A graphical approach for confidence limits of optimal preventive maintenance cycles

Facilities management (FM) is the management of infrastructure resources and services to support and sustain the operational strategy of an organization over time. Maintenance is often the business process that has not been optimized and is considered as a liability of business operations. Therefore, extensive studies have been done to determine the optimal replacement interval for irreparable parts of repairable systems where typically the time between failures is characterized by lifetime distribution in which the parameters are estimated from failure data. As a result, the optimal preventive maintenance (PM) interval computed is exposed to sampling risk as the repair cost and failure data used for estimation are typically highly censored due to issues related to data collection and unobserved failures. In this paper, we present a graphical approach to obtain the confidence interval for the optimal PM interval that resulted from sampling variations parameter estimates. The proposed methodology is applied in the context of FM as a strategy for opportunistic replacement and for the purpose of validating the cost components in maintenance. Copyright © 2008 John Wiley & Sons, Ltd.     

Oxidation Hardening Kinetics of the Rheological Function G′/(η′/G′) in Asphalts

Abstract

The authors used 9 asphalts oxidized at various temperatures and pressures to determine the hardening kinetics for the DSR function, an easily measured and meaningful surrogate for 15°C ductility that relates well to age-related binder deterioration. For each asphalt, there is a rapid initial period that slows to a constant rate period. This constant rate period can be represented by carbonyl formation (oxidation) rate times a hardening susceptibility (HS). For the DSR function and viscosity, the HS and initial jump were pressure- but not temperature-dependent. The DSR function initial jump was relatively higher than the viscosity initial jump.     

A Simple Compressive Sensing Algorithm for Parallel Many-Core Architectures

In this paper we consider the l ¹-compressive sensing problem. We propose an algorithm specifically designed to take advantage of shared memory, vectorized, parallel and many-core microprocessors such as the Cell processor, new generation Graphics Processing Units (GPUs) and standard vectorized multi-core processors (e.g. quad-core CPUs). Besides its implementation is easy. We also give evidence of the efficiency of our approach and compare the algorithm on the three platforms, thus exhibiting pros and cons for each of them.     

The Multi-Mode Resource-Constrained Multi-Project Scheduling Problem

Scheduling projects is a difficult and time consuming process, and has far-reaching implications for any organization’s operations. By generalizing various aspects of project scheduling, decision makers are enabled to capture reality and act accordingly. In the context of the MISTA 2013 conference, the first MISTA challenge, organized by the authors, introduced such a general problem model: the Multi-Mode Resource-Constrained Multi-Project Scheduling Problem (MRCMPSP). The present paper reports on the competition and provides a discussion on its results. Furthermore, it provides an analysis of the submitted algorithms, and a study of their common elements. By making all benchmark datasets and results publicly available, further research on the MRCMPSP is stimulated.     

A hybrid model for a multiproduct pipeline planning and scheduling problem

Brazilian petrobras is one of the world largest oil companies. Recurrently, it faces a very difficult planning and scheduling problem: how to operate a large pipeline network in order to adequately transport oil derivatives and biofuels from refineries to local markets. In spite of being more economical and environmentally safer, the use of a complex pipeline network poses serious operational difficulties related to resource allocation and temporal constraints. The current approaches known from the literature only consider a few types of constraints and restricted topologies, hence they are far from being applicable to real instances from petrobras. We propose a hybrid framework based on a two-phase problem decomposition strategy. A novel Constraint Programming (CP) model plays a key role in modelling operational constraints that are usually overlooked in literature, but that are essential in order to guarantee viable solutions. The full strategy was implemented and produced very adequate results when tested over large real instances.     

Predicting recidivism with the Psychopathy Checklist: Are factor score composites really necessary?

In two previous studies on general and violent recidivism (Walters & Heilbrun, 2010; Walters, Knight, Grann, & Dahle, 2008), the summed composite antisocial facet of the Psychopathy Checklist displayed incremental validity relative to the other 3 facets (interpersonal, affective, lifestyle), whereas the other 3 facets generally failed to demonstrate incremental validity relative to the antisocial facet. Because summed composite scores do not account for ordinal item distributions, the 6 Walters et al. (2008) samples were reanalyzed with factor score composites derived from a 4-factor confirmatory factor analysis. The results, however, showed little change from what had been obtained earlier with summed composite scores. Two additional samples not previously included in any incremental validity analyses of the Psychopathy Checklist evidenced a 3-factor structure, with the lifestyle and antisocial facets merged into a single factor. This single factor displayed incremental validity relative to the interpersonal and affective facets, but the reverse was not true regardless of whether summed composite scores or factor score composites were used. A comparison of zero-order correlations from all 8 samples revealed that the antisocial summed composite score predicted significantly better than the summed composite scores for the other 3 facets and that a superordinate factor failed to improve on the performance of either the antisocial summed composite score or the antisocial factor score composite. (PsycINFO Database Record (c) 2011 APA, all rights reserved)