No abstract

No abstract

Abstract. We present a novel stochastic process algebra that allows the expression of models representing systems comprised of populations of agents distributed over space, where the relative positions of agents influence their interaction. This language, PALOMA, is given both discrete and continuous semantics and it captures multi-class, multi-message Markovian agent models (M 2 MAM). Here we present the definition of the language and both forms of semantics, and demonstrate the use of the language to model a flu epidemic under various quarantine regimes.

Surface roughness plays an important role in product quality and manufacturing process planning. This research focuses on developing an empirical model for surface roughness prediction in finish turning. The model considers the following working parameters: work-piece hardness (material), feed, cutter nose radius, spindle speed and depth of cut. Two competing data mining techniques, nonlinear regression analysis and computational neural networks, are applied in developing the empirical models. The values of surface roughness predicted by these models are then compared with those from some of the representative models in the literature. Metal cutting experiments and tests of hypothesis demonstrate that the models developed in this research have a satisfactory goodness of fit. It has also presented a rigorous procedure for model validation and model comparison. In addition, some future research directions are outlined.

A study of the effect of fringe binarization on the joint transform correlator has shown that the interference fringes for multiple targets could produce false alarms and misses.

No abstract

The quality loss function incorporates the cost of tolerances, however, it does not consider the manufacturing cost and design constraints. In this paper, a stochastic integer programming (SIP) approach is presented for simultaneous selection of tolerances and manufacturing processes. A direct link between the minimum manufacturing cost and the required level of manufacturing yield is established through the process capability index Cpk. As the tolerances in SIP are discrete, the solution generated is acceptable for manufacturing. It is shown that the integer programming models are applicable in the quality loss function and six sigma design approaches. The SIP approach is illustrated with a classical example of nonlinear tolerance design. The comparison of the proposed SIP approach, the Taguchi method, and the conventional mathematical models in tolerance synthesis is presented.

No abstract