The aesthetics of applying 3D printing in the design and manufacture of sustainable bags for women

1 Introduction

Rapid technological advancement has transformed fashion design and manufacturing through digital technologies in clothing and accessories (Vanderploeg et al., 2017). Three-dimensional (3D) printing, or additive manufacturing (AM), enables complex geometries, high design flexibility, and potential material savings (Dickson et al., 2020a; Huang et al., 2013), with applications extending to prototyping, textiles, garments, and accessories (Sun and Valtasa, 2019). Recent research indicates that 3D printing supports customization, rapid prototyping, design flexibility, localized production, and potentially reduced material waste (Dhiwar et al., 2024).

Fused Filament Fabrication has also been extensively reviewed as a versatile additive-manufacturing process, with applications shaped by material selection, process parameters, mechanical performance, and manufacturing efficiency (Kumar et al., 2023). Its relatively low cost, material versatility, and ability to produce customized, complex geometries make it relevant to fashion-product development (Enriconi et al., 2025). Fused Deposition Modeling (FDM), also referred to as FFF, uses a heated nozzle to melt and deposit polymer filament according to digitally generated toolpaths, allowing customized components without conventional tooling. Its digital workflow enables designers to modify geometry, dimensions, surface structures, and decorative details before fabrication. Earlier research identified these features as important advantages in fashion design and production (Abu El Esaad, 2018), while recent literature emphasizes customization, on-demand production, and flexible manufacturing (Dhiwar et al., 2024). Research has also expanded from experimental prototypes toward functional textile structures with improved flexibility, breathability, and handling characteristics (Yang et al., 2024). Thus, AM is increasingly becoming a broader platform for innovative fashion applications. Earlier studies demonstrated its potential to introduce new forms, surfaces, and construction approaches (Elgamal, 2016), while recent work highlights digital customization, complex structural design, material experimentation, and sustainable manufacturing strategies (Viziteu and Curteza, 2024).

These developments are particularly relevant to women’s handbags, which combine functional and aesthetic requirements with personal belongings, comfort, and usability (Al-Shamrani and Mohamed, 2021). Handbags contribute to outfit identity through form, materials, color, ornamentation, and carrying configuration, while their functional design must address accessibility, comfort, safety, load capacity, and ease of handling. Harby (2020) emphasized ergonomic considerations in handbag design for working women, particularly functional suitability and user requirements. Similarly, Al-Shamrani and Mohamed (2021) stressed integrating ergonomic and functional considerations into innovative accessory design. Handbags may include bodies, handles or straps, closures, linings, decorative elements, and connecting components; therefore, successful design requires balance among aesthetic quality, structural performance, usability, comfort, and durability (Harby, 2020). Digital manufacturing also enables customization, rapid prototyping, complex forms, and innovative surface structures while supporting localized and demand-oriented production (Akhoundi and Mashayekhi, 2023).

The application of FFF to functional handbags must nevertheless address mechanical performance. Fico et al. (2022) reported anisotropic mechanical behavior in FFF-produced polymer components, with interlayer bonding affecting printed-part performance. Consequently, print orientation, layer configuration, processing conditions, and material selection are important when 3D printing functional fashion products. For handbags, printed components must withstand repeated handling, carrying loads, closure forces, and contact with other materials, making structural integrity, durability, dimensional stability, and functionality as important as aesthetic experimentation.

Material selection is equally important. Polylactic acid (PLA) is widely used in FFF because of its bio-based origin, processability, and broad applicability; however, its environmental benefits depend on appropriate production, recycling, and end-of-life management rather than biodegradability under all conditions (Mujtaba et al., 2023). Bio-based and recycled materials can therefore support sustainability when integrated into appropriate circular production strategies (Dhiwar et al., 2024). The sustainability potential of 3D printing has attracted attention because controlled material deposition, small-batch production, and recycled feedstocks may contribute to resource-efficient production. However, AM should not automatically be considered environmentally sustainable.

Lodha et al. (2023) identified environmental and economic opportunities in using recycled materials in AM, including recycled polymers converted into FDM/FFF filaments, while highlighting challenges concerning their mechanical and thermal properties. Al Rashid and Koç (2023) similarly emphasized integrating AM with circular-economy principles by transforming polymer waste into useful printed products and supporting material reuse and distributed manufacturing. However, they stressed the importance of material quality, recycling processes, and application-specific performance before making comprehensive sustainability claims. In fashion, recycled polymer materials can therefore support distinctive products and reduce dependence on conventional processing, while challenges remain concerning material properties, scalability, and sustainability assessment (Dhiwar et al., 2024; Wilson, 2024).

3D printing can also complement rather than replace conventional textile and leather materials. Hybrid approaches can combine printed polymer structures with fabrics, leather, straps, fasteners, and decorative elements, assigning different materials to structural, functional, and aesthetic roles. This is particularly relevant to handbags because the rigidity or semi-rigidity of printed components can be combined with the flexibility and tactile qualities of textiles. Recent research addressing the rigidity and comfort limitations of 3D-printed fashion materials demonstrated cellulose-based textile structures with improved flexibility and comfort (Yang et al., 2024), supporting continued development of structures compatible with conventional textile performance.

Cultural heritage provides another important dimension for contemporary fashion design. In Saudi Arabia, Sadu is a traditional weaving practice associated with Bedouin culture and the desert environment, characterized by geometric patterns and tightly woven structures (Alqahtani, 2021). Traditionally made with sheep’s wool, goat hair, and camel hair, Sadu is recognized through its geometric motifs and concentrated colors, and represents an important element of Saudi cultural heritage. Its inscription on the UNESCO Intangible Cultural Heritage List in 2020 highlights its cultural significance and the importance of continued transmission and contemporary interpretation (UNESCO, 2020).

Reinterpreting Sadu through digitally fabricated fashion accessories can connect traditional cultural expression with contemporary design and manufacturing. Rather than directly reproducing traditional products, designers can abstract selected Sadu patterns, colors, textures, and material combinations and integrate them into new product forms. Such integration can connect traditional craftsmanship with contemporary technological practices while supporting cultural identity, aesthetic value, functionality, and sustainability (Pasricha and Greeninger, 2018).

The development of 3D printing in fashion has also been examined from a broader industry perspective, including its implications for product development, customization, and emerging manufacturing models (Sun and Zhao, 2017; Chan et al., 2021; Khajavi, 2021). Despite growing research on 3D printing in fashion, limited attention has been given to specific accessories such as handbags, particularly products integrating traditional textile heritage with digitally manufactured components (Akhoundi and Mashayekhi, 2023). Further research is also needed on integrating recycled materials into 3D-printed fashion products to address material circularity and sustainability (Dhiwar et al., 2024). Accordingly, this study investigates using 3D printing to design and manufacture women’s handbags inspired by Saudi Sadu heritage, integrating Sadu textile with recycled fused-filament materials. By combining Sadu-inspired elements with digital fabrication, the study connects traditional craft heritage with contemporary manufacturing. It explores how cultural identity, aesthetic value, functional requirements, and sustainability can be integrated within a unified fashion-product design approach.

2 Research gap and rationale

The literature demonstrates considerable progress in applying 3D printing to fashion, textiles, sustainable manufacturing, and customized product development. Nevertheless, much existing research has focused on garments, textile structures, footwear, or general additive manufacturing applications, whereas comparatively less attention has been given to culturally inspired handbags that combine 3D-printed structures with traditional heritage textiles and functional accessory components.

Furthermore, sustainability research emphasizes that the environmental benefits of additive manufacturing depend strongly on material selection, recycling pathways, production conditions, product lifespan, and end-of-life management rather than on 3D printing alone (Al Rashid and Koç, 2023). This creates a need for applied research that evaluates not only the aesthetic novelty of 3D-printed fashion accessories but also their functional suitability and material-related potential.

Accordingly, the present study addresses this gap by investigating the application of 3D printing technology to the design and manufacture of women’s handbags inspired by Saudi Sadu heritage. The study combines digitally fabricated structures with Sadu-inspired textile elements and other complementary materials to develop contemporary accessories integrating cultural identity, aesthetic innovation, functional performance, and material sustainability. In doing so, the research extends existing work on 3D printing in fashion from general technological applications to a culturally grounded, product-specific application in women’s handbags.

3 Methodology

3.1 Research design

The present study employed a descriptive-analytical and experimental research design to investigate the application of 3D printing technology in the design and manufacturing of women’s handbags inspired by Saudi heritage. The descriptive-analytical component examined the design, functional, and production considerations associated with 3D-printed fashion accessories, while the experimental component involved developing and fabricating selected handbag prototypes. This combined approach aligns with the potential of additive manufacturing to support iterative design, customization, rapid prototyping, and the development of complex fashion products from digital models (Dhiwar et al., 2024).

The study integrated digital fabrication with heritage-inspired textile design, focusing on incorporating Sadu-inspired elements into contemporary women’s handbags. The practical implementation employed fused filament-based 3D printing to produce selected handbag structures, which were subsequently combined with Sadu textile and complementary materials. Such hybrid approaches are relevant to contemporary fashion design because 3D-printed components can provide structural and geometric possibilities while conventional textile materials contribute flexibility, texture, and cultural identity (Yang et al., 2024).

The research evaluation focused on three principal dimensions: aesthetic quality, economic feasibility, and functional performance. The aesthetic dimension addressed the compatibility of design principles and elements, including form, color, proportion, and decorative integration. The economic dimension concerned the perceived feasibility of applying 3D printing to handbag production, while the functional dimension addressed practical characteristics of the implemented prototypes, including usability, durability, closure performance, safety, and ease of care. These dimensions reflect the need to evaluate fashion products beyond visual innovation alone, particularly where digitally fabricated components are intended for practical everyday use (Fico et al., 2022).

The experimental workflow therefore progressed from digital design and evaluation of the proposed handbag collection to selecting and physically fabricating the highest-rated designs, followed by specialist assessment of the resulting prototypes. This procedure enabled the study to examine the extent to which 3D printing could be integrated with Sadu-inspired design to produce contemporary handbags that combine cultural identity, aesthetic value, functional suitability, and material sustainability (Al Rashid and Koç, 2023).

3.2 Research framework and hypotheses

The hypotheses were developed in accordance with the methodological evaluation framework adopted in the study. Recent advancements in 3D printing technologies have significantly transformed fashion and accessories design by enabling greater flexibility, customization, and sustainability in manufacturing processes. Previous studies have emphasized that 3D printing technologies enhance aesthetic innovation, reduce production waste, and support environmentally sustainable design practices within the fashion industry (Abu El Esaad, 2018; Elgamal, 2016). Furthermore, integrating heritage-inspired elements with contemporary manufacturing technologies has emerged as an important approach for developing fashion products that combine cultural identity with modern consumer preferences. Accordingly, the present study examined whether integrating Saudi heritage-inspired Sadu textiles with recycled 3D printing materials would result in acceptable handbag designs in terms of aesthetic quality, functional performance, sustainability, safety, ergonomic efficiency, and contemporary fashion relevance.

3.2.1 Aesthetic acceptance and design compatibility

The aesthetic value of fashion accessories represents one of the primary determinants of consumer acceptance and marketability. Previous studies show that 3D printing technologies in fashion design enhance creative possibilities and introduce new aesthetic and expressive dimensions to clothing and accessories (Abu El Esaad, 2018; Elgamal, 2016). Furthermore, harmony between colors, materials, and design elements contributes significantly to perceptions of product attractiveness and quality. In the present study, aesthetic acceptance was evaluated based on color compatibility, design principles, proportions, forms, and the integration of Sadu-inspired elements with the digitally manufactured components. Therefore, the first hypothesis was formulated as follows:

H1: The proposed women’s handbag designs manufactured using 3D printing technology will achieve a high level of acceptance regarding color compatibility and the aesthetic integration of design principles and elements.

3.2.2 Functional performance and usability

Ergonomic studies on handbag and accessory design have emphasized the importance of achieving functional efficiency, comfort, ease of use, and compatibility between products and users’ daily activities (Harby, 2020; Al-Shamrani and Mohamed, 2021). Women’s handbags are not only decorative accessories but also practical products intended to support daily activities by safely and conveniently carrying personal belongings. Consequently, functional performance represents a critical factor in evaluating the success of handbag designs. In the present study, functional performance was assessed in relation to usability, carrying capacity, durability, handling, closure performance, and suitability for practical use. Based on these considerations, the second hypothesis was formulated:

H2: The proposed women’s handbag designs will demonstrate a high level of functional performance and practicality during daily use.

3.2.3 Sustainability and ease of maintenance

Sustainability has become a major concern within contemporary fashion production systems, particularly with the increasing adoption of recyclable and environmentally preferable materials in manufacturing technologies. Studies investigating sustainable polymer materials in 3D printing have highlighted the potential environmental advantages of using recycled and eco-friendly materials to reduce waste and extend product usability (Fico et al., 2022). Furthermore, ease of cleaning and maintenance can contribute to product longevity and continued usability. Accordingly, the present study incorporated ease of care and cleaning into the evaluation of the proposed handbag designs, particularly in relation to the use of recycled fused-filament materials and their integration with Sadu textiles. The third hypothesis was therefore formulated as follows:

H3: The proposed handbag designs will achieve ease of care and cleaning, thereby enhancing sustainability and long-term usability.

3.2.4 Safety and ergonomic efficiency

The ergonomic quality of handbags is strongly associated with users’ perceptions of safety, comfort, and convenience. Previous research has demonstrated that effective closure systems, supportive straps, and ergonomic design considerations improve the safety and usability of handbags in everyday activities (Harby, 2020; Al-Shamrani and Mohamed, 2021). Therefore, integrating secure functional components into innovative handbag designs is expected to improve product performance. In the present study, safety and ergonomic efficiency were evaluated based on characteristics including the security of closure systems, stability of straps and handles, ease of carrying, and protection of personal belongings. Based on this perspective, the fourth hypothesis was formulated:

H4: The proposed women’s handbag designs will provide a satisfactory level of safety and security in carrying personal belongings through the use of effective closure systems and supporting straps.

3.2.5 Contemporary fashion trends and market acceptance

The growing integration of digital manufacturing technologies into fashion production has created new opportunities for innovative and customized fashion products that align with contemporary market trends (Abu El Esaad, 2018). Furthermore, 3D printing technologies support on-demand production and individualized design solutions that satisfy evolving consumer preferences (Ahmed et al., 2019). Products that successfully combine heritage-inspired aesthetics with modern production technologies are therefore expected to achieve positive consumer and market acceptance. In the present study, contemporary relevance was assessed by the extent to which the proposed handbags combined Saudi Sadu heritage with contemporary forms, materials, digital manufacturing techniques, and fashion aesthetics. Accordingly, the fifth hypothesis was formulated:

H5: The proposed handbag designs will keep pace with contemporary fashion trends and achieve market acceptance as an innovative category of 3D-printed fashion products inspired by Saudi heritage.

The five hypotheses provided the methodological basis for evaluating the proposed handbag designs. They were subsequently examined through assessment procedures applied to the developed designs and fabricated prototypes, enabling the study to determine whether integrating 3D printing, recycled fused-filament materials, and Saudi Sadu-inspired textile elements could produce handbags that satisfy aesthetic, functional, sustainability, safety, ergonomic, and contemporary fashion requirements.

3.3 Research instruments

3.3.1 Structured design evaluation questionnaire

The Design Evaluation Questionnaire (DEQ) comprised two dimensions: (1) aesthetic quality of women’s handbag design and (2) the economic potential of applying 3D printing technology. Each dimension contained seven items, for a total of 14 items. The items were rated by 22 specialists using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. For an individual specialist, the maximum score was 35 points for each dimension (7 items × 5 points), and the maximum total score for the complete questionnaire was 70 points (14 items × 5 points). For the statistical analysis, the responses of the 22 specialists were aggregated at the item level for each proposed design. Consequently, the maximum possible aggregate score for an individual item was 110 points (22 specialists × 5 points). The descriptive values reported in the results tables therefore represent mean aggregated item-level scores rather than individual specialists’ scores on the 35-point dimension scale. Quality coefficients were calculated by dividing the corresponding aggregated item-level mean score by 110 and multiplying by 100. For example, a mean aggregated item-level score of 101.14 corresponds to a quality coefficient of 91.95% (101.14/110 × 100). Thus, the 35-point maximum applies to the score obtained by an individual specialist across the seven items of a dimension, whereas the 110-point denominator applies to the aggregated item-level scores used in the statistical analysis.

All 22 specialists evaluated the 14 proposed handbag designs. The ANOVA structure reflects the number of questionnaire items contributing to aggregated observations, not the number of specialist raters. For the aesthetic-quality analysis, the seven items in each dimension generated seven aggregated item-level observations for each of the 14 designs, resulting in 98 observations (14 designs × 7 items) and degrees of freedom of 13 between designs and 84 within designs. The same structure was applied to the economic-potential analysis. For the overall evaluation, the seven aesthetic items and seven economic-potential items were combined, resulting in 14 aggregated item-level observations for each design and 196 observations in total, with 13 between-design and 182 within-design degrees of freedom. Accordingly, the degrees of freedom reported in the ANOVA tables reflect the number of aggregated questionnaire-item observations and do not indicate that different subsets of specialists evaluated the designs.

It should be emphasized that the unit of observation in these ANOVA procedures was the aggregated questionnaire item rather than the individual specialist. The ANOVA therefore examines variation among design-level aggregated item scores and was not based on 98 or 196 independent human respondents. The resulting degrees of freedom should consequently be interpreted as reflecting the structure of the aggregated analytical dataset rather than the number of independent specialists. This analytical approach was adopted to summarize and compare the design-level evaluation patterns while retaining the complete set of item-level assessment information.

3.3.1.1 Validity and reliability of the design evaluation questionnaire

The Design Evaluation Questionnaire (DEQ) was developed to assess specialists’ evaluations of the proposed handbag designs for application of 3D printing technology. The instrument comprised two dimensions: (1) aesthetic quality, covering the principles and elements of women’s handbag design, and (2) economic potential, assessing the feasibility of applying 3D printing technology to handbag production. Each dimension comprised seven items, for a total of 14 items. Responses were recorded using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree.

3.3.1.2 Content validity

To establish content validity, the preliminary version of the questionnaire was presented to 22 specialists in clothing, textiles, fashion design, and related fields. The specialists evaluated the relevance, clarity, linguistic formulation, appropriateness, and alignment of the items with their respective dimensions and the objectives of the study. Their recommendations were considered in revising the questionnaire before its use in the substantive evaluation of the proposed handbag designs. The same 22 specialists subsequently evaluated the 14 proposed designs using the finalized questionnaire.

Inter-rater agreement was assessed using Cooper’s percentage-agreement method:

Percentage agreement = Number of agreements Number of agreements + Number of disagreements × 100

As shown in Table 1, the agreement coefficients ranged from 95.45 to 100%, indicating a high level of agreement among the experts regarding the clarity, relevance, and appropriateness of the questionnaire items.

Table 1. Expert agreement on the content and structure of the design evaluation questionnaire.

3.3.1.3 Internal consistency validity

Internal consistency validity was examined by calculating Pearson’s correlation coefficients between the scores of each questionnaire dimension and the total questionnaire score. Both dimensions demonstrated strong, statistically significant correlations with the overall instrument. The aesthetic-quality dimension showed r = 0.876, whereas the economic-potential dimension showed r = 0.886 (p < 0.01), supporting the internal consistency of the questionnaire dimensions.

Table 2 presents the Pearson correlation coefficients between each questionnaire dimension and the total questionnaire score, providing evidence of the internal consistency of the instrument.

Table 2. Correlations between questionnaire dimensions and the total questionnaire score.

**p < 0.01.

3.3.1.4 Reliability

The internal reliability of the questionnaire was assessed using Cronbach’s alpha (α). The coefficient was 0.886 for the aesthetic-quality dimension, 0.888 for the economic-potential dimension, and 0.887 for the questionnaire as a whole. These coefficients indicate high internal consistency and support the instrument’s reliability for evaluating the proposed handbag designs.

Table 3 presents the Cronbach’s alpha coefficients calculated for each questionnaire dimension and for the questionnaire as a whole, providing evidence of the instrument’s internal reliability.

Table 3. Internal reliability of the design evaluation questionnaire.

Overall, the evidence from expert review, inter-rater agreement, internal consistency, and reliability analysis supports the validity and reliability of the Design Evaluation Questionnaire for assessing the proposed handbag designs and their potential application using 3D printing technology.

3.3.2 Functional performance questionnaire

A second structured instrument, the Functional Performance Questionnaire (FPQ), was developed to evaluate the functional performance of the two handbag prototypes selected for practical implementation using 3D printing technology. The FPQ assessed structural form retention, appearance retention, closure performance, carrying-system suitability, service-life potential, and ease of care and maintenance.

The FPQ comprised six items and used a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. All 22 specialists who participated in the evaluation process were invited to assess the two fabricated prototypes, Designs 6 and 11. The functional-performance analysis is reported in Table 4. However, the analysis used the 12 design-level observations retained in the statistical dataset, comprising six observations for each prototype. This resulted in 1 and 10 degrees of freedom for between- and within-design variation, respectively. The distinction between the total number of participating specialists (n = 22) and the observations retained for the specific ANOVA is therefore made explicit here to ensure consistency between the reported sample information and the statistical results.

Table 4. One-way ANOVA of specialists’ evaluations of the functional performance of the implemented designs.

The six evaluation items addressed the following aspects:

• Suitability of 3D printing for forming the external structure of the handbag.
• Ability of the handbag to maintain its appearance after 3D fabrication.
• Performance of the closure mechanism following 3D fabrication.
• Suitability of flexible plastic straps for enhancing the durability and strength of the handbag joints.
• Potential of the 3D-printed structure to extend the service life of the handbag.
• Ease of cleaning and maintaining the 3D-printed handbag.

These items were selected to provide a focused assessment of the functional characteristics of the fabricated prototypes rather than their aesthetic qualities. The questionnaire was subsequently subjected to content-validity and reliability procedures before being used for the final evaluation. The manuscript reports expert agreement ranging from 95.45 to 100%, significant item–total correlations ranging from 0.811 to 0.828, and a Cronbach’s alpha coefficient of 0.862, supporting the instrument’s validity and internal consistency.

3.3.2.1 Validity and reliability of the functional performance questionnaire

The Functional Performance Questionnaire (FPQ) underwent systematic validation and reliability assessment before its application to the implemented handbag prototypes. Two complementary forms of validity were examined: content validity based on expert judgment and internal consistency validity based on item–total correlations. The questionnaire’s reliability was subsequently assessed using Cronbach’s alpha and split-half reliability.

3.3.2.2 Content validity

The initial version of the FPQ was submitted to 22 specialists in clothing and textiles for expert review. The experts assessed the items for linguistic formulation, clarity, scientific appropriateness, organization, alignment with the questionnaire dimensions, and coverage of the study objectives. Based on their recommendations, we revised the wording and organization of selected items before administering the final version.

Expert agreement was quantified using Cooper’s percentage-agreement method:

Percentage agreement = Number of agreements Number of agreements + Number of disagreements × 100

As shown in Table 5, expert agreement ranged from 95.45 to 100%, indicating a high level of agreement regarding the clarity, appropriateness, and relevance of the questionnaire items.

Table 5. Expert agreement on the functional performance questionnaire.

The high agreement levels provided evidence supporting the content validity of the Functional Performance Questionnaire.

3.3.2.3 Internal consistency validity

Internal consistency validity was examined by calculating Pearson’s correlation coefficients between each item score and the total questionnaire score. All six items showed strong positive correlations with the total score, ranging from r = 0.811 to r = 0.828, with all correlations statistically significant at p < 0.01.

Table 6 presents the item–total Pearson correlation coefficients for the functional performance questionnaire, showing the strength of the relationship between each statement and the overall questionnaire score.

Table 6. Item–total correlations for the functional performance questionnaire.

**p < 0.01.

The consistently strong item–total correlations indicate that the individual items were appropriately aligned with the overall functional-performance construct and provide evidence of satisfactory internal consistency.

3.3.2.4 Reliability

The internal reliability of the FPQ was assessed using Cronbach’s alpha, which yielded a coefficient of α = 0.862. Furthermore, split-half reliability coefficients ranged from 0.867 to 0.981. These results indicate a high level of internal consistency and support the reliability of the questionnaire for evaluating the functional performance of the implemented 3D-printed handbag prototypes.

Overall, the content-validity evidence, strong item–total correlations, and high reliability coefficients support using the Functional Performance Questionnaire as a consistent instrument for assessing the functional characteristics of the fabricated handbag prototypes.

3.3.3 Materials and equipment

The practical implementation phase employed the following materials and technological tools:

• Creality 3D Printer for additive manufacturing and prototype fabrication.
• Cura software for preparing, processing, and slicing digital models before printing.
• PLA (Polylactic Acid) filament, an environmentally friendly and biodegradable thermoplastic material widely used in additive manufacturing applications.
• Sadu-inspired decorative and heritage design elements integrated within the handbag structures.

3.3.3.1 3D printing technology and manufacturing methods

Three-dimensional printing technology, also known as additive manufacturing, produces objects by depositing raw materials layer by layer until the final product is completed. Printing materials may include powders, filaments, granules, and resins. Despite the availability of different manufacturing techniques, they share the fundamental principle of digitally controlled, layer-by-layer product construction (Ahmed et al., 2019).

The primary additive manufacturing methods include:

• Selective Laser Sintering (SLS)
• Photopolymerization
• Fused Deposition Modeling (FDM)

The present study employed Fused Deposition Modeling (FDM) because it is well suited to producing fashion accessories and customized handbag structures. FDM is one of the most widely used additive manufacturing techniques due to its accessibility, flexibility, and compatibility with thermoplastic materials.

In FDM, thermoplastic filament is fed from a spool into a heated extrusion mechanism, where it is heated to a semi-molten state and deposited through a nozzle. The nozzle moves according to digitally controlled instructions, depositing successive layers that solidify to gradually form the desired object (Ahmed et al., 2019). Figure 1 illustrates the 3D printing process (Ahmed et al., 2019; Dickson et al., 2020b).

3.3.3.2 Cooling and print quality optimization

Print quality in additive manufacturing is strongly influenced by cooling conditions, particularly when using PLA filament. Saleh et al. (2021) reported that cooling settings affect dimensional accuracy, structural stability, and the aesthetic quality of printed models. Inadequate or uneven cooling can reduce both visual quality and dimensional precision, particularly in protruding structures and unsupported bridges. Therefore, the present study carefully adjusted cooling parameters in the slicing software to improve the quality and stability of the handbag prototypes.

3.3.3.3 Stages of the 3D printing process

The practical implementation of the handbag designs followed a systematic additive manufacturing workflow. First, the initial handbag models were developed using Computer-Aided Design (CAD) software to create 3D digital structures and assess material behavior and structural performance (Ahmed et al., 2019). The completed designs were then converted into STL (Stereolithography) format, a standard file type used in additive manufacturing and 3D printing (Dickson et al., 2020b).

The STL files were transferred to slicing software, where the print orientation, dimensions, layer thickness, and other parameters were adjusted to ensure accuracy and structural stability (Saleh et al., 2021). PLA filament was then loaded into the Creality 3D printer, and the required temperature and extrusion settings were configured (Fico et al., 2022).

The printing stage involved sequentially depositing thermoplastic layers according to digitally controlled movements until the handbag structure was completed. Printing time varied with model dimensions, material characteristics, and machine capacity (Ahmed et al., 2019). After fabrication, the printed components were safely removed from the printing platform (Dickson et al., 2020a). Finally, post-processing included removing support materials, cleaning surfaces, refining structural details, and preparing the handbag prototypes for evaluation and use (Saleh et al., 2021).

4 Experimental design and practical implementation

The practical implementation phase involved developing a collection of women’s handbags designed for different functional contexts and occasions, including morning use for working women, evening use, travel, and casual outings. The proposed designs were developed to address women’s functional and aesthetic requirements while incorporating Saudi heritage-inspired characteristics through the integration of Sadu motifs and 3D-printing technology.

The proposed handbag designs were subsequently presented to specialists in fashion design and clothing accessories for systematic evaluation using the developed questionnaire. The evaluation focused on the established aesthetic and economic criteria for assessing the suitability of the proposed designs for 3D-printing application. Based on the specialists’ evaluations, the highest-rated designs were identified and selected for practical implementation using 3D-printing technology.

The selected designs were then digitally prepared and physically fabricated, incorporating 3D-printed components with Sadu-inspired textile elements and other complementary materials, as required by each design. The resulting prototypes constituted the final experimental products and were subsequently subjected to functional-performance evaluation using the second assessment instrument.

Table 7 presents the specifications of the proposed handbag collection, including the design number, materials, applied techniques, colors, dimensions, and intended use.

Table 7. Specifications of the proposed collection of women’s handbag designs.

Although Designs 5, 10, and 13 differ in form, structural configuration, decorative treatment, and functional features, their reported external dimensions are identical (15 cm × 12 cm). These dimensions represent the intended overall bounding dimensions of the respective designs, not identical 3D geometries. The dimensions were verified against the original design specifications and fabrication measurements.

4.1 The stage of designing the bags using the Cura program for 3D design

Design No. 6 was developed using the Cura program for 3D design. The design consists of a handbag body printed with PLA filament and attached to a decorated strap incorporating Sadu patterns. It is further embellished with a printed loop connected to a bundle of threads, as shown in Figure 2.

Design No. 11 was developed using the Cura 3D design program. The outer part of the handbag was printed in a U-shaped form, while the inner part was constructed from Sadu fabric and incorporated printed rings. A leather strip passes through these rings to function as the handbag closure, while a leather strap is attached to both sides of the outer body to facilitate carrying, as shown in Figure 3.

4.2 The stage of the 3D printing process of the bags using a Creality 3D printer

At this stage, the researchers used the 3D printer to implement the prepared Design No. (6) Using the Cura program and printed all parts until they reached the final form of the design, as shown in Figure 4.

The researchers used a 3D printer to fabricate the prepared Design No. 11 using the Cura program. All printed components were fabricated and assembled until the final form of the handbag was achieved, as shown in Figure 5.

5 Findings

5.1 Demographic

The instrument-validation panel comprised 22 specialists in clothing, textiles, fashion design, and related fields. Table 8 presents their demographic and professional characteristics, including gender, age, academic qualification, specialization, professional position, and years of professional experience. These characteristics provide context on the experts who participated in the content-validation process.

Table 8. Demographic and professional characteristics of the expert validation panel.

The demographic and professional characteristics reported in Table 8 represent the actual characteristics of the 22 specialists who participated in the questionnaire validation and subsequent evaluation of the proposed handbag designs.

All 22 specialists participated in the questionnaire-validation process and subsequently evaluated the proposed handbag designs using the finalized Design Evaluation Questionnaire. Therefore, 22 specialists participated in the study. The degrees of freedom in the design-level ANOVA tables reflect the number of observations entered into each specific statistical analysis rather than the number of specialists who participated in the study as a whole. For the aesthetic and economic analyses, the reported degrees of freedom indicate 98 design-level observations (14 designs × 7 observations per design), whereas the overall analysis contains 196 observations (14 designs × 14 observations per design) because the aesthetic and economic evaluation observations were combined. For the functional-performance analysis, Table 4 reports 12 observations, corresponding to six observations per prototype. These differences reflect the structure of the datasets used for the respective statistical analyses and should not be interpreted as indicating that separate groups of specialists were recruited for validation and evaluation.

5.2 Results of the design evaluation questionnaire

To determine the level of acceptance of the proposed handbag designs for application using 3D printing technology, the specialists’ evaluations were analyzed across two dimensions: aesthetic design quality and economic potential of 3D printing application. One-way analysis of variance (ANOVA) was used to examine whether the specialists’ evaluations differed significantly across the 14 proposed designs.

5.2.1 First: aesthetic design quality

The first dimension assessed the extent to which the proposed handbag designs achieved the aesthetic principles and elements of women’s handbag design. This dimension consisted of seven items, each rated by the 22 participating specialists using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. For statistical analysis, the responses provided by the 22 specialists were aggregated at the item level for each proposed design. Thus, each design produced seven aggregated item-level scores, corresponding to the seven items of the aesthetic-quality dimension. Because each item was evaluated by 22 specialists, the maximum possible aggregate score for an individual item was 110 points (22 specialists × 5 points).

An ANOVA was used to conduct using these aggregated item-level observations to examine whether the aesthetic-quality evaluations differed significantly across the 14 proposed handbag designs. Accordingly, the analysis comprised 98 observations (14 designs × 7 items), resulting in 13 degrees of freedom between designs and 84 degrees of freedom within designs. As shown in Table 9, the analysis revealed a statistically significant difference among the proposed designs, F(13, 84) = 36.082, p < 0.001. This finding indicates that the proposed handbag designs differed significantly in their evaluated aesthetic quality.

Table 9. One-way ANOVA of aggregated item-level aesthetic-quality scores across the proposed designs.

The analysis is based on seven aggregated item-level scores for each design. Each item-level score represents the aggregated responses of the 22 specialists; therefore, the seven observations per design correspond to the seven questionnaire items and not to seven specialist raters.

Table 10 presents the descriptive statistics and quality coefficients for the aesthetic-quality dimension. Across the seven aggregated item-level scores, the overall mean was M = 94.04 (SD = 5.24). Design 11 received the highest mean aggregated item-level score (M = 101.14, SD = 0.69), corresponding to a quality coefficient of 91.95%. This was followed by Design 6 (M = 100.14, SD = 1.07; quality coefficient = 91.04%) and Design 9 (M = 99.57, SD = 0.79; quality coefficient = 90.52%). Design 14 received the lowest mean aggregated item-level score (M = 85.71, SD = 1.25), corresponding to the lowest quality coefficient of 77.92%.

Table 10. Descriptive statistics and quality coefficients for aesthetic design quality.

The descriptive statistics for each design were calculated across the seven aggregated item-level scores corresponding to the seven aesthetic-quality items. Each item-level score could reach a maximum of 110 points because it represented the combined responses of 22 specialists (22 × 5). The quality coefficient was calculated as (M/110) × 100. For example, Design 11 obtained a mean aggregated item-level score of 101.14, corresponding to a quality coefficient of 91.95% (101.14/110 × 100). The original 35-point maximum applies to the score obtained by an individual specialist across the seven items of the dimension, whereas the 110-point denominator applies to the aggregated item-level scores reported in this table.

Figure 6 illustrates the quality coefficients derived from the aggregated item-level evaluations of the proposed handbag designs with respect to the effectiveness of 3D printing in achieving the aesthetic principles and design elements.

Design 14 received the lowest aesthetic evaluation, with a mean aggregated item-level score of 85.71 and a quality coefficient of 77.92%, ranking 14th among the proposed designs.

The superior aesthetic evaluation of Design 11 was attributed in the original analysis to the effective coordination of colors and materials, particularly the integration of Sadu fabric with leather straps and the 3D-printed PLA structure. Conversely, the lower evaluation of Design 14 was associated with its circular form and the perceived effectiveness of integrating the Sadu-inspired aesthetic elements.

Overall, the results demonstrate statistically significant variation in the aesthetic-quality evaluations of the 14 proposed handbag designs. Accordingly, the hypothesis concerning differences among the proposed designs in achieving the aesthetic principles and elements of handbag design was supported.

The superior aesthetic evaluation of Design 11 was attributed in the original analysis to the effective contrast and coordination of colors and materials, particularly the integration of Sadu fabric with leather straps and the 3D-printed PLA structure. Conversely, the lower evaluation of Design 14 was associated with its circular form and less effective integration of the Sadu-inspired aesthetic elements.

Overall, the findings demonstrate significant variation in specialists’ aesthetic evaluations of the proposed handbag designs. Thus, the hypothesis concerning differences among the designs in achieving the aesthetic principles and elements of handbag design was supported.

5.2.2 Second: economic potential of 3D printing

The second dimension assessed the perceived economic potential and feasibility of applying 3D printing technology to women’s handbag production. This dimension consisted of seven items, each rated by the 22 participating specialists using a five-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. For statistical analysis, the responses provided by the 22 specialists were aggregated at the item level for each proposed design. Thus, each design produced seven aggregated item-level scores, corresponding to the seven items of the economic-potential dimension. Because 22 specialists evaluated each item, the maximum possible aggregate score for an individual item was 110 points (22 specialists × 5 points).

An ANOVA was conducted to examine whether the economic-potential evaluations differed significantly across the 14 proposed handbag designs. Accordingly, the analysis comprised 98 aggregated item-level observations (14 designs × 7 items), resulting in 13 degrees of freedom between designs and 84 within designs. As shown in Table 11, the analysis revealed a statistically significant difference among the proposed designs, F(13, 84) = 19.680, p < 0.001. This finding indicates that the proposed designs differed significantly in their evaluated economic potential for applying 3D printing technology.

Table 11. One-way ANOVA of aggregated item-level scores for the economic potential of 3D printing.

The analysis is based on seven aggregated item-level scores for each design. Each item-level score represents the aggregated responses of the 22 specialists; therefore, the seven observations per design correspond to the seven questionnaire items and not to seven specialist raters.

Table 12 presents the descriptive statistics and quality coefficients for the economic-potential dimension across the 14 proposed designs. Across the seven aggregated item-level scores, the overall mean was M = 95.05 (SD = 4.78). Design 11 obtained the highest mean aggregated item-level score (M = 101.43, SD = 1.40), corresponding to the highest quality coefficient of 92.21%. This was followed by Design 3 (M = 99.71, SD = 1.38; quality coefficient = 90.65%). Designs 6 and 9 also received relatively high evaluations, each with a quality coefficient of 90.26%. Design 10 obtained the lowest mean aggregated item-level score (M = 86.86, SD = 1.57), corresponding to the lowest quality coefficient of 78.96%.

Table 12. Descriptive statistics and quality coefficients for the economic potential of 3D Printing.

The descriptive statistics for each design were calculated across the seven aggregated item-level scores corresponding to the seven economic-potential items. Each item-level score could reach a maximum of 110 points because it represented the combined responses of 22 specialists (22 × 5). The quality coefficient was calculated as (M/110) × 100. For example, Design 11 obtained a mean aggregated item-level score of 101.43, corresponding to a quality coefficient of 92.21% (101.43/110 × 100). The original 35-point maximum applies to the score obtained by an individual specialist across the seven items of the dimension, whereas the 110-point denominator applies to the aggregated item-level scores reported in this table.

The results presented in Table 12 indicate generally favorable evaluations of the proposed handbag designs regarding the perceived economic potential of applying 3D printing technology. Design 11 achieved the highest mean aggregated item-level score (M = 101.43, SD = 1.40) and the highest quality coefficient (92.21%), ranking first among the proposed designs. Design 3 ranked second, with a mean aggregated item-level score of M = 99.71 (SD = 1.38) and a quality coefficient of 90.65%, followed by Design 6, with a quality coefficient of 90.26%. Design 9 also obtained a quality coefficient of 90.26%.

At the lower end of the ranking, Design 10 obtained the lowest mean aggregated item-level score (M = 86.86, SD = 1.57) and the lowest quality coefficient (78.96%), followed by Design 14, which obtained a quality coefficient of 81.30%. The remaining designs achieved quality coefficients ranging from 83.12 to 88.83%, indicating generally favorable evaluations with variation across the proposed designs.

Overall, the results demonstrated statistically significant differences in perceived economic-potential evaluations across the 14 proposed handbag designs, F(13, 84) = 19.680, p < 0.001. Design 11 received the highest evaluation, whereas Design 10 received the lowest. These findings indicate that specialists’ perceptions of the economic potential of applying 3D printing varied by proposed handbag design and provided a basis for identifying the highest-rated designs for subsequent practical implementation (Figure 7).

5.2.3 Third: overall evaluation of the proposed designs

To assess the overall evaluation of the proposed handbag designs for application using 3D printing technology, the two dimensions of the Design Evaluation Questionnaire (DEQ)—aesthetic quality of women’s handbag design and economic potential of applying 3D printing technology—were examined jointly. Each dimension comprised seven items, for a total of 14 items for the overall evaluation.

For the overall statistical analysis, the responses provided by the 22 specialists were aggregated at the item level. Thus, each proposed design was represented by 14 aggregated item-level scores, corresponding to the seven aesthetic-quality items and seven economic-potential items. Because 22 specialists evaluated each item using a five-point Likert scale, the maximum possible aggregate score for an individual item was 110 points (22 specialists × 5 points). Accordingly, the overall analysis comprised 196 aggregated item-level observations (14 designs × 14 items), resulting in 13 degrees of freedom between designs and 182 degrees of freedom within designs.

An ANOVA was conducted to determine whether the overall aggregated item-level evaluations differed significantly among the 14 proposed designs. As presented in Table 13, the analysis revealed a statistically significant difference among the designs, F(13, 182) = 45.816, p < 0.001. This result indicates that the overall evaluations varied significantly across the proposed handbag designs.

Table 13. One-way ANOVA of aggregated item-level scores for the overall evaluation of the proposed designs.

The analysis is based on 14 aggregated item-level scores for each design, representing the seven aesthetic-quality items and seven economic-potential items. Each item-level score represents the aggregated responses of the 22 specialists and has a maximum possible value of 110 points. Therefore, the 196 observations represent aggregated item-level scores rather than 196 individual specialist responses.

Table 14 presents the descriptive statistics and quality coefficients for the overall evaluation of the 14 proposed designs. Across the aggregated item-level scores from the two assessment dimensions, the overall mean was M = 94.55 (SD = 5.03). Design 11 achieved the highest mean aggregated item-level score (M = 101.29, SD = 1.07), corresponding to the highest overall quality coefficient of 92.08%. This was followed by Design 6 (M = 99.71, SD = 1.07; quality coefficient = 90.65%) and Design 9 (M = 99.43, SD = 1.45; quality coefficient = 90.39%). Design 10 recorded the lowest overall quality coefficient (79.55%).

Table 14. Descriptive statistics and quality coefficients for the overall evaluation.

The descriptive statistics for each design were calculated across the 14 aggregated item-level scores corresponding to the seven aesthetic-quality items and seven economic-potential items. Each item-level score could reach a maximum of 110 points because it represents the combined responses of 22 specialists (22 × 5). The quality coefficient was calculated as (M/110) × 100. For example, Design 11 obtained a mean aggregated item-level score of 101.29, corresponding to a quality coefficient of 92.08% (101.29/110 × 100). The original 70-point maximum applies to the combined 14-item questionnaire score of an individual specialist, whereas the 110-point denominator applies to the aggregated item-level scores used in the statistical analysis.

The results presented in Table 14 indicate variation in the overall evaluations of the proposed handbag designs. Design 11 achieved the highest mean aggregated item-level score (M = 101.29, SD = 1.07) and the highest quality coefficient (92.08%), ranking first among the proposed designs. Design 6 ranked second, with a quality coefficient of 90.65%, followed by Design 9, with 90.39%. Design 3 also received a relatively high overall quality coefficient of 89.81%.

At the lower end of the ranking, Design 10 recorded the lowest overall quality coefficient (79.55%), followed by Design 14 (79.61%) and Design 7 (81.95%). The remaining designs obtained quality coefficients ranging from 82.01 to 87.85%.

The statistically significant ANOVA result, F(13, 182) = 45.816, p < 0.001, demonstrates that the overall aggregated item-level evaluations differed significantly among the 14 proposed designs. Design 11 received the highest overall evaluation, whereas Design 10 received the lowest. These results provided the basis for identifying the highest-ranked designs for subsequent practical implementation using 3D printing technology (Figure 8).

5.2.4 Fourth: comparison of the evaluation dimensions

To examine whether specialists’ evaluations differed between the two dimensions used to assess the proposed handbag designs, the aesthetic quality of women’s handbag design and the perceived economic potential of applying 3D printing technology were compared. The results are presented in Table 15.

Table 15. Analysis of variance of specialists’ evaluations across the two assessment dimensions.

For this comparison, the analysis was based on the aggregated item-level scores described previously. Each dimension comprised seven items, and each item-level score represented the aggregated responses of the 22 specialists. Therefore, each item had a maximum possible aggregate score of 110 points (22 specialists × 5 points). The analysis included 98 aggregated item-level observations for each dimension (14 designs × 7 items), for a total of 196 observations.

As shown in Table 15, the analysis indicated that the difference between the two evaluation dimensions was not statistically significant, F(1, 194) = 1.989, p = 0.160. Thus, there was no statistically significant evidence that specialists evaluated the aesthetic-quality and perceived economic-potential dimensions differently. Although the economic-potential dimension had a slightly higher descriptive mean, this difference should not be interpreted as evidence of statistical superiority.

Table 16 presents the descriptive statistics and quality coefficients for the two evaluation dimensions. The perceived economic potential of applying 3D printing obtained the higher descriptive mean (M = 95.05, SD = 4.78) and quality coefficient (86.41%), whereas the aesthetic quality of the handbag designs recorded a mean of 94.04 (SD = 5.24) and a quality coefficient of 85.49%. The overall mean across the two dimensions was 94.55 (SD = 5.03).

Table 16. Descriptive statistics and quality coefficients for the evaluation dimensions.

The means reported in this table represent aggregated item-level scores rather than raw scores on the 35-point dimension scale. Each dimension comprised seven items, and each item-level score represented the aggregated responses of 22 specialists, with a maximum possible value of 110 points (22 × 5). Quality coefficients were calculated by dividing the mean aggregated item score by 110 and multiplying by 100. Accordingly, the aesthetic-quality mean of 94.04 corresponds to a quality coefficient of 85.49%, while the economic-potential mean of 95.05 corresponds to 86.41%. The overall mean represents the combined descriptive mean across the two dimensions.

Although the economic-potential dimension ranked slightly higher descriptively, the non-significant ANOVA result indicates that this difference was not statistically significant. Therefore, the results do not provide statistical evidence that specialists evaluated one dimension more favorably than the other.

5.2.5 Overall ranking of the proposed designs

To identify the designs with the strongest overall evaluations, the quality coefficients obtained for the two evaluation dimensions were considered jointly. As shown in Table 17, Design 11 achieved the highest overall quality coefficient (92.08%), followed by Design 6 (90.65%) and Design 9 (90.39%). Conversely, Design 10 recorded the lowest overall quality coefficient (79.55%), followed by Design 14 (79.61%).

Table 17. Overall ranking of the proposed designs according to quality coefficients.

The overall quality coefficient for each design was calculated as the arithmetic mean of its aesthetic-quality and economic-potential quality coefficients. For example, the overall coefficient for Design 11 was calculated as (91.95 + 92.21)/2 = 92.08%.

The overall ranking demonstrates that Design 11 performed consistently well across both evaluation dimensions, achieving the highest quality coefficients for aesthetic quality (91.95%) and perceived economic potential (92.21%). Design 6 ranked second overall, with an overall quality coefficient of 90.65%, while Design 9 ranked third, with 90.39%. Based on these descriptive quality coefficients, Designs 11 and 6 were identified as the two highest-ranked alternatives and were subsequently selected for practical implementation using 3D printing technology.

Overall, the findings indicate that the proposed handbag designs received generally favorable specialist evaluations across both aesthetic quality and perceived economic potential. However, considerable variation was observed among the individual designs. Design 11 achieved the highest overall quality coefficient, whereas Design 10 received the lowest. The comparison between the two evaluation dimensions did not reveal a statistically significant difference, indicating that the observed difference between their descriptive means should not be interpreted as evidence that one dimension was statistically superior to the other.

Figure 9 presents the quality coefficients of the two highest-ranked handbag designs across the three reported evaluation measures: aesthetic quality, perceived economic potential of 3D printing, and overall evaluation. Design 11 recorded quality coefficients of 91.95, 92.21, and 92.08%, respectively, whereas Design 6 recorded 91.04, 90.26, and 90.65%, respectively. Across the three measures and the two selected designs, the quality coefficients ranged from 90.26 to 92.21%, indicating consistently high specialist evaluations of the two highest-ranked designs.

These results provide the basis for selecting Designs 11 and 6 for subsequent fabrication and functional-performance assessment. The subsequent analysis therefore examined the functional performance of the two selected prototypes after their fabrication using 3D printing technology.

Figure 10 illustrates the quality-factor results for the lowest-performing proposed handbag designs in relation to the application of 3D printing. The radar chart compares the three main evaluation dimensions: aesthetics, foundations, and design elements; the economic potential of using 3D printing; and the overall evaluation. The results indicate that these designs received comparatively lower quality-factor scores across the evaluated dimensions, with values concentrated within the range of approximately 78.0–80.5. The aesthetic dimension recorded the highest value, whereas the economic dimension showed the lowest evaluation. The overall evaluation was also relatively low, indicating that specialists assessed these designs less favorably than the higher-performing proposed designs.

5.2.6 Selection of the highest-ranked designs

The overall evaluation revealed statistically significant differences among the 14 proposed handbag designs when aesthetic quality and the perceived economic potential of applying 3D printing technology were considered jointly, F(13, 182) = 45.816, p < 0.001. The overall quality coefficients ranged from 79.55 to 92.08%, indicating variation in specialists’ overall evaluations of the proposed designs.

Based on the overall quality coefficients, Design 11 achieved the highest evaluation (92.08%), followed by Design 6 (90.65%). As shown in Table 18, these two designs were therefore selected for practical implementation using 3D printing technology and for subsequent assessment of their functional performance.

Table 18. Quality coefficients of the highest-ranked proposed designs.

The overall quality coefficient represents the arithmetic mean of the aesthetic-quality and perceived economic-potential quality coefficients for each design.

Designs 11 and 6 were selected because they had the highest observed overall quality coefficients across the two assessment dimensions. Following fabrication, the two implemented prototypes were evaluated using the Functional Performance Questionnaire (FPQ).

5.2.7 Fifth: functional performance of the 3D-printed handbag prototypes

The functional-performance assessment evaluated the suitability of the two selected handbag prototypes after fabrication using 3D printing technology. The assessment focused on the six functional characteristics specified in the Functional Performance Questionnaire (FPQ), including structural suitability, appearance retention, closure performance, durability, service-life potential, and ease of care and maintenance.

The FPQ comprised six items rated on a five-point Likert scale. Consistent with the scoring procedure used for the Design Evaluation Questionnaire, the responses to each FPQ item were aggregated across the 22 specialists. Thus, each item-level aggregate score had a maximum possible value of 110 points (22 specialists × 5 points). For each fabricated prototype, the six FPQ items therefore produced six aggregated item-level scores. Accordingly, the functional-performance analysis comprised six observations for each prototype and 12 observations in total, corresponding to the six FPQ items evaluated for each of the two implemented designs.

An ANOVA was conducted to determine whether the functional-performance evaluations differed between Designs 6 and 11. The results are presented in Table 4.

The analysis showed that the difference between the two implemented designs was not statistically significant, F(1, 10) = 2.149, p = 0.173. Therefore, there was insufficient statistical evidence to conclude that Designs 6 and 11 differed significantly in their functional-performance evaluations.

Table 19 presents the descriptive statistics and quality coefficients for the two implemented prototypes. Design 11 obtained the higher descriptive functional-performance mean (M = 96.83, SD = 3.49) and quality coefficient (88.03%), whereas Design 6 obtained a mean of M = 93.83 (SD = 3.60) and a quality coefficient of 85.30%. The combined descriptive mean was M = 95.33 (SD = 3.73).

Table 19. Descriptive statistics and quality coefficients for the functional performance of the implemented designs.

The means represent aggregated item-level FPQ scores. Each FPQ item was aggregated across the 22 specialists, resulting in a maximum possible item-level score of 110 points. Quality coefficients were calculated as (M/110) × 100. Accordingly, the mean of 93.83 for Design 6 corresponds to 85.30%, and the mean of 96.83 for Design 11 corresponds to 88.03%. The six observations per design correspond to the six FPQ items rather than six individual specialist respondents.

Although Design 11 received a higher descriptive functional-performance evaluation than Design 6, the difference was not statistically significant. Accordingly, both implemented prototypes received favorable functional-performance evaluations, with no statistically significant difference between them.

Descriptively, the higher evaluation obtained by Design 11 may be associated with its practical characteristics, including its suitability for carrying personal belongings, flexibility in carrying options, and coordination among the PLA filament, leather, and Sadu fabric components. Design 6 also received a favorable evaluation, although its smaller size and more conventional form may have limited its perceived versatility for different uses.

5.3 Hypothesis assessment

The functional-performance results did not provide statistically significant evidence of a difference between the two implemented handbag designs. Although Design 11 received a higher descriptive mean (M = 96.83) and quality coefficient (88.03%) than Design 6 (M = 93.83; 85.30%), the difference was not statistically significant, F(1, 10) = 2.149, p = 0.173. Accordingly, the hypothesis predicting a statistically significant difference in the functional performance of the two implemented designs was not supported.

5.3.1 Overall findings and hypothesis assessment

Taken together, the findings indicate generally favorable specialist evaluations of the proposed handbag designs across the two assessment dimensions: aesthetic quality and perceived economic potential of applying 3D printing technology. The overall quality coefficients ranged from 79.55 to 92.08%, indicating variation in the specialists’ evaluations of the 14 proposed designs.

The overall evaluation revealed a statistically significant difference among the 14 proposed designs, F(13, 182) = 45.816, p < 0.001. Design 11 achieved the highest overall quality coefficient (92.08%), followed by Design 6 (90.65%) and Design 9 (90.39%). Based on their highest overall quality coefficients, Designs 11 and 6 were selected for fabrication using 3D printing technology and subsequent functional-performance assessment.

At the individual-dimension level, statistically significant differences were also observed among the 14 proposed designs in both aesthetic quality, F(13, 84) = 36.082, p < 0.001, and perceived economic potential of 3D printing, F(13, 84) = 19.680, p < 0.001. These findings indicate that specialists’ evaluations varied significantly across the proposed designs on both assessment dimensions.

Conversely, the comparison between the two assessment dimensions did not reveal a statistically significant difference, F(1, 194) = 1.989, p = 0.160. Although perceived economic potential obtained a slightly higher descriptive mean (M = 95.05, SD = 4.78) than aesthetic quality (M = 94.04, SD = 5.24), this difference was not statistically significant. Therefore, the results do not provide sufficient evidence to conclude that either dimension was rated significantly higher than the other.

Following fabrication, both selected prototypes received favorable functional-performance evaluations. Design 11 obtained a higher descriptive mean (M = 96.83, SD = 3.49) and quality coefficient (88.03%) than Design 6 (M = 93.83, SD = 3.60; quality coefficient = 85.30%**). However, the difference between the two prototypes was not statistically significant, F(1, 10) = 2.149, p = 0.173. Thus, although Design 11 received a higher descriptive evaluation, the statistical results do not support a significant functional-performance advantage of Design 11 over Design 6.

Overall, the findings indicate that the proposed handbag designs differed significantly in specialists’ evaluations of aesthetic quality, perceived economic potential, and overall evaluation. At the same time, the two selected prototypes received favorable functional-performance evaluations with no statistically significant difference between them. These findings provide evidence of specialist acceptance of the proposed designs and prototypes, but they should not be interpreted as direct evidence of actual economic profitability, environmental sustainability, consumer acceptance, or long-term mechanical performance, as these outcomes were not directly measured in the present study.

5.3.2 Summary of statistical hypothesis testing

Table 20 summarizes the statistical tests conducted to assess the differences specified in the study hypotheses. It presents the statistical test, degrees of freedom, significance level, and corresponding decision.

Table 20. Summary of statistical hypothesis testing.

The statistical findings indicate that the 14 proposed designs differed significantly in specialists’ evaluations of aesthetic quality, perceived economic potential, and overall evaluation. Design 11 achieved the highest overall quality coefficient (92.08%), followed by Design 6 (90.65%) and Design 9 (90.39%). These results provided the basis for selecting Designs 11 and 6 for practical fabrication and subsequent functional-performance assessment.

However, the comparison between the two assessment dimensions was not statistically significant, indicating that the specialists’ evaluations of aesthetic quality and perceived economic potential were statistically comparable. Furthermore, the functional-performance comparison between the two fabricated prototypes did not reveal a statistically significant difference. Although Design 11 obtained higher descriptive values than Design 6, the available evidence does not support concluding that Design 11 had superior functional performance.

6 Conclusion

This study examined the application of 3D printing as a digital fabrication approach for developing women’s handbags incorporating Saudi heritage-inspired design elements. By combining 3D-printed structures with Sadu-inspired textile elements and complementary materials such as leather, the study explored a hybrid design approach that brought together technological innovation, cultural identity, aesthetic expression, and functional considerations within the product-development process.

The findings showed that the 14 proposed handbag designs received generally favorable specialist evaluations. Statistically significant differences were identified among the designs in aesthetic quality, perceived economic potential of applying 3D printing, and overall evaluation. Design 11 achieved the highest overall quality coefficient (92.08%), followed by Design 6 (90.65%). These two designs were subsequently fabricated using 3D printing technology and subjected to functional-performance evaluation.

The comparison between the two assessment dimensions did not reveal a statistically significant difference. Although the perceived economic-potential dimension had a slightly higher descriptive mean than the aesthetic-quality dimension, this difference was not statistically significant. The findings therefore suggest that the two dimensions contributed comparably to the specialists’ overall assessment of the proposed designs.

Following fabrication, both selected prototypes received favorable functional-performance evaluations. Design 11 obtained a higher descriptive functional-performance score and quality coefficient than Design 6; however, the difference was not statistically significant. Accordingly, the findings do not support the conclusion that Design 11 had a statistically superior functional-performance level compared with Design 6.

From a cultural-design perspective, the study illustrates the potential of digital fabrication to reinterpret heritage-inspired design elements within contemporary fashion accessories. Rather than reproducing traditional Sadu products directly, heritage-related motifs, patterns, textures, and material characteristics can be incorporated into contemporary handbag forms. Combining 3D-printed components with textile and leather elements also shows how different materials can be assigned complementary structural, aesthetic, tactile, and functional roles.

The findings also suggest potential applications of 3D printing for customized and small-scale fashion-product development. However, the present study did not directly measure material efficiency, environmental impact, production cost, profitability, recyclability, or lifecycle performance. Therefore, the favorable specialist evaluations of perceived economic potential should not be interpreted as direct evidence that the proposed products are economically viable or environmentally sustainable. The sustainability implications of 3D-printed fashion products depend on factors such as material sourcing, energy consumption, production conditions, durability, material recovery, recycling pathways, and end-of-life management.

Overall, the study provides evidence that 3D printing can be used to develop contemporary handbag prototypes incorporating Saudi heritage-inspired design elements and that such prototypes can receive favorable evaluations from specialists in relevant fields. The study therefore contributes to the emerging intersection of digital fabrication, contemporary fashion design, and cultural heritage-inspired product development.

Future research should extend these findings by examining consumer acceptance, larger and more diverse evaluation samples, objective mechanical and ergonomic performance, detailed production-cost analysis, lifecycle environmental assessment, material efficiency, production scalability, durability, and end-of-life management. Such investigations would provide stronger evidence regarding the commercial, functional, and environmental potential of heritage-inspired 3D-printed fashion products.

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Footnotes

Edited by: Jayakrishna Kandasamy, Vellore Institute of Technology, India

Reviewed by: Kushendarsyah Saptaji, Sampoerna University, Indonesia

Stefan Lie, University of Technology Sydney, Australia