Figure 2.

Figure 2. Framework of the proposed design methodology.

The proposed methodology is composed of three steps.

The first step of the method is a Disassemblability Analysis. Starting from the general product structure (e.g. a 3D CAD model), it is possible to analyse the product’s disassemblability by calculating the best disassembly sequence for a specific target component or for the overall product and the related disassembly time to minimise the de-manufacturing operations. Because the disassembly time is not stored as a product feature, it needs to be calculated through disassembly analyses and algorithms, starting from the 3D solid model and using data stored in a dedicated disassembly time database (Germani et al. 2014). The main outcome of this design step is the generation of the best disassembly sequence and, consequently, the assessment of the disassembly time, which is an essential parameter for calculating and quantifying the proposed EoL indices. As a result, the disassembly path is built with two purposes:

•	to evaluate alternative disassembly solutions for product redesign and
•	to extrapolate guidelines (disassembly report) for product dismantlers.

The second step, EoL indices Calculation, is the core of the method. The four proposed indices (see the next section for their definitions) are evaluated based on data from the previous step. The disassembly time is calculated during the first step by using a dedicated algorithm (Germani et al. 2014). Other data are automatically retrieved from the 3D CAD model (e.g. constituent materials and component weight) and/or from the PLM system (e.g. cost of the components and cost of the materials), using specific queries for data reading. All these data are used for the calculation of the four indices, using a dedicated spreadsheet.

First, the evaluation of the EoL indices is useful to allow companies to establish whether a closed-loop scenario can be conveniently implemented for the product, component or part under analysis. The most promising and ‘effective’ EoL strategy is a trade-off between different company objectives (e.g. costs and environmental aspects) and can be selected based on the following features:

•	the calculated index values;
•	the possibility to practically implement each scenario (e.g. reuse could not be implemented in some cases);
•	the long-term company strategies (e.g. environmental objectives and the time for return of investments); and
•	the environmental hierarchy of different scenarios.

The third step of the proposed method is the Re-design process. Once the EoL strategy has been established, the company defines a target value (I*) to reach with the redesign activities (both Deep and Minor re-design, as reported in Figure 2). The definition of the target value is essentially based on characteristics of the component under analysis (e.g. value of materials) and on the company objectives (e.g. business models). The target value (I*) represents the final objective to fulfil to achieve a product, component or part with a closed-loop EoL scenario.

After the definition of the EoL strategy and the specific target value (I*), the evaluation of the proposed indices helps designers to monitor whether the project fits the EoL design requirements during its development and to compare alternative solutions from both economic and environmental points of view. The gap between the target value (I*) and the value calculated for the current design solution suggests how deep the redesign process should be to reach the target. Furthermore, considering the design analysis, useful information can support the selection of materials, the assembly liaison types between components and the general product layout. It is important to emphasise that the EoL indices can be used for rapid evaluation of the design choices to increase the reusability, remanufacturability and recyclability of industrial products, but they do not represent an economic feasibility study.

Definition and interpretation of the EoL indices

A set of EoL indices has been defined to establish the best EoL strategy based on the sustainability of each EoL scenario, comparing the cost and revenues of each considered strategy. In this framework, it is possible to both evaluate the best scenario and define the efficiency gap between the current condition and the optimal or theoretical one for each scenario. This section presents the index formulas with the explanation of the related parameters as well as the indices value interpretation.

EoL parameters

Several parameters occur in the definition of EoL indices. Their values can be derived from different sources:

(Source 1)	PLM for product-related costs and other parameters;
(Source 2)	specific DBs for material-related costs and other parameters (e.g. Granta MI®, etc.);
(Source 3)	calculated data (e.g. disassembly time, disassembly cost, recycling factors, etc.); and
(Source 4)	estimated data from market surveys (i.e. dismantling centres interviews) and literature analyses.

Table 1 summarises the items (including sources) involved in each EoL scenario and counted in the related EoL indices. The priority list is given by the sustainability ranking related to the environmental benefits associated with each EoL treatment.

Table 1. List of the parameters considered in the EoL indices definitions.

EoL treatment	Costs	Revenues		Sustainability
		Direct	Indirect
Reuse (Ru)	• Reverse supply chain (CRL) – Source 4 • Selective disassembly operations (CSd) – Source 3 • Cleaning operations (CC) – Source 4	• Value of the reused part (VRe) – Source 1	• No virgin material used to produce the part (VMat) • No manufacturing operations to build up the part (VMan)	↑↑↑↑
Remanufacture (Rm)	• Reverse supply chain (CRL) – Source 4 • Selective disassembly operations (CSd) – Source 3 • Cleaning operations (CC) – Source 4 • Additional remanufacture operations (CRem) – Source 4	• Value of the remanufactured part (VRem) – Source 1	• No virgin material used to produce the part (VMat) • Value of original manufacturing operations to produce the part not necessary for remanufacture (VMan_s)	↑↑↑
Recycling (Rc)	• Reverse supply chain (CRL) – Source 4 • Destructive disassembly operations (CDd) – Source 3 • Cleaning operations (CC) – Source 4	• Value of the recycled material (VRc) – Source 2	• Energy saved by not producing virgin material (VEn)	↑↑
Incineration with energy recovery (Inc)	• Reverse supply chain (CRL) – Source 4 • Destructive disassembly operations (CDd) – Source 3	• Energy gained from combustion (VEInc) – Source 2		↑
Incineration without energy recovery	• Reverse supply chain (CRL) – Source 4 • Destructive disassembly operations (CDd) – Source 3			↓
Landfill	• Reverse supply chain (CRL) – Source 4 • Destructive disassembly operations (CDd) – Source 3			↓↓

Considering that some revenue parameters are composed of different items, the formulas used to define these revenues are reported in Table 2. All the defined parameters have been taken into account and weighted for the definitions of the EoL indices.

Table 2. List of the complex revenues determined in the formulas.

Formulas	Parameters
VMat = m * CMat	• m = Mass [kg] – Source 1 • CMat = Cost of the virgin material [€/kg] – Source 2
VMan = CMan + Ct	• CMan = Cost of the manufacture activities [€] – Source 1 • Ct = Cost of the transport phases [€] – Source 1
VEn = m * Es * Ce	• m = Mass [kg] – Source 1 • Es = Energy saved (difference between primary embodied energy and recycling energy) [MJ / kg] – Source 2 • Ce = Energy cost (industrial) [€ / MJ] – Source 1
VRc = m * Rf * CRc	• m = Mass [kg] – Source 1 • Rf = Recycling factor – Source 3 • CRc = Cost of recycled material [€ / kg] – Source 2
VEInc = m * Pc * Ce	• m = Mass [kg] – Source 1 • Pc = Heat value [MJ / kg] – Source 2 • Ce = Energy cost (industrial) [€ / MJ] – Source 1
VRe	This is a percentage of the original value of the part under analysis considering mechanical/fatigue deterioration due to use and taking into account the consumers’ lower quality perception of used parts and products (Hazen, Cegielski, and Hanna 2011).
VRem	This is a percentage of the original value of the part under analysis considering deterioration, degradation and corrosion due to the use and the overall process to refurbish the part. Furthermore, this item takes into account the consumers’ lower quality perception of used parts and products (Hazen, Cegielski, and Hanna 2011).

Index formulas

Reuse index

The Reuse index considers the possibility of a given component being reused in the same product or in similar products (Equation 1(1) ). This EoL scenario is possible only when the component’s lifetime is longer than the lifetime of the product itself.(1)

Remanufacture index

The Remanufacture index evaluates the possibility of a component being regenerated on the basis of different cost types and revenues involved in the ‘remanufacture loop’ (Equation 2(2) ). Similar to the reuse scenario, remanufacture is possible only when the component’s lifetime is longer than the lifetime of the product itself.(2)

Recycling index

The Recycling index compares the difference between the production costs for virgin materials and the revenues coming from the recycling process (Equation 3(3) ). In particular, it takes into account the energy savings resulting from the recycling process of a material and the revenues from recycled material. This index establishes the real effective opportunity in terms of energy and cost reduction.(3)

Incineration index (with energy recovery)

The Incineration index establishes whether particular combinations of materials can be directly incinerated for energy production (Equation 4(4) ). In fact, incineration is an opportunity for the EoL treatment of particular materials with high heating values or for materials that cannot be easily recycled. In this case, the components can be separated by destructive de-manufacturing techniques, and the de-manufacturing operations can be performed without special care. The time required for de-manufacturing is therefore greatly reduced.(4)

Interpretation of EoL indices

Designers aim to boost EoL closed-loop scenarios for the largest fraction of the product possible. Pursuing this aim, the designer can make clear decisions by comparing the values of these indices for each component to obtain quantitative feedbacks about the best strategy to apply. From the environmental point of view, a priority list has been set up, where reuse is the best option, followed by remanufacture, recycling and incineration for energy recovery. Landfill is the last alternative, which is selected only when all of the other strategies are not feasible or cannot generate any profit.

From the formulas presented in the previous section, it is clear that the maximum potential value for all of the indices is one, which corresponds to the optimal situation, where the cost items tend toward zero. This is also the theoretical limit for each index. Thus, the general engineering strategy should consist in trying to improve the calculated index value for a given product structure to reach the predefined threshold value (I*) and to get as close as possible to the maximum theoretical value. Different cases can arise after assessing the EoL indices:

(1)	(IEoL-Ru < 0) AND (IEoL-Rm < 0) AND (IEoL-Rc < 0)

In this case, the product or the selected component is not designed for an optimised EoL management because none of the sustainable EoL options are currently convenient. The component (or the product) requires a Deep Re-design process to significantly decrease the disassembly time or to modify the properties or the features of the component. Some examples of Deep redesign actions are reported in Table 3. Whenever the closed-loop scenarios are not economically feasible, the Incineration index (I_EoL-Inc) can be considered to find an alternative EoL solution for the component under analysis.

(2)	(0 ≤ IEoL-Ru < I*) OR (0 ≤ IEoL-Rm < I*) OR (0 ≤ IEoL-Rc < I*)

Table 3. Examples of re-design suggestions.

Design suggestion	Deep re-design activity	Minor re-design activity
To change, whenever possible, the constituent materials of the selected component	X
To change the entire product architecture and the position of the selected component in the general layout (product structure)	X
To use specific assembly methods (such as snap-fits or AD) to reduce the disassembly time for the target components	X	X
To merge components, whenever possible, with the aim to minimise the number of components and to reduce the number of assembly and disassembly operations	X
To create modular sub-assemblies which do not require further disassembly operations	X
To modify components’ geometry and shape with the purpose of facilitating handling operations during de-manufacturing	X
To reduce the number of screws and threaded elements	X	X
To locate parts with the highest value in easily accessible positions	X	X
To change positions of components in the general layout of the product structure		X
To increase product accessibility (eliminate visual and physical obstructions)		X
To avoid painting or plating parts (especially for recycling purpose)		X
To mark parts which must be firstly removed		X

In this case, the target component is currently designed to have sustainable EoL management, but the disassembly performances do not reach the expected value I*. A Minor Re-design is required to further decrease the relative costs of de-manufacturing operations and disassembly time. Some examples of Minor redesign actions are reported in Table 3.

(3)	(IEoL-Ru ≥ I*) OR (IEoL-Rm ≥ I*) OR (IEoL-Rc ≥ I*)

This is the desired situation, where one or all the EoL closed-loop scenarios can be carried out in a convenient and effective way. In general, this condition can be reached only after an iterative process of redesign activities (Deep and Minor) is able to systematically improve the performances.

It is important to note how the three EoL closed-loop alternatives have different impacts in terms of environmental sustainability and economic returns. Whenever possible, reuse and remanufacture must be encouraged by designers rather than the recycling solution due to their higher economic returns and lower environmental costs. However, reuse cannot be physically implemented with continuous changes in the geometric features of the selected component (e.g. shape or dimensions) due to marketing strategies (such as in the case of the aesthetic cover of a household appliance). On the other hand, reuse could be a good strategy to use when the component is standardised or used among different models of the same product family (such as the electric motor of a household appliance). Despite reuse being the best EoL scenario from the environmental perspective, the indices contain different cost items so that selecting this EoL scenario is affected by the economic benefit. It is worth noting that some scenarios are not always possible (N.A.); for instance, it is not easy to recycle plastic composite materials because they are made of thermosetting polymers or composite materials, such as fibre-reinforced composites (FRC).

The proposed interpretation refers to the closed-loop scenarios, but as highlighted above, reuse, remanufacture and recycling are not always possible. Therefore, when one of the closed-loop scenarios cannot be applied, the objective is to increase the incineration index value (if possible), to recover at least the energy (electrical and/or thermal) from the selected component.

Case studies

Adopting the proposed approach in a real case study can potentially lead to relevant advantages, as discussed in the previous section. Designers can easily consider all of the possible EoL scenarios as early as possible in the design phase. The accurate calculation of the disassembly time, disassembly cost and the EoL indices enables a quick evaluation of the percentage of components that can be recycled, remanufactured or reused. In this way, designers are able to modify specific product features to improve the disassemblability and, as a consequence, the sustainability of the EoL management solutions.

A preliminary test of the approach and indices validation was established for several sub-assemblies and parts for two mechatronics products:

•	the Blower support of a freestanding cooker hood and
•	the Main boiler of a professional espresso coffee machine.

The Original Design (OD) of the two products was investigated to retrieve useful data for the calculation of the proposed EoL indices (i.e. disassembly sequences, joint methods, disassembly time, components costs, materials costs, etc.). The original product designs were modified according to the indications provided by the indices evaluation. New Design (ND) was developed within this research work to demonstrate the benefits of the proposed approach in the de-manufacturing operations for component EoL management.

Redesign process of freestanding cooker hood: blower support example

A domestic cooker hood has been redesigned to improve the recyclability and re-manufacturability of different components or sub-assemblies for sustainable EoL management. In fact, environmental and economic profitability can be obtained for most of the cooker hood components and sub-assemblies.

Adopting the proposed approach, the result of the indices assessment for the original design of a cooker hood underlines that the management of sustainable EoL scenarios for the current model is not optimised. As reported in Table 4, the majority of the cooker hood is landfilled (approximately 75%), and only approximately 25% of the entire hood follows alternative EoL scenarios. A deep redesign was performed, and the following guidelines were implemented:

•	reduction in the number of components in the general product assembly to reduce the disassembly depth and the number of disassembly operations;
•	reduction in the number of different materials used in the product assembly for easy management of product EoL;
•	increasing the number of more efficient joining methods (such as snap-fits) to replace fasteners (bolts, nuts and screws) and non-removable connections (rivets and welding) to drastically reduce the disassembly time; and
•	changing the geometry, shape and layout of components to increase accessibility and handling for dismantling operators.

Table 4. Comparison between the original design (OD) and the new design (ND) of a free-standing cooker hood.

Free-standing cooker hood		OD	ND
Number of materials used		21	12
Number of components		205	82
End of life	Reuse	0%	0%
	Remanufacture	0%	11.2%
	Recycling	18.2%	39.9%
	Incineration	7.6%	9.3%
	Other (landfill, etc.)	74.2%	39.6%

A general overview of the comparison between the old and the new cooker hood versions is described in Table 4.

In general, significant product simplification was achieved in terms of reducing components and typologies of materials used in the product. Moreover, a weight reduction was observed due to substituting plastic materials for carbon steel.

From the EoL perspective, considering the new design solution, it is possible to recycle materials (approximately 40%) and remanufacture components (approximately 11%). In this way, more than 60% of the cooker hood components were developed to follow an established closed-loop life cycle. A very important result is the significant reduction in the percentage of landfill wastes for the new design compared with the old solution (approximately 75 vs. 40%). The reduction in landfill wastes for the cooker hood product is the direct consequence of increasing the components with more sustainable closed-loop EoL scenarios and the incineration rate. This aspect is fundamental to supporting worldwide policies for reducing goods waste production.

As an example, the main feature changes in the blower support sub-assembly are described. The sub-assembly has been redesigned and manufactured using only two components of the same material (polypropylene flame retardant) connected with a plastic snap-fit (Figure 3). Furthermore, considering material recycling as a possible sustainable EoL scenario, no other disassembly operations are required to separate these components.

Figure 3. Assembled (A) and disassembled (B) blower support designed and manufactured using two components of the same material (PP flame retardant).

After the redesign process, the best EoL scenario for the selected sub-assembly is recycling the constituent material (PP flame retardant). As reported in Table 5, the Recycling Index value for the Blower Support increased from 0.08 for the OD to 0.16 for the ND (see bold values in Table 5). As described in the index formulas section, some EoL scenarios are not always feasible; for instance, it is not possible to recycle thermosetting polymers or to incinerate metals. For this reason, these options are indicated in the table by ‘N.A.’ In terms of economic revenues, the estimated value calculated considering the recycling option is approximately 3.35€ for the Blower Support. On the other hand, the overall costs including disassembly costs and reverse supply chain is approximately 2.82€.

Table 5. Comparison of the original design (OD) and the new design (ND) of a Blower Support sub-assembly in a free-standing cooker hood.

	Parts	Materials	IEoL-Ru	IEoL-Rm	IEoL-Rc	IEoL-Inc
Support (OD)
	Cap	PP flame ret.	−12.74	−13.68	−7.49	−10.25
	Support ass.		−0.80	N.A.	0.08	N.A.
	Back frame	Carbon steel	−2.64	−2.83	−0.51	N.A.
	Bottom part	Carbon steel	−3.94	−3.22	−15.88	N.A.
	Front cover	Carbon steel	−3.00	−4.20	−1.38	N.A.
	Rivets	Carbon steel	N.A.	N.A.	N.A.	N.A.
Support (ND)				/
	Support ass.		−0.42	N.A.	0.16	−0.10
	Top part	PP flame ret.	−3.35	−3.73	−2.04	−2.98
	Bottom part	PP flame ret.	−1.14	−1.33	−0.17	−0.53

Redesign process of a professional espresso coffee machine: main boiler example

The professional espresso coffee machine analysed is a complex product with more than 1400 components and 37 different materials (see Table 6). One of the most important characteristics of this product is the intrinsic value of the components manufactured, starting from precious and noble metals such as copper. The proper management of EoL scenarios for this type of product could generate both environmental and economic revenues. Adopting the proposed approach, the new product design favours recycling and remanufacture as a possible sustainable method to manage the components at the EoL.

Table 6. Comparison of the original design (OD) and the new design (ND) of an espresso coffee machine.

Espresso coffee machine		OD	ND
Number of materials used		37	24
Number of components		1406	1029
End of life	Reuse	1.6%	3.1%
	Remanufacture	11.4%	25.1%
	Recycling	38.2%	54.1%
	Incineration	0.6%	1%
	Other (landfilling, etc.)	48.2%	16.7%

In general, after the redesign process, the reduction in the number of components (approximately 10% compared with the original design solution) was mostly related to the reduced use of fasteners such as bolts, nuts and screws. Moreover, the redesign process allowed levelling out the materials used for the components. In the case of the coffee machine, the EoL indices values, calculated using the proposed method, lead to a minor redesign process, where the following actions were applied:

•	reducing the total number of fasteners (bolts, nuts and screws) with an optimised distribution in the general assembly;
•	increasing the use of more efficient joining methods (such as snap-fits) to replace fasteners (bolts, nuts and screws) to reduce the disassembly time; and
•	reducing the number of different materials and adopting the same material for permanently connected components (such as welded components).

The indices improvement for the Main Boiler is described below. As reported in Table 7, the Remanufacturing index value for the Main Boiler assembly increased from 0.81 for the OD to 0.85 for the ND (see bold values in Table 7). Furthermore, an improvement in the Recycling index for the heating element was noted (from 0.10 to 0.18).

Table 7. Comparison of the original design (OD) and the new design (ND) of the Main Boiler sub-assembly in an espresso coffee machine.

	Parts	Materials	IEoL-Ru	IEoL-Rm	IEoL-Rc	IEoL-Inc
Main boiler (OD)
	Boiler assembly	Copper	0.75	0.81	0.74	N.A.
	Body	Copper	N.A.	N.A.	N.A.	N.A.
	SX cap v.0	Copper	N.A.	N.A.	N.A.	N.A.
	DX cap	Copper	N.A.	N.A.	N.A.	N.A.
	Flange	Brass	−5.03	−4.05	−5.35	N.A.
	3–8 gas connectors	Brass	−25.17	−28.56	−61.29	N.A.
	Pipe	Copper	−7.69	−7.40	−7.47	N.A.
	Heating element	Copper	−0.49	−0.38	0.10	N.A.
	T-connectors	Brass	−10.35	−11.82	−14.57	N.A.
	Elbow connectors	Brass	−16.16	−18.38	−30.14	N.A.
Main boiler (ND)				/
	Boiler assembly	Copper	0.82	0.85	0.82	N.A.
	Body	Copper	N.A.	N.A.	N.A.	N.A.
	SX cap v.1	Copper	N.A.	N.A.	N.A.	N.A.
	DX cap	Copper	N.A.	N.A.	N.A.	N.A.
	OT57 connectors	Brass	−21.03	−24.42	−45.44	N.A.
	Pipe	Copper	−6.00	−5.89	−6.98	N.A.
	Heating element	Copper	−0.18	−0.11	0.18	N.A.
	T-connectors	Brass	−8.56	−10.03	−10.61	N.A.
	Elbow connectors	Brass	−13.44	−15.66	−22.22	N.A.

Concluding remarks

This paper presents a research study dedicated to supporting the Design for EoL paradigm during early design activities. The proposed method is based on four novel EoL indices that allow companies to quantitatively measure the EoL performance of products. Each index is related to a particular EoL scenario (reuse, remanufacture, recycling and incineration with energy recovery), but all of them allow a comparison of costs and revenues to assess the possibility of practically and sustainably implementing each strategy. Through the method application, it is possible to establish the most convenient and effective EoL strategy for each component or part. Designers can rapidly assess whether the pre-defined targets have been reached and a product, component, or part can be efficiently recovered at the EoL. If the targets have not been met, a deep or minor product redesign is necessary to improve the EoL performances, from both the environmental and economic points of view.

The advantage of such an approach is given by the ability to assess the product sustainability oriented toward the EoL phase of the product life cycle during the design phase. The four presented indices allow designers to evaluate the percentage of product components with a closed-loop life cycle and to support them accordingly. The final goal is to encourage the implementation of reuse, remanufacture and recycling scenarios to recover materials from products at the EoL or to at least recover energy through incineration. The case studies demonstrate the effectiveness of the approach to select the most convenient EoL scenario for each component and part and to help the designers to reduce the quantities of components and parts with an open-loop EoL scenario during the product improvement phase. For example, as reported in the case of the cooker hood Blower Support, an improvement of approximately 50% was noted for the Recycling index (deep redesign). In addition, for the Main Boiler of an espresso coffee machine, an improvement of approximately 5% was achieved for the Remanufacturing index (minor re-design).

In the future, the proposed approach will be used to analyse new products (e.g. components of cars and engines) to test the robustness of the formulated indices. Once these indices have been completely validated, the next step will be to implement the proposed approach in a software tool that is able to automatically calculate the index values using information extracted directly from 3D models and from company repositories (e.g. PLM). This step will certainly enhance the usability of the proposed approach and its diffusion in technical design departments, making the analysis faster and automated. In addition, a great improvement could be achieved by working on the definition of a design tool to support the redesign process and linking the proposed approach with, for example, a Case-Based Reasoning tool. In this way, designers would be guided to make the most appropriate modifications of the product, taking into account disassembly guidelines and past design choices.

Notes on contributors

Claudio Favi is a researchfellow at the Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Italy. His area of research includes eco-design methods and tools, and lifecycle methodologies applied to the product design and development.

Michele Germani is a full professor of Design Tools and Methods for Industrial Engineering at the Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Italy. He currently focuses his research activities on product configuration, sustainable design and manufacturing, design to cost, design for disassembly, end of life management, product-service systems, product ergonomics and human-computer interaction technologies.

Andrea Luzi is a former research fellow at the Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Italy. His area of research mainly included tools and methods for end-of-life management and sustainable manufacturing.

Marco Mandolini is a research fellow at the Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Italy. His area of research includes ecodesign, design for X (end of life, cost and manufacturing), Total Cost of Ownership, multi-objective optimization and biomedical devices.

Marco Marconi is a research fellow at the Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, Italy. His area of research includes lifecycle assessment, ecodesign, design for disassembly, tools and methods for end-of-life management and sustainable manufacturing.

Disclosure statement

No potential conflict of interest was reported by the authors.