Search Results (21)

In the early stages of concurrent engineering, the ability to assess design change impact is fundamentally limited by the availability of expert knowledge. Knowledge-Based Engineering (KBE) provides structured approaches for the capture, formalization, management, and diffusion of knowledge within complex organizations. KBE has increasingly turned toward ontology-based methodologies, leveraging their robust framework for shared conceptualization and reasoning capabilities. Integrated with Model-Based Systems Engineering (MBSE), such Ontology-Based Engineering (OBE) methodologies provide the necessary infrastructure for knowledge-driven workflows in a Digital Engineering (DE) context. Such integration is critical for complex engineering sectors such as the aerospace industry. However, the traditional knowledge acquisition process is expert-centric and, consequently, resource-intensive. The digital transformation of the industry has led to an explosion of data volumes, and raised concerns toward statistical approaches. This study implements a hybrid knowledge acquisition method within the OBE framework and MBSE environment. Specifically, this method combines human expertise and interpretable machine learning techniques to formalize knowledge models and instantiate them with concrete design rules. Applied in a real-world use-case involving workload estimation, this paper aims to enhance cross-domain collaboration during the conceptual design phase of new aircrafts. Full article

Sustainable development and innovation are increasingly relevant in startup branding strategies. While existing studies have explored sustainability-oriented branding and social media–brand equity relationships, evidence remains limited on how sustainability and social media attributes jointly shape brand equity in knowledge-based enterprises (KBEs). To address this specific underexplored area, this study develops the Innovation–Brand Equity–Sustainability (IBES) model to enhance brand equity in KBEs through strategic social media use, focusing on managers’ perspectives from such enterprises in science and technology parks. Employing partial least squares structural equation modeling, the research analyzed data from 471 participants in science and technology parks and KBEs, using SmartPLS 4 to ensure statistical robustness. The findings confirmed 13 proposed hypotheses, demonstrating IBES’ robustness. Social media factors, including identity (β = 0.510 for brand awareness), active presence (β = 0.561 for brand associations), content sharing (β = 0.401 for brand loyalty), and reputation (β = 0.615 for perceived quality), may influence components of brand equity. Brand innovation emerged as the strongest driver, with a total effect of 0.668 on brand equity enhancement and 0.586 on sustainable development. Both constructs serve as critical factors, channeling social media effects through a multistage indirect path (β = 0.225 for brand innovation to sustainable development to brand equity). This study bridges critical gaps in the digital branding literature and underscores the pivotal role of brand innovation and sustainable development in achieving competitive advantage in knowledge-driven economies. Full article

This paper presents a hybrid knowledge-based expert system (KBES) designed to predict crack incubation and fatigue life in gear design, serving as both a research tool and an educational resource. While crack growth and initiation are well understood, crack incubation remains a challenging area. The presented expert system (KBES) integrates a novel mathematical model for crack incubation based on analogy and defect analysis principles with an optimization algorithm for gear design. The system uses genetic algorithms to optimize gear parameters, demonstrating a 5–10% deviation from experimental values in a specific gear design problem case study. Based on this KBES and a hybrid approach, we developed a learning environment based on an intelligent tutoring system (ITS) which serves older students (MSc and PhD) as a learning environment for the acquisition of knowledge and, above all, for the development of an in-depth understanding of the phenomena that occur both during incubation and initialization and during the further propagation of cracks in the root of the gear tooth, which is the basis for determining the lifespan of gear transmissions. Full article

Sustainability-driven products rely heavily on market success and customer awareness to achieve their intended impact. While knowledge-based enterprises (KBEs) are committed to enhancing the sustainability of their products and services, they often face challenges in building brand equity and raising awareness of what makes their products sustainable, particularly within social media engagement. AI agents transfer social media and enable KBEs to promote sustainable products by enhancing brand equity. However, this requires an effective strategy to enhance brand equity among the new social media generation. This study highlights critical factors identified through a rigorous literature review that influence the enhancement of brand equity in KBEs, with a focus on sustainable development and brand innovation. This research employs a mixed-method approach using VOSviewer and NVivo software. A scientometric review of articles published in the Scopus database and a critical thematic analysis were conducted. Furthermore, Google Trends data were utilized to complement the analysis and propose a set of key factors and future directions. Out of 1552 articles extracted from scientific databases from 1994 until 2024, 33 articles were selected and thoroughly analyzed after a rigorous screening and evaluation process. The review demonstrates that social media enhances brand equity for KBEs by increasing brand awareness, improving their efforts in sustainable development, strengthening brand image, strengthening customer loyalty, and facilitating effective interactions. Moreover, leveraging brand innovation and focusing on sustainable development through social media amplifies these positive impacts, further influencing the brand’s perceived quality. This research uniquely identifies the value of sustainability in the brand equity model and the moderating roles of technological complexity and customer environmental sensitivity in this process. The research offers significant insights for managers of science and technology parks, guiding them to adopt effective social media strategies that create sustainable competitive differentiation and strengthen brand positioning in competitive markets. This study also establishes a strong foundation for future studies focusing on AI-powered tools for brand equity within the digital environment by proposing a set of factors that can be used by researchers to develop an initial model. Full article

Society awareness and environmental goals are forcing the aerospace industry to develop new sustainable system architectures. The components in the new system have to meet new functional requirements using alternative technologies and design solutions while ensuring that the physical performance of the component is maintained. However, design space exploration of both domains is challenging due to the intrinsic differences and nature of each: functional domain exploration deals with alternative means to solve functions, while physical exploration deals with parametric values, such as geometric dimensions and material types. Here, we present a method that enables concurrent exploration of the functional and physical design space. The method is based on a review of existing design space exploration methodologies. It has been developed in collaboration with industry and validated within a use case. We expect that this method will be useful for designers in conceptual phases where there are several functions containing multiple design alternatives and incompatibilities among them. The results of the method will allow designers to narrow down the design space to a few architectural candidates, including a baseline of physical dimensioning for each candidate. Full article

In this paper, we show that it is possible to obtain an optimal configuration variant of Modular Strongrooms (MSR) that satisfies the individual requirements of customers and is most economically advantageous for manufacturers. A model of the automatic configuration system for configuring MSR type MODULPRIM was developed, integrating the procedures for generating product variants, choosing the optimal configuration, and designing detailed products and technological processes. The developed model’s importance lies in its ability to automatically select the optimal configuration from a set of possible configurations on a multidisciplinary basis. The problem of choosing was solved by integrating the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods from the group of Multi-Attribute Decision Making (MADM). Validation of the proposed model was performed on eight examples of Modular Strongrooms type MODULPRIM 5 and showed great opportunities to improve efficiency and effectiveness in the process of innovative product development, as well as to obtain a product configuration with significantly improved quality. The proposed model has a high degree of flexibility and universality; thus, it can be further upgraded and integrated into a company’s business system. Full article

DFT and TD-DFT studies of B3LYP/6–31 g(d,p) with the D2 version of Grimme’s dispersion are used to examine the adsorption of a CH₂O molecule on Be₁₂O₁₂ and MBe₁₂O₁₂ nano-cages (M = K, Mn, or Cu atom). The energy gap for Be₁₂O₁₂ was 8.210 eV, while the M encapsulation decreased its value to 0.685–1.568 eV, whereas the adsorption of the CH₂O gas decreased the E_g values for Be₁₂O₁₂ and CuBe₁₂O₁₂ to 4.983 and 0.876 eV and increased its values for KBe₁₂O₁₂ and MnBe₁₂O₁₂ to 1.286 and 1.516 eV, respectively. The M encapsulation enhanced the chemical adsorption of CH₂O gas with the surface of Be₁₂O₁₂. The UV-vis spectrum of the Be₁₂O₁₂ nano-cage was dramatically affected by the M encapsulation as well as the adsorption of the CH₂O gas. In addition, the adsorption energies and the electrical sensitivity of the Be₁₂O₁₂ as well as the MBe₁₂O₁₂ nano-cages to CH₂O gas could be manipulated with an external electric field. Our results may be fruitful for utilizing Be₁₂O₁₂ as well as MBe₁₂O₁₂ nano-cages as candidate materials for removing and sensing formaldehyde gas. Full article

The design and production of prefabricated buildings pose challenges in achieving standardization, limiting their extensive adoption. In order to address issues of prefabricated components, such as the low reusability of design knowledge, limited standardization, and design disconnection, this paper adopted the prefabricated cantilevered structure components as the research object. It employs knowledge-based engineering (KBE) theory and secondary split modularization approach in conjunction with Revit secondary development technology to establish a modular design system. The system formalizes complex design knowledge into concise user interfaces and a logically clear programming language, ensuring the design system’s ease of use and accessibility. To validate the authenticity and applicability of the modular design system developed in this paper, a comparison is made between the traditional modeling tool and modular modeling tool. Through empirical analysis, the result indicates that the new tool proposed in this paper can enhance the efficiency of design professionals by 72.92%. Among these, the tool meets the modeling and design requirements of 96.1% of the prefabricated components in the project, making it highly suitable for the modeling and design process of the vast majority of prefabricated components. Therefore, this design approach, which integrates KBE and three-dimensional geometric technology, makes the modular design of prefabricated cantilevered structural components feasible, providing a reference for future research in the design of other prefabricated components. Full article

This study aimed to investigate the binding constraints on building a knowledge-based economy (KBE) in Qatar. The research used descriptive and qualitative approaches within the new institutional economics paradigm using data from the Global Entrepreneurship Monitor. Taking cognizance that natural-resource-driven economic development may not be sustainable, the Qatar National Vision 2030 was launched with the expectation that educational expansion and reform would turn Qatar’s carbon economy into a “knowledge economy”. The Qatari government’s National Development Strategy 2018–2022 has anchored the economic diversification agenda on building a knowledge-based economy. The findings demonstrated that per the Global Entrepreneurship Monitor analysis, compared with selected countries, Qatar scored relatively high across various dimensions of new institutional economics, including institution, governance, market, and culture. This shows that the knowledge-based economy in Qatar is developing. Several studies examined a variety of issues in building a knowledge-based economy in Qatar, but this is the first study to explore the binding constraints of building a knowledge-based economy in Qatar using the new institutional economics theory as a tool of analysis. Full article

The beam stability factor (C_L) is applied in construction practices to adjust the reference bending design value (F_b) of sawn lumber to consider the lateral-torsional buckling. Bending tests were carried out on 272 specimens of four wood species, namely, red meranti (Shorea sp.), mahogany (Swietenia sp.), pine (Pinus sp.), and agathis (Agathis sp.), to analyze a simply supported beam subjected to concentrated loads at several points. The empirical C_L value is a ratio of the modulus of rupture (S_R) of a specimen to the average S_R of the standard-size specimens. The non-linear regression estimated the Euler buckling coefficient for sawn lumber beam (K_bE) in this study as 0.413, with 5% lower and 5% upper values of 0.338 and 0.488. Applying the 2.74 factor, which represents an approximately 5% lower exclusion value on the pure bending modulus of elasticity (E_min) and a factor of safety, the adjusted Euler buckling coefficient (K_bE′) value for a timber beam was 1.13 (0.92–1.34), which is within the range approved by the NDS (K_bE′ = 1.20). This study harmonizes the NDS design practices of C_L computation with the empirical results. Because agathis has the lowest ductility (μ), most natural defects (smallest strength ratio, S), and highest E/S_R ratio, the agathis beam did not twist during the bending test; instead, it failed before twisting could occur, indicating inelastic material failure. Meanwhile the other specimens (pinus, mahogany, and red meranti), which have smaller E/S_R ratio, higher ductility, and less natural defects, tended to fail because of lesser beam stability. This phenomenon resulted in the C_L curve of agathis being the highest among the others. The C_L value is mathematically related to the beam slenderness ratio (R_B) and the E/S_R ratio. Because the strength ratio (S) and ductility ratio (μ) have significant inverse correlations with the E/S_R ratio, they are correlated with the C_L value. Applying the C_L value to adjust the characteristic bending strength is safe and reliable, as less than 5% of the specimens’ S_R data points lie below the curve of the adjusted characteristics values. Full article

The aim of the article is to analyze the level of the knowledge-based economy (KBE) in the European Union countries in terms of sustainable development. The added value of the work is the presentation of research results at different levels of data aggregation (EU countries, EU macro-regions, EU regions). This type of approach was used for the first time in this study. The research assumes that knowledge and skills are one of the basic factors in implementing the concept of sustainable development. Currently, there are very large disproportions at the level of KBE in the countries, macro-regions, and regions of the EU. It also translates into their socio-economic situation and thus into competitiveness and innovation. The highest level of KBE is in north-western and central Europe countries, while the lowest is in the countries of eastern and south-eastern Europe. This regularity also applies to macro-regions and regions located in these countries. Full article

The development process of the knowledge-based engineering (KBE) system for the structural size optimization of external fixation device is presented in this paper. The system is based on algorithms for generative modeling, finite element model (FEM) analysis, and size optimization. All these algorithms are integrated into the CAD/CAM/CAE system CATIA. The initial CAD/FEM model of external fixation device is verified using experimental verification on the real design. Experimental testing is done for axial pressure. Axial stress and displacements are measured using tensometric analysis equipment. The proximal bone segment displacements were monitored by a displacement transducer, while the loading was controlled by a force transducer. Iterative hybrid optimization algorithm is developed by integration of global algorithm, based on the simulated annealing (SA) method and a local algorithm based on the conjugate gradient (CG) method. The cost function of size optimization is the minimization of the design volume. Constrains are given in a form of clinical interfragmentary displacement constrains, at the point of fracture and maximum allowed stresses for the material of the external fixation device. Optimization variables are chosen as design parameters of the external fixation device. The optimized model of external fixation device has smaller mass, better stress distribution, and smaller interfragmentary displacement, in correlation with the initial model. Full article

This work reports on the simulated neutron and self-emitted gamma attenuation of ultra-high-molecular-weight polyethylene (UHMWPE) composites containing varying Sm₂O₃ contents in the range 0–50 wt.%, using a simulation code, namely MCNP-PHITS. The neutron energy investigated was 0.025 eV (thermal neutrons), and the gamma energies were 0.334, 0.712, and 0.737 MeV. The results indicated that the abilities to attenuate thermal neutrons and gamma rays were noticeably enhanced with the addition of Sm₂O₃, as seen by the increases in µ_m and µ, and the decrease in HVL. By comparing the simulated neutron-shielding results from this work with those from a commercial 5%-borated PE, the recommended Sm₂O₃ content that attenuated thermal neutrons with equal efficiency to the commercial product was 11–13 wt.%. Furthermore, to practically improve surface compatibility between Sm₂O₃ and the UHMWPE matrix and, subsequently, the overall wear/mechanical properties of the composites, a silane coupling agent (KBE903) was used to treat the surfaces of Sm₂O₃ particles prior to the preparation of the Sm₂O₃/UHMWPE composites. The experimental results showed that the treatment of Sm₂O₃ particles with 5–10 pph KBE903 led to greater enhancements in the wear resistance and mechanical properties of the 25 wt.% Sm₂O₃/UHMWPE composites, evidenced by lower specific wear rates and lower coefficients of friction, as well as higher tensile strength, elongation at break, and surface hardness, compared to those without surface treatment and those treated with 20 pph KBE903. In conclusion, the overall results suggested that the addition of Sm₂O₃ in the UHMWPE composites enhanced abilities to attenuate not only thermal neutrons but also gamma rays emitted after the neutron absorption by Sm, while the silane surface treatment of Sm₂O₃, using KBE903, considerably improved the processability, wear resistance, and strength of the composites. Full article

Chagas disease, caused by the kinetoplastid parasite Trypanosoma cruzi, is a human tropical illness mainly present in Latin America. The therapies available against this disease are far from ideal. Proteases from pathogenic protozoan have been considered as good drug target candidates. T. cruzi acidic M17 leucyl-aminopeptidase (TcLAP) mediates the major parasite’s leucyl-aminopeptidase activity and is expressed in all parasite stages. Here, we report the inhibition of TcLAP (IC₅₀ = 66.0 ± 13.5 µM) by the bestatin-like peptidomimetic KBE009. This molecule also inhibited the proliferation of T. cruzi epimastigotes in vitro (EC₅₀ = 28.1 ± 1.9 µM) and showed selectivity for the parasite over human dermal fibroblasts (selectivity index: 4.9). Further insight into the specific effect of KBE009 on T. cruzi was provided by docking simulation using the crystal structure of TcLAP and a modeled human orthologous, hLAP3. The TcLAP-KBE009 complex is more stable than its hLAP3 counterpart. KBE009 adopted a better geometrical shape to fit into the active site of TcLAP than that of hLAP3. The drug-likeness and lead-likeness in silico parameters of KBE009 are satisfactory. Altogether, our results provide an initial insight into KBE009 as a promising starting point compound for the rational design of drugs through further optimization. Full article

The demand for electric machines has increased in the last decade, mainly due to applications that try to make a full transition from fuel to electricity. These applications encounter the need for tailor-made electric machines that must meet demanding requirements. Therefore, it is necessary for small-medium companies to adopt new technologies offering customized products fulfilling the customers’ requirements according to their investment capacity, simplify their development process, and reduce computational time to achieve a feasible design in shorter periods. Furthermore, they must find ways to retain know-how that is typically kept within each designer to retrieve it or transfer it to new designers. This paper presents a framework with an implementation example of a knowledge-based engineering (KBE) system to design industrial electric machines to support this issue. The devised KBE system groups the main functionalities that provide the best outcome for an electric machine designer as development-process traceability, knowledge accessibility, automation of tasks, and intelligent support. The results show that if the company effectively applies these functionalities, they can leverage the attributes of KBE systems to shorten time-to-market. They can also ensure not losing all knowledge, information, and data through the whole development process. Full article