10,722 research outputs found
Intelligent systems in manufacturing: current developments and future prospects
Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS
Interconnect yield analysis and fault tolerance for field programmable gate arrays
Imperial Users onl
Fault Tolerance in Programmable Metasurfaces: The Beam Steering Case
Metasurfaces, the two-dimensional counterpart of metamaterials, have caught
great attention thanks to their powerful control over electromagnetic waves.
Recent times have seen the emergence of a variety of metasurfaces exhibiting
not only countless functionalities, but also a reconfigurable or even
programmable response. Reconfigurability, however, entails the integration of
tuning and control circuits within the metasurface structure and, as this new
paradigm moves forward, new reliability challenges may arise. This paper
examines, for the first time, the reliability problem in programmable
metamaterials by proposing an error model and a general methodology for error
analysis. To derive the error model, the causes and potential impact of faults
are identified and discussed qualitatively. The methodology is presented and
instantiated for beam steering, which constitutes a relevant example for
programmable metasurfaces. Results show that performance degradation depends on
the type of error and its spatial distribution and that, in beam steering,
error rates over 10% can still be considered acceptable
Learning disabilities and mental retardation: an investigation into the existence of a continuum or dichotomy
The purpose of this paper was to examine research concerned with the definition, labeling, and learning characteristics of the learning disabled and the mentally retarded in order to determine if these disciplines represent a continuum of psychological processes disabilities based upon arbitrary criteria or whether the empirical data indicates that these areas are clearly distinguishable. Although emphasis was placed upon current research, thorough review of the initial research culminating in these various definitions was made
Fault Tolerance for Spacecraft Attitude Management
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83657/1/AIAA-2010-8301-426.pd
An efficient logic fault diagnosis framework based on effect-cause approach
Fault diagnosis plays an important role in improving the circuit design process and the
manufacturing yield. With the increasing number of gates in modern circuits, determining
the source of failure in a defective circuit is becoming more and more challenging.
In this research, we present an efficient effect-cause diagnosis framework for
combinational VLSI circuits. The framework consists of three stages to obtain an accurate
and reasonably precise diagnosis. First, an improved critical path tracing algorithm is
proposed to identify an initial suspect list by backtracing from faulty primary outputs
toward primary inputs. Compared to the traditional critical path tracing approach, our
algorithm is faster and exact. Second, a novel probabilistic ranking model is applied to
rank the suspects so that the most suspicious one will be ranked at or near the top. Several
fast filtering methods are used to prune unrelated suspects. Finally, to refine the diagnosis,
fault simulation is performed on the top suspect nets using several common fault models.
The difference between the observed faulty behavior and the simulated behavior is used to rank each suspect. Experimental results on ISCAS85 benchmark circuits show that this
diagnosis approach is efficient both in terms of memory space and CPU time and the
diagnosis results are accurate and reasonably precise
Prognostics and health management for maintenance practitioners - Review, implementation and tools evaluation.
In literature, prognostics and health management (PHM) systems have been studied by many researchers from many different engineering fields to increase system reliability, availability, safety and to reduce the maintenance cost of engineering assets. Many works conducted in PHM research concentrate on designing robust and accurate models to assess the health state of components for particular applications to support decision making. Models which involve mathematical interpretations, assumptions and approximations make PHM hard to understand and implement in real world applications, especially by maintenance practitioners in industry. Prior knowledge to implement PHM in complex systems is crucial to building highly reliable systems. To fill this gap and motivate industry practitioners, this paper attempts to provide a comprehensive review on PHM domain and discusses important issues on uncertainty quantification, implementation aspects next to prognostics feature and tool evaluation. In this paper, PHM implementation steps consists of; (1) critical component analysis, (2) appropriate sensor selection for condition monitoring (CM), (3) prognostics feature evaluation under data analysis and (4) prognostics methodology and tool evaluation matrices derived from PHM literature. Besides PHM implementation aspects, this paper also reviews previous and on-going research in high-speed train bogies to highlight problems faced in train industry and emphasize the significance of PHM for further investigations
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