Search Results (168)

With globalization and technology advancement, traditional teaching models are facing challenges due to the diverse needs of modern learners. It is necessary to enhance learner engagement and motivation, and incorporating Internet of Things (IoT)-assisted teaching tools has become a major concern for educators. However, the time it takes to develop new teaching tools and integrate IoT technology must be shortened by combining educational content with game mechanics seamlessly. Therefore, we developed a gamified teaching model by incorporating IoT technology. We used the “System, Indicators, Criteria” framework to develop a three-tiered board game evaluation and development model. Based on this framework, a teaching tool was designed to provide personalized learning experiences with IoT technology. The tool provides abstract knowledge, fosters interaction and collaboration among learners, and thus enhances engagement. To ensure a rigorous design and evaluation process, we employed quality function deployment (QFD), analytic hierarchy process (AHP), and fuzzy comprehensive evaluation (FCE). The developed model facilitates the integration of IoT technology with innovative design concepts and enhances the application value of teaching tools in education. The model also enhances intelligence, interactivity, and creativity for traditional education to revitalize learning experiences. Full article

Background/Objectives: This study aimed to identify the functional adaptations that enable competitive performance in a Paralympic cyclist with optimized bilateral transtibial prostheses compared to a conventional cyclist. Additionally, it describes the development of the prosthesis, designed through a user-centered engineering process incorporating Quality Function Deployment (QFD), Computer-Aided Design (CAD), Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), and topological optimization, with the final design (Design 1.4) achieving optimal structural integrity, aerodynamic efficiency, and anatomical fit. Methods: Both athletes performed a progressive cycling test with 50-watt increments every three minutes until exhaustion. Cardiorespiratory metrics, lactate thresholds, and joint kinematics were assessed. Results: Although the conventional cyclist demonstrated higher Maximal Oxygen Uptake (VO₂max) and anaerobic threshold, the Paralympic cyclist exceeded 120% of his predicted VO₂max, had a higher Respiratory Exchange Ratio (RER) [1.32 vs. 1.11], and displayed greater joint ranges of motion with lower trunk angular variability. Lactate thresholds were similar between athletes. Conclusions: These findings illustrate, in this specific case, that despite lower aerobic capacity, the Paralympic cyclist achieved comparable performance through efficient biomechanical and physiological adaptations. Integrating advanced prosthetic design with individualized evaluation appears essential to optimizing performance in elite adaptive cycling. Full article

Facing the global competitive market and ever-changing customer demands, manufacturers must navigate intense competition and uncertain demand while striving to enhance customer satisfaction. As a result, the demand for customized products has become a crucial design consideration. To respond accurately and swiftly in a competitive market, manufacturers must focus on customer needs, analyze market trends and competitor information, and leverage data analysis as a reference for new product development and design. This study presents a new product development model by integrating quality function deployment (QFD), decision-making trial and evaluation laboratory (DEMATEL), analytic network process (ANP), and fuzzy set theory. It first uses a 2-tuple fuzzy DEMATEL to identify significant interrelationships among factors. A revised house of quality (HOQ) is then constructed to map relationships among customer requirements (CRs), engineering requirements (ERs), and the influences of CRs on ERs. To address uncertainty in human judgment, fuzzy set theory is incorporated into the ANP. The integrated model can determine the relative importance of the ERs. The proposed model is applied to touch panel development, and the results are recommended to the R&D team for new product development. Full article

With the advancement of low-carbon and sustainable development initiatives, electric scooters, recognized as essential transportation tools and leisure products, have gained significant popularity, particularly among young people. However, the current electric scooter market is plagued by severe product similarity. Once the initial novelty fades for users, the usage frequency declines, resulting in considerable resource wastage. This research collected user needs via surveys and employed the KJ method (affinity diagram) to synthesize fragmented insights into cohesive thematic clusters. Subsequently, a hierarchical needs model for electric scooters was constructed using analytical hierarchy process (AHP) principles, enabling systematic prioritization of user requirements through multi-criteria evaluation. By establishing a house of quality (HoQ), user needs were transformed into technical characteristics of electric scooter products, and the corresponding weights were calculated. After analyzing the positive and negative correlation degrees of the technical characteristic indicators, it was found that there are technical contradictions between functional zoning and compact size, lightweight design and material structure, and smart interaction and usability. Then, based on the theory of inventive problem solving (TRIZ), the contradictions were classified, and corresponding problem-solving principles were identified to achieve a multi-functional innovative design for electric scooters. This research, leveraging a systematic industrial design analysis framework, identified critical pain points among electric scooter users, established hierarchical user needs through priority ranking, and improved product lifecycle sustainability. It offers novel methodologies and perspectives for advancing theoretical research and design practices in the electric scooter domain. Full article

Background/Objectives: Sepsis-induced cardiomyopathy (SIC) is a serious clinical disorder with a high death rate. Qifu decoction (QFD) is a renowned traditional Chinese medicine with documented pharmacological actions, such as anti-inflammatory, anti-oxidant and anti-apoptosis activities, and it has good therapeutic effects on cardiovascular diseases. This study aimed to reveal the cardioprotective effects and underlying mechanisms of QFD against SIC. Methods: Electrocardiography, histopathological examination, and biochemical indicator determination were carried out to investigate the cardioprotective effects of QFD in the treatment of LPS-induced SIC mice. Metabolomics and network pharmacology strategies were employed to preliminarily analyze and predict the mechanisms of QFD against SIC. Molecular docking and Western blot were further applied to validate the core targets and potential pathways for the treatment of SIC in in vitro and in vivo models. Results: It was found that QFD considerably enhanced cardiac function; attenuated myocardial injury; and reduced the serum levels of LDH, CK-MB, IL-1β, and TNF-α by 28.7%, 32.3%, 38.6%, and 36.7%, respectively. Metabolomic analysis showed that QFD could regulate seven metabolic pathways, namely, glutathione metabolism; alanine, aspartate, and glutamate metabolism; arachidonic acid metabolism; glycerophospholipid metabolism; purine metabolism; sphingolipid metabolism; and fatty acid metabolism. Network pharmacology suggested that the anti-SIC effect of QFD may be mediated through the TNF, toll-like receptor, NOD-like receptor, NF-κB, and PPAR signaling pathways. Additionally, 26 core targets were obtained. Molecular docking revealed that active ingredients such as formononetin, kaempferol, quercetin, and (R)-norcoclaurine in QFD had a high affinity for binding to PPARα and TLR4. Further Western blot validation indicated that QFD could regulate the protein levels of NLRP3, TLR4, NF-κB, IL-6, TNF-α, COX2, sPLA2, PPARα, CPT1B, and CPT2. Conclusions: This study demonstrates that QFD can alleviate SIC by suppressing the TLR4/NF-κB/NLRP3 inflammatory pathway and modulating impaired FAO through the activation of the PPARα/CPT pathway, highlighting QFD as a promising candidate drug for SIC treatment. Full article

In the context of the rapid digital transformation of the catering industry, the design of ordering interfaces—key hubs of human–computer interaction—has become critical to user service quality and brand competitiveness, especially in terms of usability, visual appeal, and emotional resonance. Based on a human–computer interaction design framework, this study proposes a dual-path optimization model integrating user demand mapping and conflict resolution to synergize explicit need translation with innovative design problem solving. The model employs KE to capture implicit user needs, applies AHP to construct a weighted design element system, and uses QFD to establish a matrix linking user needs with technical attributes. To address contradictions among design elements, TRIZ is introduced to resolve conflicts between functional redundancy and interaction efficiency. Additionally, generative AI tools such as MidJourney are incorporated to accelerate concept generation and improve innovation. Based on user evaluations and controlled experiments, the optimized design demonstrates measurable improvements in task efficiency and visual appeal. Overall, the dual-path approach effectively bridges the gap between vague user needs and concrete design solutions, achieving a balanced integration of functionality, aesthetics, and interactivity. The proposed model overcomes the limitations of experience-driven design by offering a systematic methodology encompassing demand analysis, technological transformation, conflict resolution, and intelligent generation, with practical value for enhancing the user experience of digital service touchpoints in the catering sector. Full article

Production involves processes such as raw material extraction, energy consumption, and waste management, which can lead to significant environmental consequences. Therefore, supplier selection based not only on technical performance but also on environmental sustainability criteria has become a fundamental component of eco-friendly manufacturing strategies. Moreover, in the selection of electric vehicle batteries, it is essential to consider customer demands alongside environmental factors. Accordingly, selected suppliers should fulfill company expectations while also reflecting the “voice” of the customer. The objective of this study is to propose an integrated approach for green supplier selection by taking into account various environmental performance requirements and criteria. The proposed approach evaluates battery suppliers with respect to both customer requirements and green criteria. To construct the relational structure, the DEMATEL method was employed to analyze the interrelationships among customer requirements (CRs). Subsequently, the Quality Function Deployment (QFD) model was used to establish a central relational matrix that captures the degree of correlation between each pair of supplier selection criteria and CRs. Finally, to evaluate and rank alternative suppliers, the Interval Type-2 Fuzzy VIKOR (IT2 F-VIKOR) method was applied. The hybrid approach proposed by us, integrating DEMATEL, QFD, and IT2 F-VIKOR, offers significant improvements over traditional methods. Unlike previous approaches that focus independently on customer preferences or supplier criteria, our model provides a unified evaluation by considering both dimensions simultaneously. Furthermore, the use of Interval Type-2 Fuzzy Logic enables the model to better manage uncertainty and ambiguity in expert judgments, yielding more reliable results compared to conventional fuzzy approaches. Additionally, the applicability of the model has been demonstrated through a real-world case study, confirming its practical relevance and robustness in the selection of green suppliers for electric vehicle battery procurement. Full article

Sustainable development requires manufacturers to deliver products that are not only of good quality but also environmentally friendly. The materials used play a crucial role in product manufacturing. They not only directly determine quality but also influence the environment throughout the product’s life cycle. Therefore, the aim was to develop an innovative approach based on the modelling of the relationship between materials and product quality within the framework of the sustainable design of alternative product solutions. The model framework includes selected elements of Quality Functional Development (QFD) and the first stage of life cycle assessment (LCA), namely, material acquisition and extraction. Its novelty lies in supporting the modelling process with life cycle data on materials characterised by their environmental burden. This modelling is based on their potential negative environment impact. Using this foundation, it becomes possible to consider alternative design solutions in terms of both quality (i.e., fulfilling customer satisfaction during use) and environmental performance (i.e., reducing the negative impact throughout the life cycle). The proposed modelling process was also tested, demonstrating its effectiveness in the material analysis of products. The solution can be applied to any material, and, with minor modifications, adapted to various product types. Full article

This paper tackles the logistics dilemma of how to meet customer expectations while at the same time respecting the internal processes and financial interests of the company and ensuring long-term sustainability. In this paper, integrated Quality Function Deployment (QFD) and Balanced Scorecard (BSC) techniques developed a method for the structured planning of logistics strategies. BSC, combined with QFD, gives the opportunity not only to “translate” the voice of the customer but also to focus on the company’s interests from four perspectives. For example, for products, we evaluated the interactions between different expectations, and the focus was on the disputes that arise during the expectations. The result of this paper is that Extended QFD provides a new method to formulate the various requirements. This method is suitable for creating a sustainable logistics strategy. Full article

With the increasing diversification of modern home textile design (HTD), the integration of traditional cultural elements has become an important trend. This study investigates the impact of symmetry in traditional patterns on the optimization of home textile product design and examines its role in consumer acceptance. First, the affinity diagram method was employed to collect core affective vocabularies. Based on a selection of home textile products incorporating traditional patterns available in the market, a questionnaire was developed to solicit consumers’ evaluations of these affective descriptors. Principal component analysis (PCA) was conducted to extract key perceptual dimensions, with particular emphasis on the influence of pattern symmetry on consumer perception. Subsequently, the Fuzzy Analytic Hierarchy Process (FAHP) was applied to determine the relative weights of the affective terms. Incorporating expert input, five representative traditional patterns from the Homespun Fabric of Jiangnan (HFoJ) were selected and reinterpreted with a focus on symmetrical design. Through the Quality Function Deployment (QFD) method, the effective vocabularies were mapped to the redesigned patterns, leading to the identification of the scheme that most effectively embodied the symmetrical principle for integration into HTD. Finally, the Grey Relation Analysis (GRA) was used to conduct a comprehensive evaluation of multiple design alternatives. The optimal design was selected and subsequently validated through consumer feedback to assess its market feasibility. This study contributes a symmetric approach to the application of symmetry in traditional pattern design, offering both traditional insights and practical guidance for the modernization and innovative transformation of cultural elements in HTD. Full article

The rapid emergence of the platform economy has accelerated the practice of embedded innovation, with ecosystem partner selection serving as a critical first step in platform enterprises’ innovation collaborations and playing a key role in enhancing innovation efficiency and outcomes. Based on the theory of embedded innovation, this study identifies the core innovation demands of platform enterprises at distinct stages. It then employs QFD to quantify decision indicator weights for ecosystem partner selection. By integrating Prospect Theory with Field Theory, this study develops both a decision evaluation model and an optimization model to achieve the optimal screening of ecosystem partners. Specifically, this study contributes in the following ways: (1) It constructs an embedded innovation direction selection model to uncover the evolving innovation demands at each stage. Within the QFD framework, we map these demands onto selection evaluation indicators, assess their importance via the maximum entropy principle, and determine indicator weights through a correlation matrix. (2) It proposes a Prospect Theory-based TOPSIS evaluation model, incorporating decision-makers’ psychological preferences to mitigate bias arising from singular or excessive risk attitudes. This model ranks potential partners according to their closeness to an ideal solution. Finally, (3) it designs a Field Theory-based optimization model that accounts for the platform enterprise’s perspective, partner-matching rationality, and continuity of interaction. This model emphasizes the complementarity and synergy of innovation resources to enhance cooperation fit and strategic alignment between the platform and its partners. Finally, this study conducts an empirical analysis on platform enterprise XM and validates the model’s feasibility and stability through sensitivity testing and comparative analyses. This study enriches the understanding of ecosystem partner selection within platform ecosystems by advancing methods for quantifying partner demands and refining the selection of evaluation indicators. It also deepens the depiction of non-rational characteristics in behavioral decision-making and elucidates the mechanisms underlying the ongoing interactions between platform enterprises and their ecosystem partners. These theoretical contributions not only extend the scope of research on platform ecosystems and embedded innovation but also provide feasible approaches for platform enterprises to improve partner governance and foster collaborative innovation in dynamic and complex environments. Ultimately, the findings offer strong support for enhancing innovation performance and building sustainable competitive advantages. Full article

This study presents a practical methodology for systematically incorporating customer expectations and needs into the market implementation of electric vehicles (EVs). Utilising Quality Function Deployment (QFD), companies can evaluate and understand customer requirements, optimise product improvements, and allocate resources efficiently. Though not widely adopted in many Western contexts, QFD proves valuable in enhancing strategic decision making and improving market penetration. Moreover, the integration of EVs with renewable energy and advancements in battery and grid technologies strengthens their environmental and economic benefits. As technological progress and policy support continue, EVs are positioned to drive sustainable transportation and contribute to global carbon reduction goals. Full article

This work presents a novel, compact (six pieces), low-cost (<$500 USD), and easy-to-manufacture metallography mounting device. The device is designed to produce high-quality polymer encapsulated samples that rival those obtained from commercial equipment ($5000–$10,000 USD). Utilizing the House of Quality (HoQ) framework within Quality Function Deployment (QFD), the device prioritizes critical customer requirements, including safety (validated via finite element method, FEM), affordability, and compatibility with standard hydraulic presses. FEM analysis under 29 MPa pressure revealed a maximum Von Mises stress of 80 MPa, well below the AISI 304 stainless steel yield strength of 170 MPa, yielding a static safety factor of 2.1. Fatigue analysis under cyclic loading (mean stress ${\sigma }_m$ = 40 MPa, amplitude stress ${\sigma }_a$ = 40 MPa) using the Modified Goodman Criterion demonstrated a fatigue safety factor of 3.75, ensuring infinite cycle durability. The device was validated at 140 °C (413.15 K) with a 5-min dwell time, encapsulating samples in a cylindrical configuration (31.75 mm diameter) using a 200 W heating band. Benchmarking confirmed performance parity with commercial systems in edge retention and surface uniformity, while reducing manufacturing complexity (vs. conventional 100-piece systems). This solution democratizes access to metallography, particularly in resource-constrained settings, fostering education and industrial innovation. Full article

Product Lifecycle Management (PLM) provides a paradigmatic model that enables companies to operate more effectively in the face of shorter product lifecycles, global networking, and increasing complexity. However, despite strengthening the PLM initiative, companies still struggle to implement this concept. The limited results of current PLM implementations often stem from a lack of unique indicators or consistent methodologies that help companies prioritize their implementation efforts. This article proposes an approach to set a PLM strategy, focusing on enhancing company innovation potential by introducing a structured methodology capable of (i) capturing latent needs based on the normative-contingent New Product Development (NPD) evaluation model and (ii) quantifying the influence of various PLM functional aspects on NPD capability. The proposed methodology is based on the Quality Function Deployment (QFD) method, modified to overcome the limitations of the conventional approach, employing the Analytic Hierarchy Process (AHP) for prioritizing request attributes and the Evaluation based on Distance from Average Solution (EDAS) method for quality attribute importance ranking. Motivated by the arbitrary and vague nature of the decision-making environment in the PLM implementation projects, which introduces uncertainties that could be effectively managed by fuzzy logic, the study introduces Interval Type-2 Fuzzy Sets (IT2FSs) to minimize ambiguity and inconsistency in expressing and modeling preferences. The main study contribution pertains to generating quantitative and objective guidelines for adequately grounding a PLM strategy from the perspective of enhancing the company’s innovation potential. The findings of this study ultimately contribute to establishing an optimal model of the PLM concept implementation process, tailored to specific company requirements. Finally, an empirical case study demonstrates the effectiveness and practicality of the proposed approach. Full article

Postal services have re-emerged across numerous emerging economies worldwide as essential logistics providers, harnessing their vast coverage and dependability in the face of expanding e-commerce platforms and technological innovations. This study investigates India Post, one of the largest postal networks globally, to determine the key logistics service parameters prioritized by customers in southern India. Quantitative data obtained from 255 India Post end-users were evaluated using the logistics service quality (LSQ) scale, assessing eight dimensions including information quality, timeliness, ordering procedure, order accuracy, order condition, personal contact quality, order discrepancy handling, and order release quantities. The Analytical Hierarchy Process (AHP) ranked these elements, while Quality Function Deployment (QFD) bridged customer expectations with service improvements. The findings highlight the need to improve sorting and distribution processes to meet customer demands for timely, high-quality delivery. By refining logistics efficiency, this study provides suggestions and recommendations for boosting satisfaction and profitability, shedding light on service-led economic advancement for postal services in emerging economies. These insights equip postal service providers to cultivate loyalty and maintain competitiveness within the dynamic logistics landscape. Full article