Search Results (44)

Vulnerabilities in conventional agri-food supply chains (CAFSCs) necessitate a shift toward resilient, localized production models. Within the Agri-Food 4.0 landscape, urban Controlled-Environment Hydroponic Agriculture (CEHA) systems address these challenges by shortening supply chains and mitigating climate-induced breakdowns. However, structurally aligning Triple Bottom Line (TBL)-oriented stakeholder needs with complex technical specifications remains a critical challenge in sustainable CEHA system design. To address this challenge, the present study proposes a novel framework integrating the Full Consistency Method (FUCOM) and Quality Function Deployment (QFD) within a Finite Interval Type-2 (FIT2) Gaussian fuzzy environment. This approach systematically translates TBL-oriented priorities into precise engineering specifications, mapping 17 stakeholder needs (SNs) to 30 technical design requirements (TDRs) while capturing linguistic uncertainty and hesitation. The findings reveal a clear strategic focus on environmental and social sustainability. Specifically, high product quality, food safety and traceability, consumer acceptance, and minimization of environmental impacts emerge as the primary drivers of CEHA adoption. The QFD translation identifies scalable IoT infrastructure, sensor maintenance and calibration, and AI-enabled decision support as the most critical TDRs. The framework’s reliability and structural robustness were rigorously validated through comprehensive analyses, including Kendall’s W test to confirm expert consensus, alongside a Leave-One-Out (LOO) approach, weight perturbations, and a structural evaluation of TDR intercorrelations. These findings provide a scientifically grounded roadmap for designing sustainable, intelligent urban agricultural systems. Ultimately, this framework offers actionable managerial implications for agribusiness stakeholders to bridge strategic TBL-oriented goals with practical engineering, significantly enhancing agri-food supply chain resilience. Full article

The study presents a methodology that supports the development of the Information Technology Project Management Plan (PMP) and Scope Plan (SP) elements by formulating structured sentences from Quality Function Deployment (QFD) outputs produced through the House of Quality (HoQ) matrix. Rather than proposing QFD as a new planning tool, the novelty lies in systematically mapping HoQ results to newly structured PMP and SP elements based on established standards and then transforming these results into planning statements through an integrated fuzzy logic layer. Additionally, the introduced fuzzy logic component addresses the uncertainty, prioritization needs, and subjectivity inherent in stakeholder inputs. This enables more accurate and consistent assistance in formulating plan elements, while strengthening the alignment between customer needs and project deliverables. Finally, the usefulness of the proposed methodology is demonstrated through an applied IT project case study that evaluates selected elements and highlights the concrete benefits of improving planning efficiency. Full article

The objective of this study is to construct a “Double-Circulation Double-Diamond” model integrating AHP, QFD, and TRIZ. This will enable the resolution of contradictions between user requirements and technical solutions in the design of highway maintenance unmanned vehicles. The construction of an efficient, safe, and iterative systematic design framework will be achieved by following these steps. The model incorporates both internal and external feedback loops into the conventional Double-Diamond framework, thereby establishing a dynamic closed-loop process of “requirement identification—technical transformation—contradiction resolution—feedback optimization.” AHP is employed to conduct a hierarchical analysis of user requirements; QFD is utilized to map these requirements to technical characteristics; and TRIZ is integrated to facilitate innovative problem-solving and solution generation. The proposed model has been demonstrated to be an effective means of achieving requirement hierarchy decomposition, technical translation, and resolution of key contradictions. MATLAB R2025b (version 25.2.0) simulations were employed to verify the role of the external feedback loop in scheme iteration and optimization. This confirmed the A* algorithm as the optimal path planning approach, which achieves a balance between efficiency and safety. The fuzzy comprehensive evaluation yielded a score of 3.142, indicating performance between “well achieved” and “fully achieved”. In comparison with conventional linear development methodologies, the “Double-Circulation Double-Diamond” model has been shown to markedly enhance the systematicness and dynamic adaptability of complex equipment design through the utilization of cross-phase feedback and methodological coupling. This approach provides a transferable design framework applicable to highway maintenance, unmanned vehicles, and other complex engineering systems. Full article

Shading system design is a complex, multi-objective optimization problem that requires balancing interdependent economic, environmental, social, energy, architectural, and daylighting factors, while also integrating decision-makers’ preferences and user satisfaction. This study aims to develop and validate a hybrid decision-support framework that addresses both quantitative and qualitative data under uncertainty to improve shading system performance. This paper proposes a novel framework that integrates fuzzy logic with multi-criteria decision-making (MCDM) methods. The Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) is employed for criteria prioritization, whereas the Fuzzy Quality Function Deployment (Fuzzy-QFD) translates customer needs into technical requirements. Two evolutionary algorithms, the Single-Objective Genetic Algorithm (SOGA) and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), were implemented and compared. The framework was validated through its application to an existing educational building in Mansoura, Egypt, evaluating both fixed and dynamic shading solutions. The results indicate that the proposed framework effectively translates customer requirements into design criteria and accurately identifies optimal shading solutions, with SOGA outperforming NSGA-II in optimization performance, while dynamic shading systems significantly enhance glare control and visual comfort, thereby confirming the framework’s efficiency in managing interdependent objectives under uncertain conditions. Overall, the framework provides a robust and systematic methodology for incorporating customer satisfaction into shading design and advancing sustainable building performance. Full article

High uncertainty in new product development is primarily driven by multidimensional risks arising from dynamic interactions among factors including customer requirements (CRs), design characteristics (DCs), and solution decisions. To effectively address decision-making risks in uncertain environments, an integrative framework is proposed incorporating the Best–Worst Method (BWM), Interval-Valued Intuitionistic Fuzzy Quality Function Deployment (IVIF-QFD), and the IVIF-VlseKriterijumska Optimizacija I Kompromisno Resenje (IVIF-VIKOR) approach. Initially, CRs are identified through market research and focus group interviews, with weights determined by the BWM to enhance consensus and efficiency in judgment. Subsequently, an IVIF-QFD model is constructed. This model effectively addresses the fuzziness in expert judgments during the translation of CRs into DCs, strengthening its expressive capability in uncertain environments. Finally, candidate solutions are generated for critical DCs, and the IVIF-VIKOR method is employed to rank these solutions, identifying the Pareto-optimal solution. The framework’s effectiveness is validated by a steering wheel design, in addition, sensitivity analysis and comparative experiments are employed to quantify the robustness of the framework against parameter variations. This paper not only theoretically establishes a collaborative decision-making paradigm for uncertain environments but also provides an operational end-to-end decision support toolchain. Full article

The rapid development of contemporary artificial intelligence and Internet of Things (IoT) technologies has given rise to the emerging paradigm of the AIoT (Artificial Intelligence of Things), which is profoundly impacting human life and driving the digital transformation of industries and society. The AIoT not only enhances product functionality and convenience but also accelerates the achievement of the United Nations Sustainable Development Goals (SDGs). However, the widespread adoption of these technologies still poses challenges related to social inclusivity, particularly regarding insufficient accessibility for elderly users, which may exacerbate the digital divide and social inequality, contradicting SDG 10 (reducing inequality). This study integrates AIoT product development processes based on sustainability and universal design principles using methods such as Quality Function Deployment, the Analytic Hierarchy Process, the Scenario Method, the Entropy Weight Method, and Fuzzy Comprehensive Evaluation. The features of this process include ease of operation and high flexibility, making it suitable for cross-departmental product development while prioritizing the needs of diverse age groups throughout the development process. The research findings indicate that the AIoT product concepts proposed can meet the needs of diverse users, contributing to the realization of age-friendly products. This study provides a reference point for future AIoT product development, promoting the inclusive and sustainable development of smart technology. Full article

Lean construction is considered a new methodology for minimizing the causes of waste that hinder the achievement of green building (GB) goals. The main aim of this study is to develop a lean model using fuzzy logic technique to mitigate causes of waste effect in GB projects and to determine the most appropriate lean tools affecting these causes. The inputs of this model include GB waste and four lean tools, comprising Quality Function Deployment (QFD), Last Planner System (LPS), Value Stream Mapping (VSM), and 5S, while the outputs include four improvement level indices based on the lean tools. The model uses various logical rules to achieve several relations among the inputs and outputs, and it is applied and verified using data related to several causes of waste categorized under five groups. The strongest correlation is found between VSM and 5S indices, while an adverse relationship is observed between QFD and 5S indices. The results indicate that a cause of waste that refers to poor assessment of site conditions is considered the most substantial one due to its high improvement level indices across all lean tools. The most significant waste group is related to GB stakeholders, which contains 38% of key causes of waste. The improvement using QFD increases by 10% compared to VSM and 28.20% compared to 5S. QFD and LPS are measured as the most suitable lean tools to mitigate the causes of waste effects due to their high impact and high improvement level indices. Full article

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

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

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

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

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

Fiercer competition across all industries has made identifying and eliminating lean wastes to enhance sustainability performance an effective route that many companies take. This study focuses on the production process of wood park/garden benches at a company that manufactures outdoor wood furniture. The goal was to identify lean wastes within a sustainability framework across seven operations and integrate multi-criteria decision making (MCDM) methodologies for waste elimination. Eleven lean KPIs addressing economic and environmental sustainability were used to develop and prioritize 13 lean failure modes (LFMs) with Risk Priority Numbers (RPNs) above 100, leading to lean project proposals for each LFM. Eighteen lean tools were ranked using the Fuzzy Quality Function Deployment (Fuzzy QFD) method. A total of eight improvement propositions, namely, Kaizen and continuous improvement, upgrade machinery for energy efficiency, Just-In-Time (JIT), optimize production processes with lean methodologies, implement cost reduction strategies, Total Productive Maintenance (TPM), Investing in Automation, and Andon were implemented. Significant improvements were observed post-implementation: total lead time was reduced by approximately 38.46%, value-added time by 22.05%, and non-value-added time by 47.64%. The required number of workers decreased by 14.29%, and the total inventory decreased by approximately 57.31%. The results contribute to sustainability goals by reducing energy consumption and waste while increasing economic efficiency. It also provides a robust framework for decision making in fuzzy environments, guiding practitioners and academics in lean management and sustainability. Full article

To increase user satisfaction with emergency rescue drone products, a product modelling design method based on the fuzzy Kano-QFD-FBS model is proposed. First, the initial user requirements for the emergency rescue drone products are obtained through a questionnaire, and the fuzzy Kano model is utilised and combined with the better–worse coefficient method to categorise the attributes, define the priorities of the user requirements, and screen out the key user requirements. Second, the QFD model is used to construct the quality house, analyse the key user requirements quantitatively, and obtain the design elements and weights of the emergency rescue drone product. The obtained key design elements are subsequently imported into the FBS model to complete the mapping transformation from the functional elements to the structural elements of the emergency rescue drone products and realise the styling design of the emergency rescue drone products. Finally, the user satisfaction scale based on appearance, functionality, and interaction was developed and the System Usability Scale (SUS) was used to evaluate user satisfaction with the emergency rescue drone design scheme. The new design scheme scored higher and showed significant differences in satisfaction ratings compared to the previous scheme. Hefei Jiaxun Technology Co., Ltd. carried out product development for the design scheme. At present, physical products have been sold on the market and have achieved good results. Hefei Jiaxun Technology Co., Ltd. conducted a survey on consumer satisfaction with this product, and the results revealed that customer satisfaction increased by 11.9% compared with that of previous products. Compared with similar products in the market, the consumer satisfaction with this product increased by 13.5%, indicating that it has obvious market competitiveness. This study shows that the method of product styling design based on the fuzzy Kano-QFD-FBS model can comprehensively acquire and analyse user requirements, realise accurate mapping from user requirements to product design elements, and output the specific solution of the emergency rescue drone product styling design. The design scheme performs well in meeting user requirements, verifies the feasibility and effectiveness of the fuzzy Kano-QFD-FBS model in the styling design study of emergency rescue drones, and provides a new paradigm for emergency rescue product design. Full article

With the growth of the worldwide population and depletion of natural resources, the sustainable development of food systems cannot be ignored. The demand for agri-food waste valorization practices like high-value compounds production has received widespread attention; however, numerous challenges still exist. The present study aims to identify those challenges of agri-food waste valorization and propose effective solutions based on smart technologies. Based on a systematic review of the literature, the study combs existing challenges of agri-food waste valorization and constructs a six-dimension conceptual model of agri-food waste valorization challenges. Moreover, the study integrates a Fermatean fuzzy set (FFS) with multi-criteria decision-making (MCDM) methods including stepwise weight assessment ratio analysis (SWARA), decision-making trial and evaluation laboratory-interpretative structural modeling method (DEMATEL-ISM), and quality function deployment (QFD) to evaluate the weights of each dimension, find causal interrelationships among the challenges and fundamental ones, and rank the potential smart solutions. Finally, the results indicate that the “Government” dimension is the severest challenge and point out five primary challenges in agri-food waste valorization. The most potential smart solution is the “Facilitating connectivity and information sharing between supply chain members (S8)”, which may help government and related practitioners manage agri-food waste efficiently and also facilitate circular economy. Full article