Product Design Method Research Articles

An enhanced multidimensional requirement oriented quality function deployment method for sustainable self service machine design

Self-service machines provide round-the-clock access to various services, enhancing operational efficiency, reducing waiting times, and minimizing human errors. However, their design has traditionally prioritized business functionality and user experience, with minimal attention to sustainability principles. As finite resources and environmental concerns gain prominence, embedding sustainability into self-service machine design is crucial for promoting resource efficiency, environmental protection, and social responsibility. Current sustainable product design methods tend to focus on environmental features, often overlooking the multidimensional requirements necessary for a balanced approach. Addressing this gap, this study proposes an enhanced multidimensional requirement-oriented quality function deployment method, which uses multiple one-dimensional quality of houses to independently process requirements across different dimensions. This approach effectively reduces the complexity associated with traditional quality function deployment, enabling a more comprehensive and strategically aligned design process. By prioritizing key sustainability dimensions, this method offers a robust framework for developing sustainable self-service machines, aligning design outcomes with sustainability goals.

Research on product design priority allocation based on user characteristics classification

In order to rationally define the product usability demand preference and its priority level to improve the user experience, a product design priority allocation method based on user characteristic classification is proposed. The Pearson correlation coefficient is integrated into the finite rationality hypothesis model to classify user characteristics, and the factors influencing the phenomenon of divergence between user needs and behaviors are screened according to the Pearson correlation coefficient and used as the basis for the classification of characteristic users. Then, we constructed a product usability evaluation and analysis system mainly based on the hierarchical analysis method (AHP) from the three dimensions of product attributes, symbolic elements, and human-computer factors, and quantitatively analyzed the elements of product features, explored the priorities of different featured users for the elements of product design, and controlled the demand direction of featured users in the process of choosing and using the products, so that we could enhance the experience of product usability based on this method. This paper takes female protective clothing as an example, verifies the effectiveness of the method, and provides a product design prioritization method for female protective clothing and other product design and development.

A Needs-Based Design Method for Product–Service Systems to Enhance Social Sustainability

A Needs-Based Design Method for Product–Service Systems to Enhance Social Sustainability

Research on the whole life cycle attribute decision method for gearbox product design based on WLS and TOPSIS

Research on the whole life cycle attribute decision method for gearbox product design based on WLS and TOPSIS

Data-driven demand analysis and design reliability study of critical components of complex products.

Distinguished from the traditional general framework of product design, under the background of digital intelligence, the complex product design method presents the characteristics of rapid iteration and high degree of integration, and adopts the simulation and modeling technology, advanced production methods, etc. to further improve the quality and reliability of complex product design. Therefore, the demand analysis and design reliability study of critical components of complex products need to consider the sustainability, resources and economy of design, manufacturing and service. In this paper, starting from the product requirement analysis, the Kano-QFD model is used to clarify the requirement identification path of the critical components of complex products and ensure that the quality characteristics of the critical components of complex products are consistent with the customer requirements. The multi-dimensional characteristics of product design parameters, manufacturing process and quality are integrated to construct a design manufacturing analysis (DMA) model, which it's based design reliability analysis method for critical components of complex products. Finally, the method proposed in this article was validated by taking the demand analysis and design reliability of critical components of automotive engines as an example. The study shows that the method proposed in this paper is highly compatible with the practice of complex product design and manufacturing at the early stage, and the method proposed in this paper also can provide product design and quality management reference for the research and development and manufacturing personnel of complex products to meet the changing needs and challenges of complex products.

Research on driving factors and influencing mechanism of consumer behavior in fashion management

This paper aims to investigate the underlying causes and mechanisms that drive consumer behaviours in the field of fashion management. Firstly, it examines the impact of fashion trends, popular components, social influences, reference groups, personal values, lifestyle, psychological motivation, perception, eco-nomic variables, purchasing power, cultural background, and geographical dif-ferences on consumer behaviour. Then it examines the impact of fashion man-agement on customer cognition, emotion, and behaviour, specifically through product design, marketing strategy, and other methods. In addition this study examines and validates the amount of spontaneous consumption among local people using data analysis. Furthermore, it analyses the elements that drive and the mechanisms that influence consumer behaviours in fashion management. Regarding the determinants, the study posits that consumer behaviours is im-pacted by five factors: fashion trends and prevailing elements, social influences and reference groups, economic factors and personal values, cultural back-ground, and geographical disparities. This research examines the influence mechanism by considering consumer cognition and decision-making process, emotional drive and experiential marketing, social media and online word of mouth, brand image and positioning strategy, and consumer loyalty and brand relationship. Its goal is to offer guidance for fashion enterprises in implementing fashion management practices that are rooted in consumer behaviours.

Research on Evaluation Methods of Complex Product Design Based on Hybrid Kansei Engineering Modeling

The field of complex product design evaluation can attract high ambiguity due to difficulties in establishing indicators and the subjectivity of expert evaluation scoring. Indeed, traditional Kansei Engineering (KE) relies on user requirements and feedback for design evaluation, which may not fully and effectively validate the design evaluation results, let alone determine whether they apply to complex products with more evaluation index systems. To overcome these drawbacks, this study proposes an evaluation method based on Hybrid Kansei Engineering (HKE) modeling for complex product design evaluation. HKE modeling consists of two parts, namely Forward Kansei Engineering (FKE) and Backward Kansei Engineering (BKE). In this study, four electric forklift designs are used as an example. The FKE system adopts the multi-attribute decision evaluation method; obtains the evaluation indexes of the forklift product imagery and then establishes the perceptual word collection; constructs the evaluation index system of the forklift via the Analytic Hierarchy Process (AHP); calculates the weights of the evaluation indexes of each level and their rankings; and calculates the final rankings of the four electric forklift design solutions by adopting the Fuzzy Comprehensive Evaluation (FCE) method. The BKE system adopts eye tracking (ET) to extract the attention time, visual attention hotspot, and other eye movement index data, and the Gray Relation Analysis (GRA) method was used to validate the model to derive the ranking, which verifies the effectiveness and scientific validity of the evaluation method. The results of this study show that the two-way evaluation of HKE modeling can effectively avoid subjective factors in product design, improve the scientific nature of the design, and guarantee the logical rigor of the perceptual design procedure.

A Customer Journey Mapping Approach With Mobile Application

Abstract Customer journey mapping (CJM) is a product and service design method that is widely used by design researchers and practitioners. It tracks the customer’s or user’s interactions with products and services during experiences and maps out significant changes in those experiences. While CJM has been praised for its ability to understand customer experiences from their perspectives (i.e., empathy building), it suffers from limitations such as limited sample sizes and cognitive biases, mostly due to its reliance on traditional ethnographic methods such as interviews, observations, and surveys. To address these issues, this article presents an approach to performing CJM with mobile applications (apps) and quantitatively analyzing the gathered data. By dividing CJM into data collection and analytics stages, challenges in each stage are tackled separately. In the data collection stage, a custom-built mobile app is designed to gather information on customer experiences. Then, a two-step data analysis approach is developed to gain insights into those experiences. To demonstrate the approach’s effectiveness in tracking customer experiences, it was applied to the errand experiences of students during the pandemic, and the results were compared with those from a parallel study using traditional CJM approaches. The findings demonstrated the feasibility of the proposed approach in performing CJM and showed that additional insights can be obtained through the proposed approach. This work provides a more effective and objective CJM approach for designers to understand their customers, thereby contributing toward the broader effort to develop reliable empathy-building design methods.

Design and Development of a Foldable Multifunction Travel Hanger Using the Rational Product Design Method

The growing mobility of modern society has increased the demand for innovative travel accessories that offer practicality, efficiency, and multifunctionality. This study seeks to meet these demands by designing a foldable travel hanger that maximizes storage space while ensuring clothing remains neat, addressing the needs of both business and leisure travelers. The design process follows Nigel Cross's Rational Product Design and Development Method, a systematic approach that involves clarifying objectives, defining functions, establishing requirements, identifying key features, generating design alternatives, and selecting the best solutions. The final solution effectively reduces the risk of wrinkled clothing during travel and speeds up the drying process, offering dual benefits. Its compact and user-friendly design ensures long-term usability, making it a sustainable and cost-effective option for modern travelers. The product contributes to enhancing users' professional image by providing reliable and efficient clothing management, thus addressing critical customer needs. The study emphasizes the importance of incorporating user feedback to improve product usability and satisfaction. By aligning technological innovation with consumer needs, this work establishes a benchmark for future travel accessory development, demonstrating how structured design methodologies can resolve user challenges and drive innovation in consumer products. The results of this study show that the Multifunctional Foldable Hanger with a built-in heating system can help smooth out clothes easily during travel, weighing only 700g and featuring 7 folding hinges. With a portable design, heat-resistant ABS material, and 3 adjustable temperature settings, this product innovation has also been tested using von Mises stress analysis to assess its strength.

Determination of key characteristics of seam strength of double thread chain stitch in a superimposed woven fabric seam assembly

This study addresses the challenge of seam failure in men’s casual wear trousers made from woven fabrics, a significant quality issue stemming from reliance on trial and error due to limited knowledge on enhancing seam strength. Focusing on superimposed seams joined by a 401-double thread chain stitch, the research utilizes a 2k factorial experimental design to examine the effects of variables: sewing thread tension (A), sewing thread strength (B), fabric stability (C), stitch density (D), and fabric tensile strength (E) on seam strength. Through this design, which included a single replication for cost and time efficiency, the study analysed 32 treatment combinations to identify significant factors and their optimum levels for maximizing seam strength. Normal probability plots pinpointed significant main effects (C, D, E) and a marginal two-way interaction (CD), revealing A and B as insignificant. Optimal seam strength was achieved by controlling C, D, and E at lower levels. The study’s major contribution lies in delineating the significant factors influencing seam strength, thereby offering a statistical foundation to replace the trial and error method in product design and development. This research underlines the importance of managing key variables to optimize seam strength, and enhance the quality of trousers.

Digital packaging design method of intelligent products based on internet of things technology

Digital packaging design method of intelligent products based on internet of things technology

Optimisation method for product design based on improved genetic algorithm

Optimisation method for product design based on improved genetic algorithm

Optimisation method for product design based on improved genetic algorithm

Optimisation method for product design based on improved genetic algorithm

Application of Information Fusion in Product Packaging Art Design

Application of Information Fusion in Product Packaging Art Design

UPCYCLE PENGEMBANGAN LIMBAH KANTONG SEMEN MENJADI PRODUK FASHION TAS DENGAN MENGGUNAKAN TEKNIK PEWARNAAN SUMINAGASHI

Upcycling is a part of the broader concept of Sustainable Development. Based on statistical data from Asosiasi Semen Indonesia (ASI), the growth of cement production capacity in the last ±5 years from 2020 to 2024 (may) has increased. Judging from the increase in cement production, more cement bag waste will be generated. This research aims to develop environmentally friendly material products with sustainable ideas that optimize the characteristics of cement bag paper waste to have functional and economic value. The product produced is a fashion item, specifically a bag. This research uses a mixed-method approach with product design methods based on design thinking, exploration, and experimentation. This research shows that cement bag waste can be made into upcycled products that have functional and economic value, one of which is made into a bag. The motif coloring technique used is the Suminagashi technique which produces unexpected elements of color and beauty and becomes an aesthetic value in the resulting motif. However, the bag products produced are not 100% environmentally friendly because there are additional complementary components in a bag

Addressing OSH challenges in non-standardized work practices in small-scale FMCG units by introducing context-specific ergonomic pouch/sachet cutting apparatus.

The FMCG manufacturing industry in industrially developing countries operates in a manual or semi-automatic setup, employing a vast labor force. Several non-standardized work activities prevail on the FMCG shop floor and remain prone to safety-related risks involving repetitive motions, forceful exertions, and awkward postures. Among those, the rework of defective pouches/sachets is an unsafe activity of prime concern. It is prone to minor nicks, cuts, and injuries due to inadequate tools being used. It involves sharp cutters/blades and extensive forceful manual hand squeezing, which leads to drudgery and safety concerns. There lies the lack of standardized tools/apparatus for rework activity, and efforts towards its mitigation are required. Current research aims to address occupational safety-related issues in non-standardized rework activity in small-scale FMCG units through an innovative product design approach. An ergo-audit was conducted in eight small-scale FMCG units to identify the prevailing ergonomic stressors and safety concerns. The most critical area of concern, i.e., rework activity, was chosen through card-sorting sessions and discussions held with the stakeholders. An appropriate context-specific apparatus was designed/developed to ensure better safety and occupational health utilizing a systematic product design method involving three phases: initial field survey, design and development, and field trials. The apparatus, which was developed and factory-trialed, was evaluated for productivity improvement and ensuring user compatibility from various human factors' perspectives. In field trials, the developed apparatus was found effective in mitigating safety concerns and various ergonomic stressors associated with FMCG rework.

Design and Analysis of a Three-Phase High-Frequency Transformer for Three-Phase Bidirectional Isolated DC-DC Converter Using Superposition Theorem

Battery energy storage systems based on bidirectional isolated DC-DC converters (BIDCs) have been employed to level the output power of intermittent renewable energy generators and to supply power to electric vehicles. Moreover, BIDCs use high-frequency transformers (HFTs) to achieve voltage matching and galvanic isolation. Various studies have recently been conducted using soft magnetic materials, such as nanocrystalline, amorphous solids, and ferrite, to develop more compact and effective transformers with superior power densities. The HFTs in three-phase BIDCs are composed of three magnetic cores. However, this leads to low power density and high cost. Besides, the three-phase (3P) ferrite core has not been investigated for high-power converters such as 3P-BIDCs. This paper presents the design and development of a 3P-EE ferrite magnetic core for 3P-BIDCs. The area product design method was used to determine the core and winding design. The paper also proposes the use of the superposition theorem in conducting a magnetic circuit analysis to predict the flux density and magnetising inductance of the transformer core. Moreover, the use of the superposition theorem allowed the required air-gap length for balancing the distribution of flux density and magnetizing inductance in the transformer core to be determined. The balanced flux distribution and magnetizing inductance resulted in a uniform core loss and temperature in the transformer. This paper also presents the experimental results of the designed HFT operated in a 300-V, 3-kW 3P-BIDC. The experimental results showed that the proposed HFT achieved a balanced flux density and magnetizing inductance with a high power density and low cost. Moreover, the transformer performed at a maximum efficiency of 98.67%, with a decrease of 3.33 °C in the overall temperature of the transformer as compared to the transformer without air gaps.

Combining style generative adversarial networks with particle swarm optimisation-support vector regression to design affective social robot for public health intervention

In order to improve the attractiveness of social robot serving health interventions in public workspace, we propose a product design method with the combination of Style-generative adversarial network (StyleGAN) model and particle swarm optimisation-support vector regression (PSO-SVR). This paper aims to explore the modelling generation method of social robots for health intervention based on artificial intelligence generated content (AIGC) and a mapping model between the shape characteristics and users’ visual perception based on Kansei Engineering (KE). Firstly, to address the defects of typical KE over-reliance on existing samples, we introduce the StyleGAN model in AIGC to learn and train existing robots’ shape samples and generate new robots’ shape sample images. Secondly, the morphological deconstruction method is used to deconstruct the shape features of the new robot sample. Factor analysis (FA) is also used to reduce dimension and cluster emotional words and establish a Likert scale between the shape features of robots and users’ emotional vocabulary. Finally, particle swarm optimisation-support vector regression (PSO-SVR) is used to establish a mapping model between the shape features of social robots and the emotional images of users, thus obtaining the most attractive shape combination scheme. The research results showed that the StyleGAN model in AIGC can be used to assist industrial designers in creative expression and provide rich sample sources for KE; and the PSO-SVR of machine learning can be used to build a mapping model among users’ visual feelings, emotional images and shape features. In the end, we designed an attractive social robot for public health intervention.

A Product Design Method Based on Functional Similarity

A Product Design Method Based on Functional Similarity

Inspiring Designers’ Innovative Thinking: An Evolutionary Design Method for Product Forms

The product form serves as a crucial information carrier for expressing design concepts and encompasses significant valuable references. During the product iteration process, changes in design subjects, such as designers and decision-makers, result in substantial variability and uncertainty in the direction of product form evolution. To address these issues, an evolutionary design method for product forms based on the gray Markov model and an evolutionary algorithm is proposed in this study. Firstly, quadratic curvature entropy is utilized to quantify historical form features of product evolution. Subsequently, the original data on product form feature evolution are fitted and predicted using the gray Markov model, thereby obtaining the predicted value of the latest generation of product form features, which is determined to be 0.14586. Finally, this study uses this predicted value to construct a fitness function in the framework of an evolutionary algorithm, which in turn identifies next-generation product forms that can stimulate designers’ creative thinking. The method’s application is illustrated using the side outer contour of the Audi A4 automobile as an example. The research findings demonstrate that combining the gray Markov model with an evolutionary algorithm can effectively simulate designers’ understanding of previous generations’ design concepts and achieve stable inheritance of these design concepts during product iteration. This approach mitigates the risk of abrupt changes in design concepts caused by designers and decision-makers due to personal cognitive biases, thereby enhancing product development efficiency.