Prognostics-Based Two-Operator Competition for Maintenance and Service Part Logistics

Prognostics and timely maintenance of components are critical to the continuing operation of a system. By implementing prognostics, it is possible for the operator to maintain the system in the right place at the right time. However, the complexity in the real world makes near-zero downtime difficult to achieve partly because of a possible shortage of required service parts. This is realistic and quite important in maintenance practice. To coordinate with a prognostics-based maintenance schedule, the operator must decide when to order service parts and how to compete with other operators who also need the same parts. This research addresses a joint decision-making approach that assists two operators in making proactive maintenance decisions and strategically competing for a service part that both operators rely on for their individual operations. To this end, a maintenance policy involving competition in service part procurement is developed based on the Stackelberg game-theoretic model. Variations of the policy are formulated for three different scenarios and solved via either backward induction or genetic algorithm methods. Unlike the first two scenarios, the possibility for either of the operators being the leader in such competitions is considered in the third scenario. A numerical study on wind turbine operation is provided to demonstrate the use of the joint decision-making approach in maintenance and service part logistics

Spontaneous Adrenal Hematoma in a Pregnant Woman; a Case Report

Spontaneous adrenal hematoma is a very rare condition and its prevalence has been reported to be about 1% in previous studies. Although various causes have been proposed to explain its incidence in existing case reports, the etiology and pathology of this condition is still not known. The present study presents a case of spontaneous adrenal hematoma in a pregnant 31 year old woman without history of trauma or other probable risk factors of hemorrhage, presenting to the emergency department with chief complaint of pain in the right flank. Diagnostic measures, imaging and laparotomy, confirmed the diagnosis of spontaneous adrenal hematoma for her

Effect of Vitamin C on Serum Cortisol after Etomidate Induction of Anesthesia

Objectives: Etomidate is suitable for induction of anesthesia, especially in elderly patients and patients who have cardiovascular compromise. Vitamin C has been introduced as a treatment option to decrease Etomidate induced adrenal insufficiency but its actual effect is still controversial. Objective is to determine the effect of Vitamin C on reduction of serum cortisol after etomidate induction of anesthesia. Methods: In a randomized clinical trial, 40 patients of ASA class I & II, aged between 25 to 70 years old, candidate for elective laparatomy were selected. One hour before induction of surgery, 1 gram of intravenous Vitamin C were administered to the patients in Vitamin C group. Two blood samples were obtained 5 minutes before induction and then another sample 4 hours after induction with etomidate after surgery. All samples were measured for serum free cortisol, ACTH, and C-reactive protein (CRP). Results: There were no significant differences between duration of surgery, preoperative and post-operative blood pressure and heart rate in two groups (p>0.05). Serum cortisol was significantly declined in control group from 16.2±6.3 μg/dl in preoperative to 8.5±4.2 in postop (p=0.0005), but not in Vitamin C group from 17.5±5.6 in preop to 16.8±6.4 in postop (p=0.75). ACTH levels increased non-significantly from preop to postop period in both Vitamin C (pre: 52.1±15 vs. post: 56.4±18 pg/ml) (p=0.48) and in control group (pre:50.5±16 vs. post:56.2±20). Conclusion: Etomidate could significantly decrease postoperative serum free cortisol and induce adrenocortical suppression and CRP increase. This effect could be reversed by using Vitamin C premedication to maintain serum cortisol at preoperative level

Comprehensive Gene Expression Analysis of Human Embryonic Stem Cells during Differentiation into Neural Cells

Global gene expression analysis of human embryonic stem cells (hESCs) that differentiate into neural cells would help to further define the molecular mechanisms involved in neurogenesis in humans. We performed a comprehensive transcripteome analysis of hESC differentiation at three different stages: early neural differentiation, neural ectoderm, and differentiated neurons. We identified and validated time-dependent gene expression patterns and showed that the gene expression patterns reflect early ESC differentiation. Sets of genes are induced in primary ectodermal lineages and then in differentiated neurons, constituting consecutive waves of known and novel genes. Pathway analysis revealed dynamic expression patterns of members of several signaling pathways, including NOTCH, mTOR and Toll like receptors (TLR), during neural differentiation. An interaction network analysis revealed that the TGFβ family of genes, including LEFTY1, ID1 and ID2, are possible key players in the proliferation and maintenance of neural ectoderm. Collectively, these results enhance our understanding of the molecular dynamics underlying neural commitment and differentiation

Gender Differences in the Effect of Resilience Training on Emotional Intelligence in At-Risk Students in Shiraz, Iran

Background: The current study examined the effectivenessof resilience trainingon emotionalintelligence(EI) and assessedgender differences in this regard among adolescents living in the outskirts of Shiraz, Iran. Methods: This pre-post study included 191 students and used an intervention consisting of nine resilience-training sessions. The evaluated outcomes were EI and its 15 components. The paired-samples and independent-samples t-tests were used to analyze the data. Results: Out of 191 students, 88 (46.1%) were boys. Before and after the intervention, the mean EI score for boys was 312.52 ± 37.79 and 327.31 ± 37.75, while for girls, it was 310.74 ± 30.05 and 312.20 ± 29.51, respectively. Following the intervention, the scores of boys in problem-solving (P = 0.007), happiness (P = 0.001), emotional self-awareness (P = 0.044), optimism (P = 0.029), self-regard (P = 0.046), impulse control (P = 0.013), and social responsibility (P = 0.042), as well as the total score of EI (P = 0.005), increased significantly. However, only the optimism score (P = 0.004) rose significantly in girls post-intervention. In addition, there were significant differences in the mean of problem-solving (P = 0.006), happiness (P = 0.001), impulse control (P = 0.042), and the total score (P = 0.035) between boys and girls, before and after the intervention. Conclusions: Resilience training may help moderate high-risk behaviors among adolescents living on the outskirts of Iran’s major cities, particularly boys. Based on the gender differences in EI components, it was suggested that female adolescents required significantly more attention. Nonetheless, gender differences in EI components were contentious, and it was concluded that a variety of factors, including the socio-cultural context, may be involved. Keywords: Emotional Intelligence, Gender Differences, Iran, Resilience, Student

Nanowire Growth Process Modeling and Reliability Models for Nanodevices

Nowadays, nanotechnology is becoming an inescapable part of everyday life. The big barrier in front of its rapid growth is our incapability of producing nanoscale materials in a reliable and cost-effective way. In fact, the current yield of nano-devices is very low (around 10 %), which makes fabrications of nano-devices very expensive and uncertain. To overcome this challenge, the first and most important step is to investigate how to control nano-structure synthesis variations. The main directions of reliability research in nanotechnology can be classified either from a material perspective or from a device perspective. The first direction focuses on restructuring materials and/or optimizing process conditions at the nano-level (nanomaterials). The other direction is linked to nano-devices and includes the creation of nano-electronic and electro-mechanical systems at nano-level architectures by taking into account the reliability of future products. In this dissertation, we have investigated two topics on both nano-materials and nano-devices. In the first research work, we have studied the optimization of one of the most important nanowire growth processes using statistical methods. Research on nanowire growth with patterned arrays of catalyst has shown that the wire-to-wire spacing is an important factor affecting the quality of resulting nanowires. To improve the process yield and the length uniformity of fabricated nanowires, it is important to reduce the resource competition between nanowires during the growth process. We have proposed a physical-statistical nanowire-interaction model considering the shadowing effect and shared substrate diffusion area to determine the optimal pitch that would ensure the minimum competition between nanowires. A sigmoid function is used in the model, and the least squares estimation method is used to estimate the model parameters. The estimated model is then used to determine the optimal spatial arrangement of catalyst arrays. This work is an early attempt that uses a physical-statistical modeling approach to studying selective nanowire growth for the improvement of process yield. In the second research work, the reliability of nano-dielectrics is investigated. As electronic devices get smaller, reliability issues pose new challenges due to unknown underlying physics of failure (i.e., failure mechanisms and modes). This necessitates new reliability analysis approaches related to nano-scale devices. One of the most important nano-devices is the transistor that is subject to various failure mechanisms. Dielectric breakdown is known to be the most critical one and has become a major barrier for reliable circuit design in nano-scale. Due to the need for aggressive downscaling of transistors, dielectric films are being made extremely thin, and this has led to adopting high permittivity (k) dielectrics as an alternative to widely used SiO₂ in recent years. Since most time-dependent dielectric breakdown test data on bilayer stacks show significant deviations from a Weibull trend, we have proposed two new approaches to modeling the time to breakdown of bi-layer high-k dielectrics. In the first approach, we have used a marked space-time self-exciting point process to model the defect generation rate. A simulation algorithm is used to generate defects within the dielectric space, and an optimization algorithm is employed to minimize the Kullback-Leibler divergence between the empirical distribution obtained from the real data and the one based on the simulated data to find the best parameter values and to predict the total time to failure. The novelty of the presented approach lies in using a conditional intensity for trap generation in dielectric that is a function of time, space and size of the previous defects. In addition, in the second approach, a k-out-of-n system framework is proposed to estimate the total failure time after the generation of more than one soft breakdown

PROGNOSTICS-BASED REPLACEMENT AND COMPETITION IN SERVICE PART PROCUREMENT

ABSTRACT Timely maintenance of degrading components is critical to the continuing operation of a system. By implementing prognostics, it is possible for the operator to maintain the system in the right place at the right time. However, the complexity of real-world operating environment makes nearzero downtime difficult to achieve, partly because of a possible shortage of required service parts. To coordinate with a prognostics-based maintenance schedule, it is necessary for the operator to decide when to order the service parts and how to compete with other operators in service part procurement. In this paper, we investigate a situation where two operators are to make prognostics-based replacement decisions and strategically compete for a service part that both operators need at around the same time. A Stackelberg game is formulated in this context. A sequential, constrained maximin space-filling experimental-design approach is developed to facilitate the implementation of backward induction. This approach is efficient in searching the Nash equilibrium when the follower's best response to the leader's strategies has no closed-form expression. A numerical study on wind turbine operation is provided to demonstrate the use of the joint decision-making tool in solving such complex, yet realistic maintenance and service part logistic problems

A Two-dimensional Warranty Model with Consideration of Customer and Manufacturer Objectives Solved with Non-dominated Sorting Genetic Algorithm

Warranty is a powerful implement for marketing strategy that is used by manufacturers and creates satisfaction for consumers by ensuring to compensate for incorrect operation of the product. Warranty service results in a cost named warranty cost for a manufacturer.This cost is a function of warranty policy, regions, and product failures pattern. Since this service covers the cost of uncertain failure of the product, it makes some utility for customers. In this paper, we developed a novel customer utility function that is used as a customer objective to be maximized. In addition to the manufacturer objective, minimizing the warranty cost is considered simultaneously. There are four restrictions on warranty parameters such as time, usage, unit product price and the R&D expenditure to be considered. Finally, we will propose a novel bi-objective model that maximizes the utility function for customers and minimizes the warranty cost for the manufacturer. This model will be solved with an evolutionary algorithm called Non-Dominated Sorting Genetic Algorithm (NSGA-II) and non-dominated Pareto solutions will be gained from this method.To give a numerical instance, for a certain usage rate’s range of costumers, different warranties are provided and compared. It is believed that the computational results can help manufacturers to determine optimal solutions for the objective functions and consequently warranty parameters