In manufacturing, automation has replaced many dangerous, mundane, arduous and routine manual operations, for example, transportation of heavy parts, stamping of large parts, repetitive welding and bolt fastening. However, skilled operators still carry out critical manual processes in various industries such as aerospace, automotive and heavy-machinery. As automation technology progresses through more flexible and intelligent systems, the potential for these processes to be automated increases. However, the decision to undertake automation is a complex one, involving consideration of many factors such as return of investment, health and safety, life cycle impact, competitive advantage, and resources and technology availability. A key challenge to manufacturing automation is the ability to adapt to process variability. In manufacturing processes, human operators apply their skills to adapt to variability, in order to meet the product and process specifications or requirements. This thesis is focussed on understanding the 'variability involved in these manual processes, and how it may influence the automation solution'. Two manual industrial processes in polishing and de-burring of high-value components were observed to evaluate the extent of the variability and how the operators applied their skills to overcome it. Based on the findings from the literature and process studies, a framework was developed to categorise variability in manual manufacturing processes and to suggest a level of automation for the tasks in the processes, based on scores and weights given to the parameters by the user. The novelty of this research lies in the creation of a framework to categorise and evaluate process variability, suggesting an appropriate level of automation. The framework uses five attributes of processes; inputs, outputs, strategy, time and requirements and twelve parameters (quantity, range or interval of variability, interdependency, diversification, number of alternatives, number of actions, patterned actions, concurrency, time restriction, sensorial domain, cognitive requisite and physical requisites) to evaluate variability inherent in the process. The level of automation suggested is obtained through a system of scores and weights for each parameter. The weights were calculated using Analytical Hierarchical Process (AHP) with the help of three experts in manufacturing processes. Finally, this framework was validated through its application to two processes consisting of a lab-based peg-in-a-hole manual process and an industrial process on welding. In addition, the framework was further applied to three processes (two industrial processes and one process simulated in the laboratory) by two subjects for each process to verify the consistency of the results obtained. The results suggest that the framework is robust when applied by different subjects, presenting high similarity in outputs. Moreover, the framework was found to be effective when characterising variability present in the processes where it was applied. The framework was developed and tested in manufacturing of high value components, with high potential to be applied to processes in other industries, for instance, automotive, heavy machinery, pharmaceutical or electronic components, although this would need further investigation. Thus, future work would include the application of the framework in processes in other industries, hence enhancing its robustness and widening its scope of applicability. Additionally, a database would be created to assess the correlation between process variability and the level of automation.

Epidemiological studies are rich in information that could improve the understanding of concept complexity of a health problem, and are important sources for evidence based medicine. However, epidemiologists experience difficulties in recognising and aggregating key characteristics in related research due to an increasing number of published articles. The main aim of this dissertation is to explore how text mining techniques can assist epidemiologists to identify important pieces of information and detect and integrate key knowledge for further research and exploration via concept maps. Concept maps are widely used in medicine for exploration and representation as a relatively formal, easy to design and understand knowledge representation model. To support this aim, we have developed a methodology for the extraction of key epidemiological characteristics from all types of epidemiological research articles in order to visualise, explore and aggregate concepts related to a health care problem. A generic rule-based approach was designed and implemented for the identification of mentions of six key characteristics, including study design, population, exposure, outcome, covariate and effect size. The system also relies on automatic term recognition and biomedical dictionaries to identify concepts of interests. In order to facilitate knowledge integration and aggregation, extracted characteristics are further normalized and mapped to existing resources. Study design mentions are mapped to an expanded version of the Ontology of Clinical Research (OCRe), whereas exposure, outcome and covariate mentions are mapped to Unified Medical Language System (UMLS) semantic groups and categories. Population mentions are mapped to age groups, gender and nationality/ethnicity, and effect size mentions are normalised with the regards to the used metric and confidence interval and related concept. The evaluation has shown reliable results, with an average micro F-score of 87% for recognition of epidemiological mentions and 91% for normalisation. Normalised concepts are further organised in an automatically generated concept map, which has three sections for exposures, outcomes and covariates. To demonstrate the potential of the developed methodology, it was applied to a large-scale corpus of epidemiological research abstracts related to obesity. Obesity was chosen as a case study since it has emerged as one of the most important global health problems of the 21st century. Using the concepts extracted from the corpus, we have built a searchable database of key epidemiological characteristics explored in obesity and an automatically generated concept map represented the normalized exposures, outcomes and covariates. An epidemiological workbench (EpiTeM) was designed to enable further exploration and inspection of the normalized extracted data, with direct links to the literature. The generated results also allow exploration of trends in obesity research and can facilitate understanding of its concept complexity. For example, we have noted the most frequent concepts and the most common pairs of characteristics that have been studied in obesity epidemiology. Finally, this thesis also discusses a number of challenges for text mining of epidemiological literature and suggests various opportunities for future work.

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For the grid to be stable, the supply of power must equal the demands of the consumer at every moment during the day. The unpredictable intermittent nature of wind results in inconsistent power generation. Energy storage technologies coupled with a wind farm can not only provide power during fluctuations but also maintain a stable and reliable grid. The objective of the thesis is to perform a comprehensive analysis of different types of energy storage technologies that can be coupled with a wind farm. The analysis is performed on the basis of multiple characteristics which affect their viability. We identified key characteristics for a range of storage technologies, including lead-acid, sodium-sulphur, nickel cadmium, lithium-ion, superconducting magnetic energy storage, electrochemical capacitors, flywheels, flow batteries, pumped hydro and compressed air energy storage systems. We performed a comparison study to analyze trade-offs and assessed potential improvement areas that will make them more competitive in the electric power industry. We suggested viable energy storage systems that could be better and suitable for different applications for an electric grid integrated with a wind farm.

The concept of key characteristics deals with the particular moods which different tonalities are believed to provide to music. Discussions regarding their existence and the validity of the phenomena have always been controversial because of a lack of fundamental reasons and explanations for them. Nevertheless, references to key characteristics have appeared in various fields of study and over many centuries: the Greek doctrine of ethos, writings of Guido d’Arezzo, Jean-Philippe Rameau’s Traité de l’harmonie, scribbles in Beethoven’s sketches, and several passages in Hermann von Helmholtz’s On the Sensations of Tones. The attitudes and opinions towards key characteristics have varied in each period of its history. Among the ancient Greeks and Romans, the characteristics of modes were discussed among philosophers, namely, Plato, Aristotle, Lucianus and Cassiodorus. They were believed to affect moral development but were also associated with mysticism. In the Middle Ages and Renaissance, references to key characteristics can be found in the writings of numerous theorists, including Gioseffo Zarlino, Ramos de Pariea and Heinrich Glarean. The studies and discussions of key characteristics in those periods became so well explored as to result in the first appearance of a list of the characteristics of each mode. In Germany and France especially, the discussion of key characteristics reached its peak in the first half of the eighteenth century, when it was studied as a part of Rhetoric. Theorists and composers equally showed their interest in the elements each key could offer to music and how to use keys advantageously in order to enrich the musical experience of the listener. While key characteristics were studied commonly as a vital subject by composers in the eighteenth century and as a fundamental of musical education by many young musicians in the early nineteenth, this tradition had all but disappeared by the middle of the twentieth. The concept of key characteristics is no longer commonly taught in our musical institutions, and this desertion from such a traditionally significant discipline is ever puzzling and particularly interesting to me. In my thesis, I will focus on writings from the last half of the nineteenth century and the first half of the twentieth to determine the various paths taken in the study of key characteristics. I will investigate the writings and discussions of three scholarly groups—music theorists, composers and scientists—from late nineteenth and early twentieth centuries and discuss how the survival of the study of key characteristics was influenced by aspects of the time: popular aspects and aims in the fields of music theory; cultural and social expectations in the validity of phenomena; pronouncements of composers (Arthur Bliss, Alexander Scriabin, Olivier Messiaen, Arnold Schoenberg and Vincent D’Indy) in their musical styles; the rise of a naturalistic view of physical reality as a field and changes it brought to music and societies. I will also include a comparative summary of the status of key characteristics in various periods.

Im Rahmen des 16. Jahreskongresses der GMTH hat ein Workshop stattgefunden, der sich zum Ziel gesetzt hat, hörend die Sensibilität zu wecken für den Klang einer Musik in einer bestimmten Tonart bei einer jeweils historischen Stimmung. Aufgrund der vom 16. bis ins 19. Jahrhundert benutzten ungleichstufigen Temperaturen ›funktionieren‹ nämlich viele Stücke nicht in jeder beliebigen Tonart. Hieraus ergeben sich wichtige Fragen für die Interpretation, für die Komposition und Improvisation, für die Werkanalyse und schließlich für den wissenschaftlichen Diskurs. / During the 16th Annual Conference of the GMTH a workshop was held that aimed to increase the awareness for listening to the sound of a composition in a specific key (within an appropriate historical tuning). Because of the unequal temperaments used from the 16th to the 19th century, many pieces don’t ›work‹ in every key. From this, important questions arise regarding performance, composition, improvisation, analysis, and, finally, scientific discourse.

Continuous technological development and increasing efficiency demands are driving products toward becoming more and more complex. For the aerospace industry - where the requirements for performance, safety and low environmental impact already are substantial - this means that more extensive quality assurance measures must be taken to ensure the fulfillment of the requirements of each individual component.However, to avoid that the work with quality improvement become too extensive and increase the product cost to unbearable levels it is necessary to have methods to prioritize and focus improvement efforts on the product features that matters most for fulfilling customer requirements. Therefore, the concept of Key Characteristics is used today, both in the aerospace and other industries; a term for those characteristics that have a significant impact on requirement compliance and whose outcomes at the same time are expected to vary considerably in manufacturing.The concept itself is similar among those who use it but the purpose of and methodology for identifying and managing Key Characteristics vary, even within the same industry. This thesis is therefore aimed to create a view of which factors that characterize an effective and efficient way for companies in the aerospace industry to work with Key Characteristics. The thesis involves a case study to create a framework for how companies within this industry work with Key Characteristics, a literature review to see which approaches are advocated by previous research and two benchmark studies to see examples of how Key Characteristics are used and handled in practice in industry.The results show that the work of Key Characteristics should meet three main criteria in order to be effective and efficient: • it must be clearly focused on the characteristics that have critical impact on customer requirements and at the same time considerable variation in production, • it should be initiated early in the product development process and then performed iteratively during the process of continuously reducing variation problems in manufacturing, and • it should identify Key Characteristics using both qualitative and quantitative tools to best capture all different kinds of requirements on the product.Finally a practical example is given of how the work with Key Characteristics should look like at GKN Sweden AB, the case study company in the aerospace industry, to effectively minimize the costs associated with production variation, and yet satisfy all customer requirements. / <p>Validerat; 20140811 (global_studentproject_submitter)</p>