Parameter design considerations in precision engineering

Parameter design is an experimental design and analysis methodology for developing robust processes and products. Robustness implies insensitivity to noise disturbances. Subtle experimental realities, such as the joint effect of process knowledge and analysis methodology, may affect the effectiveness of parameter design in precision engineering; where the objective is to detect minute variation in product and process performance. In this thesis, approaches to statistical forced-noise design and analysis methodologies were investigated with respect to detecting performance variations. Given a low degree of process knowledge, Taguchi's methodology of signal-to-noise ratio analysis was found to be more suitable in detecting minute performance variations than the classical approach based on polynomial decomposition. Comparison of inner-array noise (IAN) and outer-array noise (OAN) structuring approaches showed that OAN is a more efficient design for precision engineering. ^

Variables affecting the precision and accuracy of the Intoxilyzer 5000

The Intoxilyzer 5000 was tested for calibration curve linearity for ethanol vapor concentration between 0.020 and 0.400g/210L with excellent linearity. Calibration error using reference solutions outside of the allowed concentration range, response to the same ethanol reference solution at different temperatures between 34 and 38$\sp\circ$C, and its response to eleven chemicals, 10 mixtures of two at the time, and one mixture of four chemicals potentially found in human breath have been evaluated. Potential interferents were chosen on the basis of their infrared signatures and the concentration range of solutions corresponding to the non-lethal blood concentration range of various volatile organic compounds reported in the literature. The result of this study indicates that the instrument calibrates with solutions outside the allowed range up to $\pm$10% of target value. Headspace FID dual column GC analysis was used to confirm the concentrations of the solutions. Increasing the temperature of the reference solution from 34 to 38$\sp\circ$C resulted in linear increases in instrument recorded ethanol readings with an average increase of 6.25%/$\sp\circ$C. Of the eleven chemicals studied during this experiment, six, isopropanol, toluene, methyl ethyl ketone, trichloroethylene, acetaldehyde, and methanol could reasonably interfere with the test at non-lethal reported blood concentration ranges, the mixtures of those six chemicals showed linear additive results with a combined effect of as much as a 0.080g/210L reading (Florida's legal limit) without any ethanol present. ^

Eyewitness memory: Balancing the accuracy, precision, and quantity of information through metacognitive monitoring and control

Historically, memory has been evaluated by examining how much is remembered, however a more recent conception of memory focuses on the accuracy of memories. When using this accuracy-oriented conception of memory, unlike with the quantity-oriented approach, memory does not always deteriorate over time. A possible explanation for this seemingly surprising finding lies in the metacognitive processes of monitoring and control. Use of these processes allows people to withhold responses of which they are unsure, or to adjust the precision of responses to a level that is broad enough to be correct. The ability to accurately report memories has implications for investigators who interview witnesses to crimes, and those who evaluate witness testimony. ^ This research examined the amount of information provided, accuracy, and precision of responses provided during immediate and delayed interviews about a videotaped mock crime. The interview format was manipulated such that a single free narrative response was elicited, or a series of either yes/no or cued questions were asked. Instructions provided by the interviewer indicated to the participants that they should either stress being informative, or being accurate. The interviews were then transcribed and scored. ^ Results indicate that accuracy rates remained stable and high after a one week delay. Compared to those interviewed immediately, after a delay participants provided less information and responses that were less precise. Participants in the free narrative condition were the most accurate. Participants in the cued questions condition provided the most precise responses. Participants in the yes/no questions condition were most likely to say “I don’t know”. The results indicate that people are able to monitor their memories and modify their reports to maintain high accuracy. When control over precision was not possible, such as in the yes/no condition, people said “I don’t know” to maintain accuracy. However when withholding responses and adjusting precision were both possible, people utilized both methods. It seems that concerns that memories reported after a long retention interval might be inaccurate are unfounded. ^

Algorithms for scheduling parallel batch processing machines with non-identical job ready times

This research is motivated by a practical application observed at a printed circuit board (PCB) manufacturing facility. After assembly, the PCBs (or jobs) are tested in environmental stress screening (ESS) chambers (or batch processing machines) to detect early failures. Several PCBs can be simultaneously tested as long as the total size of all the PCBs in the batch does not violate the chamber capacity. PCBs from different production lines arrive dynamically to a queue in front of a set of identical ESS chambers, where they are grouped into batches for testing. Each line delivers PCBs that vary in size and require different testing (or processing) times. Once a batch is formed, its processing time is the longest processing time among the PCBs in the batch, and its ready time is given by the PCB arriving last to the batch. ESS chambers are expensive and a bottleneck. Consequently, its makespan has to be minimized. ^ A mixed-integer formulation is proposed for the problem under study and compared to a formulation recently published. The proposed formulation is better in terms of the number of decision variables, linear constraints and run time. A procedure to compute the lower bound is proposed. For sparse problems (i.e. when job ready times are dispersed widely), the lower bounds are close to optimum. ^ The problem under study is NP-hard. Consequently, five heuristics, two metaheuristics (i.e. simulated annealing (SA) and greedy randomized adaptive search procedure (GRASP)), and a decomposition approach (i.e. column generation) are proposed—especially to solve problem instances which require prohibitively long run times when a commercial solver is used. Extensive experimental study was conducted to evaluate the different solution approaches based on the solution quality and run time. ^ The decomposition approach improved the lower bounds (or linear relaxation solution) of the mixed-integer formulation. At least one of the proposed heuristic outperforms the Modified Delay heuristic from the literature. For sparse problems, almost all the heuristics report a solution close to optimum. GRASP outperforms SA at a higher computational cost. The proposed approaches are viable to implement as the run time is very short. ^

Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

Minimizing makespan for hybrid flowshops with batch, discrete processing machines and arbitrary job sizes

This research aims at a study of the hybrid flow shop problem which has parallel batch-processing machines in one stage and discrete-processing machines in other stages to process jobs of arbitrary sizes. The objective is to minimize the makespan for a set of jobs. The problem is denoted as: FF: batch1,sj:Cmax. The problem is formulated as a mixed-integer linear program. The commercial solver, AMPL/CPLEX, is used to solve problem instances to their optimality. Experimental results show that AMPL/CPLEX requires considerable time to find the optimal solution for even a small size problem, i.e., a 6-job instance requires 2 hours in average. A bottleneck-first-decomposition heuristic (BFD) is proposed in this study to overcome the computational (time) problem encountered while using the commercial solver. The proposed BFD heuristic is inspired by the shifting bottleneck heuristic. It decomposes the entire problem into three sub-problems, and schedules the sub-problems one by one. The proposed BFD heuristic consists of four major steps: formulating sub-problems, prioritizing sub-problems, solving sub-problems and re-scheduling. For solving the sub-problems, two heuristic algorithms are proposed; one for scheduling a hybrid flow shop with discrete processing machines, and the other for scheduling parallel batching machines (single stage). Both consider job arrival and delivery times. An experiment design is conducted to evaluate the effectiveness of the proposed BFD, which is further evaluated against a set of common heuristics including a randomized greedy heuristic and five dispatching rules. The results show that the proposed BFD heuristic outperforms all these algorithms. To evaluate the quality of the heuristic solution, a procedure is developed to calculate a lower bound of makespan for the problem under study. The lower bound obtained is tighter than other bounds developed for related problems in literature. A meta-search approach based on the Genetic Algorithm concept is developed to evaluate the significance of further improving the solution obtained from the proposed BFD heuristic. The experiment indicates that it reduces the makespan by 1.93 % in average within a negligible time when problem size is less than 50 jobs.

Slot Machines: Methodologies and Myths

The proliferation of legalized gaming has significantly changed the nature of the hospitality industry. While several aspects of gaming have flourished, none has become more popular, profitable, or technologically advanced as the slot machine. While more than half of all casino gambling, and earnings, is generated by slot machines, little has been written about the technology integral to these devices. The author describes the workings of computer-controlled slot machines and exposes some of the popular operating myths.

Eyewitness Memory: Balancing the Accuracy, Precision, and Quantity of Information through Metacognitive Monitoring and Control

Historically, memory has been evaluated by examining how much is remembered, however a more recent conception of memory focuses on the accuracy of memories. When using this accuracy-oriented conception of memory, unlike with the quantity-oriented approach, memory does not always deteriorate over time. A possible explanation for this seemingly surprising finding lies in the metacognitive processes of monitoring and control. Use of these processes allows people to withhold responses of which they are unsure, or to adjust the precision of responses to a level that is broad enough to be correct. The ability to accurately report memories has implications for investigators who interview witnesses to crimes, and those who evaluate witness testimony. This research examined the amount of information provided, accuracy, and precision of responses provided during immediate and delayed interviews about a videotaped mock crime. The interview format was manipulated such that a single free narrative response was elicited, or a series of either yes/no or cued questions were asked. Instructions provided by the interviewer indicated to the participants that they should either stress being informative, or being accurate. The interviews were then transcribed and scored. Results indicate that accuracy rates remained stable and high after a one week delay. Compared to those interviewed immediately, after a delay participants provided less information and responses that were less precise. Participants in the free narrative condition were the most accurate. Participants in the cued questions condition provided the most precise responses. Participants in the yes/no questions condition were most likely to say “I don’t know”. The results indicate that people are able to monitor their memories and modify their reports to maintain high accuracy. When control over precision was not possible, such as in the yes/no condition, people said “I don’t know” to maintain accuracy. However when withholding responses and adjusting precision were both possible, people utilized both methods. It seems that concerns that memories reported after a long retention interval might be inaccurate are unfounded.

Approaches to Provisioning Network Topology of Virtual Machines in Cloud Systems

The current infrastructure as a service (IaaS) cloud systems, allow users to load their own virtual machines. However, most of these systems do not provide users with an automatic mechanism to load a network topology of virtual machines. In order to specify and implement the network topology, we use software switches and routers as network elements. Before running a group of virtual machines, the user needs to set up the system once to specify a network topology of virtual machines. Then, given the user’s request for running a specific topology, our system loads the appropriate virtual machines (VMs) and also runs separated VMs as software switches and routers. Furthermore, we have developed a manager that handles physical hardware failure situations. This system has been designed in order to allow users to use the system without knowing all the internal technical details.

The State of our Toolbox: A Meta-analysis of Reliability Measurement Precision

My study investigated internal consistency estimates of psychometric surveys as an operationalization of the state of measurement precision of constructs in industrial and organizational (I/O) psychology. Analyses were conducted of samples used in research articles published in the Journal of Applied Psychology between 1975 and 2010 in five year intervals (K = 934) from 480 articles yielding 1427 coefficients. Articles and their respective samples were coded for test-taker characteristics (e.g., age, gender, and ethnicity), research settings (e.g., lab and field studies), and actual tests (e.g., number of items and scale anchor points). A reliability and inter-item correlations depository was developed for I/O variables and construct groups. Personality measures had significantly lower inter-item correlations than other construct groups. Also, internal consistency estimates and reporting practices were evaluated over time, demonstrating an improvement in measurement precision and missing data.

A real time electromagnetic analysis of electric machines for educational purposes and laboratory implementation

This thesis presents a system for visually analyzing the electromagnetic fields of the electrical machines in the energy conversion laboratory. The system basically utilizes the finite element method to achieve a real-time effect in the analysis of electrical machines during hands-on experimentation. The system developed is a tool to support the student's understanding of the electromagnetic field by calculating performance measures and operational concepts pertaining to the practical study of electrical machines. Energy conversion courses are fundamental in electrical engineering. The laboratory is conducted oriented to facilitate the practical application of the theory presented in class, enabling the student to use electromagnetic field solutions obtained numerically to calculate performance measures and operating characteristics. Laboratory experiments are utilized to help the students understand the electromagnetic concepts by the use of this visual and interactive analysis system. In this system, this understanding is accomplished while hands-on experimentation takes place in real-time.