<p>Our work focuses on an analysis of the processes for full and partial annealing of aluminium coils. Due to inefficient production management these processes show high inventory levels, long lead times and decreased delivery performance. </p><p>We have also found inadequacies in the ways costs for these processes are distributed. We have established a new process mapping by initially investigating the strategic dimensions of the company and the processes for annealing, in order to later on establish performance measures congruent with the business objectives. Furthermore we have conducted extensive calculations and analyses to facilitate the successful implementation of a Just-in-time production philosophy, including necessary process improvements and redesigns to be made. Our proposed changes will lead to shorter lead times and low levels of WIP, which are important success factors of a JIT-based production philosophy. </p><p>To do this we have developed a capacity analysis tool with which it is also possible to analyse other processing scenarios or the effect of load changes and/or product mix variations. This tool can also serve as a benchmark for capacity analysis of other processes. </p><p>Finally, we have been able to establish more accurate costs per machine hour for full and partial annealing to be implemented in the managerial system. We believe that the processes for annealing are not the only ones suffering from poor cost control, why we would suggest that Sapa Heat Transfer investigates the cost distribution in more processes, and also develops and follows better guidelines for cost control.</p>

<p>In the field of systems biology the task of finding optimal model parameters is a common procedure. The optimization problems encountered are often multi-modal, i.e., with several local optima. In this thesis, a class of algorithms for multi-modal problems called metaheuristics are studied. A downside of metaheuristic algorithms is that they are dependent on algorithm settings in order to yield ideal performance.This thesis studies an approach to tune these algorithm settings using user constructed test functions which are faster to evaluate than an actual biological model. A statistical procedure is constructed in order to distinguish differences in performance between different configurations. Three optimization algorithms are examined closer, namely, scatter search, particle swarm optimization, and simulated annealing. However, the statistical procedure used can be applied to any algorithm that has configurable options.The results are inconclusive in the sense that performance advantages between configurations in the test functions are not necessarily transferred onto real biological models. However, of the algorithms studied a scatter search implementation was the clear top performer in general. The set of test functions used must be studied if any further work is to be made following this thesis.In the field of systems biology the task of finding optimal model parameters is a common procedure. The optimization problems encountered are often multi-modal, i.e., with several local optima. In this thesis, a class of algorithms for multi-modal problems called metaheuristics are studied. A downside of metaheuristic algorithms is that they are dependent on algorithm settings in order to yield ideal performance.</p><p>This thesis studies an approach to tune these algorithm settings using user constructed test functions which are faster to evaluate than an actual biological model. A statistical procedure is constructed in order to distinguish differences in performance between different configurations. Three optimization algorithms are examined closer, namely, scatter search, particle swarm optimization, and simulated annealing. However, the statistical procedure used can be applied to any algorithm that has configurable options.</p><p>The results are inconclusive in the sense that performance advantages between configurations in the test functions are not necessarily transferred onto real biological models. However, of the algorithms studied a scatter search implementation was the clear top performer in general. The set of test functions used must be studied if any further work is to be made following this thesis.</p>

<p>The longitudinal controller at DaimlerChrysler AG consists of two cascade controllers. The outer control loop contains the driver assistance functions such as speed limiter, cruise control, etc. The inner control loop consists of a PID-controller and an observer. The task of the observer is to estimate the part of the vehicle's acceleration caused by large disturbances, for example by a changed vehicle mass or the slope of the road.</p><p>As observer the Kalman filter is selected. It is the optimal filter when the process model is linear and the process noise and measurement noise can be modeled as Gaussian noise. In this Master's thesis the theory for the Kalman filter is presented and it is shown how to choose the filter parameters. Simulated annealing is a global optimization technique which can be used when autotuning, i.e., automatically find the optimal parameter settings. To be able to perform autotuning for the longitudinal controller one has to model the environment and driving situations.</p><p>In this Master's thesis it is verified that the parameter choice is a compromise between a fast but jerky, or a slow but smooth estimate. As the output from the Kalman filter is directly added to the control value for the engine and brakes, it is important that the output is smooth. It is shown that the Kalman filter implemented in the test vehicles today can be exchanged with a first-order lag function, without loss in performance. This makes the filter tuning easier, as there is only one parameter to choose.</p><p>Change detection is a method that can be used to detect large changes in the signal, and react accordingly - for example by making the filter faster. A filter using change detection is implemented and simulations show that it is possible to improve the estimate using this method. It is suggested to implement the change detection algorithm in a test vehicle and evaluate it further.</p>

Iron-cobalt alloys have been extensively studied as potential hard disk drive write head materials due to their potentially high saturation flux densities (~2.4T), low coercivities and ease of deposition. Iron-cobalt plating solutions have, however, been shown to have stability issues, necessitating that they be used at low pH or that a stabilizing agent be added to the solution. The purpose of this thesis is to evaluate the stability of a dibasic ammonium citrate plating solution and to characterize the deposits which result from its use. The plating solutions are found to be less stable than previously claimed. The solutions are oxidized by dissolved oxygen, which leads to a valence change in the iron ions and eventually the formation of iron oxide/hydroxide precipitates. These effects are exacerbated by heating or the application of a voltage across the solution. Deposits plated from the solution are fine grained (<40nm) and compact through their thickness. While normally deposited as the equilibrium BCC phase, metastable phases are deposited at elevated temperatures, high pH or in the absence of a stabilizing agent. A metastable phase which is isomorphous to α-Mn is deposited at elevated temperatures. This phase transforms to the BCC phase when annealed at >174ºC and is highly textured. Its presence is detrimental to deposit coercivity. / Materials Engineering

A hybrid design optimization method combining the stochastic method based on simultaneous perturbation stochastic approximation (SPSA) and the deterministic method of Broydon-Fletcher-Goldfarb-Shanno (BFGS) is developed in order to take advantage of the high efficiency of the gradient based methods and the global search capabilities of SPSA for applications in the optimal aerodynamic shape design of a three dimensional elliptic nozzle. The performance of this hybrid method is compared with that of SPSA, simulated annealing (SA) and gradient based BFGS method. The objective functions which are minimized are estimated by numerically solving the 3D Euler and Navier-Stokes equations using a TVD approach and a LU implicit scheme. Computed results show that the hybrid optimization method proposed in this study shows a promise of high computational efficiency and global search capabilities. / Singapore-MIT Alliance (SMA)

Simultaneous Perturbation Stochastic Approximation method has attracted considerable application in many different areas such as statistical parameter estimation, feedback control, simulation-based optimization, signal & image processing, and experimental design. In this paper, its performance as a viable optimization tool is demonstrated by applying it first to a simple wing geometry design problem for which the objective function is described by an empirical formula from aircraft design practice and then it is used in a transonic fan blade design problem in which the objective function is not represented by any explicit function but is estimated at each design iteration by a computational fluid dynamics algorithm for solving the Navier-Stokes equations / Singapore-MIT Alliance (SMA)

In this thesis we study the general problem of reconstructing a function, defined on a finite lattice from a set of incomplete, noisy and/or ambiguous observations. The goal of this work is to demonstrate the generality and practical value of a probabilistic (in particular, Bayesian) approach to this problem, particularly in the context of Computer Vision. In this approach, the prior knowledge about the solution is expressed in the form of a Gibbsian probability distribution on the space of all possible functions, so that the reconstruction task is formulated as an estimation problem. Our main contributions are the following: (1) We introduce the use of specific error criteria for the design of the optimal Bayesian estimators for several classes of problems, and propose a general (Monte Carlo) procedure for approximating them. This new approach leads to a substantial improvement over the existing schemes, both regarding the quality of the results (particularly for low signal to noise ratios) and the computational efficiency. (2) We apply the Bayesian appraoch to the solution of several problems, some of which are formulated and solved in these terms for the first time. Specifically, these applications are: teh reconstruction of piecewise constant surfaces from sparse and noisy observationsl; the reconstruction of depth from stereoscopic pairs of images and the formation of perceptual clusters. (3) For each one of these applications, we develop fast, deterministic algorithms that approximate the optimal estimators, and illustrate their performance on both synthetic and real data. (4) We propose a new method, based on the analysis of the residual process, for estimating the parameters of the probabilistic models directly from the noisy observations. This scheme leads to an algorithm, which has no free parameters, for the restoration of piecewise uniform images. (5) We analyze the implementation of the algorithms that we develop in non-conventional hardware, such as massively parallel digital machines, and analog and hybrid networks.

Numerous publications are available on the structure and properties correlation of fibers spun from polymers with flexible chains such as polyethylene terephthalate (PET), nylon, polypropylene. Also considerable amount of work is reported in fibers spun from rigid rod polymers like poly(p-phenylene terephthalamide) due to their value in high performance fibers category. However, very limited literature is available on the structure-properties relationship in fibers manufactured from poly(phenylene sulfide) (PPS), a high performance polymer which possesses chain flexibility between above two classes of polymers. A few researchers have studied crystallization kinetics and the fibers by extruding the polymer using capillary rheometers. However, there is a lack of in-depth study of conversion of PPS into fibers through melt spinning and further enhancement of properties by drawing and annealing experiments. The purpose of the present research was to fill this void by systematically studying the fiber manufacture from PPS polymers. Four variances of proprietary Fortron® linear PPS resins differing in MW were analyzed for their characteristics such as molecular weight (MW) and MW distribution (MWD) using gel permeation chromatography (GPC), rheological properties using melt flow indexer (MFI) and capillary extrusion rheometer, and crystallization kinetics using differential scanning calorimetry (DSC). The fibers were spun on a pilot melt spinning facility, using a multi-hole spinneret, under different processing conditions. As-spun fibers were drawn and annealed subsequently by varying draw-annealing conditions. Thorough characterization of the as-spun and drawn-annealed fibers was carried out using various analytical techniques such as tensile testing, DSC, polarized light optical microscopy (POM), wide angle X-ray scattering (WAXS), and small angle X-ray scattering (SAXS). Relationship between polymer characteristics, process conditions and structure-properties in the fibers was analysed statistically. A strong correlationship between polymer molecular weight, processing conditions during melt spinning and draw-annealing, processing behavior during melt spinning and drawing, fiber tensile properties and fiber morphology is reported herein. Interaction effects of material and process variables in evolving fiber structure and properties are also discussed. Through optimal combination of material and process variables, PPS fibers of tenacity close to six gpd were obtained. With the help of several characterization tools listed earlier, melting behavior of PPS polymers and fibers is decoded, and probable structural model of high tenacity PPS fibers is proposed.

Our work focuses on an analysis of the processes for full and partial annealing of aluminium coils. Due to inefficient production management these processes show high inventory levels, long lead times and decreased delivery performance. We have also found inadequacies in the ways costs for these processes are distributed. We have established a new process mapping by initially investigating the strategic dimensions of the company and the processes for annealing, in order to later on establish performance measures congruent with the business objectives. Furthermore we have conducted extensive calculations and analyses to facilitate the successful implementation of a Just-in-time production philosophy, including necessary process improvements and redesigns to be made. Our proposed changes will lead to shorter lead times and low levels of WIP, which are important success factors of a JIT-based production philosophy. To do this we have developed a capacity analysis tool with which it is also possible to analyse other processing scenarios or the effect of load changes and/or product mix variations. This tool can also serve as a benchmark for capacity analysis of other processes. Finally, we have been able to establish more accurate costs per machine hour for full and partial annealing to be implemented in the managerial system. We believe that the processes for annealing are not the only ones suffering from poor cost control, why we would suggest that Sapa Heat Transfer investigates the cost distribution in more processes, and also develops and follows better guidelines for cost control.

<p>An electrolytic cell was designed and constructed for the preparation of TiO2 nanotubes. Conditions of anodic oxidation were established to reproducibly prepare TiO2 nanotubes of average length 35-50 &mu / m vertically orientated relative to the plain of a pure titanium metal sheet. A non-aqueous solution of ethylene glycol containing small percentage of ammonium fluoride was used as the electrolyte with an applied voltage of 60 V. The morphology and dimensions of the nanotube arrays were studied by scanning (SEM) and transmission (TEM) electron microscopy. The effect of calcination under different conditions of temperature and atmosphere (nitrogen, argon and air) were assessed by both X-ray diffraction (XRD) and cyclic voltammetry (CV). Cyclic voltammetry studies were made possible by construction of a specially designed titanium electrode upon which the nanotubes were prepared. CV studies established a positive correlation between crystallinity and conductivity of the nanotubes. Doping of the nanotubes with nitrogen and carbon was established by elemental analysis, X-ray photoelectron spectroscopy (XPS) and Rutherford back scattering (RBS). The effect of nonmetal doping on the band gap of the TiO2 nanotubes was investigated by diffuse reflectance spectroscopy (DRS).</p>