Traditional and modern methods of construction: comparative study of the sustainability of single-family homes

ARTICLE Traditional and modern methods of construction: Comparative study of the sustainability of single-family homes Irene Josa 1 | Albert de la Fuente 2 1 The Bartlett School of Sustainable Construction, University College London (UCL), London, UK 2 Department of Civil & Environmental Engineering, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain Correspondence Albert de la Fuente, Department of Civil & Environmental Engineering, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain. Email: [email protected] Abstract Modern construction methods, such as additive manufacturing, are aimed to enhance the efficiency and quality of construction processes while potentially reducing waste generation and material use, thus contributing to sustainability performance (SP). However, comprehensively understanding the sustainability trade-offs associated with these methods is crucial for guiding both research and practical applications toward sustainable development. This study aims at quantifying the SP of various construction methods for housing, including traditional, prefabricated, and additive manufacturing approaches. A sustainability index, integrating economic, environmental, social, and technological criteria, is utilized to assess different alternatives. Findings reveal promising aspects of 3D printing technologies, such as potential cost reductions through scale increase and process optimization, minimized material waste generation, creation of skilled employment opportunities, and enhanced construction flexibility and ease. Nevertheless, challenges persist, notably significant greenhouse gas emissions and limited supplier availability. Addressing these challenges is imperative for advancing the sustainable implementation of additive manufacturing in construction. KEYWORDS economic impact, environmental impact, housing, LCA, social impact, sustainability, sustainable development 1|INTRODUCTION The construction industry is undergoing a transformative phase with the advent of modern technologies, such as the emergence of concrete 3D printing in construction. 1,2 The ability to fabricate complex structures layer by layer is challenging traditional methods and is attracting interest due to its potential to revolutionize the construction landscape. The use of concrete 3D printing in the construction sector has been popular in different applications, including construction elements, formworks and on-site structures. 3 One particularly promising application is 3D concrete printing for houses. Pioneering projects have already demonstrated the feasibility of this technology, with structures like the world's tallest 3D-printed building in Riyadh, 4 with a height of 9.9 m. Received: 17 June 2024 Revised: 17 September 2024 Accepted: 21 October 2024 DOI: 10.1002/suco.202400802 This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. © 2024 The Author(s). Structural Concrete published by John Wiley & Sons Ltd on behalf of International Federation for Structural Concrete. Structural Concrete. 2024;1–19. wileyonlinelibrary.com/journal/suco 1 However, 3D concrete printing for houses is still in its early stages. Technical limitations remain, such as the need for reinforcement which can complicate the printing process and reduce overall efficiency. 3 Additionally, a lack of standardized regulations and the initial high costs associated with this emerging technology pose challenges for widespread adoption in the construction market. 5 As societies confront the urgent need for sustainable development, the construction sector is compelled to reassess its methods and materials. Sustainability in construction extends beyond merely environmental considerations. To ensure positive impacts and avoid unintended consequences, aholisticapproachisimperative. This necessitates a comprehensive evaluation encompassing economic efficiency, environmental impact, social implications, and technological aspects. A nuanced understanding of these dimensions can help make informed decisions that balance the need for progress with the imperative of sustainability. At the same time, traditional methods such as steel structures and in-situ concrete continue to be frequently used as they demonstrate proven reliability and economic feasibility. 6,7 In this context, and recognizing the complexity of sustainability in construction, multi-criteria evaluation methodologies are useful to integrate several parameters (e.g., economic, environmental, and social) into a single assessment. Until the present, several such methodologies have been developed, including the Integrated Value Method for the Assessment of Sustainability (MIVES). MIVES has been applied as a multiple-criteria decisionmaking tool in various fields like buildings and structures, 8–10 tunnels, 11,12 electricity generation systems, 13 and post-disaster housing management. 14 Notably, MIVES has also been employed to evaluate the sustainability of 3D-printed structures. 5 In light of the above, the objective of this study is to assess the sustainability of 3D-printed concrete housing alternatives in comparison to traditional and prefabricated construction methods. Through a multi-criteria analysis based on economic, environmental, social, and technological considerations, the article discusses the advantages and disadvantages of 3D-printed concrete housing, traditional methods, and prefabricated construction. The study's findings hold the potential to inform industry practices, guide policy decisions, and contribute to the ongoing discourse on sustainable construction practices. 2|MATERIALS AND METHODS 2.1 |MIVES The methodology employed in this study is MIVES. 15,16 MIVES is a multicriteria decision-making methodology that allows for the estimation of the sustainability index (SI) for each of the alternatives of a defined generic problem. Within this methodology, to obtain the SI for each alternative, a decision tree is developed which is usually structured in three levels—requirements, criteria, and indicators. These levels range from most generic to most specific, being the last level (i.e., indicators) the items that are quantified. Indicators are selected in such a way that they are representative of the systems assessed and independent of each other. In MIVES, indicators are then normalized using value functions, which convert indicator values into a 0-to-1 scale. These functions have five adjustable parameters that control how sensitive they are to different parts of the indicator's data distribution. The indicators commonly used for this type of sustainability analysis and decision-making processes are modeled by means of concave, convex, linear, and S-shaped curves. The function is defined by five key parameters (X min , X max ,C i ,K i ,P i ) detailed in Equation (1). Vind ¼B1exp Ki XiXmin jj Ci  Pi !"# ,ð1Þ In this equation, X min represents the minimum value possible for the indicators being evaluated; X i refers to the specific value of the indicator being assessed; C i is a parameter that approximates the x-coordinate (abscissa) of the function's inflection point; K i is a value that influences the function's behavior near the inflection point, tending toward a specific value; and P i is a “shape factor” that determines the curve's shape. It is less than 1 for concave curves, greater than 1 for convex, equal to 1 for linear, and has a more complex behavior for S-shapes (see Reference [16]). Lastly, the parameter B helps normalize the indicator value within the 0-to-1 range for the final output, as shown in Equation (2). B¼1exp Ki Xmax Xmin jj Ci  Pi !"# 1 :ð2Þ Once indicators have been normalized, each branch of the tree is aggregated using weights. 2.2 |Decision-making model The three essential requirements commonly associated with sustainability are economic, environmental, and social impacts. In the case of the present study, in addition to these three aspects, the technological component is also considered to integrate and consider aspects related to innovation, flexibility, and other relevant 2JOSA and DE LA FUENTE 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License factors associated with each technology that impact decision-making. Note that this approach has been recommended in cases where technologies assessed are newly developed or emerging and differ considerably from the traditional construction (see, for instance, Reference [5]), but is not necessarily required in all sustainability assessments. Thus, the tree is formed by four main requirements (R). These requirements are divided into eight criteria (C) and 14 indicators (I). For this study, the decision-making tree developed together with its components is presented in Tables 1and 2, presents the value functions assigned to each indicator. Complementarily to Table 2, Figure A1 in the appendix shows the shapes of each value function. The definition of the indicators and the shapes of the assigned value functions was based on literature in studies of similar nature (i.e., comparison of a 3D-printed or innovative alternative with more traditional construction TABLE 1 Decision-making tree. Requirements Criteria Indicators R 1 Economic 25% C 1 Costs 100% I 1 Production and assembly cost 50% I 2 Maintenance cost 50% R 2 Environmental 25% C 2 Emissions 50% I 3 Greenhouse gas emissions 100% C 3 Resource consumption 50% I 4 Energy consumption 50% I 5 Material consumption 50% R 3 Social 25% C 4 Innovation 33% I 6 Generation of skilled jobs 50% I 7 Brand benefits 50% C 5 Working conditions 33% I 8 Occupational Risk Index (ORI) 50% I 9 Employment generation 50% C 6 Third-party effects 33% I 10 Local nuisance 100% R 4 Technological 25% C 7 Adaptability 25% I 11 Design flexibility 50% I 12 Ease of construction 50% C 8 Availability 25% I 13 Availability of providers 50% I 14 Availability of regulations 50% Note: In the sensitivity analysis scenarios defined in this study, the range of weights for each requirement are the following. R 1 : 20%–60%, R 2 : 20%–60%, R 3 : 10%–25%, R 4 : 10%–25%. TABLE 2 Value functions of the indicators. Indicator Units Shape X min X max CKP I 1 Production and assembly cost €DS 75,000 0 32,500 0.15 4 I 2 Maintenance cost €DS 20,000 0 10,000 0.15 4 I 3 Greenhouse gas emissions kgCO 2 -eq DCx 20,000 0 10,000 0.9 0.75 I 4 Energy consumption MJ DCx 200,000 0 100,000 0.9 0.75 I 5 Material consumption Scale (3–9) IL 3 9 4 0 1 I 6 Generation of skilled jobs Number IL 1 3 2 0 1 I 7 Brand benefits Scale (1–5) IL 1 3 2 0 1 I 8 Occupational Risk Index (ORI) Hours person DL 100 0 50 0 1 I 9 Employment generation Number IL 0 1500 2 0 1 I 10 Local nuisance Scale (1–5) DL 0.3 0 0.25 0 1 I 11 Design flexibility Scale (1–5) IL 0 0.5 0.25 0 1 I 12 Ease of construction Scale (1–5) IL 0 0.3 0.25 0 1 I 13 Availability of providers Scale (1–5) IL 0 0.5 0.25 0 1 I 14 Availability of regulations Scale (1–5) IL 1 3 2 0 1 Abbreviations: DL, decreasing linear; DS, decreasing S-shape, DCx, decreasing convex; IL, increasing linear. JOSA and DE LA FUENTE 3 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License alternatives). 5,17 The weights were determined after discussion with industry experts (see the appendix for more information regarding the experts consulted). While these discussions resulted in all indicators within the decisionmaking tree being assigned the same weight— representing a strict perspective of sustainability—the sensitivity analysis presented in Section 2.4.1 allows us to evaluate the results when these weights are not evenly distributed. Further indicators were also identified (e.g., finishing's quality, technology socials' acceptability). Nonetheless, these indicators were found not to be sufficiently relevant in comparison with the others that compose the decision-making tree. In this regard, should other decision-makers consider other sets of indicators as more representative, these could be incorporated accordingly following the approach presented in Section 2.1 in order to maintain both consistency and coherence. Equivalently, the weights' set could also be adapted to other contexts and stakeholders' preferences. Note that a summary of data sources for each indicator can be found in Table A2. 2.2.1 | Economic requirement The economic requirement is composed of a single criterion, C 1 , which in turn contains two different indicators: production costs and maintenance costs. •Production costs (I 1 ). These include material costs, labor, machinery, equipment, and auxiliary elements necessary for the production and assembly of housing. These costs were calculated with data from CYPE Ingenieros. 18 This database allows obtaining construction costs adjusted to the market. It includes both manufacturer products and generic products. •Maintenance costs (I 2 ). These include the material costs, labor, machinery, equipment, and auxiliary elements necessary to guarantee the service capacity and functionality of the housing throughout its useful life. Database in CYPE Ingenieros 18 was used to calculate this indicator's values. 2.2.2 | Environmental requirement The environmental requirement is composed of two distinct criteria. The first (C 2 ) refers to emissions, while the second (C 3 ) is related to resources consumption, including energy and materials. The emissions criterion (C 2 ) is composed of the following indicators: •Greenhouse gas emissions (I 3 ). This indicator accounts for all greenhouse gas emissions, which are essential to consider as they have a direct relationship with temperature increases on Earth and, consequently, in terms of climate change. Data for this indicator consisted of emissions factors, which were obtained from Catalonia Institute of Construction Technology— ITeC. 19 The resources criterion (C 3 ) is composed of the following two indicators: •Energy consumption (I 4 ). This indicator includes data on energy consumed in the considered life cycle processes, considering renewable and non-renewable energy sources. Energy consumption factors to calculate this indicator were obtained from Catalonia Institute of Construction Technology—ITeC. 19 •Material consumption (I 5 ). For this indicator, both renewable materials (such as wood) and nonrenewable materials (e.g., cement and aggregates) used in housing construction are considered. This indicator was measured using the scale presented in Table 3. For each of the elements (material scarcity, use potential of recycled materials, end of life recycling potential), a score was assigned (see Tables A3–A6, for details). Afterward, the scores were added in a way that the indicator may range between 3 and 9. 2.2.3 | Social requirement The social requirement is composed of three criteria: innovation (C 4 ), working conditions (C 5 ), and third-party effects (C 6 ). First, in innovation (C 4 ), two indicators are TABLE 3 Items considered in indicator I 5 . Materials scarcity Use potential of recycled materials EoL recycling potential 1 Scarce 1 Low 1 Low 2 Moderate 2 Moderate 2 Moderate 3 Abundant 3 High 3 High 4JOSA and DE LA FUENTE 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License considered: the generation of skilled jobs (I 6 ) and brand benefits (I 7 ). Table 4shows the details of the scale used in each of the indicators. Values were assigned upon discussion with experts. •Generation of skilled jobs (I 6 ). This indicator is intended to assess the number of skilled jobs generated during the design, production, and construction processes. Skilled jobs are those that require higher education and require a minimum level of experience. •Brand benefits (I 7 ). It evaluates the technology's contribution to increasing the reputation of the construction company and/or those with knowledge/industrial/ exploitation property rights. For working conditions (C 5 ), the two indicators evaluated are the following: •Occupational Risk Index (I 8 ). This index measures the risks associated with activities related to housing construction, as well as the probability of accidents occurring in any phase of execution. Data needed to calculate this indicator (i.e., time spent in each construction activity, number of workers) was obtained from CYPE Ingenieros. 18 •Job generation (I 9 ). This indicator evaluates the total number of jobs generated during the design and construction processes. It was measured using the scale shown in Table 5. Lastly, for third-party effects (C 6 ), the indicator is defined as follows. •Local nuisance (I 10 ). Considers disturbances to the neighborhood due to land occupation and the generation of noise, dust, and traffic, among others. This indicator was evaluated using analytic hierarchy process (AHP), 22 which allowed performing pairwise comparisons between the alternatives regarding local nuisance. 2.2.4 | Technological requirement In addition to the three pillars of sustainability (economy, environment, and society), this study also considers the technological component of the alternatives under analysis. In this requirement, two aspects are considered: adaptability (C 7 ) and availability (C 8 ). Firstly, the adaptability criterion (C 7 ) is related to design flexibility and ease of construction: •Design flexibility (I 11 ). Considers adaptability and freedom of design, including complex geometries. This indicator was evaluated using AHP. 22 •Ease of construction (I 12 ). Evaluates the simplicity of the production and construction processes of each alternative. This indicator was evaluated using AHP. 22 Criterion availability (C 8 ) is composed of two indicators as detailed below. Both indicators were evaluated using AHP 22 with the scale shown in Table 6. •Supplier availability (I 13 ). Allows considering the availability of technology suppliers (equipment and/or materials). •Availability of regulations (I 14 ). Takes into account the availability of regulations and policies, which is especially relevant in this case because new technologies are sometimes not initially regulated. TABLE 4 Scale used for indicators I 6 and I 7 .Generation of skilled jobs Brand benefits 1 Low (less than 2) 1 No significant impact on reputation 2 Moderate (between 2 and 4) 2 Moderate impact on reputation 3 High (more than 5) 3 Significant impact on reputation TABLE 5 Scale used for indicator I 9 . Job generation 1 Low (less than 2) 2 Moderate (between 2 and 4) 3 High (more than 5) TABLE 6 Scale used for the AHP of indicators I 13 and I 14 . Availability of suppliers/regulations 1 Same availability 3 Slightly higher availability 5 Moderately higher availability 7 Significantly higher availability 9 Extremely higher availability JOSA and DE LA FUENTE 5 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2.3 |Case study The floorplan of the house assessed is shown in Figure 1. It is a one-floor house and, as it can be observed, it consists of a living room, kitchen, two bathrooms and three bedrooms. Given the study's focus on the superstructure's materials and structural typologies, the analysis was restricted to vertical elements, namely walls and frames. 2.3.1 | Scenarios analyzed After analyzing the literature, 10 the most common and representative structural typologies to consider in this study were defined. They are presented in Table 7and represented in Figure 2. For the design of the alternatives, Robot Structural ® was used. Details of the sections and materials considered can be found in Table A1 in the appendix. 2.3.2 | Assumptions The functional unit considered in this study is the complete structure of the housing, considering only the superstructure (i.e., the structure without considering foundation services and operation). The assumed service life for the functional unit is 50 years. FIGURE 1 Floorplan of the house assessed. TABLE 7 Technologies considered in this study for housing construction. Process Material Structural typology Code Prefabrication (PREF) Concrete (C) Frame (F) PREF-C-F Bearing walls (BW) PREF-C-BW Steel (S) Frame (F) PREF-S-F Timber (T) Frame (F) PREF-T-F In situ (SITU) Concrete (C) Frame (F) SITU-C-F Bearing walls (BW) SITU-C-BW 3D Printing (3D) SITU-C-3D Masonry (M) Bearing walls (BW) SITU-M-BW 6JOSA and DE LA FUENTE 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License There are several stages during the life cycle of a housing unit that are relevant to consider and have an impact on the life cycle assessment results and, consequently, on the SI. In this study, the following life cycle stages are considered as representative: production stage (raw material supply, transportation, manufacturing), construction process stage (transportation, construction/ installation process), and use stage (maintenance). These stages correspond to those defined by EN 15978:2011. 23 Although it is generally accepted that the use phase of a FIGURE 2 Alternative building typologies analyzed in the study, namely (a) PREF-C-F, (b) PREF-C-BW, (c) PREF-S-F, (d) PREF-T-F, (e) SITU-C-F, (f) SITU-C-BW, (g) SITU-C-3D, (h) SITU-M-BW Design details are not shown. JOSA and DE LA FUENTE 7 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License housing unit has the most significant environmental impacts, it is not included in this case, as the focus of this study is on the impacts in the product and construction stages and, particularly, to quantify the SI of the 3Dprinted concrete construction approach and to compare its sustainability performance with the peers. It was assumed that appropriate measures are taken to ensure the same level of insulation (acoustic and thermal) for each alternative, and, consequently, the consumption and emissions associated with achieving the same level of internal comfort during the use phase are independent of the alternative. The impact on the sustainability performance of different insulation techniques could be taken into account by quantifying the economic, environmental, and social effects and incorporating these into the relevant sustainability indicators. Regarding transportation, the transport distances for the considered materials and components were defined based on the average distances typically involved in transporting the materials and equipment required between main factories and production points in Spain, and the building site of the case study for each typology. Table 8presents the distances considered in the results. However, sensitivity analyses regarding transport distances are presented at the end of this document, where sensitivity indices are calculated based on alternative assumptions regarding distances. Apart from considerations related to transport distances, other relevant aspects must be taken into account regarding the processes included within the system boundaries. First, in this analysis, the specific characteristics of the housing roofs were not considered. While roofs can play a significant role in terms of insulation, energy efficiency, and sustainability, their exclusion in this study does not affect the ranking of results among the analyzed alternatives, as all housing designs analyzed do not include a roof (and if included, it would be the same). However, it is important to note that roofs can influence the overall sustainability of a house when absolute values are sought, not just relative ones. Additionally, it was assumed that the maintenance cost of houses does not increase over time. Although maintenance costs can vary over the lifespan of a house due to wear and tear, repairs, and other factors, these changes are minimal and would not significantly impact the final results of this analysis. Finally, ceramic brick was used as the reference material for the enclosures of those alternatives that do not have the enclosure incorporated into the structural design. However, it is important to highlight that the material of enclosures can vary and adapt to the main structural material used in each alternative. 2.4 |Sensitivity analysis Performing sensitivity analyses is convenient in multicriteria decision-making as it helps assess the impact of changes in input values or criteria weights, allowing decision-makers to understand the robustness of their decisions and identify key factors influencing the outcomes. In this study, three types of sensitivity analyses were performed: sensitivity to the weighting system, sensitivity to the transportation distance, and sensitivity to the number of housing units. 2.4.1 | Sensitivity to weights The decision-making tree presented earlier was based on a set of assigned weights considering equal importance for each part of the tree. However, this set of weights may not be representative of all decision-making contexts, as they can change over time, geographical location, culture, and so forth. Therefore, this section presents a sensitivity analysis in which various weights are modified, examining the impact of these changes on sustainability indices. The two defined scenarios are presented in Table 9 and are: (1) higher environmental weight than the other two requirements, and (2) higher economic weight than the other two requirements. 2.4.2 | Sensitivity to transportation distance In order to quantify the impact of transportation (materials and components) on the emissions associated with the execution of each alternative, a sensitivity analysis has been conducted. For this analysis, minimum and maximum transport distances have been defined for the different alternatives (see Table 10). TABLE 8 Transport distances of materials considered for each alternative. Alternative Distance (km) PREF-C-F 200 PREF-C-BW 200 PREF-S-F 25 PREF-T-F 25 SITU-C-F 30 SITU-C-BW 30 SITU-C-3D 190 SITU-M-BW 25 8JOSA and DE LA FUENTE 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 2.4.3 | Sensitivity to the number of housing units In order to quantify the impact on the economic requirement of the number of housing units for the 3D printed alternative, a study has been conducted where the variable construction cost has been varied to account for the construction of 1, 3, 7, 10, 25, 50, and 100 housing units. 3|RESULTS In this section, the results obtained for each individual requirement are presented, and subsequently, the aggregated results (corresponding to the overall SI) are provided. Raw values for each indicator can be found in Table A6 in the appendix, presented in relative terms with reference to the SITU-C-F alternative. 3.1 |Sustainability index Results for the four requirements are presented in Figure 3. 3.1.1 | Economic requirement It can be observed that SITU-M-BW, PREF-C-BW, SITU-C-3D, and PREF-C-F yield the lowest values for the economic SI (between 0.01 and 0.59). The masonry alternative (SITU-M-BW) yields relatively high costs (and therefore a low SI) due to the use of rubble masonry in the design, which is a costly material to produce and obtain. 18 Also, it exhibits notably high maintenance costs, which is due to the intensive and costly maintenance required for masonry due to its composition and construction techniques. Both PREF-C-BW and PREF-C-F show significant maintenance costs, which is due to the fact that prefabricated concrete structures potentially require regular maintenance to preserve their functionality and esthetic appearance for the case study here. SITU-C-3D has the highest production costs, which are expected in technology in its early developmental stages. 3,5 It needs to be noted that, in this study, the cost does not include the printer's depreciation percentage. However, if considered, the total cost considered here would decrease with the number of houses (see Section 3.2.3). However, it has lower maintenance costs compared to prefabricated concrete structures, as it does not have joints. The other alternatives have comparatively lower costs and therefore higher sustainability indices (between 0.75 and 0.89), which is common for more traditional and consequently more optimized construction processes. Notably, the steel structure (PREF-S-F) demonstrates relatively low production costs and medium maintenance costs according to the data collected. Also, the timber structure (PREF-T-F) has a moderate maintenance cost, as it requires proper maintenance to protect it from moisture, insects, and other environmental factors. Lastly, the onsite concrete structures (SITU-C-F and SITU-C-BW) are traditional construction materials and methods that tend to provide benefits in the form of low production costs. 3.1.2 | Environmental requirement For emissions, the lowest satisfaction is obtained by PREFC-BW (index of 0.02), followed by PREF-C-F and SITUC-BW (index of 0.32). These results are expected because the concrete production process is carbon-intensive due to TABLE 9 Scenarios defined in the sensitivity analysis of the weights. Weight scenario Requirements Reference Environmental Economic R 1 Economic 25% 20% 60% R 2 Environmental 25% 60% 20% R 3 Social 25% 10% 10% R 4 Technological 25% 10% 10% TABLE 10 Scenarios defined in the sensitivity analysis of the transportation distances. Transportation distance Alternatives Min Max PREF 25 km 500 km SITU-C 10 km 50 km SITU-C-3D 0 500 km Others 0 50 km JOSA and DE LA FUENTE 9 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License 15. Boix-Cots D, Pardo-Bosch F, Blanco A, Aguado A, Pujadas P. A systematic review on MIVES: a sustainability-oriented multicriteria decision-making method [review]. Build Environ. 2022; 223:109515. https://doi.org/10.1016/j.buildenv.2022.109515 16. Josa I, Pons O, Fuente A d l, Aguado A. Multi-criteria decisionmaking model to assess the sustainability of girders and trusses: case study for roofs of sports halls. J Clean Prod. 2020; 249:119312. https://doi.org/10.1016/j.jclepro.2019.119312 17. Asensio J, Josa I, Monserrat A, de la Fuente A. 3D-printed concrete footbridges: an approach to assess the sustainability performance. Struct Concr. 2023;24(6):7705–25. https://doi.org/10. 1002/suco.202201227 18. CYPE Ingenieros. Generador de precios de la construcci on. España: CYPE Ingenieros, SA; 2023. 19. Catalonia Institute of Construction Technology—ITeC. BEDEC - Banco Construcci on. 2023. 20. Hegger M, Auch-Schwelk V, Fuchs M, Rosenkranz T. Construction materials manual. Basel: Birkhauser; 2013. 21. Casanovas M d M, Armengou J, Ramos G. Occupational risk index for assessment of risk in construction work by activity. J Constr Eng Manage. 2014;140(1):04013035. https://doi.org/ 10.1061/(asce)co.1943-7862.0000785 22. Saaty TL. Fundamentals of decision making and priority theory. Pittsburgh, PA: RWS Publications; 2001. 23. CEN/TC 350. EN 15978:2011—sustainability of construction works—assessment of environmental performance of buildings—calculation method. Brussels: European Committee for Standardization; 2011. 24. Broadbent C. Steel's recyclability: demonstrating the benefits of recycling steel to achieve a circular economy [article]. Int J Life Cycle Assess. 2016;21(11):1658–65. https://doi.org/10.1007/ s11367-016-1081-1 AUTHOR BIOGRAPHIES Irene Josa, The Bartlett School of Sustainable Construction, University College London, United Kingdom. Email: [email protected]. Albert de la Fuente, Department of Civil & Environmental Engineering, Universitat Politècnica de Catalunya (UPC), Spain. Email: albert. [email protected]. How to cite this article: Josa I, de la Fuente A. Traditional and modern methods of construction: Comparative study of the sustainability of singlefamily homes. Structural Concrete. 2024. https:// doi.org/10.1002/suco.202400802 16 JOSA and DE LA FUENTE 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License APPENDIX A FIGURE A1 Shapes of the value functions for each indicator. JOSA and DE LA FUENTE 17 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE A2 Summary of inventory data sources. Indicator Data source Details I 1 Production and assembly cost, I 2 Maintenance cost CYPE Ingenieros 18 Database codes consulted: EPS010, EPV010, FFX010, EPM010, EAS010, EAV010, EMS020, EHS010, EHV010, and EHM010, ECM010 I 3 Greenhouse gas emissions, I 4 Energy consumption Catalonia Institute of Construction Technology— ITeC 19 ; Hegger et al. 20 Database codes consulted: E4P14795, G4415115, K4F1E15N, and K4G211V9 I 5 Material consumption, I 6 Generation of skilled jobs, I 7 Brand benefits, I 9 Employment generation, I 14 Availability of regulations Literature and expert consultation Literature: Asensio et al. 17 ; Josa et al. 16 ; PonsValladares et al. 5 Experts consulted: junior robotics and automation engineer (>5 years experience), senior robotics and automation engineer (>10 years experience), digital business manager and smart society engineer (>10 years experience), engineering innovation manager (>10 years experience) I 10 Local nuisance, I 11 Design flexibility, I 12 Ease of construction, I 13 Availability of providers AHP based on discussion with experts Experts consulted: see above I 8 Occupational Risk Index (ORI) Casanovas et al. 21 ; CYPE Ingenieros 18 Risks considered: falls of persons to a different level due to winch with movable arm, conventional formwork at height, shoring, work on roofs; direct or indirect electrical contact due to electric concrete mixer; shock or entrapment due to movement or detachment of loads when handling loads by mechanical means (i.e., cranes and forklifts); blows to the upper or lower extremities due to manual handling of loads; cuts, wounds and blows due to welding, oxyacetylene cutting and adhesion of asphalt sheeting to the substrate by torch; traffic accident due to transport of elements and materials to the construction site TABLE A1 Design details for each alternative. Alternative Design details PREF-C-F Concrete HA-25, Pillars: 25 25 cm, Beams: 25 50 cm PREF-C-BW Concrete HA-25, Wall's depth: 30 cm, Beams: 25 50 cm PREF-S-F Steel S275JR, Pillars: HEA140, Beams: IPE240 PREF-T-F Timber C40, Pillars: 25 25 cm, Beams: 25 25 cm SITU-C-F Concrete HA-25, Pillars: 25 25 cm, Beams: 25 50 cm SITU-C-BW Concrete HA-25, Wall's depth: 30 cm, Beams: 25 50 cm SITU-C-3D Total concrete volume: 5.4 m 3 SITU-M-BW Wall's depth: 50 cm TABLE A3 Material scarcity scoring for indicator I 5 . Material Score Concrete 2 Concrete (3D) 1 Steel 2 Timber 2 Stone 2 TABLE A4 Use potential of recycled materials scoring for indicator I 5 . Material Score Concrete 2 Concrete (3D) 1 Steel 3 Timber 1 Stone 2 18 JOSA and DE LA FUENTE 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License TABLE A6 Quantification of indicators (given in relative terms with respect to the alternative SITU-C-F). Indicator PREFC-F PREFC-BW PREFS-F PREFT-F SITUC-F SITUC-BW SITUC-3D SITU-M-BW I 1 Production and assembly cost 1.629 2.164 1.006 0.876 1.000 0.802 6.013 4.412 I 2 Maintenance cost 2.089 3.232 0.744 1.692 1.000 0.752 0.752 5.704 I 3 Greenhouse gas emissions 1.817 2.813 1.142 0.490 1.000 1.841 1.396 0.355 I 4 Energy consumption 0.917 1.757 1.249 0.745 1.000 1.194 1.683 0.239 I 5 Material consumption 1.000 1.000 1.333 0.833 1.000 1.000 0.667 1.000 I 6 Generation of skilled jobs 1.000 1.000 1.000 1.000 1.000 1.000 3.000 2.000 I 7 Brand benefits 2.000 2.000 2.000 2.000 1.000 1.000 3.000 1.000 I 8 Occupational Risk Index (ORI) 0.149 1.503 0.573 0.328 1.000 0.995 0.020 4.598 I 9 Employment generation 0.704 0.714 0.909 0.804 1.000 0.670 2.112 4.579 I 10 Local nuisance 0.663 0.531 1.863 1.264 1.000 0.794 0.711 0.414 I 11 Design flexibility 1.039 0.563 1.859 0.405 1.000 0.473 2.932 0.346 I 12 Ease of construction 3.253 5.586 2.705 2.710 1.000 1.504 6.118 0.622 I 13 Availability of providers 0.273 0.325 0.510 0.129 1.000 0.659 0.067 0.206 I 14 Availability of regulations 1.000 1.000 1.000 0.667 1.000 1.000 0.333 1.000 TABLE A5 EoL recycling potential scoring for indicator I 5 . Material Score Concrete 2 Concrete (3D) 2 Steel 3 Timber 2 Stone 2 JOSA and DE LA FUENTE 19 17517648, 0, Downloaded from https://onlinelibrary.wiley.com/doi/10.1002/suco.202400802 by Readcube (Labtiva Inc.), Wiley Online Library on [22/11/2024]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License