13,275 research outputs found

    Axiom-based Potential Functional Failure Analysis for Risk-free Design

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    Abstract. Quality and reliability of product is not established completely in detail design process, but is brought out essentially in the course of conceptual design. A potential functional failure analysis method to improve reliability of product based on design axiom in the stage of conceptual design was introduced in this paper. This method provided designers with an analytical and non-probabilistic tool to evaluate the result of conceptual design from the opinion of design axioms. Functional failure modes can be identified by function analysis based on the ideality axiom, the independence axiom and the information axiom. These potential functional failures point out working direction for the latter improving design. A speedy cutting off valve in the TRT (Top Gas Pressure Recovery Turbine) system is studied as an example to illustrate this method's potential

    Development and analysis of the Software Implemented Fault-Tolerance (SIFT) computer

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    SIFT (Software Implemented Fault Tolerance) is an experimental, fault-tolerant computer system designed to meet the extreme reliability requirements for safety-critical functions in advanced aircraft. Errors are masked by performing a majority voting operation over the results of identical computations, and faulty processors are removed from service by reassigning computations to the nonfaulty processors. This scheme has been implemented in a special architecture using a set of standard Bendix BDX930 processors, augmented by a special asynchronous-broadcast communication interface that provides direct, processor to processor communication among all processors. Fault isolation is accomplished in hardware; all other fault-tolerance functions, together with scheduling and synchronization are implemented exclusively by executive system software. The system reliability is predicted by a Markov model. Mathematical consistency of the system software with respect to the reliability model has been partially verified, using recently developed tools for machine-aided proof of program correctness

    Supporting adaptiveness of cyber-physical processes through action-based formalisms

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    Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system

    Peacemaking among inconsistent rationalities?

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    Kacelnik, Schuck-Paim and Pompilio (this volume, p. 377) show that rationality axioms from economics are neither necessary nor sufficient to guarantee that animal behavior is biologically adaptive. To illustrate that biological adaptiveness does not imply conformity with the consistency axioms of economics, Kacelnik et al describe animals that sensibly experiment with actions yielding sub-maximum levels of short-term energy intake to monitor their environments for change, leading to apparently intransitive patterns of choice that are nevertheless biologically adaptive. Invalidating the converse claim that economic rationality implies biological adaptiveness is Kacelnik et al’s example of female ruffs that are worse off when they conform to the constant-ratio rule, frequently interpreted as a normative consistency requirement of economic rationality. Together, the two examples demonstrate that axiomatic norms are both unnecessary and insufficient for determining whether a particular behavior is biologically adaptive. Additionally, Kacelnik et al call into question what has been reported in the animal behavior literature as preference reversals, such as risk attitudes among wild rufous hummingbirds or the food-hoarding propensities of grey jays. Kacelnik et al attribute apparent reversals to state-dependent fitness functions modulated by subtle differences in the training phase of animal experiments. For example, animals trained on menus that include a strictly dominated option will tend to have lower accumulated energy reserves and therefore exhibit systematically different patterns of choice––not because they fail to maximize, but because their training has induced systematically different nutritional states. Another possible explanation for preference reversals in animal studies with strictly dominated, or “decoy” options is that menus containing dominated items may convey valid information about future opportunities (Houston and McNamara, 1999). If menus are correlated through time, then menus with inferior options today predict scarcity in the future and imply a distinct optimal course of action, in violation of regularity assumptions that posit invariance with respect to the inclusion of strictly dominated alternatives. In environments with payoff structures that can be modeled as cooperative games, a family’s best response sometimes requires individual family members to behave suboptimally as part of a diversification strategy that reduces the risk of reproductive failure (Hutchinson, 1996). Futhermore, theoretical biologists have documented the fragility of expected fitness maximizing behaviour with respect to the assumption of stable environments. Once the model allows for shocks to the environment’s stochastic structure, simple behavior rules that are suboptimal (in terms of expected fitness) when viewed narrowly from the perspective of unchanging payoffs in a fixed environment may outperform rules based on maximazation within a static small world (Bookstaber and Langsam, 1985).Rationality, rationalities, irrationality, bounded rationality, biology, biological rationality

    Experimental economics: Methods, problems and promise

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    The purpose of this paper is to discuss the growing importance of experimentation in economic analysis. We present a variety of economic issues that have been explored with laboratory techniques. We also address some common objections to experimentation, as well as some of the principal lessons that have been learned.

    Supply Chain Management of Tri-modal Sensor

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    The objective of this project is to analyze a supply chain designed to provide a prototype electronic system with multiple companies involved. The rationale for this project is that integrating multiple companies’ products and intellectual property to produce a new prototype which produces a new set of functionalities incorporates many types of risk. These risks include, but are not limited to, compatibility of technology, scheduling, cost overrun, and viability of the delivered prototype system. Results indicate that the risks can be managed to ensure successful fulfilment of the prototype production. A main conclusion is that project management that includes scheduling and risk analysis greatly reduces the risk of prototype delivery failure

    The way from Lean Product Development (LPD) to Smart Product Development (SPD)

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    Abstract Lean Product Development (LPD) is the application of lean principles to product development, aiming to develop new or improved products that are successful in the market. LPD deals with the complete process from gathering and generating ideas, through assessing potential success, to developing concepts, evaluating them to create a best concept, detailing the product, testing/developing it and handing over to manufacture. With the beginning of the fourth Industrial Revolution (Industrial 4.0) and the rising efforts to realize a smart factory environment, also product development has to perform a substantial transformation. This paper firstly describes the concept of Lean Product Development as well as new requirements for an intelligent and Smart Product Development (SPD) through the introduction of modern Industry 4.0 related technologies. Based on Axiomatic Design methodology, a set of guidelines for the design of Lean Product Development Processes is presented. These guidelines are linked with concepts from Industry 4.0 in Engineering, showing how a lean and smart product development process can be achieved by the use of advanced and modern technologies and instruments
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