The thesis provides a well-researched classical approach to fit and predict the losses (extreme) for Lloyds Bank’s Dutch mortgage portfolio, their defaulted Dutch mortgage portfolio, and their German personal and car loan portfolio. This is a crucial piece for quantification of the economic loss, required for effective credit risk management by the Bank. For starters, the distribution of losses needs to be defined in order to determine the amount of losses that a bank can possibly experience in an event that corresponds to a specific confidence level. To get to that point, the data needs to be approximated with either one or more distributions, this thesis covers the single distribution approach and the mixture model approach that uses two distributions to solve the approximation of the data. Our work concludes that the optimal distribution for the regular Dutch mortgage portfolio losses include a Beta-Beta mixture and a Lognormal-Gamma mixture. Where the Lognormal-Gamma mixture has utilized a threshold approach that splits the data into two separate data sets and then fits the data separately before combining them with a weight function. While, for the second Dutch mortgage portfolio at the specific snapshots, the Beta and the Generalized Pareto outperformed the rest. Furthermore, for the German personal and car loan portfolio, the Generalized Pareto also performed the best. This is a crucial step for calculating the necessary economic capital that Lloyds Banking Group plans to do in the near future.

No / Transportation infrastructure projects are prone to cost and schedule overruns. At the time of contract award, a construction contingency budget is often used to accommodate for unplanned events such as scope changes. Recent empirical research has shown that rework during construction as a result of design changes, errors and omission are the major contributors of overruns in projects. The statistical characteristics of rework, and cost and schedule overruns that are experienced from a project's contract award for 58 Australian transportation infrastructure projects are analysed. Theoretical probability distributions are fitted to the rework, cost and schedule overrun data. Goodness of fit tests are used in conjunction with probability-probability (P-P) plots to compare the sample distribution from the known theoretical distribution. A Generalised Logistic probability density function is found to describe the behaviour of cost-overruns and provides the best overall distribution fit. The best fitting distribution for schedule overruns and rework data were the Four Parameter Burr and a Johnson SB distribution, respectively. The distributions are used to calculate the probability of rework, cost and schedule overruns being experienced. A case illustration is presented and discussed to demonstrate how the derived probabilities may be utilised in practice.

Symbicort Turbuhaler is a medical device produced by the pharmaceutical company AstraZeneca for the treatment of asthma and symptoms of chronic obstructive pulmonary disease. The delivery reliability of the product is dependent on the performance of the whole supply chain and as part of the chain the results from the department, Quality Control (QC), are mandatory to release the produced batches to the market. The performance of QC is thus an important part of the supply chain. In order to reduce the risk of supply problems and market shortage, it is very important to investigate whether the performance of QC can be improved. The purpose of the thesis is to provide AstraZeneca with scientifically based data to identify sensitive parameters and readjust work procedures in order to improve the performance of QC. The goal of this thesis is to map out the flow of the QC Symbicort Turbuhaler operation and construct a model of it. The model is intended to be used to simulate and optimize different parameters, such as the inflow of batch samples, the utilization of the instrumentation and staff workload. QC is modelled in a simulation software. The model is used to simulate and optimize different scenarios following a discrete event simulation and an optimization technique based on evolution strategies. By reducing the number of analytical robots from 14 to 10, it is possible to maintain existing average lead time. Through a reduction, the utilization of the robots increases, simultaneously the workload decreases for some of the staff. However, it is not possible to extend the durability of the system suitability test (SST), and still achieve existing average lead time. From the investigation of different parameters, it is found that, an added laboratory engineer at the high-performance liquid chromatography (HPLC) station has the best outcome on lead time and overall equipment effectiveness. However, a reduced laboratory engineer at the Minispice robots has the worst outcome. With the resources available today the lead times cannot be maintained in the long run, if the inflow is of 35 batch samples a week or more. By adding a laboratory engineer at the HPLC station and by using a SST with durability of 48 hours, the best outcome in terms of average lead time and number of batch samples with a lead time less than 10 days is received. / Symbicort Turbuhaler är en medicinsk enhet som tillverkas av läkemedelsföretaget AstraZeneca för behandling av astma och symptomen för kronisk obstruktiv lungsjukdom. Leveranssäkerheten för produkten är beroende av hela försörjningskedjans prestanda och som en del utav kedjan är resultaten från kvalitetskontrollen (QC) obligatoriska för att släppa en batch av produkten till marknaden. QCs prestanda är därför en viktig del av försörjningskedjan. För att minska risken för leveransproblem och produktbrist på marknaden är det viktigt att undersöka huruvida prestandan hos QC kan förbättras. Syftet med arbetet är att ge AstraZeneca vetenskapligt baserat data för att identifiera känsliga parametrar och justera arbetssätt för att förbättra prestandan hos QC. Målet med detta arbete är att kartlägga flödet av QC Symbicort Turbuhaler och konstruera en modell utifrån det flödet. Modellen är avsedd för att simulera och optimera olika parametrar, såsom inflödet av batchprover, utnyttjande av instrumentering och arbetsbelastning av personal. Genom att minska antalet analytiska robotar från 14 till 10, är det möjligt att bibehålla befintlig genomsnittlig ledtid. Genom denna minskning ökar utnyttjandet av robotarna, samtidigt som arbetsbelastningen minskar för en del av bemanningen. Det är inte möjligt att förlänga hållbarheterna på robotarnas systemtest (SST) och fortfarande uppnå befintlig genomsnittlig ledtid. Vid undersökning av olika parametrar indikerar resultatet att en ytterligare laboratorieingenjör vid högpresterande vätskekromatografi-stationen (HPLC) har den bästa effekten på ledtid och produktionseffektivitet. En laboratorieingenjör som reduceras från Minispice-robotarna har däremot den värsta effekten. Med de resurser som finns tillgängliga idag kan ledtiderna inte bibehållas långsiktigt om inflödet är 35 batchprover per vecka eller mer. Genom att addera en laboratorieingenjör vid HPLC-stationen och användaen SST med en hållbarhet på 48 timmar, erhålls det bästa resultatet i termer av genomsnittlig ledtid och antal batchprover som har en individuell ledtid på mindre än 10 dagar.

Response time (RT) data are able to provide unique insight into both items and examinees regarding speededness and time-demand and should be incorporated into test development practice. To allow test developers to utilize RT information, item RT needs to be summarized into point estimate(PE)(s) that can be understood by content specialists and saved into the item pool. The recent expansion of online testing in K-12 achievement assessments brings opportunities and challenges for measurement experts to investigate and utilize RT information in a context different from that in the majority of literature, in which licensing and certification tests, graduate admission tests, and other applications that incorporate computer-adaptive testing. Using empirical data from four tests in two grade levels of a K-12 standardized achievement assessment, this study explored the empirical distributions of item RT and their fit to five probability distributions, the characteristics of four item RTPEs, and the relationships between item RTPEs and eight item attributes. Based on the principal findings across tests and grades, the empirical distributions of item RT presented widely variable shapes and did not fit any of the five proposed probability distributions; the 90th quantile showed its important capability of capturing and avoiding speededness issues; and the associations between item RTPEs and item attributes proved to be mixed. The generally idiosyncratic findings of this study call for a different perspective and approach to explore RT data and call for more empirical studies to enlighten test development practice in the K-12 standardized achievement assessment field.

Discrete Events Simulation (DES) is a powerful tool of modeling and analysis used in different disciplines. DES models require data in order to determine the different parameters that drive the simulations. The literature about DES input data management indicates that the preparation of necessary input data is often a highly manual process, which causes inefficiencies, significant time consumption and a negative user experience. The focus of this research investigation is addressing the manual data collection and processing (MDCAP) problem prevalent in DES projects. This research investigation presents an integrated framework to solve the MDCAP problem by classifying the data needed for DES projects into three generic classes. Such classification permits automating and streamlining the preparation of the data, allowing DES modelers to collect, update, visualize, fit, validate, tally and test data in real-time, by performing intuitive actions. In addition to the proposed theoretical framework, this project introduces an innovative user interface that was programmed based on the ideas of the proposed framework. The interface is called DESI, which stands for Discrete Event Simulation Inputs. The proposed integrated framework to automate DES input data preparation was evaluated against benchmark measures presented in the literature in order to show its positive impact in DES input data management. This research investigation demonstrates that the proposed framework, instantiated by the DESI interface, addresses current gaps in the field, reduces the time devoted to input data management within DES projects and advances the state-of-the-art in DES input data management automation.