A constraint programming model for the scheduling of flexible manufacturing systems with machine and tool limitations

This contribution presents an integrated constraint programming (CP) model to tackle the problems of tool allocation, machine loading, part routing, and scheduling in a flexible manufacturing system (FMS). The formulation, which is able to take into account a variety of constraints found in industrial environments, as well as several objective functions, has been successfully applied to the solution of various case studies of different sizes. Though some of the problem instances have bigger sizes than the examples reported to date in literature, very good-quality solutions were reached in quite reasonable CPU times. This good computational performance is due to two essential characteristics of the proposed model. The most significant one is the use of two sets of two-index variables to capture manufacturing activities instead of having just one set of four indexes. Thus, dimensionality is greatly reduced. The other relevant feature is the fact that the model relies on an indirect representation of tool needs by means of tool types, thus avoiding the consideration of tool copies.     

Evaluation of different disinfection calculation methods using CFD

Computational Fluid Dynamics combined with a particle tracking technique provides valuable information concerning residence times and contact times in chemical reactors. In drinking water treatment, for example an accurate estimation of the disinfection is important to predict the microbial safety. Ozone contactors are widely used for disinfection, but the complex geometry of the system causes suboptimal hydraulics and requires optimizations of the flow. This results in a lower ozone dosage, which may reduce the formation of unwanted disinfection-by-products and the consumption of energy. To that end disinfection needs to be calculated precisely, accounting for the complex hydraulics. Several calculation methods estimating the disinfection performance of ozone contactors were evaluated using Computational Fluid Dynamics. For an accurate disinfection prediction, the full distribution of ozone exposures (CT values) is needed, only a mean CT value or residence time distribution provides insufficient information for an accurate disinfection prediction. Adjustments to the geometry of the ozone contactor that reduce the short-circuit flows resulted in an increase in disinfection capacity, whereas the mean CT value remained the same. A sensitivity analysis with respect to the kinetics was conducted. The gain in disinfection capacity obtained by optimizing the hydraulics was significant for typical values used in practice.     

Passive sensor evaluation for unmanned ground vehicle mud detection

Detecting mud hazards is a significant challenge to unmanned ground vehicle (UGV) autonomous off‐road navigation. A military UGV stuck in a body of mud during a mission may need to be sacrificed or rescued, both unattractive options. The Jet Propulsion Laboratory is currently developing a daytime mud detection capability under the U.S. Army Research Laboratory Robotics Collaborative Technology Alliances program using UGV‐mounted sensors. To perform robust mud detection under all conditions, we expect that multiple sensors will be necessary. A passive mud detection solution is desirable to meet future combat system requirements. To characterize the advantages and disadvantages of candidate passive sensors, outdoor data collections have been performed on wet and dry soil using visible, multispectral (including near‐infrared), shortwave infrared, midwave infrared, long‐wave infrared, polarization, and stereo sensors. In this paper, we examine the cues for mud detection that each of these sensors provide, along with their deficiencies, and we illustrate localizing detected mud in a world model that can used by a UGV to plan safe paths. We mostly limit our examination to mud detection during the daytime under ideal conditions: isolated wet soil surrounded by dry soil during nominal weather, i.e., no precipitation, calm wind, and near‐average temperatures. © 2010 Wiley Periodicals, Inc.     

Loss and gain functions for CBR retrieval

The method described in this article evaluates case similarity in the retrieval stage of case-based reasoning (CBR). It thus plays a key role in deciding which case to select, and therefore, in deciding which solution will be eventually applied. In CBR, there are many retrieval techniques. One feature shared by most is that case retrieval is based on attribute similarity and importance. However, there are other crucial factors that should be considered, such as the possible consequences of a given solution, in other words its potential loss and gain. As their name clearly implies, these concepts are defined as functions measuring loss and gain when a given retrieval case solution is applied. Moreover, these functions help the user to choose the best solution so that when a mistake is made the resulting loss is minimal. In this way, the highest benefit is always obtained.     

Geometrically non-linear behavior of structural systems with random material property: An asymptotic spectral stochastic approach

An asymptotic spectral stochastic approach is presented for computing the statistics of the equilibrium path in the post-bifurcation regime for structural systems with random material properties. The approach combines numerical implementation of Koiter’s asymptotic theory with a stochastic Galerkin scheme and collocation in stochastic space to quantify uncertainties in the parametric representation of the load–displacement relationship, specifically in the form of uncertain post-buckling slope, post-buckling curvature, and a family of stochastic displacement fields. Using the proposed method, post-buckling response statistics for two plane frames are obtained and shown to be in close agreement with those obtained from Monte Carlo simulation, provided a fine enough spectral representation is used to model the variability in the random dimension.     

A passive tree-based backbone construction scheme for MANETs

Backbone-based broadcast schemes are effective in alleviating the broadcast storm problem in mobile ad hoc networks (MANETs). However, periodically hello packets used to maintain a backbone usually lead to extra control overhead. In this paper, passive tree-based backbone construction scheme (PTBCS) is proposed as a backbone construction scheme for MANETs. Different from other schemes, each node in PTBCS determines its role by intercepting packet transmissions in the air during a special waiting period. Hence, its most remarkable advantage is that there are no periodical packet transmissions specially for backbone construction. The property that the nodes selected by PTBCS make up a connected dominating set (CDS) of the network is proven with several ideal assumptions. Simulation results show that PTBCS is effective when compared with some other typical backbone construction schemes.     

A robust constrained reference governor approach using linear matrix inequalities

The purpose of this paper is to examine and provide a solution to the output reference tracking problem for uncertain systems subject to input saturation. As well-known, input saturation and modelling errors are very common problems at industry, where control schemes are implemented without accounting for such problems. In many cases, it is sometimes difficult to modify the existing implemented control schemes being necessary to provide them with external supervisory control approaches in order to tackle problems with constraints and modelling errors. In this way, a cascade structure is proposed, combining an inner loop containing any proper controller with an outer loop where a generalized predictive controller (GPC) provides adequate references for the inner loop considering input saturations and uncertainties. Therefore, the contribution of this paper consists in providing a state space representation for the inner loop and using linear matrix inequalities (LMI) to obtain a predictive state-vector feedback in such a way that the input reference for the inner loop is calculated to satisfy robust tracking specifications considering input saturations. Hence, the final proposed solution consists in solving a regulation problem to a fixed reference value subjected to a set of constraints described by several LMI and bilinear matrix inequalities (BMI). The main contribution of the paper is that the proposed solution is a non-linear setpoint tracking approach, that is, it is allowed that the system goes into saturation facing the problem of setpoint tracking instead of regulating to the origin. An illustrative numerical example is presented.