Wireless sensor network is a fast growing area of research, receiving attention not only within the computer science and electrical engineering communities, but also in relation to network optimization, scheduling, risk and reliability analysis within industrial and system engineering. The availability of micro-sensors and low-power wireless communications will enable the deployment of densely distributed sensor/actuator networks. And an integration of such system plays critical roles in many facets of human life ranging from intelligent assistants in hospitals to manufacturing process, to rescue agents in large scale disaster response, to sensor networks tracking environment phenomena, and others. The sensor nodes will perform significant signal processing, computation, and network self-configuration to achieve scalable, secure, robust and long-lived networks. More specifically, sensor nodes will do local processing to reduce energy costs, and key exchanges to ensure robust communications. These requirements pose interesting challenges for networking research. The most important technical challenge arises from the development of an integrated system which is 1)energy efficient because the system must be long-lived and operate without manual intervention, 2)reliable for data communication and robust to attackers because information security and system robustness are important in sensitive applications, such as military. Based on the above challenges, this dissertation provides Quality of Service (QoS) implementation and evaluation for the wireless sensor networks. It includes the following 3 modules, 1) energy-efficient routing, 2) energy-efficient coverage, 3). communication security. Energy-efficient routing combines the features of minimum energy consumption routing protocols with minimum computational cost routing protocols. Energy-efficient coverage provides on-demand sensing and measurement. Information security needs a security key exchange scheme to ensure reliable and robust communication links. QoS evaluation metrics and results are presented based on the above requirements.

As technology has continued to advance and more break-through emerge, semiconductor devices with dimensions in nanometers have entered into all spheres of our lives. Accordingly, high reliability and high yield are very much a central concern to guarantee the advancement and utilization of nanoelectronic products. However, there appear to be some major challenges related to nanoelectronics in regard to the field of reliability: identification of the failure mechanisms, enhancement of the low yields of nano products, and management of the scarcity and secrecy of available data [34]. Therefore, this dissertation investigates four issues related to the yield and reliability of nanoelectronics. Yield and reliability of nanoelectronics are affected by defects generated in the manufacturing processes. An automatic method using model-based clustering has been developed to detect the defect clusters and identify their patterns where the distribution of the clustered defects is modeled by a new mixture distribution of multivariate normal distributions and principal curves. The new mixture model is capable of modeling defect clusters with amorphous, curvilinear, and linear patterns. We evaluate the proposed method using both simulated and experimental data and promising results have been obtained. Yield is one of the most important performance indexes for measuring the success of nano fabrication and manufacturing. Accurate yield estimation and prediction is essential for evaluating productivity and estimating production cost. This research studies advanced yield modeling approaches which consider the spatial variations of defects or defect counts. Results from real wafer map data show that the new yield models provide significant improvement in yield estimation compared to the traditional Poisson model and negative binomial model. The ultra-thin SiO2 is a major factor limiting the scaling of semiconductor devices. High-k gate dielectric materials such as HfO2 will replace SiO2 in future generations of MOS devices. This study investigates the two-step breakdown mechanisms and breakdown sequences of double-layered high-k gate stacks by monitoring the relaxation of the dielectric films. The hazard rate is a widely used metric for measuring the reliability of electronic products. This dissertation studies the hazard rate function of gate dielectrics breakdown. A physically feasible failure time distribution is used to model the time-to-breakdown data and a Bayesian approach is adopted in the statistical analysis.

This dissertation is divided into two phases. The main objective of this phase is to use Bayesian MCMC technique, to attain (1) estimates, (2) predictions and (3) posterior probability of sales greater than certain amount for sampled regions and any random region selected from the population or sample. These regions are served by a single product manufacturer who is considered to be similar to newsvendor. The optimal estimates, predictions and posterior probabilities are obtained in presence of advertising expenditure set by the manufacturer, past historical sales data that contains both censored and exact observations and finally stochastic regional effects that cannot be quantified but are believed to strongly influence future demand. Knowledge of these optimal values is useful in eliminating stock-out and excess inventory holding situations while increasing the profitability across the entire supply chain. Subsequently, the second phase, examines the impact of Cournot and Stackelberg games in a supply-chain on shelf space allocation and pricing decisions. In particular, we consider two scenarios: (1) two manufacturers competing for shelf space allocation at a single retailer, and (2) two manufacturers competing for shelf space allocation at two competing retailers, whose pricing decisions influence their demand which in turn influences their shelf-space allocation. We obtain the optimal pricing and shelf-space allocation in these two scenarios by optimizing the profit functions for each of the players in the game. Our numerical results indicate that (1) Cournot games to be the most profitable along the whole supply chain whereas Stackelberg games and mixed games turn out to be least profitable, and (2) higher the shelf space elasticity, lower the wholesale price of the product; conversely, lower the retail price of the product, greater the shelf space allocated for that product.

With the growing trend for greater product variety, mixed-model assembly nowadays is commonly employed in many industries, which can enable just-in-time production for a production system with high variety. Efficient production scheduling and sequencing is important to achieve the overall material supply, production, and distribution efficiency around the mixed-model assembly line. This research addresses production scheduling and sequencing on a mixed-model assembly line for products with multiple product options, considering multiple objectives with regard to material supply, manufacturing, and product distribution. This research also addresses plant assignment for a product with multiple product options as a prior step to scheduling and sequencing for a mixed-model assembly line. This dissertation is organized into three parts based on three papers. Introduction and literature review Part 1. In an automobile assembly plant many product options often need to be considered in sequencing an assembly line with which multiple objectives often need to be considered. A general heuristic procedure is developed for sequencing automobile assembly lines considering multiple options. The procedure uses the construction, swapping, and re-sequencing steps, and a limited search for sequencing automobile assembly lines considering multiple options. Part 2. In a supply chain, production scheduling and finished goods distribution have been increasingly considered in an integrated manner to achieve an overall best efficiency. This research presents a heuristic procedure to achieve an integrated consideration of production scheduling and product distribution with production smoothing for the automobile just-in-time production assembly line. A meta-heuristic procedure is also developed for improving the heuristic solution. Part 3. For a product that can be manufactured in multiple facilities, assigning orders to the facility is a common problem faced by industry considering production, material constraints, and other supply-chain related constraints. This paper addresses products with multiple product options for plant assignment with regard to multiple constraints at individual plants in order to minimize transportation costs and costs of assignment infeasibility. A series of binary- and mixed-integer programming models are presented, and a decision support tool based on optimization models is presented with a case study. Summary and conclusions

With the physical dimensions ever scaling down, the increasing level of sophistication in nano-electronics requires a comprehensive and multidisciplinary reliability investigation. A kind of nano-devices, HfO2-based high-k dielectric films, are studied in the statistical aspect of reliability as well as electrical and physical aspects of reliability characterization, including charge trapping and degradation mechanisms, breakdown modes and bathtub failure rate estimation. This research characterizes charge trapping and investigates degradation mechanisms in high-k dielectrics. Positive charges trapped in both bulk and interface contribute to the interface state generation and flat band voltage shift when electrons are injected from the gate under a negative gate bias condition.A negligible number of defects are generated until the stress voltage increases to a certain level. As results of hot electrons and positive charges trapped in the interface region, the difference in the breakdown sequence is attributed to the physical thickness of the bulk high-k layer and the structure of the interface layer. Time-to-breakdown data collected in the accelerated life tests are modeled with a bathtub failure rate curve by a 3-step Bayesian approach. Rather than individually considering each stress level in accelerating life tests (ALT), this approach derives the change point and the priors for Bayesian analysis from the time-to-failure data under neighborhood stresses, based on the relationship between the lifetime and stress voltage. This method can provide a fast and reliable estimation of failure rate for burn-in optimization when only a small sample of data is available.

Emergence of outsourcing and global partnerships has driven the need for emergent manufacturing. Emergent manufacturing is a concept and mechanism that allows manufacturing based organizations to mitigate the risk of outsourcing their manufacturing functions. The implementation of emergent manufacturing is on a rise and yet many industrial facilities have to decide when to switch to emergent manufacturing. To achieve a strategic fit of emergent manufacturing with the existing manufacturing facilities is the current need of the Industry. There is a strong need to develop a body of literature and models specifically for this task. This thesis aims to develop a model to better forecast the demand of emergent manufacturing. This is achieved by designing mathematical, simulation and statistical models to predict the demand of emergent manufacturing. This new proposed model would develop a guide line to implement, manage and sustain emergent manufacturing in today‟s aggressively outsourcing world, where manufacturing facilities are rapidly being downsized to cut down operational costs.

The purpose of this thesis was to determine a path forward to design and implement an on-going Engineering Management Handbook. A review was performed to establish a definition of Engineering Management, the history of Engineering Management, how this history has impacted the Body of Knowledge in Engineering Management over the years, and the current state of the Engineering Management Handbook. Two surveys were performed to discover how users perceive the Handbook. It was found that there was a desire for a useful on-line EM Handbook. This research allows for decisions to be made in the future as the Handbook is updated by showing what subjects and features are most important to users, as well as the need for structure development from the beginning. The features and structure of the Handbook are proposed, along with submission guidelines. The functionality is presented through a series of examples to illustrate the use of the new Engineering Management Handbook.

Before we determine what lean tools are suitable for an office environment and how to modify those tools to make them more suitable and in order to develop a lean office, it is important to understand the different processes and aspects within an office. For this reason, better understanding of office processes and aspects helps facilitate the deployment and implementation and modification of different lean techniques to better suit the office environment. The purpose of this paper is to identify seven different factors to compare against one another and against project performance in terms of on-time delivery and budget. The seven factors are as follows: business sector, size of the organization, office layout, information processing, data flow, location, and interaction or lack of interaction among various departments within an organization. A hypothesis will be developed regarding each of these factors, and subsequently a survey will be created and conducted. A statistical analysis of this survey will be done using primarily a Chi Square test to determine whether our hypotheses can be validated by the data.

Six Sigma, is a business strategy using quality improvement tool, began in the 1980s. An important problem in business has been how to implement Six Sigma at small sized companies. Many large companies are beginning to mandate Six Sigma to their supply base (smaller manufacturing companies) as a condition of future business. This is a problem because Six Sigma implementation can require millions of dollars in investment, dedication of the best resources and training of many employees in a business. Many small manufacturing companies do not have this time or the financial resources to invest in the long-term benefits of Six Sigma. Yet, there still exists a need to implement Six Sigma in these smaller companies This study will analyze the performance of large and small manufacturing companies deploying Six Sigma. The objective is to determine whether the long-term benefits of Six Sigma programs are really worth the cost investment for smaller manufacturing companies. Quantitative and qualitative measurements are used as variables for comparison. The reported revenue, costs and savings of five Fortune 500 companies who have implemented and managed successful Six Sigma programs are examined. A data collection instrument is developed to study the small manufacturing companies. Results show that there were apparent challenges in Six Sigma deployment regardless of company size. However, the benefits of Six Sigma deployment at small manufacturing companies were very apparent. Through the research it was found that small manufacturing companies have the capacity to implement successful Six Sigma programs. Recommendations for further study and an increased research population is also suggested for future research.

Todays fast-paced economy and complex global market has made it difficult for manufacturing companies to maintain their competitive edge. Products being developed today must stand apart from others, and lead the market in the way they meet customer needs. Tools to reduce product development time have been in use for decades, but recently new tools have become available to make significant reductions in the product development cycle. Specifically, simulation tools are becoming very useful for saving time in the design-build-test phase of product development. New simulation tools that compress the product development cycle change the way design errors are found and refined. Traditional product development would create a design, prototype that design, and test it for failures, then repeat the process until the performance was acceptable. A newly developed process combines CAD, CAE, and FEA simulation tools to create an interactive feedback loop in the front part of product development to significantly reduce development time. DesignXplorer VT (DX-VT) uses CAD, CAE, and FEA to form an easy to operate virtual simulation tool that can be used by engineers and designers in multiple stages of product development. From generating innovative designs, to shedding light on how designs can be optimized for peak performance, DX-VT has tools to make product development easier. Using DX-VT in the concept design stage and throughout the CAE analysis and testing stage will give designers and engineers a complete breakdown of what design parameters need changed. I have used DX-VT to create a benchmark test of how the software can be used for product development. I have used real world virtual prototypes from Technip Inc. to evaluate the realistic applications of this software. To capture this process a best practices guide was created to be a general guide on how to efficiently use Workbench Design Modeler, Simulation, and DesignXplorer for enhancing product development. This guide was tailored to Technip Inc. and their most recent project, the Red Hawk. The best practices guide demonstrates how to use the Ansys Workbench software to simulate actual components from the Red Hawk oil rig. The guide shows all the steps and features that were required to get this real life model to solve properly. The results of this product development process will cut development time at Technip by 1000s of man hours, and help in their goal to cut design costs by $2 million per project.