A Radio Frequency Identification (RFID) system is a wireless network composed of a reader which tries to communicate with and read (identify) a subset of tags from among a larger population. There are several standards defined for this type of network including the EPCGlobal UHF Class1 Gen 2 RFID standard which is the focus of this work. The increasing number of tag and reader manufacturers necessitates the design of standard conformity tests. To create conformity tests one needs to know the possible states and transitions between states that the tags may experience. In this work a tag is modeled as a state transition machine where the tag transitions from one state to another upon receiving commands from the reader. The model is Markovian; i.e., each transition only depends on the current state and the received command and is independent of the previous transitions, states and commands. The contribution of this work is to fully define the transitions of this model such that it conforms to the specification of the EPCGlobal standard. This, in turn, is necessary for the design of a conformity testing methodology. Considering all the configurations of the internal tag parameters and command parameters yields a state transition machine with 449 unique states and 141 unique commands. For each unique command there is one unique transition out of each state; thus, there are 63,309 unique transitions that need to be considered. The transition machine has been expressed as a table which has states as rows, commands as columns and the future states as the table entries. This table has been automatically filled using roughly 3000 lines of MATLAB code. A Graphical User Interface (GUI) has also been developed to test and verify the transitions.

With deregulation, utilities in the power sector face a much more urgent imperative to emphasize cost efficiencies as compared to the days of regulation. One major opportunity for cost savings is through reductions in spare parts inventory. Most utilities are accustomed to carrying large volumes of expensive, relatively slow-moving units because of a high degree of risk-averseness. This attitude towards risk is rooted in the days of regulation. Under regulation, companies recovered capital inventory costs by incorporating them into the base rate charged to its customers. In a deregulated environment, cost recovery is no longer guaranteed. Companies must therefore reexamine their risk profile and develop policies for spare parts inventory that are appropriate for a competitive business environment. This research studies the spare parts inventory management problem in the context of electric utilities, with a focus on nuclear power. It addresses three issues related to this problem: criticality, risk, and policy. With respect to criticality and risk, a methodology is presented that incorporates the use of influence diagrams and the Analytic Hierarchy Process (AHP). A new method is developed for group aggregation in the AHP when Saaty and Vargas (2007) dispersion test fails and decision makers are unwilling or unable to revise their judgments. With respect to policy, a quantitative model that ranks the importance of keeping a part in inventory and recommends a corresponding stocking policy through the use of numerical simulation is developed. This methodology and its corresponding models will enable utilities that have transitioned from a regulated to a deregulated environment become more competitive in their operations while maintaining safety and reliability standards. Furthermore, the methodology developed is general enough so that other utility plants, especially those in the nuclear sector, will be able to use this approach. In addition to regulated utilities, other industries, such as aerospace and the military, can also benefit from extensions to these models, as risk profiles and subsequent policies can be adjusted to align with the business environment in which each industry or company operates.

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.

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.

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.

Thesis (M.S.)--Middle East Technical University, 2003. / Keywords: Single machine scheduling, discounted revenues, common due date, branch and bound.

<p> Research shows that in a system model, when the production rate is adjusted based on the number of items in queue, the nature of the model changes from an open-loop queueing system to a closed-loop feedback control system. Service-rate adjustment can be implemented in a discrete event simulation model, but the effect of this adjustment has not been thoroughly analyzed in the literature. This research considers the design of feedback signals to generate realistic simulation models of production system behavior. A series of simulation experiments is conducted to provide practical guidance for simulation modelers on how adding a service-rate adjustment feedback loop to a queueing system affects system performance.</p>

<p> This thesis studies computational approaches for mixed-integer second-order cone optimization (MISOCO) problems. MISOCO models appear in many real-world applications, so MISOCO has gained significant interest in recent years. However, despite recent advancements, there is a gap between the theoretical developments and computational practice. Three chapters of this thesis address three areas of computational methodology for an efficient branch-and-conic-cut (BCC) algorithm to solve MISOCO problems faster in practice. These chapters include a detailed discussion on practical work on adding cuts in a BCC algorithm, novel methodologies for warm-starting second-order cone optimization (SOCO) subproblems, and heuristics for MISOCO problems. </p><p> The first part of this thesis concerns the development of a novel warm-starting method of interior-point methods (IPM) for SOCO problems. The method exploits the Jordan frames of an original instance and solves two auxiliary linear optimization problems. The solutions obtained from these problems are used to identify an ideal initial point of the IPM. Numerical results on public test sets indicate that the warm-start method works well in practice and reduces the number of iterations required to solve related SOCO problems by around 30-40%. </p><p> The second part of this thesis presents novel heuristics for MISOCO problems. These heuristics use the Jordan frames from both continuous relaxations and penalty problems and present a way of finding feasible solutions for MISOCO problems. Numerical results on conic and quadratic test sets show significant performance in terms of finding a solution that has a small gap to optimality. </p><p> The last part of this thesis presents application of disjunctive conic cuts (DCC) and disjunctive cylindrical cuts (DCyC) to asset allocation problems (AAP). To maximize the benefit from these powerful cuts, several decisions regarding the addition of these cuts are inspected in a practical setting. The analysis in this chapter gives insight about how these cuts can be added in case-specific settings.</p><p>

This research deals with the development of a dynamic job quotation system for printed circuit board (PCB) fabrication, which can estimate the price and completion time of a job based on customer preference and current capacity of the shop floor. The primary purpose of building a dynamic quotation system is to maximize the company's profit by quoting optimum lead-time and competitive price for the day-to-day orders received from different customers and original equipment manufacturers. The system was developed using MS-Access relational database. Evaluating the output of the system it was observed that the dynamic system provided more reliable estimation of the lead-time needed for fabricating new jobs. The overall price quoted by the system was competitive with higher profit margin when compared to traditional static systems. This system would therefore provide a vital link between the job quoting and scheduling system of the firm enabling better utilization of the available resources.

Integer programming, simulation, and rules of thumb have been integrated to develop a simulation-based heuristic for short-term assignment of fleet in the car rental industry. It generates a plan for car movements, and a set of booking limits to produce high revenue for a given planning horizon. Three different scenarios were used to validate the heuristic. The heuristic's mean revenue was significant higher than the historical ones, in all three scenarios. Time to run the heuristic for each experiment was within the time limits of three hours set for the decision making process even though it is not fully automated. These findings demonstrated that the heuristic provides better plans (plans that yield higher profit) for the dynamic allocation of fleet than the historical decision processes. Another contribution of this effort is the integration of IP and rules of thumb to search for better performance under stochastic conditions.