Preventive maintenance and replacement scheduling : models and algorithms.

Preventive maintenance is a broad term that encompasses a set of activities aimed at improving the overall reliability and availability of a system. Preventive maintenance involves a basic trade-off between the costs of conducting maintenance/replacement activities and the cost savings achieved by reducing the overall rate of occurrence of system failures. Designers of preventive maintenance schedules must weigh these individual costs in an attempt to minimize the overall cost of system operation. They may also be interested in maximizing the system reliability, subject to some sort of budget constraint. In this dissertation, we present a complete discussion about the problem definition and review the literature. We develop new nonlinear mixed-integer optimization models, solve them by standard nonlinear optimization algorithms, and analyze their computational results. In addition, we extend the optimization models by considering engineering economy features and reformulate them as a multi-objective optimization model. We optimize this model by generational and steady state genetic algorithms as well as by a simulated annealing algorithm and demonstrate the computational results obtained by implementation of these algorithms. We perform a sensitivity analysis on the parameters of the optimization models and present a comparison between exact and metaheuristic algorithms in terms of computational efficiency and accuracy. Finally, we present a new mathematical function to model age reduction and improvement factor parameter used in optimization models. In addition, we develop a practical procedure to estimate the effect of maintenance activity on failure rate and effective age of multi component systems

Evaluation of recombinant adenovirus vectors and adjuvanted protein as a heterologous prime-boost strategy using HER2 as a model antigen.

Induction of strong antigen-specific cell-mediated and humoral responses are critical to developing a successful therapeutic vaccine. Herein, using HER2 as a model antigen, we aim to evaluate a therapeutic vaccine protocol that elicits anti-tumor antibody and cytotoxic T cells to HER2/neu antigen. Replication-competent (ΔPS AdV) and non-replicating recombinant adenoviral vectors (AdV) expressing a rat HER2/neu (ErbB2) oncogene, were generated and compared for four different doses and over four time points for their ability to induce antigen-specific T and B cell responses in mice. Although ΔPS AdV:Her2 vector was shown to induce more durable antigen-specific CD8⁺ T cell responses, overall, the AdV:Her2 vector induced broader T and B cell responses. Hence the AdV:Her2 vector was used to evaluate a heterologous prime-boost vaccination regimen using rat HER2 protein encapsulated in archaeosomes composed of a semi-synthetic glycolipid (sulfated S-lactosylarchaeol, SLA; and lactosylarchaeol, LA) (SLA/LA:HER2enc) or admixed with archaeosomes composed of SLA alone (SLA:HER2adm). We first tested AdV:Her2 using a prime-boost approach with SLA/LA:HER2enc, and thereafter evaluated a sub-optimal AdV:Her2 dose in a heterologous prime-boost approach with SLA:HER2adm. A single administration of AdV:Her2 alone induced strong cell-mediated immune responses, whereas SLA/LA:HER2enc alone induced strong antigen-specific IgG titers. In mice primed with a suboptimal dose of AdV:Her2, strong CD8⁺ T-cell responses were observed after a single dose which were not further augmented by protein boost. AdV:Her2 induced CD4⁺ specific T-cell responses were augmented by SLA:HER2adm. Homologous vaccination using SLA:HER2adm induced strong antigen-specific antibody responses. However, the overall magnitude of the responses was similar with three doses of SLA:HER2adm or Ad:HER2 prime followed by two doses of SLA:HER2adm. We demonstrate that AdV:Her2 is capable of inducing strong antigen-specific CD8⁺ T cell responses, even at a low dose, and that these responses can be broadened to include antigen-specific antibody responses by boosting with SLA adjuvanted proteins without compromising CD8 T cell responses elicited by AdV priming

Sensitivity analysis and comparison of algorithms in preventive maintenance and replacement scheduling optimization models

a b s t r a c t In this research, new optimization models are developed to determine the optimal preventive maintenance and replacement schedules in repairable and maintainable systems. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability over the planning horizon. Experimental results of a sensitivity analysis on the optimization models are presented and evaluated. These experiments investigate the effect of the parameters on the structure of optimal preventive maintenance and replacement schedules in multi-component systems. Two factorial design experiments based on the cost associated with maintenance and replacement activities and reliability characteristic parameters are constructed and analyzed. In addition, a comprehensive experiment is designed to analyze and compare the efficiency and accuracy of the exact and metaheuristic algorithms