Search Results (56)

With the increase in the global aging population, the demand for elderly-friendly game products is growing rapidly. To address existing limitations, particularly in user demand extraction and design parameter setting, this study proposed a design framework integrating the BTM–AHP–AD–TOPSIS methods. The goal was to accurately identify the core needs of elderly users and translate them into effective design solutions. User reviews of elderly-friendly game products were collected from e-commerce platforms using Python 3.8-based web scraping. The Biterm Topic Model (BTM) was employed to extract user needs from review texts. These needs were prioritized using the Analytic Hierarchy Process (AHP) and translated into specific design parameters through Axiomatic Design (AD). Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied to comprehensively evaluate multiple design schemes and select the optimal solution. The results demonstrate that the proposed design path offers a holistic method for progressing from need extraction to design evaluation. It effectively overcomes previous limitations, including inefficient need extraction, limited scope, unclear need weighting, and unreasonable design parameters. This method enhances user acceptance and satisfaction while establishing rigorous design processes and scientific evaluation standards, making it well suited for developing elderly-friendly products. Full article

Organizations worldwide are moving towards sustainability in the supply chains (SCs). Ergonomics management (EM) in SCs can contribute to their social sustainability (SS) by providing a fair, safe, and healthy environment. The literature recognizes the lack of an ergonomics management evaluation model (EMEM) for SCs contributing to SS. This research aims to propose an EMEM applicable to SCs. A continuous improvement approach with five constructs: Plan, Do, Check, Act, and Leadership and Worker participation (L&WP) was conducted, including nineteen domains, and the axiomatic design methodology was deployed. Design ranges (DRs) were defined by 34 experts from Latin America. System ranges (SRs) were assessed by self-assessments of EM practices to obtain the information content axiom in one case study of the Mexican salt industry. A new ergonomics management index for the supply chain (EMISC) and a corresponding scale were implemented. According to this scale, the index was found to be low, indicating a poor ergonomics management index (EMI) for the supplier link across the nineteen domains. The proposed EMEM effectively obtains an EMI of the supply chain (SC) by link and entirely. The model identifies opportunities to improve ergonomics practices for companies participating in sustainable supply chains (SSC). Full article

Pharmaceutical production typically focuses on individual drug types for each production line, which limits flexibility. However, the emergence of Industry 4.0 technologies presents new opportunities for more adaptable and customized manufacturing processes. Despite this promise, the development of innovative design techniques for pharmaceutical production equipment remains incomplete. Manufacturers encounter challenges due to rapid innovation cycles while adhering to stringent Good Manufacturing Practice (GMP) standards. Our research addresses this issue by introducing an information model that organizes the design, development, and testing of pharmaceutical manufacturing equipment. This model is based on an exploratory review of 176 articles concerning design principles in regulated industries and integrates concepts from Axiomatic Design, Quality by Design, Model-Based Systems Engineering, and the V-Model framework. Further refinement was achieved through insights from 10 industry experts. The resultant workflow-based information model can be implemented as software to enhance engineering and project management. This research offers a structured framework that enables pharmaceutical equipment manufacturers and users to collaboratively develop solutions in an iterative manner, effectively closing the gap between industry needs and systematic design methodologies. Full article

To enhance the adaptability and disassemblability of winter ice fishing safety auxiliary products, a modular design approach was introduced during the design process. Axiomatic design (AD) and design structure matrix (DSM) were employed as the theoretical guidance and methodological framework. In the design process, the “Z-mapping” method was used to reanalyze the product’s requirements, functions, and structure, progressively decomposing the overall function and constructing a corresponding design matrix. This approach converted initial user requirements into detailed functional specifications and design parameters. Geometric correlation was used as the evaluation criterion, with values assigned to the design matrix, leading to the development of a correlation matrix for the design parameters of the winter ice fishing safety auxiliary product. System clustering techniques were then applied to optimize the distribution of matrix values, allowing for the identification of functional module areas. Based on these results, a modular design scheme was proposed. The findings indicate that the Kano-AD-DSM-based design strategy significantly improved the disassemblability of the winter ice fishing safety auxiliary product, which is crucial for protecting the safety of ice fishers, reducing physical exertion, and enhancing the ice fishing experience. Moreover, the multi-module design allows the product to be flexibly configured and upgraded based on varying operational needs and personalized user requirements, significantly improving its adaptability and practicality. This research not only provides new theoretical insights for the innovative design of winter ice fishing safety auxiliary products but also offers valuable references for the modular design of similar products. Full article

The development of personalized drugs introduces new uncertainties and risks in production machinery design, which can be mitigated through structured workflows. As the commonly used V-Model approach has limitations in dealing with complex multi-domain problems, it is essential to address traceability and relationships between requirements and solutions in a regulated environment to ensure product quality. This study focuses on the conceptual design phase and develops a design methodology called the Case-based Axiomatic Design Assistant (CADA) to address this type of problem. It takes, as a starting point, Axiomatic Design (AD), due to its simplicity and graphical tools for quality evaluation, and Case-Based Reasoning (CBR), due to its capacity to integrate data structures and continuously improve. This combination is put into practice through a visual assistant that utilizes a knowledge graph to represent design elements comprehensively. This article describes the development, implementation, and testing process of CADA, which includes examples of the conceptual design for pharmaceutical manufacturing. The proposed CADA method facilitates systematic requirements analysis, structured reasoning, and solution evaluation, and overcomes the limitations of previous methodologies. It represents a novel approach with an intuitive workflow and advanced graphical capabilities, exemplified in the context of a conceptual design for pharmaceutical manufacturing. The inclusion of intrinsic data labeling capabilities and inference visualization enhances its relevance. Full article

Industry 4.0 has introduced a data-driven model of production and management of goods and services. This manufacturing paradigm leverages the potential of the Internet of Things (IoT), but finding the information necessary to drive manufacturing processes can be challenging. In this context, the authors propose an innovative approach based on axiomatic design to design RDF knowledge graphs from which to extract the information needed by decision makers. This approach derives from the possibility of providing RDF knowledge graphs with an equivalent matrix representation based on axiomatic design. It allows the selection of the most reliable data sources, thereby optimizing the knowledge graph construction process using matrix algebra, minimizing redundancy and improving the efficiency of query response. The goal of the presented methodology is to address the five critical aspects of Big Data (volume, velocity, variety, value, and veracity) by preordering the knowledge graph according to the information needs of business decision makers, thereby optimizing the use of the immense wealth of information made available by the Web in design. Full article

Manufacturing environments, characterized by dynamic changes and uncertainties, demand effective strategies to minimize disruptions. This study introduces an innovative approach that integrates engineering management principles with modular design to prioritize risk mitigation and enhance robustness in manufacturing processes. From a systems engineering perspective, all manufacturing activities are perceived as interconnected components within a unified system. Leveraging the Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, the study modularizes manufacturing process architecture to effectively curb risk propagation and manage system complexity. This study identifies the most optimal design as a pivotal architectural configuration, significantly improving the structural robustness and stability of the System of Interest (SOI). Empirical evidence supports this design’s capability to reduce complexities, thereby enhancing robustness within the broader system architecture. Notably, the proposed approach results in a substantial reduction in complexity, with the most optimal design exhibiting an approximately 82.79 percent reduction in work volume compared to the original design. Our research underscores the critical relationship between manufacturing and engineering management. Effective collaboration between these domains optimizes resource allocation, decision-making processes, and overall organizational strategy, leading to improved production processes and increased efficiency. Importantly, the study demonstrates a significant enhancement in modularization, resulting in elevated overall robustness in manufacturing processes. This highlights the proactive involvement of engineering management in the design phase to address production challenges, ultimately optimizing system performance. Thus, this research contributes to both practical applications and academic discourse by offering a novel approach to enhancing the robustness in manufacturing processes. By integrating engineering management principles and modular design strategies, organizations can fortify their processes against disruptions and effectively adapt to evolving circumstances. Full article

The design of an Active Reflective Surface Control System (ARCS) is a complex engineering task involving multidimensional and multi-criteria constraints. This paper proposes a novel methodological approach for ARCS design and optimization by integrating Axiomatic Design (AD) and Multi-Criteria Decision Making (MCDM) techniques. Initially, a structured design plan is formulated within the axiomatic design framework. Subsequently, four MCDM methods—Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Entropy Weight Method (EWM), Multi-Criteria Optimization and Compromise Solution (VIKOR), and the integrated TOPSIS–Grey Relational Analysis (GRA) approach—are used to evaluate and compare the alternative solutions. Additionally, fuzzy information axioms are used to calculate the total information content for each alternative to identify the optimal design. A case study is conducted, selecting the optimal actuator for a 5 m diameter scaled model of the Five-hundred-meter Aperture Spherical radio Telescope (FAST), followed by digital control experiments on the chosen actuator. Based on the optimal design scheme, an ARCS prototype is constructed, which accelerates project completion and substantially reduces trial-and-error costs. Full article

To improve the detachability performance and remanufacturing capability of existing agricultural micro-tillers, a modular design concept is introduced into the product design and development process, with Axiomatic Design (AD) and the Design Structure Matrix (DSM) serving as the methodological guidance and theoretical framework. In the design process, “Z-mapping” is used to reconstruct the demand/function/structure of the agricultural micro-tiller, decompose the total functions step by step, and establish a design matrix to transform the initial user requirements into specific functional indicators and design parameters. Geometric correlation is used as the design evaluation index to assign values to the matrix to establish a DSM for the correlations between agricultural micro-tiller design parameters. Using system clustering to optimize the distribution of matrix values, a total of five functional modules were identified to achieve a modular design scheme and design a prototype for agricultural micro-tillers. This design solution has significantly better disassembly performance than existing products, effectively enhancing the remanufacturing capability of existing equipment, proving the effectiveness of the Kano-AD-DSM-based design strategy, and providing a new theoretical reference for the innovative design of other small agricultural equipment. Full article

New product development (NPD) is crucial for helping companies to maintain competitive advantages. In this study, a methodological framework is presented combining a novel Kano model and fuzzy axiomatic design (FAD) for improving the product development capability in the whole NPD process. In the Kano model, a novel mixed-class classification method is presented to classify each evaluation indicator agreed on by the majority, and to calculate the affiliation value based on category strength (CS) to display the degree to which the indicator belongs to a certain attribute. A new importance ratio is also proposed to adjust the importance of each indicator attribute. This helps to achieve higher customer satisfaction and improve the attractiveness of the product or service. FAD is then used to measure the gap between customer satisfaction and the company’s expected levels of satisfaction in terms of product functions. This enables the company to obtain more comprehensive information for decision-making. A case study is provided to verify the practicability of the proposed method. Sensitivity analysis proves the robustness of the results based on the number of respondents. Finally, comparative analysis with existing approaches demonstrates the strengths of the proposed method. Full article

To scientifically enhance user perception in decision-making for designing interactive spaces in schools for children with intellectual disabilities, we propose an innovative design model that integrates the Kano model, Analytic Hierarchy Process (AHP), and Axiomatic Design (AD) theories based on user needs. Initially, multi-method research was used to gather the original user requirements which were then refined through data cleaning to establish the initial user needs. The Kano model was then employed to categorize these initial user needs. AHP was then used to construct a hierarchical analysis model for the interactive spaces in schools for children with intellectual disabilities, creating a judgment matrix to accurately calculate demand weight values at each level. Subsequently, AHP was used to select the most important demand items. The independence axiom of AD theory was used to achieve a “Z”-shaped mapping between the functional requirements (FRs) and design parameters (DPs) for the interactive spaces in schools for children with intellectual disabilities. This mapping was analyzed using a matrix approach to assess the design rationality and optimize solutions, thereby transforming user needs into design parameters. Finally, the design parameters were used to create interactive spaces through computer-aided design, and the resulting design plans were evaluated. Experimental results indicate that this design scheme effectively translates subjective concepts into specific design parameters through a qualitative and quantitative approach. This significantly enhances the user needs of interactive spaces in schools for children with intellectual disabilities and provides a scientific basis for the architectural design of these schools. Full article

With the advantages of new technologies and rising demand from customers, it is necessary to improve the manufacturing process. This necessity was recognized by the industry; therefore, the concept of Industry 4.0 has been implemented in various areas of manufacturing and services. The backbone and main aspect of Industry 4.0 is digitalization and the implementation of technologies into processes. While this concept helps manufacturers with the modernization and optimization of many attributes of the processes, Industry 5.0 takes a step further and brings importance to the human factor of industry practice, together with sustainability and resilience. The concept of Industry 5.0 contributes to the idea of creating a sustainable, prosperous, and human-friendly environment within companies. The main focus of the article is to analyze the existing literature regarding what is missing from the successful implementation of human centricity into industry practice, namely in small and medium-sized factories (SMEs). These findings are then presented in the form of requirements and barriers for the implementation of human centricity into SME factories, which can serve as guidelines for implementing human-centered manufacturing using axiomatic design theory in SMEs, which can serve as a roadmap for practitioners. Full article

Consumer product usability has been addressed using tools that evaluate objects to improve user interaction. However, such diversity in approach makes it challenging to select a method for the type of product being assessed. This article compiles the concepts used since the origin of usability in product design. It groups them by attributes to formulate a usability index proposal. Due to the nature of the data, fuzzy, hierarchical, and axiomatic tools were applied to a trial group of experts and users. Three questionnaires were designed and administered throughout a five-stage process to collect and select attributes, rank them in importance, assign fuzzy values, obtain their numerical representation of use, and assign a qualitative category. By analyzing a case study, this research demonstrates the value of the index by comparing the use of computer mice. Unlike other approaches to evaluating usability, the proposed index incorporates the hierarchical importance of attributes. It allows for participants to express their opinions, transforming subjective responses into linguistic values represented in triangular areas, resulting in a more accurate representation of reality. Additionally, the complexity of the human–object interaction is treated by an information axiom to compute the usability index on a scale from 0 to 1, which reflects the probability of the product meeting the desired usability attributes. Full article

The product design process, fraught with uncertainties and ambiguities in its requirements and constraints, commonly traverses multiple stages, each emphasizing distinct design aspects. This engenders heterogeneity in decision-making criteria, rendering the effective integration of information from various stages of product design decision-making (PDDM) a pivotal task in identifying the optimal design solution. Surprisingly, limited research has attended to the challenge of consolidating such heterogeneous information across multiple PDDM stages. To bridge this gap, our study employs real numbers, interval numbers, and linguistic terms to capture the heterogeneous judgments of decision-makers. We fuse the Maximization Deviation Method with the analytic hierarchy process (AHP) for determining indicators’ weights, while decision-makers’ weights are derived through a dual consideration of uncertainty measure using fuzzy entropy and a distance-minimization model applied to the PDDM matrix for achieving consistency. Leveraging the advantage of axiomatic design, product design alternatives are evaluated based on their PDDM information content of PDDM matrices. Given the multistage nature of product design, stages’ weights are computed by assessing the information content and consistency degree of PDDM matrices at each stage. Ultimately, our approach achieves multistage heterogeneous decision-making fusion in product design through information axiom weighting. A case study involving the decision-making process for a specific numerical control machine design illustrates the efficacy of our method in integrating multistage heterogeneous PDDM data, yielding a comprehensive perspective on the viability of product design schemes. Results show that the ranking sequence of the product design schemes solidifies to x₃ > x₂ > x₁ in stages 2 and 3 of PDDM, diverging from the initial order observed in stage 1 (x₂ > x₃ > x₁), while the fused result from the multistage heterogeneous PDDM analysis aligns with the later stages’ rankings, indicating the credibility and persuasiveness are fortified. This methodology thus offers a robust framework for synthesizing and navigating the uncertainties and complexities inherent in multistage heterogeneous PDDM contexts. Full article

This study aims to effectively support decision-makers in evaluating leading e-commerce companies in Vietnam from a sustainability perspective. In addition, this study evaluates and analyzes criteria that affect the performance of e-commerce companies in Vietnam to find the best practices for e-commerce implementation of managers. In this way, companies can save costs and increase marketing and promotion efficiency, helping to reach more customers. In doing so, an integrated framework based on MCDM is proposed for the first time in e-commerce industry assessment. In the first stage, the fuzzy decision making trial and evaluation Laboratory method is applied to determine the weights of 9 criteria based on collected data. This study lists prominent quantitative evaluation criteria, taking into account the sustainability aspect. In the second phase, ranking the top 12 e-commerce companies in Vietnam according to their performance based on these nine criteria was done by applying the neutrosophic fuzzy axiomatic design method. According to an analysis of the data, the external financial assistance coefficient (12.7%) is the most crucial factor determining how competitive international e-commerce businesses are. The results of this study can help underperforming companies make strategic decisions to improve their performance. Integrating these two techniques provides a new method for evaluating global trading companies that have hitherto remained unaddressed in the trading industry and, therefore, leave a gap that needs to be investigated. Full article