Search Results (101)

Modern custom machine construction and automation projects face pressure to shorten innovation cycles, reduce durations, and manage growing system complexity. Traditional methods like Waterfall and V-Model have limits where end-to-end data traceability is vital throughout the product life cycle. This study introduces the implementation of a web application that incorporates a model-based design approach to assess its applicability and effectiveness in conceptual design scenarios. At the heart of this approach is the Case-Based Axiomatic Design Assistant (CADA), which utilizes Axiomatic Design principles to break down complex tasks into structured, analyzable sub-concepts. It also incorporates Case-Based Reasoning (CBR) to systematically store and reuse design knowledge. The effectiveness of the visual assistant was evaluated through expert-led assessments across different fields. The results revealed a significant reduction in design effort when utilising prior knowledge, thus validating both the efficiency of CADA as a model and the effectiveness of its implementation within a user-centric application, highlighting its collaborative features. The findings support this approach as a scalable solution for enhancing conceptual design quality, facilitating knowledge reuse, and promoting agile development. Full article

The problem of choosing an electric generator in order to increase the reliability and continuity of energy supply to households in Ukraine was considered. It was shown that this choice is made under conditions of uncertainty. The methods of choosing alternatives to technical systems under conditions of uncertainty, based on axiomatic, heuristic and verbal decision-making methods described in the sources, were analyzed, and the Analytical Hierarchical Process (AHP) was selected to develop a model for choosing an electric generator. The technical, economic, operational and ergonomic criteria for choosing an electric generator were justified. The novelty of the article lies in the use of the developed structural hierarchical model for choosing an electric generator for a household, and the selection of the appropriate generator option for a household was carried out using the AHP. The selected F3001 generator model is characterized by the highest value of the generalized weighting factor due to the impact of estimates based on economic and operational criteria. The use of the cogeneration unit in an agricultural biogas plant was also indicated—as an alternative to household energy supply. Full article

In classical transferable-utility models, components typically participate in an all-or-nothing manner and are evaluated under a single criterion. This study generalizes such models by allowing each component to engage through multiple acting measures and by incorporating multiple evaluating attributes simultaneously. We introduce two influence-based assessments, the stable min value and the minimal self-stable value, to evaluate fair assessments of minimal impact across multi-attribute multi-choice environments. These values are rigorously defined via axiomatic characterizations grounded in minimal influence behavior, where coalitions select activity levels that jointly minimize systemic effects. A key theoretical contribution is the identification of a unique, 0-normalized, and efficient multi-attribute potential function corresponding to the minimal self-stable value. The proposed framework enables structured and interpretable evaluation of influence in complex cooperative systems with heterogeneous participation and conflicting objectives. 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

This article initiates the semantic study of distribution-free normal modal logic systems, laying the semantic foundations and anticipating further research in the area. The article explores roughly the same area, though taking a different approach, as a recent article by Bezhanishvili, de Groot, Dmitrieva and Morachini, who studied a distribution-free version of Dunn’s positive modal logic (PML). Unlike PML, we consider logics that may drop distribution and that are equipped with both an implication connective and modal operators. We adopt a uniform relational semantics approach, relying on recent results on representation and duality for normal lattice expansions. We prove canonicity and completeness in the relational semantics of the minimal distribution-free normal modal logic, assuming just the K-axiom, as well as those of its axiomatic extensions obtained by adding any of the D, T, B, S4 or S5 axioms. Adding distribution can be easily accommodated and, as a side result, we also obtain a new semantic treatment of intuitionistic modal logic. Full article

This paper provides an analysis of the meaning–reference problem, as traditionally advanced in the philosophy of language, for imperative programming languages. Addressing the problem is relevant for the philosophy of computer science in the context of the debate of whether simulative programs can be considered representational theories of their simulated systems. This paper challenges the thesis that, since programming languages have semantics, they also have reference, presumably to the external world. First, denotational, operational, game theoretic, and axiomatic semantics are epistemologically analysed to provide a theory of meaning for high-level language programs. It is argued that programming language semantics can be seen, to some extent, under the light of Fregean descriptivism, thereby rejecting the view that it is reference that determines meaning. Secondly, descriptivist, causal, character, and intentionalist theories of reference are examined to argue that meaning is not sufficient for programming languages to determine reference, thereby rejecting the view that meaning determines reference. It is argued that it is the intentions of agents that allow programming language semantics to identify referents. The paper concludes that if the semantics of programming languages may determine their reference, the latter is not to the external world but to the internal operations of the implementation executing them. This does not prevent simulative programs from representing empirical systems, but they do so not on the basis of programming language semantics. 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

Signifiable computability aims to separate what is theoretically computable from what is computable through performable processes on computers with finite amounts of memory. Mathematical objects are signifiable in a formalism $\mathcal{L}$ on an alphabet $\mathcal{A}$ if they can be written as spatiotemporally finite texts in $\mathcal{L}$ on $\mathcal{A}$. In a previous article, we formalized the signification and reference of real numbers and showed that data structures representable as multidimensional matrices of discretely finite real numbers are signifiable. In this investigation, we continue to formulate our theory of signifiable computability by offering an axiomatization of signifiable computation on discretely finite real numbers. The axiomatization implies an ontology of functions on discretely finite real numbers that classifies them as signifiable, signifiably computable, and signifiably partially computable. Relative to $\mathcal{L}$ and $\mathcal{A}$, signification is performed with two formal systems: the Former ${\widehat{\ddot{F}}}_{\mathcal{A},\mathcal{L}}$ that forms texts in $\mathcal{L}$ on $\mathcal{A}$ and the Transformer ${\widehat{\ddot{T}}}_{\mathcal{A},\mathcal{L}}$ that transforms texts formed by ${\widehat{\ddot{F}}}_{\mathcal{A},\mathcal{L}}$ into other texts in $\mathcal{L}$ on $\mathcal{A}$. Singifiable computation is defined relative to $\mathcal{L}$ on $\mathcal{A}$ as a finite sequence of signifiable program states, the first of which is generated by ${\widehat{\ddot{F}}}_{\mathcal{A},\mathcal{L}}$ and each subsequent state is deterministically obtained from the previous one by ${\widehat{\ddot{T}}}_{\mathcal{A},\mathcal{L}}$. We define a debugger function to investigate signifiable computation on finite-memory devices and to prove two theorems, which we call the Debugger Theorems. The first theorem shows that, for a singifiably partially computable function signified by a program on a finite-memory device $\mathcal{D}$, the memory capacity of $\mathcal{D}$ is exceeded when running the program on signifiable discretely finite real numbers outside of the function’s domain. The second theorem shows that there are functions signifiably computable in general that become partially signifiably computable when signified by programs on $\mathcal{D}$ insomuch as the memory capacity of $\mathcal{D}$ can be exceeded even when the programs are executed on some signifiable discretely finite real numbers in the domains of these functions. Full article

With his research on Aristotle’s syllogistic, Jan Łukasiewicz initiates the branch of logic known as the calculus of names. This field deals with axiomatic systems that analyse various fragments of the logic of names, i.e., that branch of logic that studies various forms of names and functors acting on them, as well as logical relationships between sentences in which these names and functors occur. In this work, we want not only to present the genesis of the calculus of names and its first system created by Łukasiewicz, but we also want to deliver systems that extend the first. In this work, we will also show that, from the point of view of modern logic, Łukasiewicz’s approach to the syllogistic is not the only possible one. However, this does not diminish Łukasiewicz’s role in the study of syllogism. We believe that the calculus of names is undoubtedly the legacy of Łukasiewicz. Full article

In a previous paper, we introduced an axiomatic system for information thermodynamics, deriving an entropy function that includes both thermodynamic and information components. From this function, we derived an entropic probability distribution for certain uniform collections of states. Here, we extend the concept of entropic probability to more general collections, augmenting the states by reservoir and context states. This leads to an abstract concept of free energy and establishes a relation between free energy, information erasure, and generalized work. 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

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory, Ergodic Theory and the Theory of Dynamical Systems. Specifically, we are referring to the classical entropies: the Boltzmann–Gibbs, von Neumann, Shannon, Kolmogorov–Sinai and topological entropies. In addition to their common name, which is historically justified (as we briefly describe in this review), another commonality of the classical entropies is the important role that they have played and are still playing in the theory and applications of their respective fields and beyond. Therefore, it is not surprising that, in the course of time, many other instances of the overarching concept of entropy have been proposed, most of them tailored to specific purposes. Following the current usage, we will refer to all of them, whether classical or new, simply as entropies. In particular, the subject of this review is their applications in data analysis and machine learning. The reason for these particular applications is that entropies are very well suited to characterize probability mass distributions, typically generated by finite-state processes or symbolized signals. Therefore, we will focus on entropies defined as positive functionals on probability mass distributions and provide an axiomatic characterization that goes back to Shannon and Khinchin. Given the plethora of entropies in the literature, we have selected a representative group, including the classical ones. The applications summarized in this review nicely illustrate the power and versatility of entropy in data analysis and machine learning. 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