Reliability Analysis And Optimal Maintenance Planning For Repairable Multi-Component Systems Subject To Dependent Competing Risks

Modern engineering systems generally consist of multiple components that interact in a complex manner. Reliability analysis of multi-component repairable systems plays a critical role for system safety and cost reduction. Establishing reliability models and scheduling optimal maintenance plans for multi-component repairable systems, however, is still a big challenge when considering the dependency of component failures. Existing models commonly make prior assumptions, without statistical verification, as to whether different component failures are independent or not. In this dissertation, data-driven systematic methodologies to characterize component failure dependency of complex systems are proposed. In CHAPTER 2, a parametric reliability model is proposed to capture the statistical dependency among different component failures under partially perfect repair assumption. Based on the proposed model, statistical hypothesis tests are developed to test the dependency of component failures. In CHAPTER 3, two reliability models for multi-component systems with dependent competing risks under imperfect assumptions are proposed, i.e., generalized dependent latent age model and copula-based trend-renewal process model. The generalized dependent latent age model generalizes the partially perfect repair model by involving the extended virtual age concept. And the copula-based trend renewal process model utilizes multiple trend functions to transform the failure times from original time domain to a transformed time domain, in which the repair conditions can be treated as partially perfect. Parameter estimation methods for both models are developed. In CHAPTER 4, based on the generalized dependent latent age model, two periodic inspection-based maintenance polices are developed for a multi-component repairable system subject to dependent competing risks. The first maintenance policy assumes all the components are restored to as good as new once a failure detected, i.e., the whole system is replaced. The second maintenance policy considers the partially perfect repair, i.e., only the failed component can be replaced after detection of failures. Both the maintenance policies are optimized with the aim to minimize the expected average maintenance cost per unit time. The developed methodologies are demonstrated by using applications of real engineering systems

A random effect autologistic regression model with application to the characterization of multiple microstructure samples

<div><p>ABSTRACT</p><p>The microstructure of a material can strongly influence its properties such as strength, hardness, wear resistance, etc., which in turn play an important role in the quality of products produced from these materials. Existing studies on a material's microstructure have mainly focused on the characteristics of a single microstructure sample and the variation between different microstructure samples is ignored. In this article, we propose a novel random effect autologistic regression model that can be used to characterize the variation in microstructures between different samples for two-phase materials that consist of two distinct parts with different chemical structures. The proposed model differs from the classic autologistic regression model in that we consider the unit-to-unit variability among the microstructure samples, which is characterized by the random effect parameters. To estimate the model parameters given a set of microstructure samples, we first derive a likelihood function, based on which a maximum likelihood estimation method is developed. However, maximizing the likelihood function of the proposed model is generally difficult as it has a complex form. To overcome this challenge, we further develop a stochastic approximation expectation maximization algorithm to estimate the model parameters. A simulation study is conducted to verify the proposed methodology. A real-world example of a dual-phase high strength steel is used to illustrate the developed methods.</p></div

The Fabrication and Evaluation of a Potential Biomaterial Produced with Stem Cell Sheet Technology for Future Regenerative Medicine

To date, the decellularized scaffold has been widely explored as a source of biological scaffolds for regenerative medicine. However, the acellular matrix derived from natural tissues and organs has a lot of defects, including the limited amount of autogenous tissue and surgical complication such as risk of blood loss, wound infection, pain, shock, and functional damage in the donor part of the body. In this study, we prepared acellular matrix using adipose-derived stem cell (ADSC) sheets and evaluate the cellular compatibility and immunoreactivity. The ADSC sheets were fabricated and subsequently decellularized using repeated freeze-thaw, Triton X-100 and SDS decellularization. Oral mucosal epithelial cells were seeded onto the decellularized ADSC sheets to evaluate the cell replantation ability, and silk fibroin was used as the control. Then, acellular matrix was transplanted onto subcutaneous tissue for 1 week or 3 weeks; H&E staining and immunohistochemical analysis of CD68 expression and quantitative real-time PCR (qPCR) were performed to evaluate the immunogenicity and biocompatibility. The ADSC sheet-derived ECM scaffolds preserved the three-dimensional architecture of ECM and retained the cytokines by Triton X-100 decellularization protocols. Compared with silk fibroin in vitro, the oral mucosal epithelial cells survived better on the decellularized ADSC sheets with an intact and consecutive epidermal cellular layer. Compared with porcine small intestinal submucosa (SIS) in vivo, the homogeneous decellularized ADSC sheets had less monocyte-macrophage infiltrating in vivo implantation. During 3 weeks after transplantation, the mRNA expression of cytokines, such as IL-4/IL-10, was obviously higher in decellularized ADSC sheets than that of porcine SIS. A Triton X-100 method can achieve effective cell removal, retain major ECM components, and preserve the ultrastructure of ADSC sheets. The decellularized ADSC sheets possess good recellularization capacity and excellent biocompatibility. This study demonstrated the potential suitability of utilizing acellular matrix from ADSC sheets for soft tissue regeneration and repair