Failure mode and effects analysis using a group-based evidential reasoning approach

Failure mode and effects analysis (FMEA) is a methodology to evaluate a system, design, process or service for possible ways in which failures (problems, errors, risks and concerns) can occur. It is a group decision function and cannot be done on an individual basis. The FMEA team often demonstrates different opinions and knowledge from one team member to another and produces different types of assessment information such as complete and incomplete, precise and imprecise and known and unknown because of its cross-functional and multidisciplinary nature. These different types of information are very difficult to incorporate into the FMEA by the traditional risk priority number (RPN) model and fuzzy rule-based approximate reasoning methodologies. In this paper we present an FMEA using the evidential reasoning (ER) approach, a newly developed methodology for multiple attribute decision analysis. The proposed FMEA is then illustrated with an application to a fishing vessel. As is illustrated by the numerical example, the proposed FMEA can well capture FMEA team members’ diversity opinions and prioritize failure modes under different types of uncertainties.     

Unary finite automata vs. arithmetic progressions

We point out a subtle error in the proof of Chrobak's theorem that every unary NFA can be represented as a union of arithmetic progressions that is at most quadratically large. We propose a correction for this and show how Martinez's polynomial time algorithm, which realizes Chrobak's theorem, can be made correct accordingly. We also show that Martinez's algorithm cannot be improved to have logarithmic space, unless L = NL.     

A sliding mode observer for uncertain nonlinear systems based on multiple models approach

This paper presents a method of state estimation for uncertain nonlinear systems described by multiple models approach. The uncertainties, supposed as norm bounded type, are caused by some parameters’ variations of the nonlinear system. Linear matrix inequalities (LMIs) have been established in order to ensure the stability conditions of the multiple observer which lead to determine the estimation gains. A sliding mode gain has been added in order to compensate the uncertainties. Numerical simulations through a state space model of a real process have been realized to show the robustness of the synthesized observer.     

Topology optimization for hybrid additive-subtractive manufacturing

Hybrid additive-subtractive manufacturing is gaining popularity by making full use of geometry complexity produced by additive manufacturing and dimensional accuracy derived from subtractive machining. Part design for this hybrid manufacturing approach has been done by trial-and-error, and no dedicated design methodology exists for this manufacturing approach. To address this issue, this work presents a topology optimization method for hybrid additive and subtractive manufacturing. To be specific, the boundary segments of the input design domain are categorized into two types: (i) Freeform boundary segments freely evolve through the casting SIMP method, and (ii) shape preserved boundary segments suppress the freeform evolvement and are composed of machining features through a feature fitting algorithm. Given the manufacturing strategy, the topology design is produced through additive manufacturing and the shape preserved boundary segments will be processed by post-machining. This novel topology optimization algorithm is developed under a unified SIMP and level set framework. The effectiveness of the algorithm is proved through a few numerical case studies.     

Slow and fast diffusion effects in image processing

A mathematical model for a nonlinear image multiscale analysis is studied. Processing of an image is based on a solution of the strongly nonlinear parabolic partial differential equation, which can degenerate depending on values of the greylevel intensity function. The governing PDE is a generalization of the regularized (in the sense of Catté, Lions, Morel and Coll) Perona-Malik anisotropic diffusion equation. We present numerical techniques for solving the suggested initial-boundary value problem and also existence and convergence results. Numerical experiments are discussed. Received: 6 May 1998 / Accepted: 27 July 2000     

Proteomics of brain synapses and molecular dissection of synaptic subdomains

Synapses form the nuts and bolts of the brain. Synaptic transmission involves an intricate network of synaptic proteins that forms the molecular machinery underlying transmitter release, activation of transmitter receptors, and signal transduction cascades. It is generally believed that neuronal activity-dependent change of synaptic efficacy is at the basis of learning and memory and is encoded by sequential molecular events at the synapse. In the past 2-3?years, a number of proteomics studies have been performed on synaptic subdomains, including synaptic vesicles, postsynaptic density, synaptic lipid raft, synapse protein complexes, as well as on synaptic protein PTMs, notably phosphorylation. The activity-dependent dynamics of protein constituents of the synapse are starting to be examined by quantitative proteomics. It is anticipated that these analyses will yield novel insights into the organization of the synapse, and will generate testable hypotheses of synapse function and regulation both in health and disease.     

Reexamination of slow relaxation of polymer chains in sol-gel transition

Using [2+2] photocycloaddition of coumarin groups attached to the PMMA chain backbone, we can gradually transfer a semidilute copolymer solution to a uniform speckle-free gel. We reexamined the effects of concentration, crosslinking density, solvent quality on the controversial scaling exponent (α_s) between the linewidth (Γ_s) of the slow mode and the scattering vector (q) during the sol-gel transition. Our results suggest that the slow mode is attributed to large thermally agitated density fluctuation and revealed that the variation of α_s is due to the relative length of 1/q to the correlation length (ξ) of the density fluctuation; namely, if ξ>1/q, α_s→3, while when ξ<1/q, α_s→2.     

Molecular Dynamics Simulation for Ultrafine Machining

This article surveys the advances of molecular dynamics (MD) simulation in the research of ultrafine machining and related technologies. Modeling methods, including interatomic potentials and boundary conditions, are addressed. Algorithm strategies for MD simulations are discussed. By applying simulations with Tersoff potential, a case study of the material removal mechanism of the polishing based on coupling vibrations of liquid (PCVL) is presented.     

Realistic rendering and animation of knitwear

We present a framework for knitwear modeling and rendering that accounts for characteristics that are particular to knitted fabrics. We first describe a model for animation that considers knitwear features and their effects on knitwear shape and interaction. With the computed free-form knitwear configurations, we present an efficient procedure for realistic synthesis based on the observation that a single cross section of yarn can serve as the basic primitive for modeling entire articles of knitwear. This primitive, called the lumislice, describes radiance from a yarn cross section that accounts for fine-level interactions among yarn fibers. By representing yarn as a sequence of identical but rotated cross sections, the lumislice can effectively propagate local microstructure over arbitrary stitch patterns and knitwear shapes. The lumislice accommodates varying levels of detail, allows for soft shadow generation, and capitalizes on hardware-assisted transparency blending. These modeling and rendering techniques together form a complete approach for generating realistic knitwear.