Product Design Research Articles

Promoting Child Development Through Product Design: A Case Study of Beijing Haileyland Maternity and Baby Products Co., Ltd.

This study aims to explore how Beijing Haileyland Maternity and Baby Products Co., Ltd. promotes the comprehensive development of children through its product design innovation. The article first outlines the importance of product design in the children’s toy industry and emphasizes the key role of innovation in meeting the growth needs of children. By integrating child development theories, product design principles, and innovation theories, this study constructs a multidimensional analytical framework. Using qualitative and quantitative research methods, including market research, user interviews, and product analysis, this paper delves into how Beijing Haileyland’s product design affects children’s cognitive, emotional, and social development. The results show that Beijing Haileyland’s innovative product design not only meets children’s basic entertainment needs but also actively promotes their progress in multiple developmental areas. The paper concludes by discussing the interaction between product design and child development, summarizing Beijing Haileyland’s practices and achievements in product design innovation, and providing valuable insights and suggestions for the future development of the children’s toy industry.

Prompting for products: investigating design space exploration strategies for text-to-image generative models

Abstract Text-to-image models are enabling efficient design space exploration, rapidly generating images from text prompts. However, many generative AI tools are imperfect for product design applications as they are not built for the goals and requirements of product design. The unclear link between text input and image output further complicates their application. This work empirically investigates design space exploration strategies that can successfully yield product images that are feasible, novel and aesthetic – three common goals in product design. Specifically, users’ actions within the global and local editing modes, including their time spent, prompt length, mono versus multi-criteria prompts, and goal orientation of prompts, are analyzed. Key findings reveal the pivotal role of mono versus multi-criteria and goal orientation of prompts in achieving specific design goals over time and prompt length. The study recommends prioritizing the use of multi-criteria prompts for feasibility and novelty during global editing while favoring mono-criteria prompts for aesthetics during local editing. Overall, this article underscores the nuanced relationship between the AI-driven text-to-image models and their effectiveness in product design, urging designers to carefully structure prompts during different editing modes to better meet the unique demands of product design.

Sustainable Considerations in Toy Product Design: Practices of Beijing Haileyland Maternity and Baby Products Co., Ltd.

This paper aims to explore how Beijing Haileyland Maternity and Baby Products Co., Ltd. integrates sustainable considerations into its toy product design to respond to environmental protection and social responsibility demands. By combining literature review, case analysis, and field research, this paper analyzes the company’s practices in material selection, production processes, and product life extension, and assesses the profound impact of these practices on the product, the enterprise, and the entire toy industry. The study finds that Beijing Haileyland Maternity and Baby Products Co., Ltd. has enhanced its product competitiveness and strengthened its corporate social responsibility image by adopting eco-friendly materials, optimizing production processes, and extending product life. This paper further discusses the challenges and opportunities of sustainable design in the toy industry and proposes corresponding policy recommendations and future research directions. Ultimately, the paper summarizes the efforts and achievements of Beijing Haileyland Maternity and Baby Products Co., Ltd. in achieving product design sustainability, providing valuable references and insights for other enterprises.

Towards cognitive intelligence-enabled product design: The evolution, state-of-the-art, and future of AI-enabled product design

Towards cognitive intelligence-enabled product design: The evolution, state-of-the-art, and future of AI-enabled product design

INDUSTRIAL PRODUCT DESIGN OF AN ABACA AND BIO-POLYMER COMPOSITE APPLICATION

Material science has become increasingly important in recent years, driving the de-velopment of new materials for green and sustainable design, and promoting circular economy principles. These innovative materials, composed of a natural fiber reinforcement sourced from renewable origins and a polymer matrix, exhibit promising properties, enhancing competitiveness while mitigating pollution associated with traditional materials. Creating a composite material combining abaca and a bio-based polymer matrix offers a sustainable alternative to non-recyclable petroleum-based polymers, thereby reducing environmental impact. Bio-Polyethylene reinforced with abaca holds significant potential for various applications across automotive, construction, and sports industries. This study focuses on designing an industrial product tailored to the charac-teristics of this composite material. Through comprehensive characterization, including mechani-cal property assessments and simulation-based evaluations, the feasibility of integrating the mate-rial into industrial applications, exemplified by a stackable plastic drawer, is demonstrated. The results highlight the viability of using the composite material to develop sustainable industrial products. Keywords: Bio-Polyethylene, Abaca, Product design, Mechanical properties, 3D Simulation

FRACTAL GEOMETRIES DESIGN FOR THREE-DIMENSIONAL PRINTING: ANALYSIS OF PERFORMANCE AND VIBRATION RESPONSE FOR PRODUCT DESIGN

Additive Manufacturing (AM) has enhanced the development of complex designs and geometries that are difficult or impossible to achieve with conventional manufacturing methods. Therefore, research focused on the analysis of the functional properties related to the behavior conferred by the filling material and the internal structure became especially relevant. In this sense, fractal geometry is one of the most established theories to characterize complex geometries based on repetitive self-similar patterns that allow complex shapes to be described and relate them to mechanical, rheological and morphological properties. The design of fractal microstructures promises the development of advanced materials with improved mechanical properties and multiple functions related to vibration absorption, weight reduction, among others. In relation to the compatibility of elastic materials with three-dimensional printing processes, the study of fractal geometries in terms of geometric design and its correlation with improved mechanical behavior is established as an objective. Several TPU-based fractal samples were designed and tested using compression processes to characterize the behavior of elastic fractal geometries as a function of fractal dimension. Specifically, Sierpinski pyramids-based specimens were designed to explore the influence of fractal dimensions and iterations on the elasticity of the samples. Additionally, a case study was carried out to by using Finite Element Method (FEA) in order to analyze the stress distribution and vibrational behavior based on fractal order. The results demonstrated a notable variation in compression behavior and vibrational behavior depending on the fractal order, highlighting the potential of fractal geometries to enhance mechanical performance in AM applications. Keywords: Fractal Geometries, Product Design, Three-Dimensional Printing, Performance, Thermoplastic Polyurethane.

Circular economy and sustainable manufacturing: a bibliometric analysis

Abstract This study conducts a detailed bibliometric analysis of the research landscape on circular economy and sustainable manufacturing. Using data from the Scopus database, 9,946 publications on “Circular Economy” and 212 publications on both “Circular Economy” and “Sustainable Manufacturing” were identified. The analysis with VOSviewer spanned publication trends from 2006 to July 2024. Key platforms for publication included Sustainability Switzerland, known for its multidisciplinary approach to sustainability challenges, and Lecture Notes in Mechanical Engineering and Procedia CIRP, which were prominent for their contributions to sustainable manufacturing and engineering innovations. These platforms played a pivotal role in disseminating cutting-edge research at the intersection of sustainability and engineering. The study highlighted top-cited works and leading contributors, mainly from India, Italy, and the United Kingdom. A co-occurrence analysis of author keywords identified seven thematic clusters: Sustainable Manufacturing Practices, Sustainable Economic and Environmental Practices, Green and Efficient Manufacturing Processes, Sustainable Manufacturing and Environmental Decision-Making, Industrial Ecology and Sustainable Development, Advanced Sustainable Manufacturing Technologies, and Closed-Loop Manufacturing and Product Design. These findings offered critical insights into emerging research trends and served as a foundational reference for future research and policy-making aimed at promoting sustainability in manufacturing.

The Utilization of Smart Materials in the Design of Children's Products

The Utilization of Smart Materials in the Design of Children's Products

Environmentally friendly process design for furan-based long-chain diester production aiming for bio-based lubricants

The tetrahydrofuran diesters were successfully synthesized, demonstrating wide applicability as replacements for conventional base oils. They also showed a 35% reduction in CO2 emissions, as revealed by LCA analysis.

Prediction accuracy of discrete choice experiments in health-related research: a systematic review and meta-analysis

Discrete choice experiments (DCEs) are increasingly used to inform the design of health products and services. It is essential to understand the extent to which DCEs provide reliable predictions outside of experimental settings in real-world decision-making situations. We aimed to compare the prediction accuracy of stated preferences with real-world choices, as modelled from DCE data. We searched six databases for health-related studies that used DCE to assess external validity and reported on predicted versus real-world choices, up to July 2024. A generalised linear mixed model was used for a meta-analysis to jointly pool the sensitivity and specificity. Heterogeneity was assessed using the I 2 statistic, and sources of heterogeneity using meta-regression. This study is registered with PROSPERO (CRD42023451545). We identified 14 relevant studies, of which 10 were included in the meta-analysis. Most studies were conducted in high-income countries (11/14, 79%) from the European region (9/14, 64%) and analysed using mixed logit models (5/14, 36%). Pooled sensitivity and specificity estimates were 89% (95% CI:77-95, I 2=97%) and 52% (95% CI:32-72, I 2=95%), respectively. The area under the SROC curve (AUC) was 0.81 (95% CI:0.77-0.84). Our meta-regression found that DCEs for prevention-related choices had higher sensitivity than treatment-related choices. DCEs conducted under clinical settings and analysed using the heteroskedastic multinomial logit model, incorporating systematic preference heterogeneity and random opt-out utility, had higher specificity than non-clinical settings and alternative models. DCEs are valuable for capturing health-related preferences and possess reasonable external validity to predict health-related behaviours, particularly for opt-in choices. Contextual factors (e.g., type of intervention, study setting, analysis method) influenced the predictive accuracy. JJO is supported by an Australian National Health and Medical Research Council Emerging Leadership Investigator Grant (GNT1193955). EBG is supported by the Dutch Research Council (NWO-Talent-Scheme-Vidi-Grant No, 09150171910002). YZ is supported by an Australian Government Research Training Program (RTP) scholarship.

Sentiment Analysis of Mobile Phone Reviews Using XGBoost and Word Vectors

Consumer reviews are an important source of data used to judge and examine consumer sentiment, and data mining for reviews of electronic products is an important way to help improve the design of electronic products. The research is based on the consumer reviews of online cell phone e-commerce, The paper constructs a sentiment dictionary in this field based on the Sentiment Oriented Point Mutual Information (SO-PMI) algorithm, and the sentiment weight of the review word vectors. An extreme Gradient Boosting Tree (XGBoost) is used to integrate word vectors and a Large Language Model (LLM) to construct a sentiment recognition model, and finally, a review sentiment index is derived, which unfolds from multiple dimensions to analyze the sentiment tendency in consumer reviews. The empirical analysis shows that the accuracy, recall, area under the curve (AUC), and other validation indexes of the constructed sentiment recognition model are further improved compared with the LLM model, which has a certain application value. When applying the weighted word vector method, the model has been significantly improved compared with the LLM model, the accuracy is increased by 5%, the accuracy is increased by 10%, and the comprehensive accuracy is increased by 2% after the comprehensive application of the two.

The influence of the organic trend on design and implementation of some glass products by free forming

The influence of the organic trend on design and implementation of some glass products by free forming

The Impact of Artificial Intelligence AI in Enhancing Experience Design of Physical Products

The Impact of Artificial Intelligence AI in Enhancing Experience Design of Physical Products

Preface to the proceedings of the 16th international conference on properties and phase equilibria for product and process design (PPEPPD-2023) special issue

Preface to the proceedings of the 16th international conference on properties and phase equilibria for product and process design (PPEPPD-2023) special issue

Recent innovations in interfacial strategies for DLP 3D printing process optimization.

Three-dimensional (3D) printing, also known as additive manufacturing, is capable of transforming computer-aided designs into intricate structures directly and on demand. This technology has garnered significant attention in recent years. Among the various approaches, digital light processing (DLP) 3D printing, which utilizes polymers or prepolymers as the ink, has emerged as the leading new technology, driven by high demand across diverse fields such as customized production, healthcare, education, and art design. DLP 3D printing technology employs cured slices as molding units and is recognized for its potential to achieve both high printing speed and resolution. Recent insights into the DLP printing process highlight its inherent interface transformations between liquid and solid states. This review summarizes key aspects of the printing process, speed, precision, and material diversity optimization, from the view of interfacial interactions between solid and liquid phases which are influenced by resin formation, curing surfaces and light source properties. These interactions include those at the liquid resin-UV pattern interface, the cured structure-curing surface interface, the liquid resin-curing surface interface, and the liquid resin-cured structure interface, each contributing to the unique characteristics of the printed results. Finally, this review addresses the current challenges and limitations of DLP 3D printing, providing valuable insights for future improvements and guiding potential innovations in the field.

Research on green precision manufacturing product design based on integrated thermal science and blockchain technology

Research on green precision manufacturing product design based on integrated thermal science and blockchain technology

Case study of potential design perceptions for 3D printed accessories made of used face masks

<p>This study aimed to explore consumer perceptions and acceptance of potential 3D-printed accessories made from used face masks. Based on the principles of the circular economy, a proposed conceptual framework was developed to determine the role of experiential value in the relationship between product design perception and perceived purchase intention. Data were collected through a web-based survey questionnaire, employing a nationwide convenience sample of consumers via crowdsourcing marketplaces. Among the 899 respondents, 470 were female, and 429 were male, with an average age of 38. A structural equation model was used to test the hypotheses in the proposed conceptual framework. The findings indicated that consumer experience plays a crucial role in significantly enhancing purchase intentions for 3D-printed accessories made from used face masks. Participants identified jewelry, electronic cases, and home decor items (e.g., picture frames) as the top three preferred product categories for 3D printing. Usability, social value, and environmental concerns emerged as the most influential components of consumer experience in driving purchase intentions for 3D-printed accessories. Additionally, the study confirmed the mediating role of consumer experience between design perception and purchase intention. These findings provide opportunities to rethink, redesign, and reimagine environmentally responsible, socially inclusive, and economically viable practices. The development of new 3D printing filaments using recycled plastic-based materials further aligned with 3D-printed accessories. Finally, this study offers a critical bridge between academia and industry, paving the way for a sustainable future through innovation in design and manufacturing.</p>

Innovation of environmental thermal energy management equipment for robot precision industrial manufacturing process: Digital product design

Innovation of environmental thermal energy management equipment for robot precision industrial manufacturing process: Digital product design

Thermal optimization based on the Internet of Things for simulating visual systems in precision manufacturing product design

Thermal optimization based on the Internet of Things for simulating visual systems in precision manufacturing product design

Improving component dimensional accuracy in electron beam powder bed fusion by addressing nonlinear deformations with 3D compensation strategies

ABSTRACT Electron beam powder bed fusion (EB-PBF) is effective for producing complex geometrical components with minimal residual stress because of elevated powder bed temperatures; however, it faces challenges in achieving dimensional accuracy due to nonlinear shrinkage. We systematically investigated the thermal shrinkage behaviour of large-scale EB-PBF components and developed 3D nonlinear compensation strategies. A thermal-mechanical model was developed to simulate residual stress and deformation during printing and cooling, revealing that nonlinear shrinkage is linked to thermal history, stress distribution, and material properties. The proposed method improved dimensional accuracy, reducing maximum errors from 1.81 mm to 0.16 mm, meeting industrial tolerances for components sized 77 × 48 × 326 mm. Hereafter, we developed a comprehensive digital workflow encompassing topology optimisation and compensation, validated through a case study on a topology-optimised satellite component. This approach enhances manufacturing precision and significantly reduces trial-and-error iterations in product design, resulting in substantial time and cost savings.